AIMC Topic: Binding Sites

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Generative adversarial network (GAN) model-based design of potent SARS-CoV-2 M inhibitors using the electron density of ligands and 3D binding pockets: insights from molecular docking, dynamics simulation, and MM-GBSA analysis.

Molecular diversity Nov 30, 2024
Deep learning-based generative adversarial network (GAN) frameworks have recently been developed to expedite the drug discovery process. These models generate novel molecules from scratch and validate them through molecular docking simulation to iden...
Deep Learning Antiviral Agents Protein Binding SARS-CoV-2 Humans Molecular Docking Simulation COVID-19 Drug Design Binding Sites Protease Inhibitors Coronavirus 3C Proteases Generative Adversarial Networks Molecular Dynamics Simulation Ligands COVID-19 Drug Treatment
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MERIT: Accurate Prediction of Multi Ligand-binding Residues with Hybrid Deep Transformer Network, Evolutionary Couplings and Transfer Learning.

Journal of molecular biology Nov 20, 2024
Multi-ligand binding residues (MLBRs) are amino acids in protein sequences that interact with multiple different ligands that include proteins, peptides, nucleic acids, and a variety of small molecules. MLBRs are implicated in a number of cellular fu...
Software Computational Biology Humans Deep Learning Ligands Proteins Neural Networks, Computer Protein Binding Binding Sites Machine Learning Databases, Protein
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Small Molecule Inhibitors of Topoisomerase I Identified by Machine Learning and In Vitro Assays.

International journal of molecular sciences Nov 15, 2024
Tuberculosis (TB) caused by is a leading infectious cause of death globally. The treatment of patients becomes much more difficult for the increasingly common multi-drug resistant TB. Topoisomerase I is essential for the viability of and has been v...
Small Molecule Libraries DNA Topoisomerases, Type I Topoisomerase I Inhibitors Mycobacterium tuberculosis High-Throughput Screening Assays Binding Sites Machine Learning Humans Molecular Docking Simulation Antitubercular Agents
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Estimating AChE inhibitors from MCE database by machine learning and atomistic calculations.

Journal of molecular graphics & modelling Nov 14, 2024
Acetylcholinesterase (AChE) is one of the most successful targets for the treatment of Alzheimer's disease (AD). Inhibition of AChE can result in preventing AD. In this context, the machine-learning (ML) model, molecular docking, and molecular dynami...
Molecular Docking Simulation Protein Binding Humans Machine Learning Molecular Dynamics Simulation Cholinesterase Inhibitors Ligands Databases, Chemical Acetylcholinesterase Binding Sites
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Improving drug-target interaction prediction through dual-modality fusion with InteractNet.

Journal of bioinformatics and computational biology Nov 11, 2024
In the drug discovery process, accurate prediction of drug-target interactions is crucial to accelerate the development of new drugs. However, existing methods still face many challenges in dealing with complex biomolecular interactions. To this end,...
Drug Discovery Deep Learning Protein Binding Neural Networks, Computer Machine Learning Computational Biology Algorithms Pharmaceutical Preparations Humans Binding Sites Proteins Ligands Databases, Protein
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LGS-PPIS: A Local-Global Structural Information Aggregation Framework for Predicting Protein-Protein Interaction Sites.

Proteins Nov 9, 2024
Exploring protein-protein interaction sites (PPIS) is of significance to elucidating the intrinsic mechanisms of diverse biological processes. On this basis, recent studies have applied deep learning-based technologies to overcome the high cost of we...
Binding Sites Protein Interaction Mapping Protein Interaction Domains and Motifs Humans Algorithms Deep Learning Proteins Protein Binding Databases, Protein Computational Biology
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An Integrated TCN-CrossMHA Model for Predicting circRNA-RBP Binding Sites.

Interdisciplinary sciences, computational life sciences Nov 6, 2024
Circular RNA (circRNA) has the capacity to bind with RNA binding protein (RBP), thereby exerting a substantial impact on diseases. Predicting binding sites aids in comprehending the interaction mechanism, thereby offering insights for disease treatme...
Protein Binding Computational Biology RNA-Binding Proteins Binding Sites RNA, Circular Humans Neural Networks, Computer Algorithms
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GeoNet enables the accurate prediction of protein-ligand binding sites through interpretable geometric deep learning.

Structure (London, England : 1993) Nov 1, 2024
The identification of protein binding residues is essential for understanding their functions in vivo. However, it remains a computational challenge to accurately identify binding sites due to the lack of known residue binding patterns. Local residue...
Models, Molecular RNA Ligands Computational Biology Proteins DNA Binding Sites Deep Learning Protein Binding
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GraphPBSP: Protein binding site prediction based on Graph Attention Network and pre-trained model ProstT5.

International journal of biological macromolecules Oct 28, 2024
Protein-protein/peptide interactions play crucial roles in various biological processes. Exploring their interactions attracts wide attention. However, accurately predicting their binding sites remains a challenging task. Here, we develop an effectiv...
Protein Binding Computational Biology Proteins Binding Sites Neural Networks, Computer Algorithms
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Deep learning for discriminating non-trivial conformational changes in molecular dynamics simulations of SARS-CoV-2 spike-ACE2.

Scientific reports Sep 30, 2024
Molecular dynamics (MD) simulations produce a substantial volume of high-dimensional data, and traditional methods for analyzing these data pose significant computational demands. Advances in MD simulation analysis combined with deep learning-based a...
Deep Learning Humans Mutation Binding Sites Protein Conformation COVID-19 Protein Domains Protein Binding SARS-CoV-2 Angiotensin-Converting Enzyme 2 Spike Glycoprotein, Coronavirus Molecular Dynamics Simulation
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