Ligand similarity guided receptor selection enhances docking accuracy and recall for non-nucleoside HIV reverse transcriptase inhibitors.

Abstract

Non-nucleoside reverse transcriptase inhibitors (NNRTI) are allosteric inhibitors of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT), a viral polymerase essential to infection. Despite the availability of >150 NNRTI-bound RT crystal structures, rational design of new NNRTI remains challenging because of the variability of their induced fit, hydrophobic binding patterns. Docking NNRTI yields inconsistent results that vary markedly depending on the receptor structure used, as only 27% of the >20k cross-docking calculations we performed using known NNRTI were accurate. In order to determine if a hospitable receptor for docking could be selected a priori, we evaluated more than 40 chemical descriptors for their ability to pre-select a best receptor for NNRTI cross-docking. The receptor selection was based on similarity scores between the bound- and target-ligands generated by each descriptor. The top descriptors were able to double the probability of cross-docking accuracy over random receptor selection. Additionally, recall of known NNRTI from a large library of similar decoys was increased using the same approach. The results demonstrate the utility of pre-selecting receptors when docking into difficult targets. Graphical Abstract Cross-docking accuracy increases when using chemical descriptors to determine the NNRTI with maximum similarity to the new compound and then docking into its respective receptor.