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Ligands

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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...
Protein Binding Proteins Molecular Dynamics Simulation Ligands Thermodynamics HSP90 Heat-Shock Proteins Drug Design Deep Learning
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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...
Molecular Conformation Drug Discovery Models, Molecular Ligands Neural Networks, Computer Artificial Intelligence
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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...
Machine Learning Protein Conformation Algorithms Binding Sites Protein Binding Small Molecule Libraries Molecular Structure Proteins Ligands Models, Molecular
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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 Binding Sites Protein Binding Databases, Protein Proteins Ligands 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...
Models, Molecular Phosphatidylinositol 3-Kinases Molecular Dynamics Simulation Antineoplastic Agents Protein Binding Class Ib Phosphatidylinositol 3-Kinase Ligands Protein Kinase Inhibitors Phosphoinositide-3 Kinase Inhibitors Humans Machine Learning 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...
Humans Machine Learning Drug Evaluation, Preclinical Ligands Binding Sites Drug Discovery Protein Binding Proteins Software Molecular Docking Simulation
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MultiModRLBP: A Deep Learning Approach for Multi-Modal RNA-Small Molecule Ligand Binding Sites Prediction.

IEEE journal of biomedical and health informatics Aug 6, 2024
This study aims to tackle the intricate challenge of predicting RNA-small molecule binding sites to explore the potential value in the field of RNA drug targets. To address this challenge, we propose the MultiModRLBP method, which integrates multi-mo...
Nucleic Acid Conformation Binding Sites Small Molecule Libraries Algorithms RNA Deep Learning Ligands Computational Biology
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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 ...
Proteins Databases, Protein Algorithms Ligands Neural Networks, Computer Binding Sites Drug Discovery Machine Learning Protein Binding
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Biomimetic fusion: Platyper's dual vision for predicting protein-surface interactions.

Materials horizons Jul 29, 2024
Predicting protein binding with the material surface still remains a challenge. Here, a novel approach, platypus dual perception neural network (Platyper), was developed to describe the interactions in protein-surface systems involving bioceramics wi...
Molecular Dynamics Simulation Neural Networks, Computer Surface Properties Biomimetics Protein Binding Ligands Proteins
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