AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Molecular Structure

Showing 111 to 120 of 313 articles

Clear Filters

Machine Learning Prediction of Allosteric Drug Activity from Molecular Dynamics.

The journal of physical chemistry letters Apr 12, 2021
Allosteric drugs have been attracting increasing interest over the past few years. In this context, it is common practice to use high-throughput screening for the discovery of non-natural allosteric drugs. While the discovery stage is supported by a ...
Molecular Structure Humans Pyrones Machine Learning Coumarins Molecular Dynamics Simulation Dihydropyridines Biphenyl Compounds Allosteric Regulation
View on PubMed DOI

Identification of novel inhibitors of Keap1/Nrf2 by a promising method combining protein-protein interaction-oriented library and machine learning.

Scientific reports Apr 1, 2021
Protein-protein interactions (PPIs) are prospective but challenging targets for drug discovery, because screening using traditional small-molecule libraries often fails to identify hits. Recently, we developed a PPI-oriented library comprising 12,593...
Structure-Activity Relationship Molecular Structure Molecular Dynamics Simulation Machine Learning Drug Discovery Molecular Docking Simulation Binding Sites Protein Interaction Maps Humans Small Molecule Libraries Ligands Protein Interaction Mapping Protein Binding Molecular Conformation Kelch-Like ECH-Associated Protein 1 NF-E2-Related Factor 2
View on PubMed DOI

Classification and Design of HIV-1 Integrase Inhibitors Based on Machine Learning.

Computational and mathematical methods in medicine Apr 1, 2021
A key enzyme in human immunodeficiency virus type 1 (HIV-1) life cycle, integrase (IN) aids the integration of viral DNA into the host DNA, which has become an ideal target for the development of anti-HIV drugs. A total of 1785 potential HIV-1 IN inh...
HIV Integrase HIV Infections Humans Structure-Activity Relationship HIV-1 Computational Biology Molecular Structure Machine Learning HIV Integrase Inhibitors Decision Trees Bayes Theorem Databases, Pharmaceutical Drug Design
View on PubMed DOI

Epigenetic Target Fishing with Accurate Machine Learning Models.

Journal of medicinal chemistry Mar 26, 2021
Epigenetic targets are of significant importance in drug discovery research, as demonstrated by the eight approved epigenetic drugs for treatment of cancer and the increasing availability of chemogenomic data related to epigenetics. This data represe...
Structure-Activity Relationship Molecular Structure Databases, Chemical Proof of Concept Study Histone Deacetylases Organic Chemicals Epigenomics Transcription Factors Machine Learning Drug Discovery
View on PubMed DOI

Artificial Intelligence Applied to the Rapid Identification of New Antimalarial Candidates with Dual-Stage Activity.

ChemMedChem Mar 16, 2021
Increasing reports of multidrug-resistant malaria parasites urge the discovery of new effective drugs with different chemical scaffolds. Protein kinases play a key role in many cellular processes such as signal transduction and cell division, making ...
Artificial Intelligence Dose-Response Relationship, Drug Structure-Activity Relationship Antimalarials Parasitic Sensitivity Tests Protozoan Proteins Protein Kinase Inhibitors Plasmodium falciparum Molecular Structure Drug Evaluation, Preclinical Mitogen-Activated Protein Kinase Kinases
View on PubMed DOI

A novel artificial intelligence protocol to investigate potential leads for diabetes mellitus.

Molecular diversity Mar 9, 2021
Dipeptidyl peptidase-4 (DPP4) is highly participated in regulating diabetes mellitus (DM), and inhibitors of DPP4 may act as potential DM drugs. Therefore, we performed a novel artificial intelligence (AI) protocol to screen and validate the potentia...
Hydrogen Bonding Binding Sites Dipeptidyl-Peptidase IV Inhibitors Humans Molecular Docking Simulation Protein Binding Neural Networks, Computer Workflow Drug Design Hypoglycemic Agents Drug Discovery Molecular Dynamics Simulation Molecular Structure Artificial Intelligence Quantitative Structure-Activity Relationship Machine Learning Algorithms
View on PubMed DOI

CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks.

Nature methods Feb 4, 2021
Cryo-electron microscopy (cryo-EM) single-particle analysis has proven powerful in determining the structures of rigid macromolecules. However, many imaged protein complexes exhibit conformational and compositional heterogeneity that poses a major ch...
Neural Networks, Computer Molecular Structure Macromolecular Substances Cryoelectron Microscopy
View on PubMed DOI

Classification models and SAR analysis on CysLT1 receptor antagonists using machine learning algorithms.

Molecular diversity Feb 3, 2021
Cysteinyl leukotrienes 1 (CysLT1) receptor is a promising drug target for rhinitis or other allergic diseases. In our study, we built classification models to predict bioactivities of CysLT1 receptor antagonists. We built a dataset with 503 CysLT1 re...
Models, Molecular Molecular Structure Quantitative Structure-Activity Relationship Binding Sites Cheminformatics Leukotriene Antagonists Drug Discovery ROC Curve Protein Binding Machine Learning Algorithms Reproducibility of Results Receptors, Leukotriene
View on PubMed DOI

Single-Step Retrosynthesis Prediction Based on the Identification of Potential Disconnection Sites Using Molecular Substructure Fingerprints.

Journal of chemical information and modeling Feb 3, 2021
The proper application of retrosynthesis to identify possible transformations for a given target compound requires a lot of chemistry knowledge and experience. However, because the complexity of this technique scales together with the complexity of t...
Humans Machine Learning Artificial Intelligence Molecular Structure
View on PubMed DOI

Using Domain-Specific Fingerprints Generated Through Neural Networks to Enhance Ligand-Based Virtual Screening.

Journal of chemical information and modeling Jan 26, 2021
Similarity-based virtual screening is a fundamental tool in the early drug discovery process and relies heavily on molecular fingerprints. We propose a novel strategy of generating domain-specific fingerprints by training neural networks on target-sp...
Molecular Structure Ligands Neural Networks, Computer Drug Discovery
View on PubMed DOI
Popular Topics
Recent Journals