Computational Biology and Chemistry

The integration of artificial intelligence (AI) into smart agriculture boosts production and management efficiency, facilitating sustainable agricultural development. In intensive agricultural management, adopting eco-friendly and effective ...

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• A novel insectide-likeness prediction model (IAPred) was built using the ensemble machine learning strategy.
• The 27 important insecticide-likeness features for IAPred were identified through multi-scale screening.
• The IAPred model ...

Understanding the mechanisms underlying interactions between drugs and target proteins is critical for drug discovery. In our earlier studies, we introduced the Triangular Spatial Relationship (TSR)-based algorithm, which enables the ...

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• A new approach to representing ligand and drug 3D structures is introduced and evaluated.
• A novel algorithm calculating cross TSR keys is developed for enabling comparisons of drug/ligand - target complexes.
• The results demonstrate ...

There are billions of virus species worldwide, and viruses, the smallest parasitic entities, pose a serious threat. Therefore, fighting associated disorders requires an understanding of the genetic structure of viruses. Considering the wide ...

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• Unlike previous research investigating the common genomic and evolutionary features of single-stranded RNA viruses (+ssRNA and -ssRNA viruses) in the PhyVirus dataset, this study is the first to use Machine Learning (ML) and Deep Learning (...

Hepatocellular carcinoma (HCC) is a widespread primary liver cancer with a high fatality rate. Despite several genes with oncogenic effects in HCC have been identified, many remain undiscovered. In this study, we conducted a comprehensive ...

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• Utilized gene families for enhanced computational analysis.
• Discovered rare oncogenic mutations in HCC via domain and hotspot analysis.
• Integrated omics-data to analyze ubiquitin-proteasome system abnormalities in HCC.

Accurately identifying essential proteins is vital for drug research and disease diagnosis. Traditional centrality methods and machine learning approaches often face challenges in accurately discerning essential proteins, primarily relying on ...

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• Louvain community division extracts initial topological features from the PPI network.
• Enrich features with GCN and GAT.
• Extract features from genetic sequences using BiLSTM and multi-head self-attention.
• Choosing 1024 ...

Spatial transcriptomics, a groundbreaking field in cellular biology, faces the challenge of effectively deciphering complex spatial-temporal gene expression patterns. Traditional data analysis methods often fail to capture the intricate nuances ...

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• STPDA integrates high-resolution mapping to link genomics with histopathology for spatial transcriptomic data analysis.
• The framework incorporates Autoregressive Moving Average and Long Short-Term Memory models to analyze spatio-...

Spontaneous mutations are evolutionary engines as they generate variants for the evolutionary downstream processes that give rise to speciation and adaptation. Single nucleotide mutations (SNM) are the most abundant type of mutations among them. ...

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• Global and local genomic features are correlated with SNM rates, but the patterns vary across taxa
• Prokaryotes and unicellular eukaryotes show stronger correlations with genomic features as compared with multicellular eukaryotes.
• ...

Mitochondrial disorders are a class of heterogeneous disorders caused by genetic variations in the mitochondrial genome (mtDNA) as well as the nuclear genome. The spectrum of mtDNA variants remains unexplored in the Indian population. In the ...

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• 2689 mitochondrial DNA variants found in 1017 genomes of healthy Indian individuals.
• Majority of the variants are rare and homoplasmic.
• Pathogenic variants m.1555 A>G and m.14484 T>C have been observed.
• Carrier frequency of ...

Oxyresveratrol (OXY), a natural stilbenoid in mulberry fruits, is known for its diverse pharmacological properties. However, its clinical use is hindered by low water solubility and limited bioavailability. In the present study, the inclusion ...

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• Investigation of inclusion complexes of OXY with βCD and analogs using in silico and in vitro studies.
• Utilizing novel Parallel Cascade Selection Molecular Dynamics simulations for studying drug-cyclodextrin (CD) inclusion complexes.

DEMETER-Like DNA demethylases (DMLs) are epigenetic regulators of many developmental and biological processes in plants. No comprehensive information about the DML gene family in citrus is available to date. Here, a total of three DML genes in ...

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• Three citrus DML genes were identified and analyzed.
• They contain all the conserved domains and motifs typical of plant DMLs.
• Their promoters contain cis-elements involved in abiotic stress response.
• They are differentially ...

Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels. This study aimed to analyze the changes underlying heterogeneities and communication properties of CMs in diabetes mellitus (DM).

GSE213337 ...

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• The ratio of cardiomyocytes was increased in diabetes mellitus induced by streptozotocin.
• The CM showed the significant heterogeneities in DM.
• CM played an important role in myocardial fibrosis induce by hyperglycemia.

The bioinformatic analysis of cannabinoid receptors (CBRs) CB₁ and CB₂ reveals a detailed picture of their structure, evolution, and physiological significance within the endocannabinoid system (ECS). The study highlights the evolutionary ...

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• CB1 and CB2, with sequence alignments across diverse species indicating a similarity of 44.58 % between both receptors.
• CB1 and CB2 share the seven-TM helices structural hallmark characteristic of class A GPCRs, essential for their ...

The proteins of Nipah virus ascribe to its lifecycle and are crucial to infections caused by the virus. In the absence of approved therapeutics, these proteins can be considered as drug targets. This study examined the potential of fifty-three (...

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• Tribulusamide B can inhibit Nipah virus matrix and fusion-glyco proteins.
• Principle Component Analysis, identified three major clusters in phytochemicals.
• Multiple pharamacophores are involved in stabilising protein-ligand ...

Retrosynthesis is vital in synthesizing target products, guiding reaction pathway design crucial for drug and material discovery. Current models often neglect multi-scale feature extraction, limiting efficacy in leveraging molecular descriptors. ...

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• Retrosynthesis aids in synthesizing target products, crucial for drug and material discovery.
• Current models lack multi-scale feature extraction, limiting effectiveness.
• SB-Net, a proposed deep-learning model, excels in ...

In the global fight against the COVID-19 pandemic caused by the highly transmissible SARS-CoV-2 virus, the search for potent medications is paramount. With a focused investigation on the SARS-CoV-2 papain-like protease (PL^pro) as a promising ...

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• Targeting the SARS-CoV-2 PLpro could be key for COVID-19 treatment due to its crucial role in viral replication and immune response modulation.
• The PLpro catalytic site, particularly Cys111, is a promising target for covalent bonding, ...

Global public health is confronted with significant challenges due to the prevalence of cancer and the emergence of treatment resistance. This work focuses on the identification of cyclin-dependent kinase 2 (CDK2) through a systematic ...

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• Developed ligand-based pharmacophore model for CDK2 inhibitors.
• Identified 108 hits from the ZINC database through virtual screening.
• Best compound Z1 showed binding solid affinity and stable protein-ligand interactions.
• ...

Human glutaminyl cyclase (hQC) inhibitors have great potential to be used as anti- Alzheimer's disease (AD) agents by reducing the toxic pyroform of β-amyloid in the brains of AD patients. The four-dimensional quantitative structure activity ...

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• Established a 4D-QSAR model for N-substituted urea/thioureas with good predictive ability.
• Designed and evaluated new N-substituted urea/thioureas as potential hQC inhibitors.
• Confirmed stability and interaction patterns with hQC ...

Nipah virus (NiV) remains a significant global concern due to its impact on both the agricultural industry and human health, resulting in substantial economic and health consequences. Currently, there is no cure or commercially available vaccine ...

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• The antiviral potential of Streptomyces spp. metabolites against the Nipah virus matrix protein was investigated using CADD methods.
• Six metabolites exhibited inhibitory potential against the main substrate-binding site of the Nipah ...

COVID-19, caused by the SARS-COV-2 virus, induces numerous immunological reactions linked to the severity of the clinical condition of those infected. The surface Spike protein (S protein) present in Sars-CoV-2 is responsible for the infection of ...

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• Spike protein epitopes
• SARS-CoV-2 variants
• Change in epitopes sequences
• Mutations

Long non-coding RNAs (lncRNAs) play crucial roles in the regulation of gene expression and maintenance of genomic integrity through various interactions with DNA, RNA, and proteins. The availability of large-scale sequence data from various high-...

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• ETENLNC identifies differentially expressed novel, known lncRNAs and constructs lncRNA regulatory networks from RNA-Seq data.
• ETENLNC performs lncRNA structure and functional annotation predictions alongside regulatory network ...

Anticancer peptides(ACPs) have attracted significant interest as a novel method of treating cancer due to their ability to selectively kill cancer cells without damaging normal cells. Many artificial intelligence-based methods have demonstrated ...

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• A new anticancer peptide predictor, ACP-PDAFF, outperforms on multiple datasets.
• A new method integrates multiple features with dual-channel attentional fusion.
• Transformer and ProtBert improve anticancer peptide prediction ...

The prediction of possible lead compounds from already-known drugs that may present DPP-4 inhibition activity imply a advantage in the drug development in terms of time and cost to find alternative medicines for the treatment of Type 2 Diabetes ...

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• Type 2 Diabetes Mellitus (T2DM) is a persistent condition in the world.
• dipeptidyl peptidase-4 inhibition plays a pivotal role in T2DM treatment.
• Machine learning algorithms are useful for model construction.
• Molecular dynamic ...

This study demonstrated the correlation of molecular structures of Peroxisome proliferator-activated receptor gamma (PPARγ) modulators and their biological activities. Bayesian classification, and recursive partitioning (RP) studies have been ...

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• This study focused on the supervised mathematical learning models of PPARγ modulators.
• Exploring favorable and unfavorable sub-structural fragments that regulate PPARγ modulatory activities.
• Molecular docking and MD simulation ...

Accumulation of senescent cells is a recognized feature in hepatocellular carcinoma (HCC), but their specific types and prognostic implications remain under investigation. This study aimed to delineate senescent cell types and their senescent ...

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• Unconventional T cells including NKT cells and γδT cells showed a predominant senescent signature in HCC.
• Senescent unconventional T cells in HCC might weaken the immune system against tumor development and lead to a worse overall ...

Alzheimer’s disease (AD) is characterized by neuronal loss due to hyperphosphorylated proteins induced by oxidative stress. AD remains a formidable challenge in the medical field, as current treatments focusing on single biomarkers have yielded ...

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• Allocryptopine suppressed ROS levels, increased p-Akt and p-GSK-3β, enhancing the Akt/GSK-3β signaling pathway.
• Allocryptopine regulated G1/S cell cycle, causing G1 arrest, aiding repair, potentially suppressing neural apoptosis.
• ...

Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Understanding the molecular mechanisms underlying tumor progression is of great clinical significance. This study aims to identify novel molecular ...

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• Feature Selection from Multi-Omics Data: Employed a feature-selection process integrating multi-omics data from TCGA.
• Machine Learning Integration: Utilized a range of machine learning classifiers to classify LUAD subtypes.
• ...

Triple negative breast cancer (TNBC) presents a significant global health concern due to its aggressive nature, high mortality rate and limited treatment options, highlighting the urgent need for targeted therapies. Beauvericin, a bioactive ...

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• In silico study identified MRP1, HDAC1, HDAC2, LCK and SYK as possible molecular targets of beauvericin.
• Beauvericin reduced TNBC cell viability and induced oxidative stress mediated apoptosis.
• It halted cell cycle progression at ...

The development of analytical methods for Genome-wide Association Studies (GWAS) has outpaced the evolution of simulation techniques and pipelines. This disparity underscores the importance of innovative simulation methods that can keep pace with ...

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• Introduced the SGO model using SLiM for simulating individual-level GWAS data, addressing the need of large-scale simulations (50,000+ individuals).
• Demonstrated SGO's superior efficiency over HapGen for samples >13,000, enabling ...

Alzheimer's disease (AD) is a chronic neurodegenerative disorder that is the primary cause of dementia. It is characterised by the gradual loss of brain cells, which results in memory loss and cognitive dysfunction. One of the hallmarks of AD is ...

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• In-silico studies on imidazole-based anti-ADs agents.
• Five promising compounds were identified.
• MD simulation studies to investigate the interactions at supramolecular level.