AIMC Topic: Protein Binding

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Predicting the Binding of Small Molecules to Proteins through Invariant Representation of the Molecular Structure.

Journal of chemical information and modeling Aug 28, 2024
We present a computational scheme for predicting the ligands that bind to a pocket of a known structure. It is based on the generation of a general abstract representation of the molecules, which is invariant to rotations, translations, and permutati...
Proteins Ligands Small Molecule Libraries Models, Molecular Protein Conformation Machine Learning Binding Sites Molecular Structure Algorithms Protein Binding
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A Point Cloud Graph Neural Network for Protein-Ligand Binding Site Prediction.

International journal of molecular sciences Aug 27, 2024
Predicting protein-ligand binding sites is an integral part of structural biology and drug design. A comprehensive understanding of these binding sites is essential for advancing drug innovation, elucidating mechanisms of biological function, and exp...
Deep Learning Protein Binding Proteins Databases, Protein Ligands Binding Sites Neural Networks, Computer Algorithms
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Chemical analogue based drug design for cancer treatment targeting PI3K: integrating machine learning and molecular modeling.

Molecular diversity Aug 17, 2024
Cancer is a generic term for a group of disorders defined by uncontrolled cell growth and the potential to invade or spread to other parts of the body. Gene and epigenetic alterations disrupt normal cellular control, leading to abnormal cell prolifer...
Class Ib Phosphatidylinositol 3-Kinase Models, Molecular Phosphatidylinositol 3-Kinases Molecular Dynamics Simulation Ligands Protein Kinase Inhibitors Phosphoinositide-3 Kinase Inhibitors Drug Design Antineoplastic Agents Protein Binding Neoplasms Molecular Docking Simulation Humans Machine Learning
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FitScore: a fast machine learning-based score for 3D virtual screening enrichment.

Journal of computer-aided molecular design Aug 16, 2024
Enhancing virtual screening enrichment has become an urgent problem in computational chemistry, driven by increasingly large databases of commercially available compounds, without a commensurate drop in in vitro screening costs. Docking these large d...
Ligands Binding Sites Protein Binding Proteins Drug Evaluation, Preclinical Humans Machine Learning Software Molecular Docking Simulation Drug Discovery
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Identification of mycobacterial Thymidylate kinase inhibitors: a comprehensive pharmacophore, machine learning, molecular docking, and molecular dynamics simulation studies.

Molecular diversity Aug 16, 2024
Thymidylate kinase (TMK) is a pivotal enzyme in Mycobacterium tuberculosis (Mtb), crucial for phosphorylating thymidine monophosphate (dTMP) to thymidine diphosphate (dTDP), thereby playing a critical role in DNA biosynthesis. Dysregulation or inhibi...
Protein Binding Antitubercular Agents Molecular Dynamics Simulation Machine Learning Molecular Docking Simulation Nucleoside-Phosphate Kinase Pharmacophore Mycobacterium tuberculosis Enzyme Inhibitors Protein Kinase Inhibitors
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TCR-H: explainable machine learning prediction of T-cell receptor epitope binding on unseen datasets.

Frontiers in immunology Aug 16, 2024
Artificial-intelligence and machine-learning (AI/ML) approaches to predicting T-cell receptor (TCR)-epitope specificity achieve high performance metrics on test datasets which include sequences that are also part of the training set but fail to gener...
Computational Biology Epitopes, T-Lymphocyte Humans Support Vector Machine Receptors, Antigen, T-Cell Machine Learning Protein Binding
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Protein ligand binding site prediction using graph transformer neural network.

PloS one Aug 6, 2024
Ligand binding site prediction is a crucial initial step in structure-based drug discovery. Although several methods have been proposed previously, including those using geometry based and machine learning techniques, their accuracy is considered to ...
Ligands Protein Binding Binding Sites Neural Networks, Computer Machine Learning Proteins Algorithms Databases, Protein Drug Discovery
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Combining machine learning, molecular dynamics, and free energy analysis for (5HT)-2A receptor modulator classification.

Journal of molecular graphics & modelling Aug 5, 2024
The 5-Hydroxytryptamine (5HT)-2A receptor, a key target in psychoactive drug development, presents significant challenges in the design of selective compounds. Here, we describe the construction, evaluation and validation of two machine learning (ML)...
Humans Thermodynamics Protein Binding Molecular Dynamics Simulation Machine Learning Receptor, Serotonin, 5-HT2A Molecular Docking Simulation Drug Discovery
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Geometric deep learning of protein-DNA binding specificity.

Nature methods Aug 5, 2024
Predicting protein-DNA binding specificity is a challenging yet essential task for understanding gene regulation. Protein-DNA complexes usually exhibit binding to a selected DNA target site, whereas a protein binds, with varying degrees of binding sp...
Deep Learning Models, Molecular DNA-Binding Proteins Binding Sites Protein Binding Computational Biology DNA
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Combined structure-based virtual screening and machine learning approach for the identification of potential dual inhibitors of ACC and DGAT2.

International journal of biological macromolecules Jul 31, 2024
Acetyl-coenzyme A carboxylase (ACC) and diacylglycerol acyltransferase 2 (DGAT2) are recognized as potential therapeutic targets for nonalcoholic fatty liver disease (NAFLD). Inhibitors targeting ACC and DGAT2 have exhibited the capacity to reduce he...
Acetyl-CoA Carboxylase Enzyme Inhibitors Binding Sites Diacylglycerol O-Acyltransferase Humans Machine Learning Molecular Docking Simulation Protein Binding Molecular Dynamics Simulation Drug Evaluation, Preclinical Non-alcoholic Fatty Liver Disease
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