AIMC Topic: Ligands

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Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents.

Molecular diversity Jul 19, 2021
Neurological disorders affect various aspects of life. Finding drugs for the central nervous system is a very challenging and complex task due to the involvement of the blood-brain barrier, P-glycoprotein, and the drug's high attrition rates. The ava...
Models, Molecular Neurodegenerative Diseases Ligands Big Data Drug Development Drug Repositioning Quantitative Structure-Activity Relationship Machine Learning Algorithms Databases, Factual Drug Design Drug Discovery Deep Learning Humans Artificial Intelligence
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PyRMD: A New Fully Automated AI-Powered Ligand-Based Virtual Screening Tool.

Journal of chemical information and modeling Jul 16, 2021
Artificial intelligence (AI) algorithms are dramatically redefining the current drug discovery landscape by boosting the efficiency of its various steps. Still, their implementation often requires a certain level of expertise in AI paradigms and codi...
Algorithms Drug Discovery Ligands Artificial Intelligence Software
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Machine Learning and Enhanced Sampling Simulations for Computing the Potential of Mean Force and Standard Binding Free Energy.

Journal of chemical theory and computation Jul 14, 2021
Computational capabilities are rapidly increasing, primarily because of the availability of GPU-based architectures. This creates unprecedented simulative possibilities for the systematic and robust computation of thermodynamic observables, including...
Machine Learning Bridged-Ring Compounds Ligands Protein Binding Glycogen Synthase Kinase 3 beta Imidazoles Thermodynamics Molecular Dynamics Simulation
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MolGpka: A Web Server for Small Molecule p Prediction Using a Graph-Convolutional Neural Network.

Journal of chemical information and modeling Jul 12, 2021
p is an important property in the lead optimization process since the charge state of a molecule in physiologic pH plays a critical role in its biological activity, solubility, membrane permeability, metabolism, and toxicity. Accurate and fast estima...
Ligands Humans Neural Networks, Computer Machine Learning Computers Drug Discovery
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Structure-aware machine learning identifies microRNAs operating as Toll-like receptor 7/8 ligands.

RNA biology Jul 9, 2021
MicroRNAs (miRNAs) can serve as activation signals for membrane receptors, a recently discovered function that is independent of the miRNAs' conventional role in post-transcriptional gene regulation. Here, we introduce a machine learning approach, Br...
Animals Mice Mice, Inbred C57BL Humans Machine Learning Toll-Like Receptor 7 MicroRNAs Gene Expression Regulation Ligands Microglia Toll-Like Receptor 8 Oligonucleotides
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Molecular insights on ABL kinase activation using tree-based machine learning models and molecular docking.

Molecular diversity Jun 30, 2021
Abelson kinase (c-Abl) is a non-receptor tyrosine kinase involved in several biological processes essential for cell differentiation, migration, proliferation, and survival. This enzyme's activation might be an alternative strategy for treating disea...
Quantitative Structure-Activity Relationship Molecular Structure Proto-Oncogene Proteins c-abl Humans Protein Kinase Inhibitors Molecular Dynamics Simulation Molecular Docking Simulation Machine Learning Binding Sites Ligands Drug Design Protein Binding
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Ligand Nanocluster Array Enables Artificial-Intelligence-Based Detection of Hidden Features in T-Cell Architecture.

Nano letters Jun 25, 2021
Protein patterning has emerged as a powerful means to interrogate adhering cells. However, the tools to apply a sub-micrometer periodic stimulus and the analysis of the response are still being standardized. We propose a technique combining electron ...
T-Lymphocytes Humans Ligands Intelligence Artificial Intelligence Printing
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A multi-conformational virtual screening approach based on machine learning targeting PI3Kγ.

Molecular diversity Jun 23, 2021
Nowadays, more and more attention has been attracted to develop selective PI3Kγ inhibitors, but the unique structural features of PI3Kγ protein make it a very big challenge. In the present study, a virtual screening strategy based on machine learning...
Models, Molecular Phosphoinositide-3 Kinase Inhibitors Molecular Structure Ligands ROC Curve Machine Learning Molecular Dynamics Simulation Databases, Pharmaceutical Molecular Conformation Molecular Docking Simulation Protein Binding Class Ib Phosphatidylinositol 3-Kinase Binding Sites Drug Discovery Structure-Activity Relationship
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Ensembling machine learning models to boost molecular affinity prediction.

Computational biology and chemistry Jun 12, 2021
This study unites six popular machine learning approaches to enhance the prediction of a molecular binding affinity between receptors (large protein molecules) and ligands (small organic molecules). Here we examine a scheme where affinity of ligands ...
Acetaldehyde Molecular Docking Simulation Humans Ligands Neural Networks, Computer Thrombin Machine Learning
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Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics.

Nature communications Jun 7, 2021
Characterizing the human leukocyte antigen (HLA) bound ligandome by mass spectrometry (MS) holds great promise for developing vaccines and drugs for immune-oncology. Still, the identification of non-tryptic peptides presents substantial computational...
Molecular Medicine Ligands Extracellular Matrix Proteins Histocompatibility Antigens Class II Humans Histocompatibility Antigens Class I Peptides Proteomics Tandem Mass Spectrometry Deep Learning HLA Antigens Mass Spectrometry Epitopes Cell Line
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