Identification of potential dihydrofolate reductase inhibitors using QSAR, molecular docking, dynamics simulations and free energy calculation.

Herein we describe the use of molecular docking simulations, quantitative structure-activity relationships studies and ADMETox predictions to analyse the molecular recognition of a series of 7-aryl-2,4-diaminoquinazoline derivatives on the inhibition of dihydrofolate reductase and conducted a virtual screening to discover new potential inhibitors. A quantitative structure-activity relationship model was developed using 40 compounds and two selected descriptors. These descriptors indicated the importance of pKa and molar refractivity for the inhibitory activity against DHFR.

Integration of an Inhibitor-like Rule and Structure-based Virtual Screening for the Discovery of Novel Myeloperoxidase Inhibitors.

Myeloperoxidase (MPO) is an attractive therapeutic target against inflammation. Herein, we developed an inhibitor-like rule, based on known MPO inhibitors, and generated a target database containing 6546 molecules with privileged inhibitory properties. Using a structure-based approach validated by decoys, robust statistical metrics, redocking, and cross-docking, we selected 10 putative MPO inhibitors with high chemical diversity.