AIMC Topic: Ligands

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In silico assessments of the small molecular boron agents to pave the way for artificial intelligence-based boron neutron capture therapy.

European journal of medicinal chemistry Sep 6, 2024
Boron neutron capture therapy (BNCT) is a highly targeted, selective and effective technique to cure various types of cancers, with less harm to the healthy cells. In principle, BNCT treatment needs to distribute the boron (B) atoms inside the tumor ...
Humans Boron Neutron Capture Therapy Boron Ligands Small Molecule Libraries Boron Compounds Artificial Intelligence Computer Simulation Neoplasms Molecular Docking Simulation Molecular Structure Molecular Dynamics Simulation
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Teaching old docks new tricks with machine learning enhanced ensemble docking.

Scientific reports Sep 5, 2024
We here introduce Ensemble Optimizer (EnOpt), a machine-learning tool to improve the accuracy and interpretability of ensemble virtual screening (VS). Ensemble VS is an established method for predicting protein/small-molecule (ligand) binding. Unlike...
Protein Conformation Protein Binding Proteins Ligands Software Molecular Docking Simulation Machine Learning
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An artificial intelligence accelerated virtual screening platform for drug discovery.

Nature communications Sep 5, 2024
Structure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding p...
Ubiquitin-Protein Ligases Small Molecule Libraries NAV1.7 Voltage-Gated Sodium Channel Drug Evaluation, Preclinical Ligands Crystallography, X-Ray Molecular Docking Simulation Drug Discovery Protein Binding Humans Artificial Intelligence
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Enhancing protein-ligand binding affinity prediction through sequential fusion of graph and convolutional neural networks.

Journal of computational chemistry Sep 2, 2024
Predicting protein-ligand binding affinity is a crucial and challenging task in structure-based drug discovery. With the accumulation of complex structures and binding affinity data, various machine-learning scoring functions, particularly those base...
Protein Binding Proteins Ligands Neural Networks, Computer Drug Discovery Deep Learning
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From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Aug 29, 2024
Accurate prediction of protein-ligand binding affinities is an essential challenge in structure-based drug design. Despite recent advances in data-driven methods for affinity prediction, their accuracy is still limited, partially because they only ta...
Thermodynamics HSP90 Heat-Shock Proteins Proteins Molecular Dynamics Simulation Ligands Drug Design Deep Learning Protein Binding
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Conformational Space Profiling Enhances Generic Molecular Representation for AI-Powered Ligand-Based Drug Discovery.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Aug 29, 2024
The molecular representation model is a neural network that converts molecular representations (SMILES, Graph) into feature vectors, and is an essential module applied across a wide range of artificial intelligence-driven drug discovery scenarios. Ho...
Neural Networks, Computer Ligands Molecular Conformation Artificial Intelligence Drug Discovery Models, Molecular
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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...
Ligands Protein Conformation Binding Sites Small Molecule Libraries Proteins Models, Molecular Molecular Structure Algorithms Protein Binding Machine Learning
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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...
Databases, Protein Ligands Binding Sites Deep Learning Protein Binding Proteins 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...
Humans Machine Learning Phosphatidylinositol 3-Kinases Molecular Dynamics Simulation Ligands Protein Kinase Inhibitors Phosphoinositide-3 Kinase Inhibitors Class Ib Phosphatidylinositol 3-Kinase Antineoplastic Agents Protein Binding Models, Molecular Neoplasms Molecular Docking Simulation Drug Design
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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...
Protein Binding Proteins Drug Evaluation, Preclinical Ligands Binding Sites Software Molecular Docking Simulation Drug Discovery Humans Machine Learning
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