Nothing Special   »   [go: up one dir, main page]

Next Issue
Volume 10, July
Previous Issue
Volume 10, May
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
ijms-logo

Journal Browser

Journal Browser

Int. J. Mol. Sci., Volume 10, Issue 6 (June 2009) – 22 articles , Pages 2440-2872

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Select all
Export citation of selected articles as:
265 KiB  
Review
Protease Inhibitors from Plants with Antimicrobial Activity
by Jin-Young Kim, Seong-Cheol Park, Indeok Hwang, Hyeonsook Cheong, Jae-Woon Nah, Kyung-Soo Hahm and Yoonkyung Park
Int. J. Mol. Sci. 2009, 10(6), 2860-2872; https://doi.org/10.3390/ijms10062860 - 23 Jun 2009
Cited by 183 | Viewed by 22931
Abstract
Antimicrobial proteins (peptides) are known to play important roles in the innate host defense mechanisms of most living organisms, including plants, insects, amphibians and mammals. They are also known to possess potent antibiotic activity against bacteria, fungi, and even certain viruses. Recently, the [...] Read more.
Antimicrobial proteins (peptides) are known to play important roles in the innate host defense mechanisms of most living organisms, including plants, insects, amphibians and mammals. They are also known to possess potent antibiotic activity against bacteria, fungi, and even certain viruses. Recently, the rapid emergence of microbial pathogens that are resistant to currently available antibiotics has triggered considerable interest in the isolation and investigation of the mode of action of antimicrobial proteins (peptides). Plants produce a variety of proteins (peptides) that are involved in the defense against pathogens and invading organisms, including ribosome-inactivating proteins, lectins, protease inhibitors and antifungal peptides (proteins). Specially, the protease inhibitors can inhibit aspartic, serine and cysteine proteinases. Increased levels of trypsin and chymotrypsin inhibitors correlated with the plants resistance to the pathogen. Usually, the purification of antimicrobial proteins (peptides) with protease inhibitor activity was accomplished by salt-extraction, ultrafiltration and C18 reverse phase chromatography, successfully. We discuss the relation between antimicrobial and anti-protease activity in this review. Protease inhibitors from plants potently inhibited the growth of a variety of pathogenic bacterial and fungal strains and are therefore excellent candidates for use as the lead compounds for the development of novel antimicrobial agents. Full article
(This article belongs to the Special Issue Antimicrobial Agents)
Show Figures


<p>Scheme for the purification of antimicrobial peptides from potato tubers.</p>
Full article ">
<p>Inhibition of chymotrypsin, trypsin and papain by Potide-G. Fluorescently labeled casein was incubated at room temperature with 25 μg of the indicated enzyme for 60 min, with or without the indicated concentration of potide-G, after which the fluorescence was measured. Modified with permission from REF. <a href="#b60-ijms-10-02860" class="html-bibr">60</a>.(2006) <span class="html-italic">Biochem Biophys Res Commun</span>.</p>
Full article ">
<p>Antifungal activity of potide-G on agar containg <span class="html-italic">C. albicans.</span> After peptide was untreated (A) or treated (B, 5 μg) on paper discs, the plated was incubated for 24 hr at 37 °C.</p>
Full article ">
<p>Antibacterial assay of PT-1 peptide in the absence (A) or presence (B) of DTT against <span class="html-italic">S. aureus</span>. After reducing the intramolecular disulfide bonds of peptide with DTT, substance was mixed with bacterial cell suspension.</p>
Full article ">
650 KiB  
Article
Inactivation and Unfolding of the Hyperthermophilic Inorganic Pyrophosphatase from Thermus thermophilus by Sodium Dodecyl Sulfate
by Hang Mu, Sheng-Mei Zhou, Yong Xia, Hechang Zou, Fanguo Meng and Yong-Bin Yan
Int. J. Mol. Sci. 2009, 10(6), 2849-2859; https://doi.org/10.3390/ijms10062849 - 23 Jun 2009
Cited by 9 | Viewed by 10961
Abstract
Inorganic pyrophosphatase (PPase, EC 3.6.1.1) is an essential constitutive enzyme for energy metabolism and clearance of excess pyrophosphate. In this research, we investigated the sodium dodecyl sulfate (SDS)-induced inactivation and unfolding of PPase from Thermus thermophilus (T-PPase), a hyperthermophilic enzyme. The results indicated [...] Read more.
Inorganic pyrophosphatase (PPase, EC 3.6.1.1) is an essential constitutive enzyme for energy metabolism and clearance of excess pyrophosphate. In this research, we investigated the sodium dodecyl sulfate (SDS)-induced inactivation and unfolding of PPase from Thermus thermophilus (T-PPase), a hyperthermophilic enzyme. The results indicated that like many other mesophilic enzymes, T-PPase could be fully inactivated at a low SDS concentration of 2 mM. Using an enzyme activity assay, SDS was shown to act as a mixed type reversible inhibitor, suggesting T-PPase contained specific SDS binding sites. At high SDS concentrations, T-PPase was denatured via a two-state process without the accumulation of any intermediate, as revealed by far-UV CD and intrinsic fluorescence. A comparison of the inactivation and unfolding data suggested that the inhibition might be caused by the specific binding of the SDS molecules to the enzyme, while the unfolding might be caused by the cooperative non-specific binding of SDS to T-PPase. The possible molecular mechanisms underlying the mixed type inhibition by SDS was proposed to be caused by the local conformational changes or altered charge distributions. Full article
(This article belongs to the Section Biochemistry)
Show Figures

Graphical abstract

Graphical abstract
Full article ">
<p>Subunit structure of PPase from <span class="html-italic">Thermus thermophilus</span> (T-PPase, PDB ID 2PRD). (A) Subunit structure of T-PPase by ribbon representation. The center of the active site is indicated by the position of the sulfate molecule. N and C are the N- and C-terminus of the polypeptide. (B) The cavity of the active site. The hydrophobic side chains are in white, while red and blue represent the acidic and basic side chains. The cavity is surrounded by charged residues, while the bottom of the cavity is hydrophobic. The plots were generated using WebLab ViewerLite 3.7 from Molecular Simulations.</p>
Full article ">
<p>Inactivation of T-PPase by SDS. The inactivation was performed by denaturing 11.5 μg/mL enzyme by various concentrations of SDS for 2 h, and the final concentration of the enzyme was 1.0 μg/mL in the activity assay.</p>
Full article ">
<p>Dependence of T-PPase inactivation by SDS on enzyme concentration.</p>
Full article ">
<p>Characterization of the type of PPase reversible inhibition by SDS. (A) Lineweaver-Burk plots. (B) Dixon plots. The lines are the best non-linear regression fit of the data to the parabolic function. (C) Slopes and intercepts on the Y-axis (Y-intercept) from the double reciprocal plot were plotted as a function of SDS concentration. The solid lines are the best non-linear regression fit of the data to the parabolic function. The dashed lines are the linear fit of the three lowest SDS concentrations, which yield the apparent inhibition constants using <a href="#FD1" class="html-disp-formula">Equations (1)</a> and <a href="#FD2" class="html-disp-formula">(2)</a>.</p>
Full article ">
<p>Secondary and tertiary structural changes of T-PPase during SDS-induced denaturation. The protein was incubated in buffers with the addition of various concentrations of SDS for 2 h, and then the CD or intrinsic fluorescence spectra were measured. (A) CD spectra of T-PPase denatured by various concentrations of SDS. The final enzyme concentration was 0.2 mg/mL. The arrow indicates the CD spectra are recorded in the presence of 0, 0.25, 0.75, 1.25, 1.75, 2.0, 2.5, 3.0 and 4.0 mM SDS, respectively. (B) Intrinsic fluorescence spectra of T-PPase by SDS. The excitation wavelength was 295 nm. The arrow indicates the fluorescence emission spectra measured in the presence of 0, 0.5, 1.0, 1.5, 1.75, 2.0, 2.5, 3.0, 4.0 and 5.0 mM SDS, respectively.</p>
Full article ">
<p>Transition curves of T-PPase unfolding by SDS monitored by the ellipticity at 222 nm, the emission maximum wavelength (<span class="html-italic">E</span><sub>max</sub>), intensity at <span class="html-italic">E</span><sub>max</sub>(<span class="html-italic">I</span><sub>max</sub>) and <span class="html-italic">I</span><sub>320</sub>/<span class="html-italic">I</span><sub>365</sub> of intrinsic fluorescence. The inactivation data in <a href="#f2-ijms-10-02849" class="html-fig">Figure 2</a> is also presented.</p>
Full article ">
<p>General Scheme for mixed type reversible inhibition. E, S and I denote enzyme, substrate and inhibitor respectively.</p>
Full article ">
221 KiB  
Review
Folding Mechanism of Beta-Hairpin Trpzip2: Heterogeneity, Transition State and Folding Pathways
by Yi Xiao, Changjun Chen and Yi He
Int. J. Mol. Sci. 2009, 10(6), 2838-2848; https://doi.org/10.3390/ijms10062838 - 22 Jun 2009
Cited by 31 | Viewed by 12485
Abstract
We review the studies on the folding mechanism of the β-hairpin tryptophan zipper 2 (trpzip2) and present some additional computational results to refine the picture of folding heterogeneity and pathways. We show that trpzip2 can have a two-state or a multi-state folding pattern, [...] Read more.
We review the studies on the folding mechanism of the β-hairpin tryptophan zipper 2 (trpzip2) and present some additional computational results to refine the picture of folding heterogeneity and pathways. We show that trpzip2 can have a two-state or a multi-state folding pattern, depending on whether it folds within the native basin or through local state basins on the high-dimensional free energy surface; Trpzip2 can fold along different pathways according to the packing order of tryptophan pairs. We also point out some important problems related to the folding mechanism of trpzip2 that still need clarification, e.g., a wide distribution of the computed conformations for the transition state ensemble. Full article
(This article belongs to the Special Issue Protein Folding 2009)
1024 KiB  
Article
Calculation of the Aqueous Thermodynamic Properties of Citric Acid Cycle Intermediates and Precursors and the Estimation of High Temperature and Pressure Equation of State Parameters
by Peter Dalla-Betta and Mitchell Schulte
Int. J. Mol. Sci. 2009, 10(6), 2809-2837; https://doi.org/10.3390/ijms10062809 - 22 Jun 2009
Cited by 13 | Viewed by 13427
Abstract
The citric acid cycle (CAC) is the central pathway of energy transfer for many organisms, and understanding the origin of this pathway may provide insight into the origins of metabolism. In order to assess the thermodynamics of this key pathway for microorganisms that [...] Read more.
The citric acid cycle (CAC) is the central pathway of energy transfer for many organisms, and understanding the origin of this pathway may provide insight into the origins of metabolism. In order to assess the thermodynamics of this key pathway for microorganisms that inhabit a wide variety of environments, especially those found in high temperature environments, we have calculated the properties and parameters for the revised Helgeson-Kirkham-Flowers equation of state for the major components of the CAC. While a significant amount of data is not available for many of the constituents of this fundamental pathway, methods exist that allow estimation of these missing data. Full article
(This article belongs to the Special Issue Origin of Life)
Show Figures


<p>The reverse citric acid cycle (modified from [<a href="#b25-ijms-10-02809" class="html-bibr">25</a>]).</p>
Full article ">
<p>Group contribution method used to estimate (a) the standard partial molal entropy (S<sup>°</sup>) and volume (V<sup>°</sup>) and (b) the heat capacity (C<sub>p</sub>°) and free energy (ΔG<sub>f</sub>°) of aqueous organic species considered in this study.<sup>a</sup>-value taken from reference shown in <a href="#t1-ijms-10-02809" class="html-table">Table 1</a>. <sup>b</sup>- group values from [<a href="#b35-ijms-10-02809" class="html-bibr">35</a>]. <sup>c</sup>- the carbonyl group value was estimated from the difference in <span class="html-italic">V</span><sup>0</sup> between succinic acid [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>] and α-ketoglutarate [<a href="#b36-ijms-10-02809" class="html-bibr">36</a>]. <sup>d</sup>-estimated using group values from [<a href="#b31-ijms-10-02809" class="html-bibr">31</a>]. <sup>e</sup>-malonic acid from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. <sup>f</sup>-group <math display="inline"> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> value for &gt;C=O assumed to be the difference in <math display="inline"> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> between α-ketoglutaric acid [<a href="#b37-ijms-10-02809" class="html-bibr">37</a>] and succinic acid [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. <sup>g</sup>-calculated form <span class="html-italic">p</span>Ka values from [<a href="#b33-ijms-10-02809" class="html-bibr">33</a>] and <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> for ions from <a href="#t1-ijms-10-02809" class="html-table">Table 1</a> (as described in text). <sup>h</sup>-value for <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> was taken from [<a href="#b38-ijms-10-02809" class="html-bibr">38</a>], the <math display="inline"> <mo>Δ</mo> <msubsup> <mi>H</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> was from [<a href="#b33-ijms-10-02809" class="html-bibr">33</a>], and <math display="inline"> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mtext mathvariant="italic">elements</mtext></math> were the CODATA values from [<a href="#b39-ijms-10-02809" class="html-bibr">39</a>]. <sup>i</sup>-estimated from <span class="html-italic">V</span><sup>0</sup> of H-fumarate<sup>−1</sup> (<a href="#f2-ijms-10-02809" class="html-fig">Figure 2</a>) assuming the same difference in <span class="html-italic">V</span><sup>0</sup> between the acid and ion as between succinic acid and H-succinate<sup>−1</sup> from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. <sup>j</sup>-estimated by subtracting the difference in y-intercept values for <math display="inline"> <msubsup> <mi>C</mi> <mi>P</mi> <mn>0</mn></msubsup></math> between <span class="html-italic">n</span>-alkanes and <span class="html-italic">n</span>-alkenes (taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]) from that of succinic acid (taken from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]). <sup>k</sup>- calculated from <span class="html-italic">p</span>Ka and <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> values from [<a href="#b33-ijms-10-02809" class="html-bibr">33</a>] for ions (as described in text), <math display="inline"> <mo>Δ</mo> <msubsup> <mi>H</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> was from [<a href="#b37-ijms-10-02809" class="html-bibr">37</a>)] and <math display="inline"> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mtext mathvariant="italic">elements</mtext></math> were the CODATA values from [<a href="#b39-ijms-10-02809" class="html-bibr">39</a>]. <sup>l</sup>-the <math display="inline"> <msubsup> <mi>C</mi> <mi>P</mi> <mn>0</mn></msubsup></math> for succinic acid was taken from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. The group value for the &gt;C=O was taken from [<a href="#b31-ijms-10-02809" class="html-bibr">31</a>]. <sup>m</sup>-from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]. <sup>n</sup>-group value estimated from difference in <math display="inline"> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> values between ethyl sulfide (as described in Appendix) and <span class="html-italic">n</span>-butane (taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]). <sup>o</sup>- group value from [<a href="#b40-ijms-10-02809" class="html-bibr">40</a>]. <sup>p</sup>- group value estimated from difference in <math display="inline"> <msubsup> <mi>C</mi> <mi>P</mi> <mn>0</mn></msubsup></math> values between ethyl sulfide [<a href="#b34-ijms-10-02809" class="html-bibr">34</a>] and <span class="html-italic">n</span>-butane (taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]. <sup>q</sup>-from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. <sup>r</sup>-group value estimated from difference in y-intercepts of <math display="inline"> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> between <span class="html-italic">n</span>-alkanones and n-1 <span class="html-italic">n</span>-alkanes taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]. <sup>s</sup>- group value from [<a href="#b30-ijms-10-02809" class="html-bibr">30</a>]. <sup>t</sup>- group value estimated from difference in y-intercepts of <math display="inline"> <msubsup> <mi>C</mi> <mi>P</mi> <mn>0</mn></msubsup></math> between <span class="html-italic">n</span>-alkanones and n-1 <span class="html-italic">n</span>-alkanes taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]. <sup>u</sup>- group value estimated from difference in y-intercepts of <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> between <span class="html-italic">n</span>-alkanones and n-1 <span class="html-italic">n</span>-alkanes taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]. <sup>v</sup>- group value estimated from difference in <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> values between ethyl sulfide (calculated from <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>g</mi></math> and Δ<span class="html-italic"><sub>hyd</sub>G</span> from [<a href="#b34-ijms-10-02809" class="html-bibr">34</a>] and <span class="html-italic">n</span>-butane (taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>)].</p>
Full article ">
<p>Group contribution method used to estimate (a) the standard partial molal entropy (S<sup>°</sup>) and volume (V<sup>°</sup>) and (b) the heat capacity (C<sub>p</sub>°) and free energy (ΔG<sub>f</sub>°) of aqueous organic species considered in this study.<sup>a</sup>-value taken from reference shown in <a href="#t1-ijms-10-02809" class="html-table">Table 1</a>. <sup>b</sup>- group values from [<a href="#b35-ijms-10-02809" class="html-bibr">35</a>]. <sup>c</sup>- the carbonyl group value was estimated from the difference in <span class="html-italic">V</span><sup>0</sup> between succinic acid [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>] and α-ketoglutarate [<a href="#b36-ijms-10-02809" class="html-bibr">36</a>]. <sup>d</sup>-estimated using group values from [<a href="#b31-ijms-10-02809" class="html-bibr">31</a>]. <sup>e</sup>-malonic acid from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. <sup>f</sup>-group <math display="inline"> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> value for &gt;C=O assumed to be the difference in <math display="inline"> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> between α-ketoglutaric acid [<a href="#b37-ijms-10-02809" class="html-bibr">37</a>] and succinic acid [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. <sup>g</sup>-calculated form <span class="html-italic">p</span>Ka values from [<a href="#b33-ijms-10-02809" class="html-bibr">33</a>] and <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> for ions from <a href="#t1-ijms-10-02809" class="html-table">Table 1</a> (as described in text). <sup>h</sup>-value for <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> was taken from [<a href="#b38-ijms-10-02809" class="html-bibr">38</a>], the <math display="inline"> <mo>Δ</mo> <msubsup> <mi>H</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> was from [<a href="#b33-ijms-10-02809" class="html-bibr">33</a>], and <math display="inline"> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mtext mathvariant="italic">elements</mtext></math> were the CODATA values from [<a href="#b39-ijms-10-02809" class="html-bibr">39</a>]. <sup>i</sup>-estimated from <span class="html-italic">V</span><sup>0</sup> of H-fumarate<sup>−1</sup> (<a href="#f2-ijms-10-02809" class="html-fig">Figure 2</a>) assuming the same difference in <span class="html-italic">V</span><sup>0</sup> between the acid and ion as between succinic acid and H-succinate<sup>−1</sup> from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. <sup>j</sup>-estimated by subtracting the difference in y-intercept values for <math display="inline"> <msubsup> <mi>C</mi> <mi>P</mi> <mn>0</mn></msubsup></math> between <span class="html-italic">n</span>-alkanes and <span class="html-italic">n</span>-alkenes (taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]) from that of succinic acid (taken from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]). <sup>k</sup>- calculated from <span class="html-italic">p</span>Ka and <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> values from [<a href="#b33-ijms-10-02809" class="html-bibr">33</a>] for ions (as described in text), <math display="inline"> <mo>Δ</mo> <msubsup> <mi>H</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> was from [<a href="#b37-ijms-10-02809" class="html-bibr">37</a>)] and <math display="inline"> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mtext mathvariant="italic">elements</mtext></math> were the CODATA values from [<a href="#b39-ijms-10-02809" class="html-bibr">39</a>]. <sup>l</sup>-the <math display="inline"> <msubsup> <mi>C</mi> <mi>P</mi> <mn>0</mn></msubsup></math> for succinic acid was taken from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. The group value for the &gt;C=O was taken from [<a href="#b31-ijms-10-02809" class="html-bibr">31</a>]. <sup>m</sup>-from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]. <sup>n</sup>-group value estimated from difference in <math display="inline"> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> values between ethyl sulfide (as described in Appendix) and <span class="html-italic">n</span>-butane (taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]). <sup>o</sup>- group value from [<a href="#b40-ijms-10-02809" class="html-bibr">40</a>]. <sup>p</sup>- group value estimated from difference in <math display="inline"> <msubsup> <mi>C</mi> <mi>P</mi> <mn>0</mn></msubsup></math> values between ethyl sulfide [<a href="#b34-ijms-10-02809" class="html-bibr">34</a>] and <span class="html-italic">n</span>-butane (taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]. <sup>q</sup>-from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. <sup>r</sup>-group value estimated from difference in y-intercepts of <math display="inline"> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> between <span class="html-italic">n</span>-alkanones and n-1 <span class="html-italic">n</span>-alkanes taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]. <sup>s</sup>- group value from [<a href="#b30-ijms-10-02809" class="html-bibr">30</a>]. <sup>t</sup>- group value estimated from difference in y-intercepts of <math display="inline"> <msubsup> <mi>C</mi> <mi>P</mi> <mn>0</mn></msubsup></math> between <span class="html-italic">n</span>-alkanones and n-1 <span class="html-italic">n</span>-alkanes taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]. <sup>u</sup>- group value estimated from difference in y-intercepts of <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> between <span class="html-italic">n</span>-alkanones and n-1 <span class="html-italic">n</span>-alkanes taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>]. <sup>v</sup>- group value estimated from difference in <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> values between ethyl sulfide (calculated from <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>g</mi></math> and Δ<span class="html-italic"><sub>hyd</sub>G</span> from [<a href="#b34-ijms-10-02809" class="html-bibr">34</a>] and <span class="html-italic">n</span>-butane (taken from [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>)].</p>
Full article ">
<p>Regression plot of the non-solvation parameter <span class="html-italic">a<sub>1</sub></span> against the non-solvation volumes of short-chained aqueous organic species taken from the literature [<a href="#b15-ijms-10-02809" class="html-bibr">15</a>,<a href="#b18-ijms-10-02809" class="html-bibr">18</a>,<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. The non-solvation volumes were calculated using <a href="#FD25" class="html-disp-formula">Equation (25)</a> with the partial molal volumes and effective Born coefficients of (C<sub>3</sub>-C<sub>5</sub>) carboxylic acids, (C<sub>2</sub>-C<sub>6</sub>) carboxylate anions, (C<sub>3</sub>-C<sub>5</sub>) hydroxy acids, (C<sub>3</sub>-C<sub>6</sub>) hydroxylate anions, (C<sub>2</sub>-C<sub>6</sub>) dicarboxy acids, dicarboxylate<sup>−1</sup>, and dicarboxylate<sup>−2</sup> anions [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>], (C<sub>3</sub>-C<sub>5</sub>) <span class="html-italic">n</span>-alkanones, <span class="html-italic">n</span>-alkanes, <span class="html-italic">n</span>-alkenes, <span class="html-italic">n</span>-alcohols [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>] and (C<sub>3</sub>-C<sub>5</sub>) aldehydes [<a href="#b15-ijms-10-02809" class="html-bibr">15</a>].</p>
Full article ">
<p>Regression plot of the non-solvation parameter <span class="html-italic">a<sub>2</sub></span> against the non-solvation volumes of short-chained aqueous organic species taken from the literature [<a href="#b15-ijms-10-02809" class="html-bibr">15</a>,<a href="#b18-ijms-10-02809" class="html-bibr">18</a>,<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. (a) Regression of non-solvation volumes calculated with <a href="#FD25" class="html-disp-formula">Equation (25)</a> using the partial molal volumes and effective Born coefficients of (C<sub>3</sub>–C<sub>5</sub>) carboxylic acids, (C<sub>2</sub>–C<sub>6</sub>) carboxylate anions, (C<sub>3</sub>–C<sub>5</sub>) hydroxy acids, (C<sub>3</sub>–C<sub>6</sub>) hydroxylate anions, (C<sub>2</sub>–C<sub>6</sub>) dicarboxy acids, −1, and −2 anions [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>], and aldehydes [<a href="#b15-ijms-10-02809" class="html-bibr">15</a>]. (b) Upper line: Regression plot generated from points in upper figure. Lower line: Regression of non-solvation volumes calculated with <a href="#FD25" class="html-disp-formula">Equation (25)</a> using the partial molal volumes and effective Born coefficients of (C<sub>3</sub>–C<sub>5</sub>) <span class="html-italic">n</span>-alkanones, and (C<sub>2</sub>–C<sub>5</sub>) <span class="html-italic">n</span>-alcohols [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>].</p>
Full article ">
<p>Regression plots of the non-solvation molal heat capacity variable c<sub>2</sub> against the reference state heat capacity of neutral and ionic organic species from the literature [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>,<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. (a) Plot of organic acid anions: (C<sub>2</sub>–C<sub>5</sub>) hydroxylates, (C<sub>2</sub>–C<sub>5</sub>) carboxylates and (C<sub>3</sub>–C<sub>6</sub>) H-dicarboxylate<sup>−1</sup> and dicarboxylate<sup>−2</sup> ions (all from reference [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]) used to generate <a href="#FD10" class="html-disp-formula">Equation (10)</a>. (b) Upper line: Plot of neutral acids: (C<sub>4</sub>–C<sub>5</sub>) carboxylic acids, (C<sub>3</sub>–C<sub>5</sub>) hydroxy acids, and (C<sub>4</sub>–C<sub>6</sub>) dicarboxylic acids from reference [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>] used to generate <a href="#FD11" class="html-disp-formula">Equation (11)</a>. Lower line: Plot of (C<sub>3</sub>–C<sub>5</sub>) <span class="html-italic">n</span>-alkanones and (C<sub>2</sub>–C<sub>5</sub>) <span class="html-italic">n</span>-alcohols from reference [<a href="#b18-ijms-10-02809" class="html-bibr">18</a>] used to generate <a href="#FD12" class="html-disp-formula">Equation (12)</a>.</p>
Full article ">
<p>Regression plot of the conventional Born coefficients against the partial molal entropy of various anions. The upper, middle, and lower lines are the correlations for the tri-, di-, and monovalent anions, respectively, from <a href="#FD30" class="html-disp-formula">Equations (30–32)</a> using values of inorganic ions (taken from Shock and Helgeson [<a href="#b17-ijms-10-02809" class="html-bibr">17</a>]), organic anions (taken from Shock [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]) and compounds calculated in this work.</p>
Full article ">
<p>Plot of the effective Born coefficient vs. the number of carbon atoms of neutral organic compounds. The lines are regressions generated from values of the selected functional series of compounds noted in <a href="#t1-ijms-10-02809" class="html-table">Table 1</a>. Datum points are the values of <span class="html-italic">ω<sub>e</sub></span> for the neutral compounds calculated as described in the text.</p>
Full article ">
<p>Plot of the error in partial molal properties of neutral and ionic organic compounds expected from the improper estimation of HKF parameters as a function of temperature and pressure. (a) and (b) Partial molal volume of propanoic acid, taken from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>], calculated using <a href="#FD25" class="html-disp-formula">Equations ((25)</a> + <a href="#FD26" class="html-disp-formula">(26))</a> with the over- and under-estimation of the effective Born coefficient. (a) The solid line is the predicted <span class="html-italic">V</span><sup>0</sup> of propanoic acid at Psat using the <span class="html-italic">ω<sub>e</sub></span> from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>]. The upper dashed-line is the <span class="html-italic">V</span><sup>0</sup> predicted by underestimating <span class="html-italic">ω<sub>e</sub></span> by 0.5-fold. The lower dashed-line is the <span class="html-italic">V</span><sup>0</sup> predicted by a 2-fold overestimating of <span class="html-italic">ω<sub>e</sub></span>. (b) The percent relative error expected in <span class="html-italic">V</span><sup>0</sup> as a function of pressure at 0.5x and 2.0x <span class="html-italic">ω<sub>e</sub></span>. (c) The effect of the over- and under-estimation of <span class="html-italic">ω<sub>e</sub></span> on relative error in Δ<span class="html-italic">G<sub>T,P</sub></span> at Psat (from <a href="#FD38" class="html-disp-formula">Equations (38)</a> and <a href="#FD39" class="html-disp-formula">(39)</a>). (d) Plot demonstrating the relative error in Δ<span class="html-italic">G<sub>T,P</sub></span> at Psat expected from gross misestimation of HKF parameters. Using the reference state <math display="inline"> <mo>Δ</mo> <msubsup> <mi>G</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math> (from <a href="#t1-ijms-10-02809" class="html-table">Table 1</a>) for the labeled acid or ion, the remaining values ( <math display="inline"> <mo>Δ</mo> <msubsup> <mi>S</mi> <mi>f</mi> <mn>0</mn></msubsup> <mi>a</mi> <mi>q</mi></math>, <span class="html-italic">a<sub>1</sub></span>, <span class="html-italic">a<sub>2</sub></span>, <span class="html-italic">a<sub>3</sub></span>, <span class="html-italic">a<sub>4</sub></span>, <span class="html-italic">c<sub>1</sub></span>, <span class="html-italic">c<sub>2</sub></span>, and <span class="html-italic">ω<sub>e</sub></span>) were swapped: propanoic acid (taken from [<a href="#b23-ijms-10-02809" class="html-bibr">23</a>] for pyruvic acid, and the respective α-ketoglutarate anion for H-oxaloacetate<sup>−1</sup> and oxaloacetate<sup>−2</sup> ions (<a href="#t1-ijms-10-02809" class="html-table">Table 1</a>), and vice versa.</p>
Full article ">
<p>Plot of the logarithms of equilibrium constants for dissociation reactions (as indicated) involving organic species from this work as a function of temperature at P<sub>sat</sub>.</p>
Full article ">
254 KiB  
Article
Lattice Strain Due to an Atomic Vacancy
by Shidong Li, Michael S. Sellers, Cemal Basaran, Andrew J. Schultz and David A. Kofke
Int. J. Mol. Sci. 2009, 10(6), 2798-2808; https://doi.org/10.3390/ijms10062798 - 19 Jun 2009
Cited by 43 | Viewed by 13875
Abstract
Volumetric strain can be divided into two parts: strain due to bond distance change and strain due to vacancy sources and sinks. In this paper, efforts are focused on studying the atomic lattice strain due to a vacancy in an FCC metal lattice [...] Read more.
Volumetric strain can be divided into two parts: strain due to bond distance change and strain due to vacancy sources and sinks. In this paper, efforts are focused on studying the atomic lattice strain due to a vacancy in an FCC metal lattice with molecular dynamics simulation (MDS). The result has been compared with that from a continuum mechanics method. It is shown that using a continuum mechanics approach yields constitutive results similar to the ones obtained based purely on molecular dynamics considerations. Full article
(This article belongs to the Special Issue Composite Materials)
Show Figures

Graphical abstract

Graphical abstract
Full article ">
<p>A plot of first-nearest neighbor distance from center of an atom (or void), versus simulation time steps in molecular dynamic simulations. Filled black circles indicated a full lattice and open circles indicate a vacancy, where the atom is removed at 10 ps into the data collection run. Average neighbor positions before and after atom removal are 2.891 +/–0.009 and 2.831 +/–0.010, respectively.</p>
Full article ">
<p>Void model in continuum mechanics domain.</p>
Full article ">
<p>Free body diagram under spherical coordinate system.</p>
Full article ">
<p>Plane strain element under compressive load.</p>
Full article ">
104 KiB  
Article
Termite Resistance of MDF Panels Treated with Various Boron Compounds
by Mustafa Usta, Derya Ustaomer, Saip Nami Kartal and Sedat Ondaral
Int. J. Mol. Sci. 2009, 10(6), 2789-2797; https://doi.org/10.3390/ijms10062789 - 19 Jun 2009
Cited by 12 | Viewed by 11392
Abstract
In this study, the effects of various boron compounds on the termite resistance of MDF panels were evaluated. Either borax (BX), boric acid (BA), zinc borate (ZB), or sodium perborate tetrahydrate (SPT) were added to urea-formaldehyde (UF) resin at target contents of 1%, [...] Read more.
In this study, the effects of various boron compounds on the termite resistance of MDF panels were evaluated. Either borax (BX), boric acid (BA), zinc borate (ZB), or sodium perborate tetrahydrate (SPT) were added to urea-formaldehyde (UF) resin at target contents of 1%, 1.5%, 2% and 2.5% based on dry fiber weight. The panels were then manufactured using 12% urea-formaldehyde resin and 1% NH4Cl. MDF samples from the panels were tested against the subterranean termites, Coptotermes formosanus Shiraki. Laboratory termite resistance tests showed that all samples containing boron compounds had greater resistance against termite attack compared to untreated MDF samples. At the second and third weeks of exposure, nearly 100% termite mortalities were recorded in all boron compound treated samples. The highest termite mortalities were determined in the samples with either BA or BX. Also, it was found that SPT showed notable performance on the termite mortality. As chemical loadings increased, termite mortalities increased, and at the same time the weight losses of the samples decreased. Full article
(This article belongs to the Section Biochemistry)
Show Figures


<p>Assembled containers and tests samples for termite tests.</p>
Full article ">
317 KiB  
Review
Yeast Two-Hybrid, a Powerful Tool for Systems Biology
by Anna Brückner, Cécile Polge, Nicolas Lentze, Daniel Auerbach and Uwe Schlattner
Int. J. Mol. Sci. 2009, 10(6), 2763-2788; https://doi.org/10.3390/ijms10062763 - 18 Jun 2009
Cited by 381 | Viewed by 45110
Abstract
A key property of complex biological systems is the presence of interaction networks formed by its different components, primarily proteins. These are crucial for all levels of cellular function, including architecture, metabolism and signalling, as well as the availability of cellular energy. Very [...] Read more.
A key property of complex biological systems is the presence of interaction networks formed by its different components, primarily proteins. These are crucial for all levels of cellular function, including architecture, metabolism and signalling, as well as the availability of cellular energy. Very stable, but also rather transient and dynamic protein-protein interactions generate new system properties at the level of multiprotein complexes, cellular compartments or the entire cell. Thus, interactomics is expected to largely contribute to emerging fields like systems biology or systems bioenergetics. The more recent technological development of high-throughput methods for interactomics research will dramatically increase our knowledge of protein interaction networks. The two most frequently used methods are yeast two-hybrid (Y2H) screening, a well established genetic in vivo approach, and affinity purification of complexes followed by mass spectrometry analysis, an emerging biochemical in vitro technique. So far, a majority of published interactions have been detected using an Y2H screen. However, with the massive application of this method, also some limitations have become apparent. This review provides an overview on available yeast two-hybrid methods, in particular focusing on more recent approaches. These allow detection of protein interactions in their native environment, as e.g. in the cytosol or bound to a membrane, by using cytosolic signalling cascades or split protein constructs. Strengths and weaknesses of these genetic methods are discussed and some guidelines for verification of detected protein-protein interactions are provided. Full article
(This article belongs to the Special Issue Molecular System Bioenergetics)
Show Figures


<p>The classical yeast two-hybrid system. (A) The protein of interest X, is fused to the DNA binding domain (DBD), a construct called bait. The potential interacting protein Y is fused to the activation domain (AD) and is called prey. (B) The bait, i.e. the DBD-X fusion protein, binds the upstream activator sequence (UAS) of the promoter. The interaction of bait with prey, i.e. the AD-Y fusion protein, recruits the AD and thus reconstitutes a functional transcription factor, leading to further recruitment of RNA polymerase II and subsequent transcription of a reporter gene.</p>
Full article ">
<p>Yeast two-hybrid systems, their subcellular location within a yeast cell, and their operating mode (represented at the moment of bait-prey interaction).Protein X (dark blue puzzle piece, part of bait construct) and protein Y (light blue puzzle piece, part of prey construct) directly interact (fitting puzzle pieces), thus inducing reconstitution of split-proteins (puzzle pieces of different colors in A, D, E), membrane recruitment (B, C) or protein dimerization (F). Protein fusions in bait or prey constructs are shown as solid black lines between puzzle pieces. Bait-prey interaction activates further downstream events (arrows) that directly (A) or indirectly (B, C, D, F) lead to transcriptional activation, or are independent of transcriptional activation (D, E), finally yielding screenable readouts like growth on specific media or color reactions. (A) <b><span class="html-italic">Nuclear Y2H systems</span></b> all require protein recruitment and bait-prey interaction at nuclear DNA. The <span class="underline">classic Y2H</span> and <span class="underline">RTA Y2H</span> both engage RNA polymerase II (RNA Pol II) transcription either by its activation or its inhibition. By contrast, the <span class="underline">Pol III Y2H</span>, involves RNA polymerase III (RNA Pol III) transcription. (B) <b><span class="html-italic">Ras signalling based Y2H at the plasma membrane.</span></b> The <span class="underline">SRS Y2H</span>, <span class="underline">RRS Y2H</span>, and <span class="underline">rRRS Y2H</span> are all based on protein recruitment to the plasma membrane via bait-prey interaction and subsequent activation of MAPK downstream signalling. While in the SRS and RRS Y2H the prey constructs harboring protein Y are anchored at the membrane via myristoylation to analyze interactions with cytosolic bait constructs harboring protein X, the rRRS is used to analyze interactions between soluble preys containing protein Y and partner X being a membrane protein. (C) <b><span class="html-italic">G-protein signalling-based Y2H at the plasma membrane.</span></b> In the <span class="underline">G-protein fusion Y2H</span>, bait X is a membrane or membrane-associated protein whose interaction with the prey construct disrupts protein G downstream signalling. (D) <b><span class="html-italic">Split-ubiquitin based Y2H systems</span></b> involve reconstitution of ubiquitin from two domains upon bait-prey interaction. Their subcellular localization depends on the nature of interacting proteins X or Y, and on the reporter proteins used. The <span class="underline">Split ubiquitin Y2H</span> uses non-transcriptional reporting of protein interactions in the cytosol, but can also be used for membrane proteins (not shown). The <span class="underline">MbY2H</span> is used for interaction analysis with membrane baits and thus occurs at the membrane location of protein X, e.g. the plasma membrane. The <span class="underline">CytoY2H</span> is used for membrane anchored cytosolic baits and occurs close to the ER membrane (E) <b><span class="html-italic">Split-protein sensor Y2H.</span></b> The <span class="underline">Split-Trp Y2H</span> is used to assay cytosolic bait-prey interactions based on reconstitution of an enzyme in tryptophan synthesis, allowing for non-transcriptional reporting. (F) <b><span class="html-italic">ER Y2H system.</span></b> The <span class="underline">SCINEX-P Y2H</span> allows bait-prey interaction analysis in the reducing environment of the ER, based on protein dimerization in unfolded protein signalling. ER, endoplasmic reticulum; for further abbreviations and details see chapter 3.2.</p>
Full article ">
210 KiB  
Article
Titration Calorimetry Standards and the Precision of Isothermal Titration Calorimetry Data
by Lina Baranauskienė, Vilma Petrikaitė, Jurgita Matulienė and Daumantas Matulis
Int. J. Mol. Sci. 2009, 10(6), 2752-2762; https://doi.org/10.3390/ijms10062752 - 18 Jun 2009
Cited by 77 | Viewed by 15986
Abstract
Current Isothermal Titration Calorimetry (ITC) data in the literature have relatively high errors in the measured enthalpies of protein-ligand binding reactions. There is a need for universal validation standards for titration calorimeters. Several inorganic salt co-precipitation and buffer protonation reactions have been suggested [...] Read more.
Current Isothermal Titration Calorimetry (ITC) data in the literature have relatively high errors in the measured enthalpies of protein-ligand binding reactions. There is a need for universal validation standards for titration calorimeters. Several inorganic salt co-precipitation and buffer protonation reactions have been suggested as possible enthalpy standards. The performances of several commercial calorimeters, including the VP-ITC, ITC200, and Nano ITC-III, were validated using these suggested standard reactions. Full article
(This article belongs to the Special Issue Isothermal Titration Calorimetry)
Show Figures


<p>Typical titration of 0.5 mM HNO<sub>3</sub> with 5 mM Tris base using a VP-ITC (Microcal, Inc.) microcalorimeter at 37 °C. Both the cell and syringe solutions contained 100 mM NaCl.</p>
Full article ">
<p>Tris-base – nitric acid ITC titration data obtained with a Microcal VP-ITC calorimeter at 25 °C. Filled symbols: 0.5 mM Tris base in the cell and 5 mM HNO<sub>3</sub> in the syringe. Open symbols: 0.5 mM HNO<sub>3</sub> in the cell and 5 mM Tris base in the syringe. All solutions contained 100 mM NaCl. When Tris base is in the cell (0.5 mM), the available concentration is reduced by dissolved CO<sub>2</sub>. Therefore, the stoichiometry was reduced to about 0.7. When Tris base is in the syringe (5 mM), the curve is practically unaffected by CO<sub>2</sub>. Using pre-boiled water in the preparation of Tris base solution solves the problem of reduced stoichiometry. Datapoints are the integrals of ITC raw data and the lines are fitted with Origin 5.0 using one- or two-binding site models.</p>
Full article ">
<p>Titration of 0.1 mM NaI with 1.0 mM AgNO<sub>3</sub> at 25 °C using VP-ITC (Microcal, Inc.) microcalorimeter.</p>
Full article ">
<p>Comparison of measured ligand binding enthalpies to recombinant human carbonic anhydrase II using VP-ITC and Nano ITC-III microcalorimeters. Titrations were performed at 25 °C in 50 mM sodium phosphate buffer, pH 7.0, containing 50 mM NaCl and 1% DMSO. Note that there is a significant systematic overestimation of the enthalpies measured using the Nano ITC-III calorimeter or underestimation of the enthalpies using the VP-ITC calorimeter. All raw titration curves were good with a binding stoichiometry of 0.9±0.1.</p>
Full article ">
737 KiB  
Article
Variation in Dehydration Tolerance, ABA Sensitivity and Related Gene Expression Patterns in D-Genome Progenitor and Synthetic Hexaploid Wheat Lines
by Yumeto Kurahashi, Akihiro Terashima and Shigeo Takumi
Int. J. Mol. Sci. 2009, 10(6), 2733-2751; https://doi.org/10.3390/ijms10062733 - 18 Jun 2009
Cited by 39 | Viewed by 14014
Abstract
The wild wheat Aegilops tauschii Coss. has extensive natural variation available for breeding of common wheat. Drought stress tolerance is closely related to abscisic acid (ABA) sensitivity. In this study, 17 synthetic hexaploid wheat lines, produced by crossing the tetraploid wheat cultivar Langdon [...] Read more.
The wild wheat Aegilops tauschii Coss. has extensive natural variation available for breeding of common wheat. Drought stress tolerance is closely related to abscisic acid (ABA) sensitivity. In this study, 17 synthetic hexaploid wheat lines, produced by crossing the tetraploid wheat cultivar Langdon with 17 accessions of Ae. tauschii, were used for comparative analysis of natural variation in drought tolerance and ABA sensitivity. Ae. tauschii showed wide natural variation, with weak association between the traits. Drought-sensitive accessions of Ae. tauschii exhibited significantly less ABA sensitivity. D-genome variations observed at the diploid genome level were not necessarily reflected in synthetic wheats. However, synthetic wheats derived from the parental Ae. tauschii accessions with high drought tolerance were significantly more tolerant to drought stress than those from drought-sensitive accessions. Moreover, synthetic wheats with high drought tolerance showed significantly higher ABA sensitivity than drought-sensitive synthetic lines. In the hexaploid genetic background, therefore, weak association of ABA sensitivity with drought tolerance wasobserved. To study differences in gene expression patterns between stress-tolerant and -sensitive lines, levels of two Cor/Lea and three transcription factor gene transcripts were compared. The more tolerant accession of Ae. tauschii tended to accumulate more abundant transcripts of the examined genes than the sensitive accession under stress conditions. The expression patterns in the synthetic wheats seemed to be additive for parental lines exposed to drought and ABA treatments. However, the transcript levels of transcription factor genes in the synthetic wheats did not necessarily correspond to the postulated levels based on expression in parental lines. Allopolyploidization altered the expression levels of the stress-responsive genes in synthetic wheats. Full article
(This article belongs to the Special Issue Biotic and Abiotic Stress)
Show Figures


<p>Natural variation in drought tolerance and ABA sensitivity in 30 <span class="html-italic">Ae. tauschii</span> accessions.(A) Survival rates (%) after 24 h drought stress. Means ± SDs were calculated from data from three independent experiments. In each experiment, at least 10 plants were tested. (B) Frequency distribution of the drought tolerance levels (%) in the 30 <span class="html-italic">Ae. tauschii</span> accessions. (C) Growth inhibition rate (%) in the presence of 10 μM ABA. Means ± SD were calculated from data from three independent experiments. In each experiment, at least five plants were tested. (D) Frequency distribution of ABA sensitivity in the 30 <span class="html-italic">Ae. tauschii</span> accessions.</p>
Full article ">
<p>Correlation between drought tolerance and ABA sensitivity in <span class="html-italic">Ae. tauschii</span>.(A) Scatter plot showing drought tolerance and ABA sensitivity in 30 <span class="html-italic">Ae. tauschii</span> accessions. (B) Comparison of ABA sensitivity for three <span class="html-italic">Ae. tauschii</span> groups (excluding KU-20-1, which had a distinct level of drought tolerance). Student’s <span class="html-italic">t</span>-test was used to test for statistical significance (*<span class="html-italic">P</span> &lt; 0.05) between the different categories of drought tolerance.</p>
Full article ">
<p>Variation in drought tolerance and ABA sensitivity of 17 synthetic wheats and their parental lines.(A) Drought tolerance revealed by survival rate after a 4 d drought treatment. (B) Scatter plot of drought tolerance in the synthetics and parental <span class="html-italic">Ae. tauschii</span> accessions. (C) Comparison of drought tolerance for three categories of synthetics having parental <span class="html-italic">Ae. tauschi</span> lines with distinct levels of drought tolerance. Student’s <span class="html-italic">t</span>-test was used to test for statistical significance (*<span class="html-italic">P</span> &lt; 0.05) compared with the drought-sensitive group with low drought tolerance. A, drought-sensitive accessions; B, accessions with moderate drought tolerance; C, highly drought tolerant accessions. (D) ABA sensitivity based on relative growth inhibition (%) due to 20 μM ABA treatment. Means ± SD were calculated from data from three independent experiments. In each experiment, at least five plants were tested. (E) Scatter plot of ABA sensitivity in the synthetics and parental <span class="html-italic">Ae. tauschii</span> accessions. (F) Comparison of ABA sensitivity for three categories of synthetics having parental <span class="html-italic">Ae. tauschi</span> lines with distinct levels of ABA sensitivity. I, low ABA-sensitivity accessions; II, moderately ABA-sensitive accessions; III, highly ABA-sensitive accessions.</p>
Full article ">
<p>Correlation between drought tolerance and ABA sensitivity in synthetic wheats and parental accessions.(A) Scatter plot of drought tolerance and ABA sensitivity in the parental <span class="html-italic">Ae. tauschii</span> accessions. (B) Scatter plot of drought tolerance and ABA sensitivity in the synthetic lines. (C) Comparison of ABA sensitivity for three groups of <span class="html-italic">Ae. tauschii</span> accessions with distinct levels of drought tolerance. A, drought-sensitive accessions; B, accessions with moderate drought tolerance; C, highly drought-tolerant group. (D) Comparison of ABA sensitivity for three groups of synthetic wheats with distinct levels of drought tolerance. Student’s <span class="html-italic">t</span>-test was used to test for statistical significance (*<span class="html-italic">P</span> &lt; 0.05) compared with the &gt;45% survival group with low drought tolerance.</p>
Full article ">
<p>Expression patterns of two <span class="html-italic">Cor</span>/<span class="html-italic">Lea</span> genes (<span class="html-italic">Wrab17</span> and <span class="html-italic">Wdhn13</span>) and three transcription factor genes (<span class="html-italic">TaDREB1</span>, <span class="html-italic">WABI5</span> and <span class="html-italic">TaOBF1</span>) in the synthetic wheats, parental <span class="html-italic">Ae. tauschii</span> accessions and Langdon after ABA and drought-stress treatment.(A) ABA-responsive expression. Gene expression patterns were revealed by RT-PCR analysis using the same set of RNA preparations. <span class="html-italic">Actin</span> was used as internal control. Total RNA was extracted from leaves of seedlings after the indicated times in the 20 μM ABA treatment. (B) Drought-responsive expression. Total RNA was extracted from leaves of seedlings after the indicated drought treatment.</p>
Full article ">
<p>Comparison of transcript levels in synthetic wheats and their parental lines. Quantitative RT-PCR analysis was conducted using leaves from ABA- and drought stress-treated seedlings. The postulated levels in the synthetic wheats were calculated as 2:1 ratio mixtures of the transcript levels of the parental Langdon and <span class="html-italic">Ae. tauschii</span> accessions. Each transcript level was represented as the value relative to the Langdon level at 0.5 h.(A) <span class="html-italic">TaDREB1</span> transcript levels after ABA treatment. (B) <span class="html-italic">WABI5</span> transcript levels after ABA treatment. (C) <span class="html-italic">TaOBF1</span> transcript levels after ABA treatment. (D) <span class="html-italic">TaOBF1</span> transcript levels under drought conditions.</p>
Full article ">
458 KiB  
Article
Amino Acid Synthesis in a Supercritical Carbon Dioxide - Water System
by Kouki Fujioka, Yasuhiro Futamura, Tomoo Shiohara, Akiyoshi Hoshino, Fumihide Kanaya, Yoshinobu Manome and Kenji Yamamoto
Int. J. Mol. Sci. 2009, 10(6), 2722-2732; https://doi.org/10.3390/ijms10062722 - 15 Jun 2009
Cited by 6 | Viewed by 12986
Abstract
Mars is a CO2-abundant planet, whereas early Earth is thought to be also CO2-abundant. In addition, water was also discovered on Mars in 2008. From the facts and theory, we assumed that soda fountains were present on both planets, [...] Read more.
Mars is a CO2-abundant planet, whereas early Earth is thought to be also CO2-abundant. In addition, water was also discovered on Mars in 2008. From the facts and theory, we assumed that soda fountains were present on both planets, and this affected amino acid synthesis. Here, using a supercritical CO2/liquid H2O (10:1) system which mimicked crust soda fountains, we demonstrate production of amino acids from hydroxylamine (nitrogen source) and keto acids (oxylic acid sources). In this research, several amino acids were detected with an amino acid analyzer. Moreover, alanine polymers were detected with LC-MS. Our research lights up a new pathway in the study of life’s origin. Full article
(This article belongs to the Special Issue Origin of Life)
Show Figures

Graphical abstract

Graphical abstract
Full article ">
<p>Chromatograms of amino-acid analysis. (a) Amino acid standards. (b) Pyruvic acid + Hydroxylamine at 31 ºC. (c) Pyruvic acid + Hydroxylamine at 60 ºC. (d) Glyoxylic acid + Hydroxylamine at 31 ºC. (e) Glyoxylic acid + Hydroxylamine at 60 ºC.</p>
Full article ">
<p>Total ion chromatogram (TIC) and MS chromatograms of alanine monomer and polymers.</p>
Full article ">
<p>Diagram of the autoclave reactor for the supercritical CO<sub>2</sub> reaction.</p>
Full article ">
<p>Reaction overview of the supercritical CO<sub>2</sub>/liquid H<sub>2</sub>O reactions. (a) Hydroxylamine + Pyruvic acid (Pyruvic acid oxime) (b) Hydroxylamine + Glyoxylic acid (Glyoxylic acid oxime).</p>
Full article ">
2482 KiB  
Review
Precambrian Lunar Volcanic Protolife
by Jack Green
Int. J. Mol. Sci. 2009, 10(6), 2681-2721; https://doi.org/10.3390/ijms10062681 - 11 Jun 2009
Cited by 2 | Viewed by 13201
Abstract
Five representative terrestrial analogs of lunar craters are detailed relevant to Precambrian fumarolic activity. Fumarolic fluids contain the ingredients for protolife. Energy sources to derive formaldehyde, amino acids and related compounds could be by flow charging, charge separation and volcanic shock. With no [...] Read more.
Five representative terrestrial analogs of lunar craters are detailed relevant to Precambrian fumarolic activity. Fumarolic fluids contain the ingredients for protolife. Energy sources to derive formaldehyde, amino acids and related compounds could be by flow charging, charge separation and volcanic shock. With no photodecomposition in shadow, most fumarolic fluids at 40 K would persist over geologically long time periods. Relatively abundant tungsten would permit creation of critical enzymes, Fischer-Tropsch reactions could form polycyclic aromatic hydrocarbons and soluble volcanic polyphosphates would enable assembly of nucleic acids. Fumarolic stimuli factors are described. Orbital and lander sensors specific to protolife exploration including combined Raman/laser-induced breakdown spectrocsopy are evaluated. Full article
(This article belongs to the Special Issue Origin of Life)
Show Figures


<p>Protolife target site #1 – Breached volcano and associated features.Interior of Copernicus (97) km diameter) showing (a) possible breached volcano produced by a directed volcanic blast, (b) multiple volcano-like structures on crater floor similar to multiple volcanoes on the floor of the Tengger caldera in west Java, (c) sinuous leveed channels similar to pyroxene andesite lava levees in the Gedeh caldera, west Java, (d) horizontal terraces of different ages similar to terraces in the Fernandina caldera, Galapagos Islands, and (e) apparent low dip angles of rim rocks as in calderas on earth. Photo of Lunar Orbiter II, Frame 162 H<sub>3</sub> courtesy of the National Space Science Data Center and principal investigator Mr. L.J. Kosofsky.</p>
Full article ">
<p>Protolife target site #2 – Volcanic domes.Domes in the Aitken crater. Aitken is located on the northern border of a major basin on the farside of the moon. The crater is about 150 km in diameter. An arrow in the upper Orbiter image points to a crater cluster within ramparts containing what appear to be volcanic domes. Another image of Aitken showing these domes is the Apollo 17 photograph AS17-151-23210. A high resolution Orbiter II image Frame 33 H shown on the bottom left is compared with a ramparted volcanic dome and crater cluster at Diamond Craters, (Central Crater Complex), Oregon. The approximate width of the dome cluster in Aitken is about 4.5 kilometers; that of Diamond Craters is about a kilometer. Hundreds of domal features occur on the moon, some with dimpled summits as in Euler, Alphonsus and near Hevelius and others within angular ramparts as in Barbier (60 km diameter). Shown is lunar Orbiter II photo (Frame 33H) courtesy of the National Space Science Data Center and principal investigator Mr. L.J. Kosofsky.</p>
Full article ">
<p>Comparison of arcuate central mountains in Zucchius (Smart-1 Imagery) with arcuate rhyolitic domes in the Valles caldera (NASA photo STS 062-100-195) and arcuate rhyolitic and trachyandesitic domes in the Amealco caldera, Mexico. Amealco imagery by CARDI (Mexico Digital Cartography) provided to CENAPRED (Centro Nacional de Prevención de Desastres). North to top for Zucchius and Amealco and bottom for Valles.</p>
Full article ">
<p>Protolife target site #3 – Dark spots on crater floors.Dashed lines enclose dark spots with small summit pits on the floor of Alphonsus. Some of the dark spots which may host buried fumarolic vents are named. Solid lines enclose craterlets except for “P” which is the central peak that was the source of carbon-bearing gases in a November 1958 lunar transient event recorded by N. Kozyrev in Russia. Dr. Nikolay A. Kozyrev, a Soviet astronomer, told the author in 1960 that he keenly wished to meet Dr. D. Alter, an American astronomer, who observed a haze in Alphonsus on October 26, 1956 that led to Kozyrev’s concentration on Alphonsus. Kozyrev (deceased February 27, 1983) was never able to travel to the United States. Dr. Dinsmore Alter died on September 20, 1968. For the purposes of this paper, the author calls the central ridge in Alphonsus, “Alter Ridge” and the central peak, “Kozyrev Peak.” Thus Kozyrev meets Alter. The map is based on 3.0-cm wavelength high resolution radar images and orbital photographs [<a href="#b6-ijms-10-02681" class="html-bibr">6</a>].</p>
Full article ">
<p>Protolife target site #4 – Polar shadowed zones.<b>(a) Lunar South Pole</b>Lunar South Pole region imaged by the Clementine probe of over 1500 UV-Visible images produced by the U.S. Geological Survey. Resolution is 200 meters. Crater in lower right-hand corner is Schrödinger (diameter is 320 km). Clementine mosaic is courtesy of the Naval Research Laboratory.<b>(b) Schrödinger Crater</b>The black spot in Schrödinger is believed to be one of the largest volcanoes on the moon. Note the summit pit in Schrödinger about 2 km in diameter and the interior partially concentric ring structure. Schrödinger is considered by this author to be a caldera.</p>
Full article ">
<p>Protolife target site #5 – Crater flanks of Copernicus (top, north to right) exhibit well-defined “loop” patterns analogous to “loop” patterns [<a href="#b10-ijms-10-02681" class="html-bibr">10</a>] on the flank of Halemaumau, Hawaii (bottom) caused by inflation, deflation and migration of pockets of magma on the crater flank. The “loops” in Hawaii define fumaroles and craterlets (later covered with lava flows). The now extinct fumarole, Perret, is denoted by “A”. “B” is a fault scarp. The Copernicus “loop” also hosts a dark field of volcanic domes. Eratosthenes is in the lower right of top photo. Lunar photo is from Plate C 2439, Consolidated Lunar Atlas, Lunar and Planetary Laboratory, Houston.</p>
Full article ">
<p>Protolife target site #6 – Ring fractures in calderas.Shadowed portions of fractures in the Lavoisier group of craters. Lavoisier has a diameter of 70 km. An arrow in this crater points to a small double ringed feature similar to craters C and M to the east with diameters of 35 and 18 km respectively. Other floor-fractured craters (H, E, and D) are shown as well as an unlettered crater on the western border. Crater D has been re-named “Von Braun”. Gaddis <span class="html-italic">et al.</span> [<a href="#b11-ijms-10-02681" class="html-bibr">11</a>] verify pyroclastic deposits in the Lavoisier area based on multispectral data from the Clementine mission. The spectral data resemble the lunar highlands with weak mafic bands and relatively high UV/VIS ratios. An impact origin of these craters resulting in volcanism is rejected. The Lavoisier area craters show features similar to over 40 calderas of <span class="html-italic">bona fide</span> volcanic origin on earth. Orbiter IV photos, Frame 189 H<sub>2</sub>, Frame 193 H<sub>2</sub> and Frame 183 H<sub>1</sub> courtesy of the National Space Science Data Center and principal investigator Mr. L.J. Kosofsky.</p>
Full article ">
<p>April 7, 1906 eruption of Vesuvius showing shock waves observed by Dr. F. Perret. Obviously, in 1906, cameras could not record this phenomenon. Perret drew them in. However, these waves are real.</p>
Full article ">
<p>Unpolarized absorption spectra of “fire fountain” Apollo 17 orange and green glass from Apollo sample 74220.61 compared with synthetic glasses quenched at log Po<sub>2</sub> at −9.1 (at 1350°C) and −8.1 (at 1400°C) modified after Mao <span class="html-italic">et al.</span> [<a href="#b28-ijms-10-02681" class="html-bibr">28</a>]. The synthetic glass of log Po<sub>2</sub> = −9.1 is shown as a solid line; that of synthetic glass of log Po<sub>2</sub> = −8.1 is shown as a dashed line. The absorption coefficient of the green (lunar) glass is superposed as a green line and is equivalent to a log Po<sub>2</sub> of −8.1. The orange (lunar) glass is superposed as an orange line and is equivalent to a highly oxidized log Po<sub>2</sub> significantly higher than −8.1. Terrestrial rocks have a partial pressure of oxygen of about 10<sup>−9</sup> atmospheres. Hydrous melts (a function of the partial pressure of oxygen) were probable in the Archean on the moon.</p>
Full article ">
615 KiB  
Article
Measurement of Nanomolar Dissociation Constants by Titration Calorimetry and Thermal Shift Assay – Radicicol Binding to Hsp90 and Ethoxzolamide Binding to CAII
by Asta Zubrienė, Jurgita Matulienė, Lina Baranauskienė, Jelena Jachno, Jolanta Torresan, Vilma Michailovienė, Piotras Cimmperman and Daumantas Matulis
Int. J. Mol. Sci. 2009, 10(6), 2662-2680; https://doi.org/10.3390/ijms10062662 - 10 Jun 2009
Cited by 51 | Viewed by 14720
Abstract
The analysis of tight protein-ligand binding reactions by isothermal titration calorimetry (ITC) and thermal shift assay (TSA) is presented. The binding of radicicol to the N-terminal domain of human heat shock protein 90 (Hsp90aN) and the binding of ethoxzolamide to human carbonic [...] Read more.
The analysis of tight protein-ligand binding reactions by isothermal titration calorimetry (ITC) and thermal shift assay (TSA) is presented. The binding of radicicol to the N-terminal domain of human heat shock protein 90 (Hsp90aN) and the binding of ethoxzolamide to human carbonic anhydrase (hCAII) were too strong to be measured accurately by direct ITC titration and therefore were measured by displacement ITC and by observing the temperature-denaturation transitions of ligand-free and ligand-bound protein. Stabilization of both proteins by their ligands was profound, increasing the melting temperature by more than 10 ºC, depending on ligand concentration. Analysis of the melting temperature dependence on the protein and ligand concentrations yielded dissociation constants equal to 1 nM and 2 nM for Hsp90aN-radicicol and hCAII-ethoxzolamide, respectively. The ligand-free and ligand-bound protein fractions melt separately, and two melting transitions are observed. This phenomenon is especially pronounced when the ligand concentration is equal to about half the protein concentration. The analysis compares ITC and TSA data, accounts for two transitions and yields the ligand binding constant and the parameters of protein stability, including the Gibbs free energy and the enthalpy of unfolding. Full article
(This article belongs to the Special Issue Isothermal Titration Calorimetry)
Show Figures


<p>Panel A. Isothermal titration calorimetry data from radicicol binding to Hsp90αN. Upper graph – raw ITC data, lower graph – integrated ITC data with the curve fit to the standard single binding site model. The cell contained 4 μM protein, while the syringe contained 40 μM radicicol in the same buffer - 50 mM sodium phosphate, pH 7.5, 0.5% DMSO, 100 mM NaCl, at 25 °C. Panel B. Isothermal titration calorimetry displacement assay. All conditions are the same as in Panel A, except there was 1 mM compound 1 added to the calorimeter cell. Panel C. Chemical structures of radicicol and compound 1. Panel D. Isothermal titration calorimetry data from ethoxzolamide binding to hCAII. The cell contained 7 μM protein, while the syringe contained 100 μM ethoxzolamide in the same buffer - 50 mM sodium phosphate, pH 7.0, 0.5% DMSO, 50 mM NaCl, at 37 °C.</p>
Full article ">
<p>Denaturation profiles of Hsp90αN or hCAII in the presence of inhibitors. Panel A. Hsp90αN (14 μM) in 50 mM Tris buffer, pH 7.5, with added radicicol: ▪ - 0 μM, ▴ - 2 μM, × - 3 μM, Δ - 6 μM, ○ - 10 μM, + - 20 μM, and − - 50 μM. Panel B. hCAII (5 μM) in 50 mM phosphate buffer, pH 7.0, containing 50 mM NaCl, with added ethoxzolamide: ▪ - 0 μM, ▴ - 1.5 μM, × - 2 μM, Δ - 3 μM, and ○ - 50 μM. Increased inhibitor concentrations raise the melting temperature of both proteins by more than 10 ºC, depending on concentration. Two transitions are observed when both free and ligand-bound proteins are present. Heights of both transitions are additive and proportional to the fraction of saturation by the inhibitor. The data points represent experimental observations while the lines are fit to <a href="#FD10" class="html-disp-formula">Equation (10)</a>. Parameters are listed in <a href="#t1-ijms-10-02662" class="html-table">Table 1</a>. Panel C. DSC profiles of Hsp90αN (120 μM) with radicicol: dashed line – 0 μM, dot-dashed line – 60 μM, and solid line – 360 μM. Panel D. DSC profiles of hCAII (100 μM) with ethoxzolamide: dashed line – 0 μM, dotted line – 22 μM, dot-dashed line – 50 μM, and solid line – 1 mM.</p>
Full article ">
<p>The protein melting temperature dependence on inhibitor concentration. Panel A. Hsp90αN with radicicol (from the melting curves in <a href="#f2-ijms-10-02662" class="html-fig">Figure 2A</a>). Panel B. hCAII with ethoxzolamide (from the melting curves in <a href="#f2-ijms-10-02662" class="html-fig">Figure 2B</a>). The data points show the melting temperatures of the ligand-bound (•) and ligand-free (▪) forms of the protein. The leftmost data point is the control where no inhibitor was added. Lines are the fit to the data according to <a href="#FD12" class="html-disp-formula">Equation (12)</a>.</p>
Full article ">
<p>The dependence of the melting temperature of Hsp90αN on radicicol concentration. The data points show the melting temperatures of ligand-bound components at three protein concentrations: ▪ - 4.1 μM, Δ - 7.5 μM, and • - 14 μM. The <span class="html-italic">T<sub>m</sub></span> of the ligand-free Hsp90αN component is omitted for clarity. The leftmost data points are controls with no radicicol added. Lines are drawn according to <a href="#FD12" class="html-disp-formula">Equation (12)</a> and represent the best possible fit of the data. The solid line is for 4.1 μM, the dashed line for 7.5 μM, and the dotted line for 14 μM protein.</p>
Full article ">
<p>The dependence of Hsp90αN melting temperature on radicicol concentration with various rates of heating. Data points show the melting temperatures of ligand-bound and free components at three heating rates: ▪ - 2 ºC/min, Δ - 1 ºC/min, and • - 0.5 ºC/min. Lines are drawn according to <a href="#FD12" class="html-disp-formula">Equation (12)</a>. Note that the <span class="html-italic">T<sub>m</sub></span> values obtained at different heating rates yield the same binding constant.</p>
Full article ">
1633 KiB  
Review
Periodic Density Functional Theory Investigation of the Uranyl Ion Sorption on Three Mineral Surfaces: A Comparative Study
by Jérôme Roques, Edouard Veilly and Eric Simoni
Int. J. Mol. Sci. 2009, 10(6), 2633-2661; https://doi.org/10.3390/ijms10062633 - 4 Jun 2009
Cited by 32 | Viewed by 21133
Abstract
Canister integrity and radionuclides retention is of prime importance for assessing the long term safety of nuclear waste stored in engineered geologic depositories. A comparative investigation of the interaction of uranyl ion with three different mineral surfaces has thus been undertaken in order [...] Read more.
Canister integrity and radionuclides retention is of prime importance for assessing the long term safety of nuclear waste stored in engineered geologic depositories. A comparative investigation of the interaction of uranyl ion with three different mineral surfaces has thus been undertaken in order to point out the influence of surface composition on the adsorption mechanism(s). Periodic DFT calculations using plane waves basis sets with the GGA formalism were performed on the TiO2(110), Al(OH)3(001) and Ni(111) surfaces. This study has clearly shown that three parameters play an important role in the uranyl adsorption mechanism: the solvent (H2O) distribution at the interface, the nature of the adsorption site and finally, the surface atoms’ protonation state. Full article
(This article belongs to the Special Issue Application of Density Functional Theory)
Show Figures

Graphical abstract

Graphical abstract
Full article ">
<p>Dry TiO<sub>2</sub> rutile (110) face.</p>
Full article ">
<p>Top view of the 2×3 supercell for the 4 / 2 case. The oxygen atoms of the added water molecules (O<sub>t</sub>) are displayed in yellow colour for clarity.</p>
Full article ">
<p>Thetwo-layer gibbsite model used for all calculations.</p>
Full article ">
<p>An example of the two possible water adsorption structures (after optimization) is presented on a simplified scheme in panel (a) and (b). Hydrogen bonds are displayed in red color with distances.(a): In blue color, water molecule is linked with two out of plane surface hydrogen atoms and one surface oxygen atom.(b): In green color, water molecule is linked with only one out of plane surface hydrogen atom and two surface oxygen atoms.(c): Top view of the four kinds of H<sub>2</sub>O adsorption sites.</p>
Full article ">
<p>Example of a water monolayer on the (001) gibbsite face. Hydrogen bonds are displayed in red color with distances.</p>
Full article ">
<p>(a) Top view of the water adsorption sites on Ni(111). (1) top, (2) face centered cubic (fcc site), (3) bridge and (4) hexagonal compact (hcp site) adsorption sites. (b) Cut view of the four layer Ni(111) model.</p>
Full article ">
<p>The three water layers on the Ni(111) face.</p>
Full article ">
<p>Pentahydrated uranyl structure [UO<sub>2</sub>(H<sub>2</sub>O)<sub>5</sub>]<sup>2+</sup>.</p>
Full article ">
<p>The three studied adsorption sites.</p>
Full article ">
129 KiB  
Review
The Eukaryotic Cell Originated in the Integration and Redistribution of Hyperstructures from Communities of Prokaryotic Cells Based on Molecular Complementarity
by Vic Norris and Robert Root-Bernstein
Int. J. Mol. Sci. 2009, 10(6), 2611-2632; https://doi.org/10.3390/ijms10062611 - 4 Jun 2009
Cited by 12 | Viewed by 12089
Abstract
In the “ecosystems-first” approach to the origins of life, networks of non-covalent assemblies of molecules (composomes), rather than individual protocells, evolved under the constraints of molecular complementarity. Composomes evolved into the hyperstructures of modern bacteria. We extend the ecosystems-first approach to explain the [...] Read more.
In the “ecosystems-first” approach to the origins of life, networks of non-covalent assemblies of molecules (composomes), rather than individual protocells, evolved under the constraints of molecular complementarity. Composomes evolved into the hyperstructures of modern bacteria. We extend the ecosystems-first approach to explain the origin of eukaryotic cells through the integration of mixed populations of bacteria. We suggest that mutualism and symbiosis resulted in cellular mergers entailing the loss of redundant hyperstructures, the uncoupling of transcription and translation, and the emergence of introns and multiple chromosomes. Molecular complementarity also facilitated integration of bacterial hyperstructures to perform cytoskeletal and movement functions. Full article
(This article belongs to the Special Issue Origin of Life)
333 KiB  
Review
Application of Ionic Liquids in High Performance Reversed-Phase Chromatography
by Ye Wang, Minglei Tian, Wentao Bi and Kyung Ho Row
Int. J. Mol. Sci. 2009, 10(6), 2591-2610; https://doi.org/10.3390/ijms10062591 - 4 Jun 2009
Cited by 92 | Viewed by 14490
Abstract
Ionic liquids, considered “green” chemicals, are widely used in many areas of analytical chemistry due to their unique properties. Recently, ionic liquids have been used as a kind of novel additive in separation and combined with silica to synthesize new stationary phase as [...] Read more.
Ionic liquids, considered “green” chemicals, are widely used in many areas of analytical chemistry due to their unique properties. Recently, ionic liquids have been used as a kind of novel additive in separation and combined with silica to synthesize new stationary phase as separation media. This review will focus on the properties and mechanisms of ionic liquids and their potential applications as mobile phase modifier and surface-bonded stationary phase in reversed-phase high performance liquid chromatography (RP-HPLC). Ionic liquids demonstrate advantages and potential in chromatographic field. Full article
(This article belongs to the Section Green Chemistry)
Show Figures


<p>Scheme illustrating potential reorientation of bonded imidazolium ligands in response to deprotonation of residual silanols. Anion is not shown for clarity (adapted from [<a href="#b37-ijms-10-02591" class="html-bibr">37</a>]).</p>
Full article ">
<p>Synthesis steps used in the preparation of zwitterionic stationary phase [<a href="#b43-ijms-10-02591" class="html-bibr">43</a>].</p>
Full article ">
<p>Scheme illustrating the modification of silica particles with the synthesized 1-allyl-3-(butyl-4-sulfonate)imidazolium ionic liquids [<a href="#b49-ijms-10-02591" class="html-bibr">49</a>].</p>
Full article ">
<p>Separation of test mixtures composed of cytosine (1), thymine (2), adenine (3), 2-aminopyrimidine (4), and 6-chloroguanine (5). Mobile phase: water, detection: UV at 254 nm [<a href="#b55-ijms-10-02591" class="html-bibr">55</a>].</p>
Full article ">
<p>Chromatograms of ephedrines with a mobile phase containing different concentrations of [BMIM][BF4] at pH 3.0. (a) 0, (b) 2.6, (c) 5.2, (d) 20.8, and (e) 62.4 mM. Chromatographic conditions: column: C18 (5 μm, 100×4.6 mm I.D.); rate-flow: 1.0 mL/min; detection: 252 nm. Peaks: (1) NE, (2) E, (3) PE, (4) ME, [<a href="#b57-ijms-10-02591" class="html-bibr">57</a>].</p>
Full article ">
<p>Effect of different ionic liquids on the separation of the seven antibiotics studied. Mobile phase: 10 mmol/L ammonium acetate at pH 3.0 with 13% (v/v) acetonitrile and (a) 6 mmol/L [Et4N][BF4]; (b) 6 mmol/L [EMIM][BF4]; (c) 6 mmol/L [BMIM][BF4]; (d) 6 mmol/L [HMIM][BF4]; (e) 6 mmol/L [MOIM][BF4]. Flow rate: 1 mL/min. Detection: λexc=280 nm and λem=450 nm. Peak identification: 1, FLERO; 2, CIPRO; 3, LOME; 4, DANO; 5, ENRO; 6, SARA and 7, DIFLO [<a href="#b74-ijms-10-02591" class="html-bibr">74</a>].</p>
Full article ">
227 KiB  
Article
Tryptophanase-Catalyzed L-Tryptophan Synthesis from D-Serine in the Presence of Diammonium Hydrogen Phosphate
by Akihiko Shimada, Haruka Ozaki, Takeshi Saito and Fujii Noriko
Int. J. Mol. Sci. 2009, 10(6), 2578-2590; https://doi.org/10.3390/ijms10062578 - 3 Jun 2009
Cited by 12 | Viewed by 11950
Abstract
Tryptophanase, an enzyme with extreme absolute stereospecificity for optically active stereoisomers, catalyzes the synthesis of L-tryptophan from L-serine and indole through a β-substitution mechanism of the ping-pong type, and has no activity on D-serine. We previously reported that tryptophanase changed its stereospecificity to [...] Read more.
Tryptophanase, an enzyme with extreme absolute stereospecificity for optically active stereoisomers, catalyzes the synthesis of L-tryptophan from L-serine and indole through a β-substitution mechanism of the ping-pong type, and has no activity on D-serine. We previously reported that tryptophanase changed its stereospecificity to degrade D-tryptophan in highly concentrated diammonium hydrogen phosphate, (NH4)2HPO4 solution. The present study provided the same stereospecific change seen in the D-tryptophan degradation reaction also occurs in tryptophan synthesis from D-serine. Tryptophanase became active to D-serine to synthesize L-tryptophan in the presence of diammonium hydrogen phosphate. This reaction has never been reported before. D-serine seems to undergo β-replacement via an enzyme-bonded α-aminoacylate intermediate to yield L-tryptophan. Full article
(This article belongs to the Special Issue Origin of Life)
Show Figures


<p>Thin layer chromatogram of the tryptophan synthesized from <span class="html-small-caps">l</span>- or <span class="html-small-caps">d</span>-serine by tryptophanase. For comparison, <span class="html-small-caps">d</span>-tryptophan, <span class="html-small-caps">l</span>-tryptophan, <span class="html-small-caps">d</span>-serine and <span class="html-small-caps">l</span>-serine were developed in the left half. Reaction products were developed in the right half. Lane1: <span class="html-small-caps">l</span>-serine + indole + tryptophanase in a potassium phosphate buffer; lane 2: <span class="html-small-caps">d</span>-serine + indole + 20 % saturation diammoniumhydrogen phosphate in a potassium phosphate buffer; lane 3: <span class="html-small-caps">d</span>-serine + indole + tryptophanase in a potassium phosphate buffer; lane 4: <span class="html-small-caps">d</span>-serine + indole + tryptophanase + 20 % saturation diammoniumhydrogen phosphate in a potassium phosphate buffer.</p>
Full article ">
<p>Tryptophan synthesis from <span class="html-small-caps">l</span>- or <span class="html-small-caps">d</span>-serine against diammonium hydrogen phosphate saturation concentration. ○: <span class="html-small-caps">l</span>-serine, •: <span class="html-small-caps">d</span>-serine.</p>
Full article ">
<p>Resolution chromatograms of the reactant products (monitored by UV detection at λ = 280 nm). (a) Advanced resolution chromatography was carried out to determine a retention time of <span class="html-small-caps">l</span>-tryptophan. (b) There is no tryptophan peak in the absence of tryptophanase. (c) <span class="html-small-caps">l</span>-tryptophan (a peak at 14.6 min) was synthesized from <span class="html-small-caps">l</span>-serine and indole by tryptophanase in a potassium phosphate buffer solution. (d) Tryptophan was synthesized from <span class="html-small-caps">d</span>-serine and indole by tryptophanase in the presence of diammonium hydrogen phosphate.</p>
Full article ">
<p>Detection of the reactant product with CD detector. (a) <span class="html-small-caps">d</span>, <span class="html-small-caps">l</span>-tryptophan as a standard substance was eluted onto a resolution column Crownpack CR (+). (b) The tryptophan synthesized was eluted onto the same column. Optical isomeric form of the tryptophan was established to be <span class="html-small-caps">l</span> type.</p>
Full article ">
186 KiB  
Review
QSPR Studies on Aqueous Solubilities of Drug-Like Compounds
by Pablo R. Duchowicz and Eduardo A. Castro
Int. J. Mol. Sci. 2009, 10(6), 2558-2577; https://doi.org/10.3390/ijms10062558 - 3 Jun 2009
Cited by 53 | Viewed by 14764
Abstract
A rapidly growing area of modern pharmaceutical research is the prediction of aqueous solubility of drug-sized compounds from their molecular structures. There exist many different reasons for considering this physico-chemical property as a key parameter: the design of novel entities with adequate aqueous [...] Read more.
A rapidly growing area of modern pharmaceutical research is the prediction of aqueous solubility of drug-sized compounds from their molecular structures. There exist many different reasons for considering this physico-chemical property as a key parameter: the design of novel entities with adequate aqueous solubility brings many advantages to preclinical and clinical research and development, allowing improvement of the Absorption, Distribution, Metabolization, and Elimination/Toxicity profile and “screenability” of drug candidates in High Throughput Screening techniques. This work compiles recent QSPR linear models established by our research group devoted to the quantification of aqueous solubilities and their comparison to previous research on the topic. Full article
(This article belongs to the Special Issue Recent Advances in QSAR/QSPR Theory)
Show Figures

Graphical abstract

Graphical abstract
Full article ">
<p>Balanced data set of molecular structures under analysis. Training Set 1–97 Test Set 98–145.</p>
Full article ">
<p>Balanced data set of molecular structures under analysis. Training Set 1–97 Test Set 98–145.</p>
Full article ">
<p>Balanced data set of molecular structures under analysis. Training Set 1–97 Test Set 98–145.</p>
Full article ">
<p>Balanced data set of molecular structures under analysis. Training Set 1–97 Test Set 98–145.</p>
Full article ">
<p>Balanced data set of molecular structures under analysis. Training Set 1–97 Test Set 98–145.</p>
Full article ">
<p>Normal distribution of the experimental log<sub>10</sub><span class="html-italic">Sol</span> values under analysis (<span class="html-italic">N</span> = 166).</p>
Full article ">
1267 KiB  
Review
Trends in the Molecular Pathogenesis and Clinical Therapeutics of Common Neurodegenerative Disorders
by Yahya E. Choonara, Viness Pillay, Lisa C. Du Toit, Girish Modi, Dinesh Naidoo, Valence M.K. Ndesendo and Sibongile R. Sibambo
Int. J. Mol. Sci. 2009, 10(6), 2510-2557; https://doi.org/10.3390/ijms10062510 - 3 Jun 2009
Cited by 66 | Viewed by 20023
Abstract
The term neurodegenerative disorders, encompasses a variety of underlying conditions, sporadic and/or familial and are characterized by the persistent loss of neuronal subtypes. These disorders can disrupt molecular pathways, synapses, neuronal subpopulations and local circuits in specific brain regions, as well as higher-order [...] Read more.
The term neurodegenerative disorders, encompasses a variety of underlying conditions, sporadic and/or familial and are characterized by the persistent loss of neuronal subtypes. These disorders can disrupt molecular pathways, synapses, neuronal subpopulations and local circuits in specific brain regions, as well as higher-order neural networks. Abnormal network activities may result in a vicious cycle, further impairing the integrity and functions of neurons and synapses, for example, through aberrant excitation or inhibition. The most common neurodegenerative disorders are Alzheimer’s disease, Parkinson’s disease, Amyotrophic Lateral Sclerosis and Huntington’s disease. The molecular features of these disorders have been extensively researched and various unique neurotherapeutic interventions have been developed. However, there is an enormous coercion to integrate the existing knowledge in order to intensify the reliability with which neurodegenerative disorders can be diagnosed and treated. The objective of this review article is therefore to assimilate these disorders’ in terms of their neuropathology, neurogenetics, etiology, trends in pharmacological treatment, clinical management, and the use of innovative neurotherapeutic interventions. Full article
(This article belongs to the Special Issue Advances in Molecular Neuropathology)
Show Figures


<p>Schematic diagram outlining the pathogenesis of common neurodegenerative diseases (Adapted from Yuan and Yanker, [<a href="#b16-ijms-10-02510" class="html-bibr">16</a>]).</p>
Full article ">
<p>The role of glial cells in central nervous system inflammation and neurodegeneration. BDNF = brain-derived neurotrophic factor, MP = macrophages, MMP = membrane metalloproteinase, TIMP = tissue inhibitors of metalloproteinase (Adapted from: Ghorpade <span class="html-italic">et al.</span> [<a href="#b113-ijms-10-02510" class="html-bibr">113</a>]).</p>
Full article ">
<p>Molecular mechanisms leading to cell death in neurons and the yeast PD model (Adapted from: Winderickx <span class="html-italic">et al.</span> [<a href="#b164-ijms-10-02510" class="html-bibr">164</a>]).</p>
Full article ">
<p>Depiction of adult neural stem demonstrating their intrinsic potential to generate cell types of the brain and spinal cord (Adapted from: Karimi and Eftekharpour, Fehlings lab, McEwan Centre for Regnerative Medicine; <a href="http://www.mcewencentre.com/res_prog_scnd.asp" target="_blank">www.mcewencentre.com/res_prog_scnd.asp</a>, [<a href="#b182-ijms-10-02510" class="html-bibr">182</a>]).</p>
Full article ">
<p>Schematic of SOD-1 mutations activating cell death pathways in familial Amyotrophic Lateral Sclerosis (Source: Yuan and Yankner, [<a href="#b16-ijms-10-02510" class="html-bibr">16</a>]).</p>
Full article ">
<p>Schematic depicting a pathway of oxidative damage in HD (Source: Trushina and McMurray, [<a href="#b232-ijms-10-02510" class="html-bibr">232</a>]).</p>
Full article ">
<p>A minimally-invasive intrathecal drug delivery system for spinal cord injury repair (Source: Shoichet lab, McEwen Centre for Regenerative Medicine, [<a href="#b276-ijms-10-02510" class="html-bibr">276</a>]).</p>
Full article ">
282 KiB  
Article
Purification, Crystallization and Preliminary X-ray Crystallographic Studies of RAIDD Death-Domain (DD)
by Tae-ho Jang and Hyun Ho Park
Int. J. Mol. Sci. 2009, 10(6), 2501-2509; https://doi.org/10.3390/ijms10062501 - 3 Jun 2009
Cited by 8 | Viewed by 10597
Abstract
Caspase-2 activation by formation of PIDDosome is critical for genotoxic stress induced apoptosis. PIDDosome is composed of three proteins, RAIDD, PIDD, and Caspase-2. RAIDD is an adaptor protein containing an N-terminal Caspase-Recruiting-Domain (CARD) and a C-terminal Death-Domain (DD). Its interactions with [...] Read more.
Caspase-2 activation by formation of PIDDosome is critical for genotoxic stress induced apoptosis. PIDDosome is composed of three proteins, RAIDD, PIDD, and Caspase-2. RAIDD is an adaptor protein containing an N-terminal Caspase-Recruiting-Domain (CARD) and a C-terminal Death-Domain (DD). Its interactions with Caspase-2 and PIDD through CARD and DD respectively and formation of PIDDosome are important for the activation of Caspase-2. RAIDD DD cloned into pET26b vector was expressed in E. coli cells and purified by nickel affinity chromatography and gel filtration. Although it has been known that the most DDs are not soluble in physiological condition, RAIDD DD was soluble and interacts tightly with PIDD DD in physiological condition. The purified RAIDD DD alone has been crystallized. Crystals are trigonal and belong to space group P3121 (or its enantiomorph P3221) with unit-cell parameters a = 56.3, b = 56.3, c = 64.9 Å and γ = 120°. The crystals were obtained at room temperature and diffracted to 2.0 Å resolution. Full article
(This article belongs to the Section Biochemistry)
Show Figures


<p>Purification of the RAIDD DD. The profile showing the elution of the RAIDD DD on Gel-filtration chromatography. SDS-PAGE (15% gel) of the purified RAIDD DD.</p>
Full article ">
<p>Crystal of RAIDD DD. A native RAIDD DD crystal grown in three days in the condition of 2 M Na/K phosphate at pH 7.0. Its approximate dimentions are 0.2 X 0.2 X 0.2 mm.</p>
Full article ">
<p>Functional test of RAIDD DD. A. Profile of Gel-filtration chromatography. Elution volume around 12 mL indicates molecular weight of 120 kDa; B. 15 % SDS-PAGE showed that the peak from profile of gel-filtration chromatography is a complex. Fraction #12 and #14 showed that uncomplexed left over proteins; C. The equilibrium radial absorbance profiles at 25,000 rev./min by analytical ultracentrifugation analysis for RAIDD DD: PIDD DD complex.</p>
Full article ">
377 KiB  
Article
Association Study between BDNF Gene Polymorphisms and Autism by Three-Dimensional Gel-Based Microarray
by Lu Cheng, Qinyu Ge, Pengfeng Xiao, Beili Sun, Xiaoyan Ke, Yunfei Bai and Zuhong Lu
Int. J. Mol. Sci. 2009, 10(6), 2487-2500; https://doi.org/10.3390/ijms10062487 - 2 Jun 2009
Cited by 22 | Viewed by 17476
Abstract
Single nucleotide polymorphisms (SNPs) are important markers which can be used in association studies searching for susceptible genes of complex diseases. High-throughput methods are needed for SNP genotyping in a large number of samples. In this study, we applied polyacrylamide gel-based microarray combined [...] Read more.
Single nucleotide polymorphisms (SNPs) are important markers which can be used in association studies searching for susceptible genes of complex diseases. High-throughput methods are needed for SNP genotyping in a large number of samples. In this study, we applied polyacrylamide gel-based microarray combined with dual-color hybridization for association study of four BDNF polymorphisms with autism. All the SNPs in both patients and controls could be analyzed quickly and correctly. Among four SNPs, only C270T polymorphism showed significant differences in the frequency of the allele (χ2 = 7.809, p = 0.005) and genotype (χ2 = 7.800, p = 0.020). In the haplotype association analysis, there was significant difference in global haplotype distribution between the groups (χ2 = 28.19,p = 3.44e-005). We suggest that BDNF has a possible role in the pathogenesis of autism. The study also show that the polyacrylamide gel-based microarray combined with dual-color hybridization is a rapid, simple and high-throughput method for SNPs genotyping, and can be used for association study of susceptible gene with disorders in large samples. Full article
(This article belongs to the Section Biochemistry)
Show Figures

Graphical abstract

Graphical abstract
Full article ">
<p>Schematic outline of gel-immobilization microarray approach for SNP genotyping in a large number of samples. The platform for SNP genotyping mainly involves five steps: polymerase chain reaction (PCR), immobilization of PCR products, hybridization, electrophoresis of microarray and scanning for genotyping.</p>
Full article ">
<p>Hybridized image of four SNPs of BDNF gene for part of samples.The images acquired by the confocal scanner which was fitted with filters for Cy3 and Cy5. The green spots indicate wild homozygous, the red spots indicate mutant homozygous, and the yellow spots indicate heterozygote. (A) scan image of rs988748, (B) scan image of rs2049046, (C) scan image of C270T, (D) scan image of rs6265.</p>
Full article ">
<p>A schematic outline of SNP genotyping approach using dual-color fluorescence hybridization.(A) homozygous wild type; (B) heterozygote type; (C) homozygous mutant type.</p>
Full article ">
268 KiB  
Article
Voltage-Dependent Anion Channel 2 of Arabidopsis thaliana (AtVDAC2) Is Involved in ABA-Mediated Early Seedling Development
by Jinping Yan, Han He, Shibo Tong, Wanrong Zhang, Jianmei Wang, Xufeng Li and Yi Yang
Int. J. Mol. Sci. 2009, 10(6), 2476-2486; https://doi.org/10.3390/ijms10062476 - 26 May 2009
Cited by 27 | Viewed by 14285
Abstract
The voltage-dependent anion channel (VDAC) is the major transport protein in the outer membrane of mitochondria and plays crucial roles in energy metabolism, apoptosis, and metabolites transport. In plants, the expression of VDACs can be affected by different stresses, including drought, salinity and [...] Read more.
The voltage-dependent anion channel (VDAC) is the major transport protein in the outer membrane of mitochondria and plays crucial roles in energy metabolism, apoptosis, and metabolites transport. In plants, the expression of VDACs can be affected by different stresses, including drought, salinity and pathogen defense. In this study, we investigated the expression pattern of AtVDAC2 in A. thaliana and found ABA suppressed the accumulation of AtVDAC2 transcripts. Further, phenotype analysis of this VDAC deregulated-expression transgenic Arabidopsis plants indicated that AtVDAC2 anti-sense line showed an ABA-insensitivity phenotype during the early seedling development under ABA treatment. The results suggested that AtVDAC2 might be involved in ABA signaling in A. thaliana. Full article
(This article belongs to the Section Biochemistry)
Show Figures

Graphical abstract

Graphical abstract
Full article ">
<p>Effect of ABA on AtVDAC2 gene expression at the transcriptional level detected by semi-quantitative PCR. (a) The effect of ABA on AtVDAC2 mRNA level. Four-week old Arabidopsis seedlings were treated with 30μM ABA for 0, 2 h, 8 h, 16 h and 24 h, respectively. (b) The relative AtVDAC2 abundance in Arabidopsis mesophyll protoplasts under 5 μM, 50 μM ABA treatment. The quantitative analysis of the PCR signal performed with imaging software (Gel-Pro analyzer 3.0) and the bands intensities relative to their actin.</p>
Full article ">
<p>The relative activity of 5′ upstream region of AtVDAC2 regulated by ABA. (a) Construction of the pBI221-pVDAC::LUC vector for the transient gene expression in Arabidopsis mesophyll protoplasts. (b) The luciferase activity of AtVDAC2 promoter in protoplasts was regulated by different level of ABA (0.1, 1, 10 and 100 μM). Luciferase activity was means ± SD (n = 3) from one of three independent experiments. * Significant at P&lt;0.05 compared with the control (treated with 0 μM ABA) based on Student’s test.</p>
Full article ">
<p>Identification of the AtVDAC2 transgenic Arabidopsis plants by semi-quantitative analysis. (a) The amplified DNA fragment of AtVDAC2 in different transgenic lines were stained by ethidium bromide in agarose gel and the ralative level in each sample was normalized for actin transcripts. (b) The relative amount of AtVDAC2 mRNA were quantified using a software Gel-Pro analyzer 3.0. OE, Dn, WT represent AtVDAC2 sense lines, anti-sense lines and wild type, respectively.</p>
Full article ">
<p>Effect of exogenous ABA on seed germination of different AtVDAC2 tansgenic lines. After stratification, seeds of AtVDAC2 sense (OE) or antisense (Dn) lines and wild-type (WT) were grown with 0.7μM ABA and Germination was scored every 24 hour in two independent seed batches. Values are means ± SD (n=3) from one representative of three independent experiments with similar results. Asterisks indicate significant difference from wild type (P&lt;0.05) based on Student’s test.</p>
Full article ">
<p>The AtVDAC2 transgenic plants showed different sensitivity to ABA during the early seedling development. Early seedling of AtVDAC2 sense (OE) or antisense (Dn) lines and wild-type (WT) plants after 10 days of growth on control MS (a) or on MS media added with 0.7μM ABA (b). Similar results were obtained in three replicates.</p>
Full article ">
383 KiB  
Review
An Updated Review of Tyrosinase Inhibitors
by Te-Sheng Chang
Int. J. Mol. Sci. 2009, 10(6), 2440-2475; https://doi.org/10.3390/ijms10062440 - 26 May 2009
Cited by 1266 | Viewed by 65306
Abstract
Tyrosinase is a multifunctional, glycosylated, and copper-containing oxidase, which catalyzes the first two steps in mammalian melanogenesis and is responsible for enzymatic browning reactions in damaged fruits during post-harvest handling and processing. Neither hyperpigmentation in human skin nor enzymatic browning in fruits are [...] Read more.
Tyrosinase is a multifunctional, glycosylated, and copper-containing oxidase, which catalyzes the first two steps in mammalian melanogenesis and is responsible for enzymatic browning reactions in damaged fruits during post-harvest handling and processing. Neither hyperpigmentation in human skin nor enzymatic browning in fruits are desirable. These phenomena have encouraged researchers to seek new potent tyrosinase inhibitors for use in foods and cosmetics. This article surveys tyrosinase inhibitors newly discovered from natural and synthetic sources. The inhibitory strength is compared with that of a standard inhibitor, kojic acid, and their inhibitory mechanisms are discussed. Full article
Show Figures


<p>Biosynthetic pathway of melanin [<a href="#b1-ijms-10-02440" class="html-bibr">1</a>–<a href="#b4-ijms-10-02440" class="html-bibr">4</a>]. TYR, tyrosinase; TRP; tyrosinase related protein; dopa, 3,4-dihydroxyphenylalanine; DHICA, 5,6-dihydroxyindole-2-carboxylic acid; DHI, 5,6-dihydroxyindole; ICAQ, indole-2-carboxylic acid-5,6-quinone; IQ, indole-5,6-quinone; HBTA, 5-hydroxy-1,4-benzothiazinylalanine.</p>
Full article ">
<p>Catalytic cycles of the hydroxylation of monophenol and oxidation of o-diphenol to <span class="html-italic">o</span>-quinone by tyrosinase [<a href="#b23-ijms-10-02440" class="html-bibr">23</a>–<a href="#b24-ijms-10-02440" class="html-bibr">24</a>]. E<sub>oxy</sub>, E<sub>met</sub>, and E<sub>deoxy</sub> are the three types of tyrosinase, respectively. E<sub>oxy</sub>D, E<sub>oxy</sub>M, and E<sub>met</sub>M are E<sub>oxy</sub>-Diphenol, E<sub>oxy</sub>-Monophenol, and E<sub>met</sub>-Monophenol complexes, respectively.</p>
Full article ">
<p>Chemical structures of selected tyrosinase inhibitors belonging to some standard ones (a), flavonoids (b–j) or <span class="html-italic">N</span>-benzylbenzamides analogs (k). RA<sup>a</sup> and RA<sup>b</sup> are the relative diphenolase and monophenolase inhibitory activity, respectively, against mushroom tyrosinase compared to the standard kojic acid, where 1.0F means one time activity of kojic acid.</p>
Full article ">
<p>Chemical structures of selected tyrosinase inhibitors belonging to stilbenes (a), bibenzyl derivatives (b), coumarins (c), and benzaldehyde derivatives (d). RA<sup>a</sup> and RA<sup>b</sup> have the same meanings as those of <a href="#f3-ijms-10-02440" class="html-fig">Figure 3</a>.</p>
Full article ">
<p>Chemical structures of selected tyrosinase inhibitors belonging to long-chain lipids (a) or steroids (b). RA<sup>a</sup> and RA<sup>b</sup> have the same meanings as those of <a href="#f3-ijms-10-02440" class="html-fig">Figure 3</a>.</p>
Full article ">
<p>Chemical structures of other tyrosinase inhibitors from natural (a) or synthetic (b) sources. RA<sup>a</sup> and RA<sup>b</sup> have the same meanings as those of <a href="#f3-ijms-10-02440" class="html-fig">Figure 3</a>.</p>
Full article ">
<p>Chemical structures of irreversible tyrosinase inhibitors.</p>
Full article ">
<p>Molecular reaction mechanism of suicide inactivation of tyrosinase by the oxidation of an <span class="html-italic">o</span>-diphenol substrate. The curly arrows shows the effect of deprotonation leading to the reduction of copper from bivalent to zero-valent form, elimination of an <span class="html-italic">o</span>-quinone and inactivated tyrosinase [<a href="#b168-ijms-10-02440" class="html-bibr">168</a>].</p>
Full article ">
<p>Action mechanism of reversible inhibitors. E, S, I, and P are the enzyme, substrate, inhibitor, and product, respectively; ES is the enzyme-substrate complex, and EI and ESI are the enzyme-inhibitor and enzyme-substrate-inhibitor complexes, respectively.</p>
Full article ">
Previous Issue
Next Issue
Back to TopTop