Accurate Prediction of Inhibitor Binding to HIV-1 Protease Using CANDOCK.

Zackary Falls,Gaurav Chopra,Ram Samudrala,Jonathan Fine

doi:10.3389/fchem.2021.775513

Abstract

The human immunodeficiency virus 1 (HIV-1) protease is an important target for treating HIV infection. Our goal was to benchmark a novel molecular docking protocol and determine its effectiveness as a therapeutic repurposing tool by predicting inhibitor potency to this target. To accomplish this, we predicted the relative binding scores of various inhibitors of the protease using CANDOCK, a hierarchical fragment-based docking protocol with a knowledge-based scoring function. We first used a set of 30 HIV-1 protease complexes as an initial benchmark to optimize the parameters for CANDOCK. We then compared the results from CANDOCK to two other popular molecular docking protocols Autodock Vina and Smina. Our results showed that CANDOCK is superior to both of these protocols in terms of correlating predicted binding scores to experimental binding affinities with a Pearson coefficient of 0.62 compared to 0.48 and 0.49 for Vina and Smina, respectively. We further leveraged the Database of Useful Decoys: Enhanced (DUD-E) HIV protease set to ascertain the effectiveness of each protocol in discriminating active versus decoy ligands for proteases. CANDOCK again displayed better efficacy over the other commonly used molecular docking protocols with area under the receiver operating characteristic curve (AUROC) of 0.94 compared to 0.71 and 0.74 for Vina and Smina. These findings support the utility of CANDOCK to help discover novel therapeutics that effectively inhibit HIV-1 and possibly other retroviral proteases.

Highlights

Inhibition of the Human immunodeficiency virus (HIV) protease blocks viral maturation and replication, making inhibitors of this vital enzyme an important class of drugs for the treatment of HIV infection (Wlodawer et al, 1989; Wlodawer and Vondrasek, 1998)
The performance of CANDOCK on the Database of Useful Decoys: Enhanced (DUD-E) HIV protease set exceeded Vina and Smina with an area under the receiver operating characteristic curve (AUROC) of 0.94 for CANDOCK compared to 0.71 for Vina and 0.74 for Smina. These results demonstrate the predictive power of CANDOCK for the specific case of assessing inhibitor potency against human immunodeficiency virus 1 (HIV-1) protease
This visualization showed us that rmr and fmr with all cutoffs were very high-performing rankers, where variation of the selector shows negligible effect on the correlations. These results were interesting from a high-level perspective by showing the efficacy of the fmr and rmr rankers, but we wanted to assess specific parameter sets to determine which would be the most accurate for the HIV-1 protease–inhibitor complexes

Summary

Introduction

Inhibition of the Human immunodeficiency virus (HIV) protease blocks viral maturation and replication, making inhibitors of this vital enzyme an important class of drugs for the treatment of HIV infection (Wlodawer et al, 1989; Wlodawer and Vondrasek, 1998). Previous efforts to predict inhibitor activity against human immunodeficiency virus 1 (HIV-1) proteases include rule-based methods (Shafer et al, 1999; Kantor et al, 2001), support vector machine (SVM) models (Beerenwinkel et al, 2002; Cai et al, 2003), chemical shape and features (Yadav et al, 2012; Pandit et al, 2006; DesJarlais and Dixon, 1994; Wei et al, 2015), various docking protocols (Chang et al, 2007, 2010), and molecular dynamics (MD) simulations (Rick et al, 1998; Wang and Kollman, 2001; Wang K. et al, 2004; Jenwitheesuk and Samudrala, 2003; Jenwitheesuk et al, 2004; Jenwitheesuk and Samudrala, 2005a; Jenwitheesuk and Samudrala, 2005b) These different approaches have displayed varying results. These results display the tradeoff between sensitivity and specificity and the limitations of this model

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Conclusion