AIMC Topic: Ligands

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Ligand binding affinity prediction with fusion of graph neural networks and 3D structure-based complex graph.

Physical chemistry chemical physics : PCCP Sep 13, 2023
Accurate prediction of protein-ligand binding affinity is pivotal for drug design and discovery. Here, we proposed a novel deep fusion graph neural networks framework named FGNN to learn the protein-ligand interactions from the 3D structures of prote...
Computational Biology Ligands Drug Design Neural Networks, Computer Algorithms
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NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics.

Journal of chemical information and modeling Sep 11, 2023
Machine learning potentials have emerged as a means to enhance the accuracy of biomolecular simulations. However, their application is constrained by the significant computational cost arising from the vast number of parameters compared with traditio...
Molecular Dynamics Simulation Ligands Neural Networks, Computer Machine Learning
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Combining SILCS and Artificial Intelligence for High-Throughput Prediction of the Passive Permeability of Drug Molecules.

Journal of chemical information and modeling Sep 8, 2023
Membrane permeability of drug molecules plays a significant role in the development of new therapeutic agents. Accordingly, methods to predict the passive permeability of drug candidates during a medicinal chemistry campaign offer the potential to ac...
Chemistry, Pharmaceutical Cell Membrane Permeability Permeability Ligands Artificial Intelligence
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CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning.

Journal of chemical information and modeling Sep 7, 2023
The endocannabinoid system, which includes cannabinoid receptor 1 and 2 subtypes (CBR and CBR, respectively), is responsible for the onset of various pathologies including neurodegeneration, cancer, neuropathic and inflammatory pain, obesity, and inf...
Ligands Receptors, Cannabinoid Machine Learning Internet
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Streamlining Large Chemical Library Docking with Artificial Intelligence: the PyRMD2Dock Approach.

Journal of chemical information and modeling Aug 8, 2023
The present contribution introduces a novel computational protocol called PyRMD2Dock, which combines the Ligand-Based Virtual Screening (LBVS) tool PyRMD with the popular docking software AutoDock-GPU (AD4-GPU) to enhance the throughput of virtual sc...
Ligands Small Molecule Libraries Proteins Artificial Intelligence Software Molecular Docking Simulation Drug Discovery
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D3CARP: a comprehensive platform with multiple-conformation based docking, ligand similarity search and deep learning approaches for target prediction and virtual screening.

Computers in biology and medicine Jul 29, 2023
Resource- and time-consuming biological experiments are unavoidable in traditional drug discovery, which have directly driven the evolution of various computational algorithms and tools for drug-target interaction (DTI) prediction. For improving the ...
Protein Binding Ligands Deep Learning Reproducibility of Results Algorithms Molecular Docking Simulation
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Discovery of novel TRPV1 modulators through machine learning-based molecular docking and molecular similarity searching.

Chemical biology & drug design Jul 25, 2023
The transient receptor potential vanilloid 1 (TRPV1) channel belongs to the transient receptor potential channel superfamily and participates in many physiological processes. TRPV1 modulators (both agonists and antagonists) can effectively inhibit pa...
Humans Machine Learning Ligands Molecular Docking Simulation TRPV Cation Channels Molecular Dynamics Simulation
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De novo generation of dual-target ligands for the treatment of SARS-CoV-2 using deep learning, virtual screening, and molecular dynamic simulations.

Journal of biomolecular structure & dynamics Jul 14, 2023
De novo generation of molecules with the necessary features offers a promising opportunity for artificial intelligence, such as deep generative approaches. However, creating novel compounds having biological activities toward two distinct targets con...
Molecular Dynamics Simulation Ligands Deep Learning Artificial Intelligence COVID-19 Humans SARS-CoV-2 Molecular Docking Simulation
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Prediction of IDO1 Inhibitors by a Fingerprint-Based Stacking Ensemble Model Named IDO1Stack.

ChemMedChem Jun 30, 2023
Indoleamine 2,3-dioxygenase 1 (IDO1) is viewed as an extremely promising target for cancer immunotherapy. Here, we proposed a two-layer stacking ensemble model, IDO1Stack, that can efficiently predict IDO1 inhibitors. First, we constructed a series o...
Immunotherapy Ligands Indoleamine-Pyrrole 2,3,-Dioxygenase Algorithms Machine Learning
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AiKPro: deep learning model for kinome-wide bioactivity profiling using structure-based sequence alignments and molecular 3D conformer ensemble descriptors.

Scientific reports Jun 24, 2023
The discovery of selective and potent kinase inhibitors is crucial for the treatment of various diseases, but the process is challenging due to the high structural similarity among kinases. Efficient kinome-wide bioactivity profiling is essential for...
Eye, Artificial Protein Kinase Inhibitors Drug Design Deep Learning Sequence Alignment Ligands
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