Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19

Abstract

We present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.

Benchmarking the Ability of Common Docking Programs to Correctly Reproduce and Score Binding Modes in SARS-CoV-2 Protease Mpro

“…Indeed, MD simulations have pointed to several water molecules, as important for M pro . 11 , 18 , 20 , 24 , 26 , 29 , 77 …”

Discovery of SARS-CoV-2 MproPeptide Inhibitors from Modelling Substrate and Ligand Binding

“…11,12 Multiple crystallographic and computational modelling studies concerning the M pro mechanism [13][14][15][16] and inhibition are available. [17][18][19][20][21][22] (For a list of modelling studies on M pro and related coronaviruses, see the CORD-19 database 23 ). It is proposed that during M pro catalysis, His-41 deprotonates the Cys-145 thiol, which then reacts with the carbonyl of the scissile amide to give an acyl-enzyme intermediate stabilised by a hydrogen bond network that includes the scissile amide carbonyl in an 'oxyanion hole'.…”

Biomolecular modeling thrives in the age of technology

“…The past two decades took us through huge triumphs, as successes in key areas were realized. These include protein folding (for example, millisecond all-atom simulations of protein folding 6 ), mechanisms of large biomolecular networks (for example, virus simulations 7 ) and drug applications (for example, search of drugs for coronavirus disease 2019 (COVID-19) 8 ). On the shoulders of the force-field pioneers Allinger, Lifson, Scheraga and Kollman, computations in biology were celebrated in 2013 with the Nobel Prize in Chemistry recognizing the work of Martin Karplus, Michael Levitt and Arieh Warshel 9 .…”