Development and validation of an adjustment factor for the AutoDock4 scores of ACE inhibitors - Asia, Albert Thomas L.; Bayle, Franco Angelo C.; Dornagon, Rhoen Mae P.; Padilla, Vince Lambert H. (Manila: Department of Pharmacy, College of Pharmacy, University of the Philippines Manila, 2022)
Molecular docking is a powerful technique for simulating ligand-protein interactions and predicting how drugs interact with their targets. However, it often produces scores that do not correlate with experimental binding affinity. Thus, the researchers aimed to determine an ideal ligand preparation method and validate it through redocking, determine a series of pretest scores that will serve as a baseline, and lastly, assess the individual effects of three layers of adjustment factors, as well as their combined effects in the resulting correlation between the adjusted binding scores and the experimental ICs0 values. AutoDock4 was used to generate the binding scores because of its comprehensive and detailed docking outputs that allowed for such adjustments. First, the combination of a conformer search with modifiers applied, followed by a Fine Build was determined and validated to be the ideal method, showing an average binding energy of -7.82 kcal/mol. and an RMSD of 0.648 Å. The effects of these adjustment factors were then validated across the binding scores of 26 ligands with known inhibitory activity towards the target protein. The most amount of variation within the binding scores that each layer of adjustment factors ASM, clustering, and weighting (ligand efficiency and component)were able to explain alone are 33%, 27%, 51%, and 78% respectively, as compared to the 3-11% of the baseline; The isolated effects of component weighting using the ligands' bound and unbound internal energy were both promising. These adjustment factors do not appear to be synergistic, instead limiting the improvement of R2 when these factors are combined. Additionally, these adjustment factors may only be applicable for ligand data sets with large positive skews in ICs0 and heavy atom count.
Thesis (Bachelor of Science in Pharmacy)--University of the Philippines Manila, August 2022.
Keywords: Molecular models; ACE inhibitors