article

Ab initio Tertiary Structure Prediction of Proteins

Authors:

C. A. FloudasAuthors Info & Claims

Journal of Global Optimization, Volume 25, Issue 1

Pages 113 - 140

https://doi.org/10.1023/A:1021331514642

Published: 01 January 2003 Publication History

Abstract

A daunting challenge in the area of computational biology has been to develop a method to theoretically predict the correct three-dimensional structure of a protein given its linear amino acid sequence. The ability to surmount this challenge, which is known as the protein folding problem, has tremendous implications. We introduce a novel ab initio approach for the protein folding problem. The accurate prediction of the three-dimensional structure of a protein relies on both the mathematical model used to mimic the protein system and the technique used to identify the correct structure. The models employed are based solely on first principles, as opposed to the myriad of techniques relying on information from statistical databases. The framework integrates our recently proposed methods for the prediction of secondary structural features including helices and strands, as well as β-sheet and disulfide bridge formation. The final stage of the approach, which culminates in the tertiary structure prediction of a protein, utilizes search techniques grounded on the foundations of deterministic global optimization, powerful methods which can potentially guarantee the correct identification of a protein's structure. The performance of the approach is illustrated with bovine pancreatic trypsin inhibitor protein and the immunoglobulin binding domain of protein G.

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Cited By

Hao XZhang GZhou XYu X(2016)A Novel Method Using Abstract Convex Underestimation in Ab-Initio Protein Structure Prediction for Guiding Search in Conformational Feature SpaceIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2015.249722613:5(887-900)Online publication date: 1-Sep-2016
https://dl.acm.org/doi/10.1109/TCBB.2015.2497226
Dorn Me Silva MBuriol LLamb L(2014)Three-dimensional protein structure predictionComputational Biology and Chemistry10.1016/j.compbiolchem.2014.10.00153:PB(251-276)Online publication date: 1-Dec-2014
https://dl.acm.org/doi/10.1016/j.compbiolchem.2014.10.001
Skjäl AWesterlund TMisener RFloudas C(2012)A Generalization of the Classical źBB Convex Underestimation via Diagonal and Nondiagonal Quadratic TermsJournal of Optimization Theory and Applications10.1007/s10957-012-0033-6154:2(462-490)Online publication date: 1-Aug-2012
https://dl.acm.org/doi/10.1007/s10957-012-0033-6
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Ab initio Tertiary Structure Prediction of Proteins

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cover image Journal of Global Optimization

Journal of Global Optimization Volume 25, Issue 1

January 2003

135 pages

ISSN:0925-5001

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Copyright © Copyright © 2003 Kluwer Academic Publishers.

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Kluwer Academic Publishers

United States

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Published: 01 January 2003

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Cited By

Hao XZhang GZhou XYu X(2016)A Novel Method Using Abstract Convex Underestimation in Ab-Initio Protein Structure Prediction for Guiding Search in Conformational Feature SpaceIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2015.249722613:5(887-900)Online publication date: 1-Sep-2016
https://dl.acm.org/doi/10.1109/TCBB.2015.2497226
Dorn Me Silva MBuriol LLamb L(2014)Three-dimensional protein structure predictionComputational Biology and Chemistry10.1016/j.compbiolchem.2014.10.00153:PB(251-276)Online publication date: 1-Dec-2014
https://dl.acm.org/doi/10.1016/j.compbiolchem.2014.10.001
Skjäl AWesterlund TMisener RFloudas C(2012)A Generalization of the Classical źBB Convex Underestimation via Diagonal and Nondiagonal Quadratic TermsJournal of Optimization Theory and Applications10.1007/s10957-012-0033-6154:2(462-490)Online publication date: 1-Aug-2012
https://dl.acm.org/doi/10.1007/s10957-012-0033-6
Raza MHussain OHussain FChang E(2011)Maturity, distance and density (MD2) metrics for optimizing trust prediction for business intelligenceJournal of Global Optimization10.1007/s10898-010-9598-551:2(285-300)Online publication date: 1-Oct-2011
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Dimaggio PMcallister SFloudas CFeng XRabinowitz JRabitz H(2010)A network flow model for biclustering via optimal re-ordering of data matricesJournal of Global Optimization10.1007/s10898-008-9349-z47:3(343-354)Online publication date: 1-Jul-2010
https://dl.acm.org/doi/10.1007/s10898-008-9349-z
Mcallister SFloudas C(2010)An improved hybrid global optimization method for protein tertiary structure predictionComputational Optimization and Applications10.1007/s10589-009-9277-y45:2(377-413)Online publication date: 1-Mar-2010
https://dl.acm.org/doi/10.1007/s10589-009-9277-y
Mansour NKehyayan CKhachfe H(2009)Scatter Search algorithm for Protein Structure PredictionInternational Journal of Bioinformatics Research and Applications10.1504/IJBRA.2009.0286795:5(501-515)Online publication date: 1-Sep-2009
https://dl.acm.org/doi/10.1504/IJBRA.2009.028679
McAllister SFloudas C(2009)Enhanced bounding techniques to reduce the protein conformational search spaceOptimization Methods & Software10.1080/1055678090275348624:4-5(837-855)Online publication date: 1-Aug-2009
https://dl.acm.org/doi/10.1080/10556780902753486
Mcallister SDimaggio PFloudas C(2009)Mathematical modeling and efficient optimization methods for the distance-dependent rearrangement clustering problemJournal of Global Optimization10.1007/s10898-008-9393-845:1(111-129)Online publication date: 1-Sep-2009
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Floudas CGounaris C(2009)A review of recent advances in global optimizationJournal of Global Optimization10.1007/s10898-008-9332-845:1(3-38)Online publication date: 1-Sep-2009
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