Combining Machine Learning and Molecular Dynamics to Predict P-Glycoprotein Substrates

Deep learning-based molecular dynamics simulation for structure-based drug design against SARS-CoV-2 - Computational and Structural Biotechnology Journal

Kinetic modelling of the P-glycoprotein mediated efflux with a large-scale matched molecular pair analysis - ScienceDirect

Prediction and characterization of P-glycoprotein substrates potentially bound to different sites by emerging chemical pattern and hierarchical cluster analysis - ScienceDirect

Machine learning/molecular dynamic protein structure prediction approach to investigate the protein conformational ensemble

Optimizing variant-specific therapeutic SARS-CoV-2 decoys using deep- learning-guided molecular dynamics simulations

Combining Machine Learning and Molecular Dynamics to Predict P-Glycoprotein Substrates

Differences in ligand-induced protein dynamics extracted from an unsupervised deep learning approach correlate with protein–ligand binding affinities

Machine learning for small molecule drug discovery in academia and industry - ScienceDirect

Pharmaceuticals, Free Full-Text

Structure-based discovery of novel P-glycoprotein inhibitors targeting the nucleotide binding domains

Accelerating drug target inhibitor discovery with a deep generative foundation model

PDF] Computational models for predicting substrates or inhibitors of P- glycoprotein.

Molecules, Free Full-Text

Machine learning for small molecule drug discovery in academia and industry - ScienceDirect

Molecules, Free Full-Text