AIMC Topic: Ligands

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A Protein-Context Enhanced Master Slave Framework for Zero-Shot Drug Target Interaction Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Drug Target Interaction (DTI) prediction plays a crucial role in in-silico drug discovery, especially for deep learning (DL) models. Along this line, existing methods usually first extract features from drugs and target proteins, and use drug-target ...
Humans Algorithms Drug Discovery Proteins Databases, Protein Ligands Deep Learning Computational Biology
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Intra-Inter Graph Representation Learning for Protein-Protein Binding Sites Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Graph neural networks have drawn increasing attention and achieved remarkable progress recently due to their potential applications for a large amount of irregular data. It is a natural way to represent protein as a graph. In this work, we focus on p...
Binding Sites Databases, Protein Ligands Neural Networks, Computer Machine Learning Algorithms Protein Binding Computational Biology Proteins
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Structure-Aware Graph Attention Diffusion Network for Protein-Ligand Binding Affinity Prediction.

IEEE transactions on neural networks and learning systems Dec 2, 2024
Accurate prediction of protein-ligand binding affinities can significantly advance the development of drug discovery. Several graph neural network (GNN)-based methods learn representations of protein-ligand complexes via modeling intermolecule intera...
Algorithms Drug Discovery Protein Binding Proteins Databases, Protein Ligands Humans Neural Networks, Computer
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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...
Humans COVID-19 Protease Inhibitors Antiviral Agents SARS-CoV-2 Ligands Protein Binding Coronavirus 3C Proteases Drug Design Molecular Docking Simulation COVID-19 Drug Treatment Molecular Dynamics Simulation Generative Adversarial Networks Deep Learning Binding Sites
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SurfDock is a surface-informed diffusion generative model for reliable and accurate protein-ligand complex prediction.

Nature methods Nov 27, 2024
Accurately predicting protein-ligand interactions is crucial for understanding cellular processes. We introduce SurfDock, a deep-learning method that addresses this challenge by integrating protein sequence, three-dimensional structural graphs and su...
Protein Binding Humans Algorithms Ligands Proteins Protein Conformation Molecular Docking Simulation Deep Learning Software
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Improved Prediction of Ligand-Protein Binding Affinities by Meta-modeling.

Journal of chemical information and modeling Nov 22, 2024
The accurate screening of candidate drug ligands against target proteins through computational approaches is of prime interest to drug development efforts. Such virtual screening depends in part on methods to predict the binding affinity between liga...
Proteins Databases, Protein Ligands Deep Learning Protein Binding Molecular Docking Simulation
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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...
Neural Networks, Computer Machine Learning Software Humans Ligands Binding Sites Computational Biology Deep Learning Proteins Protein Binding Databases, Protein
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CPIScore: A Deep Learning Approach for Rapid Scoring and Interpretation of Protein-Ligand Binding Interactions.

Journal of chemical information and modeling Nov 19, 2024
Protein-ligand binding affinity prediction is a crucial and challenging task in the field of drug discovery. However, traditional simulation-based computational approaches are often prohibitively time-consuming, limiting their practical utility. In t...
Proteins Ligands Small Molecule Libraries Drug Discovery Deep Learning Protein Binding
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Deep learning pipeline for accelerating virtual screening in drug discovery.

Scientific reports Nov 16, 2024
In the race to combat ever-evolving diseases, the drug discovery process often faces the hurdles of high-cost and time-consuming procedures. To tackle these challenges and enhance the efficiency of identifying new therapeutic agents, we introduce Vir...
Antiviral Agents Drug Evaluation, Preclinical Ligands Molecular Docking Simulation Drug Discovery Humans Deep Learning Software
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Predicting Protein-Ligand Binding Affinity Using Fusion Model of Spatial-Temporal Graph Neural Network and 3D Structure-Based Complex Graph.

Interdisciplinary sciences, computational life sciences Nov 14, 2024
The investigation of molecular interactions between ligands and their target molecules is becoming more significant as protein structure data continues to develop. In this study, we introduce PLA-STGCNnet, a deep fusion spatial-temporal graph neural ...
Protein Binding Proteins Ligands Neural Networks, Computer Algorithms Protein Conformation Graph Neural Networks
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