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

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

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

Frontiers Homology Modeling, de Novo Design of Ligands, and Molecular Docking Identify Potential Inhibitors of Leishmania donovani 24-Sterol Methyltransferase

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

Frontiers Involvement of P-gp on Reversing Multidrug Resistance Effects of 23-Hydroxybetulinic Acid on Chemotherapeutic Agents

Structures of P-glycoprotein in different conformations (A) Domain

Machine learning approaches and their applications in drug discovery and design - Priya - 2022 - Chemical Biology & Drug Design - Wiley Online Library

Cells, Free Full-Text

Machine learning models for classification tasks related to drug safety