AIMC Topic: Ligands

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Versatile Framework for Drug-Target Interaction Prediction by Considering Domain-Specific Features.

Journal of chemical information and modeling Jul 8, 2024
Predicting drug-target interactions (DTIs) is one of the crucial tasks in drug discovery, but traditional wet-lab experiments are costly and time-consuming. Recently, deep learning has emerged as a promising tool for accelerating DTI prediction due t...
Drug Discovery Ligands Protein Domains Deep Learning Pharmaceutical Preparations Proteins
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Docking Score ML: Target-Specific Machine Learning Models Improving Docking-Based Virtual Screening in 155 Targets.

Journal of chemical information and modeling Jul 3, 2024
In drug discovery, molecular docking methods face challenges in accurately predicting energy. Scoring functions used in molecular docking often fail to simulate complex protein-ligand interactions fully and accurately leading to biases and inaccuraci...
Proteins Drug Evaluation, Preclinical Ligands Antineoplastic Agents User-Computer Interface Molecular Docking Simulation Drug Discovery Humans Machine Learning
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Proximity Graph Networks: Predicting Ligand Affinity with Message Passing Neural Networks.

Journal of chemical information and modeling Jul 2, 2024
Message passing neural networks (MPNNs) on molecular graphs generate continuous and differentiable encodings of small molecules with state-of-the-art performance on protein-ligand complex scoring tasks. Here, we describe the proximity graph network (...
Ligands Protein Binding Proteins Neural Networks, Computer Molecular Docking Simulation
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Equivariant Line Graph Neural Network for Protein-Ligand Binding Affinity Prediction.

IEEE journal of biomedical and health informatics Jul 2, 2024
Binding affinity prediction of three-dimensional (3D) protein-ligand complexes is critical for drug repositioning and virtual drug screening. Existing approaches usually transform a 3D protein-ligand complex to a two-dimensional (2D) graph, and then ...
Neural Networks, Computer Computational Biology Proteins Ligands Algorithms Protein Binding
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A DNA robotic switch with regulated autonomous display of cytotoxic ligand nanopatterns.

Nature nanotechnology Jul 1, 2024
The clustering of death receptors (DRs) at the membrane leads to apoptosis. With the goal of treating tumours, multivalent molecular tools that initiate this mechanism have been developed. However, DRs are also ubiquitously expressed in healthy tissu...
Humans Tumor Microenvironment Animals Cell Line, Tumor Female Breast Neoplasms Hydrogen-Ion Concentration Nanostructures Ligands Robotics DNA Mice Apoptosis
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Scaffold-Hopped Compound Identification by Ligand-Based Approaches with a Prospective Affinity Test.

Journal of chemical information and modeling Jul 1, 2024
Scaffold-hopped (SH) compounds are bioactive compounds structurally different from known active compounds. Identifying SH compounds in the ligand-based approaches has been a central issue in medicinal chemistry, and various molecular representations ...
Ligands Protein Kinase Inhibitors Support Vector Machine Humans Models, Molecular Algorithms
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AlphaFold2 structures guide prospective ligand discovery.

Science (New York, N.Y.) Jun 21, 2024
AlphaFold2 (AF2) models have had wide impact but mixed success in retrospective ligand recognition. We prospectively docked large libraries against unrefined AF2 models of the σ and serotonin 2A (5-HT2A) receptors, testing hundreds of new molecules a...
Humans Protein Conformation Molecular Docking Simulation Cryoelectron Microscopy Drug Design Protein Folding Serotonin 5-HT2 Receptor Agonists Small Molecule Libraries Ligands Drug Discovery Serotonin 5-HT2 Receptor Antagonists Receptor, Serotonin, 5-HT2A Deep Learning Receptors, sigma
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SAnDReS 2.0: Development of machine-learning models to explore the scoring function space.

Journal of computational chemistry Jun 20, 2024
Classical scoring functions may exhibit low accuracy in determining ligand binding affinity for proteins. The availability of both protein-ligand structures and affinity data make it possible to develop machine-learning models focused on specific pro...
Machine Learning Molecular Docking Simulation Software Proteins Ligands
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Accelerating Molecular Docking using Machine Learning Methods.

Molecular informatics Jun 8, 2024
Virtual screening (VS) is one of the well-established approaches in drug discovery which speeds up the search for a bioactive molecule and, reduces costs and efforts associated with experiments. VS helps to narrow down the search space of chemical sp...
Machine Learning Drug Discovery Ligands Molecular Docking Simulation
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CENsible: Interpretable Insights into Small-Molecule Binding with Context Explanation Networks.

Journal of chemical information and modeling Jun 7, 2024
We present a novel and interpretable approach for assessing small-molecule binding using context explanation networks. Given the specific structure of a protein/ligand complex, our CENsible scoring function uses a deep convolutional neural network to...
Protein Binding Proteins Neural Networks, Computer Machine Learning Ligands Small Molecule Libraries
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