AIMC Topic: Ligands

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Evaluation of Machine Learning/Molecular Mechanics End-State Corrections with Mechanical Embedding to Calculate Relative Protein-Ligand Binding Free Energies.

Journal of chemical theory and computation Jan 3, 2025
The development of machine-learning (ML) potentials offers significant accuracy improvements compared to molecular mechanics (MM) because of the inclusion of quantum-mechanical effects in molecular interactions. However, ML simulations are several ti...
Thermodynamics Quantum Theory Ligands Machine Learning Proteins Molecular Dynamics Simulation Protein Binding
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Unveiling key drivers of hepatocellular carcinoma: a synergistic approach with network pharmacology, machine learning-driven ligand discovery and dynamic simulations.

SAR and QSAR in environmental research Jan 3, 2025
Hepatocellular carcinoma (HCC) ranks fourth in cancer-related mortality worldwide. This study aims to uncover the genes and pathways involved in HCC through network pharmacology (NP) and to discover potential drugs via machine learning (ML)-based lig...
Carcinoma, Hepatocellular Humans Molecular Docking Simulation Drug Discovery Glycogen Synthase Kinase 3 beta Machine Learning Proto-Oncogene Proteins c-akt Molecular Dynamics Simulation Network Pharmacology Liver Neoplasms Ligands Quantitative Structure-Activity Relationship
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PharmRL: pharmacophore elucidation with deep geometric reinforcement learning.

BMC biology Dec 31, 2024
BACKGROUND: Molecular interactions between proteins and their ligands are important for drug design. A pharmacophore consists of favorable molecular interactions in a protein binding site and can be utilized for virtual screening. Pharmacophores are ...
Humans Pharmacophore Deep Learning Binding Sites Algorithms Proteins Drug Design Ligands
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Evaluations of the Perturbation Resistance of the Deep-Learning-Based Ligand Conformation Optimization Algorithm.

Journal of chemical information and modeling Dec 26, 2024
In recent years, the deep learning (DL) technique has rapidly developed and shown great success in scoring the protein-ligand binding affinities. The protein-ligand conformation optimization based on DL-derived scoring functions holds broad applicati...
Algorithms Protein Conformation Deep Learning Protein Binding Proteins Ligands Molecular Docking Simulation
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A 4D tensor-enhanced multi-dimensional convolutional neural network for accurate prediction of protein-ligand binding affinity.

Molecular diversity Dec 23, 2024
Protein-ligand interactions are the molecular basis of many important cellular activities, such as gene regulation, cell metabolism, and signal transduction. Protein-ligand binding affinity is a crucial metric of the strength of the interaction betwe...
Neural Networks, Computer Deep Learning Models, Molecular Ligands Binding Sites Protein Binding Proteins Convolutional Neural Networks
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BioStructNet: Structure-Based Network with Transfer Learning for Predicting Biocatalyst Functions.

Journal of chemical theory and computation Dec 20, 2024
Enzyme-substrate interactions are essential to both biological processes and industrial applications. Advanced machine learning techniques have significantly accelerated biocatalysis research, revolutionizing the prediction of biocatalytic activities...
Deep Learning Molecular Dynamics Simulation Biocatalysis Enzymes Ligands Machine Learning Algorithms
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Residue-Level Multiview Deep Learning for ATP Binding Site Prediction and Applications in Kinase Inhibitors.

Journal of chemical information and modeling Dec 17, 2024
Accurate identification of adenosine triphosphate (ATP) binding sites is crucial for understanding cellular functions and advancing drug discovery, particularly in targeting kinases for cancer treatment. Existing methods face significant challenges d...
Drug Discovery Deep Learning Adenosine Triphosphate Humans Molecular Docking Simulation Binding Sites Ligands Protein Kinase Inhibitors
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Combined usage of ligand- and structure-based virtual screening in the artificial intelligence era.

European journal of medicinal chemistry Dec 10, 2024
Drug design has always been pursuing techniques with time- and cost-benefits. Virtual screening, generally classified as ligand-based (LBVS) and structure-based (SBVS) approaches, could identify active compounds in the large chemical library to reduc...
Humans Artificial Intelligence Small Molecule Libraries Molecular Structure Machine Learning Drug Evaluation, Preclinical Drug Design 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 Proteins Databases, Protein Drug Discovery Deep Learning Ligands 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...
Proteins Databases, Protein Binding Sites Ligands Algorithms Neural Networks, Computer Protein Binding Machine Learning Computational Biology
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