AI Medical Compendium Journal:
Journal of chemical information and modeling

Showing 141 to 150 of 934 articles

Meta-Learning Enables Complex Cluster-Specific Few-Shot Binding Affinity Prediction for Protein-Protein Interactions.

Journal of chemical information and modeling Jan 7, 2025
Predicting protein-protein interaction (PPI) binding affinities in unseen protein complex clusters is essential for elucidating complex protein interactions and for the targeted screening of peptide- or protein-based drugs. We introduce MCGLPPI++, a ...
Protein Interaction Mapping Protein Binding Proteins Receptors, Antigen, T-Cell Machine Learning
View on PubMed DOI

High-Accuracy Identification and Structure-Activity Analysis of Antioxidant Peptides via Deep Learning and Quantum Chemistry.

Journal of chemical information and modeling Jan 7, 2025
Antioxidant peptides (AOPs) hold great promise for mitigating oxidative-stress-related diseases, but their discovery is hindered by inefficient and time-consuming traditional methods. To address this, we developed an innovative framework combining ma...
Structure-Activity Relationship Antioxidants Quantum Theory Peptides Deep Learning
View on PubMed DOI

Enhanced Sampling Simulations of RNA-Peptide Binding Using Deep Learning Collective Variables.

Journal of chemical information and modeling Jan 7, 2025
Enhanced sampling (ES) simulations of biomolecular recognition, such as binding small molecules to proteins and nucleic acid targets, protein-protein association, and protein-nucleic acid interactions, have gained significant attention in the simulat...
Peptides RNA Molecular Dynamics Simulation Nucleic Acid Conformation Protein Binding RNA, Viral Deep Learning
View on PubMed DOI

PathInHydro, a Set of Machine Learning Models to Identify Unbinding Pathways of Gas Molecules in [NiFe] Hydrogenases.

Journal of chemical information and modeling Jan 7, 2025
Machine learning (ML) is a powerful tool for the automated data analysis of molecular dynamics (MD) simulations. Recent studies showed that ML models can be used to identify protein-ligand unbinding pathways and understand the underlying mechanism. T...
Carbon Monoxide Hydrogenase Desulfovibrio Molecular Dynamics Simulation Hydrogen Oxygen Machine Learning
View on PubMed DOI

Semisupervised Contrastive Learning for Bioactivity Prediction Using Cell Painting Image Data.

Journal of chemical information and modeling Jan 6, 2025
Morphological profiling has recently demonstrated remarkable potential for identifying the biological activities of small molecules. Alongside the fully supervised and self-supervised machine learning methods recently proposed for bioactivity predict...
Machine Learning Drug Discovery Humans Supervised Machine Learning Drug Repositioning Image Processing, Computer-Assisted
View on PubMed DOI

ComNet: A Multiview Deep Learning Model for Predicting Drug Combination Side Effects.

Journal of chemical information and modeling Jan 3, 2025
As combination therapy becomes more common in clinical applications, predicting adverse effects of combination medications is a challenging task. However, there are three limitations of the existing prediction models. First, they rely on a single vie...
Humans Drug Combinations Drug-Related Side Effects and Adverse Reactions Deep Learning
View on PubMed DOI

Neighborhood Topology-Aware Knowledge Graph Learning and Microbial Preference Inferring for Drug-Microbe Association Prediction.

Journal of chemical information and modeling Jan 2, 2025
The human microbiota may influence the effectiveness of drug therapy by activating or inactivating the pharmacological properties of drugs. Computational methods have demonstrated their ability to screen reliable microbe-drug associations and uncover...
Machine Learning Humans Microbiota Computational Biology
View on PubMed DOI

Machine Learning for Reaction Performance Prediction in Allylic Substitution Enhanced by Automatic Extraction of a Substrate-Aware Descriptor.

Journal of chemical information and modeling Jan 2, 2025
Despite remarkable advancements in the organic synthesis field facilitated by the use of machine learning (ML) techniques, the prediction of reaction outcomes, including yield estimation, catalyst optimization, and mechanism identification, continues...
Algorithms Density Functional Theory Machine Learning Allyl Compounds Iridium Automation Catalysis
View on PubMed DOI

Interpretable Deep-Learning p Prediction for Small Molecule Drugs via Atomic Sensitivity Analysis.

Journal of chemical information and modeling Dec 30, 2024
Machine learning (ML) models now play a crucial role in predicting properties essential to drug development, such as a drug's logscale acid-dissociation constant (p). Despite recent architectural advances, these models often generalize poorly to nove...
Small Molecule Libraries Deep Learning Pharmaceutical Preparations Neural Networks, Computer
View on PubMed DOI

SchNet_IIA: Potential Energy Surface Fitting by Interatomic Interactions Attention Based on Transfer Learning Analysis.

Journal of chemical information and modeling Dec 30, 2024
Machine learning methods for fitting potential energy surfaces and molecular dynamics simulations are becoming increasingly popular due to their potentially high accuracy and savings in computational resources. However, existing application models of...
Surface Properties Thermodynamics Molecular Dynamics Simulation Machine Learning Neural Networks, Computer
View on PubMed DOI
Popular Topics
Popular Journals