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.
Subject(s)
Antiviral Agents/chemistry , COVID-19 Drug Treatment , SARS-CoV-2/drug effects , Viral Nonstructural Proteins/chemistry , Artificial Intelligence , Binding Sites , Computer Simulation , Databases, Chemical , Drug Design , Drug Evaluation, Preclinical , Humans , Molecular Docking Simulation , Protein Conformation , Spike Glycoprotein, Coronavirus/chemistry , Structure-Activity RelationshipABSTRACT
BACKGROUND: The new coronavirus of 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread globally and has repercussions within ophthalmological care. It has caused ocular manifestations in some patients, which can spread through eye secretions. OBJECTIVES: The purpose of this review was to summarize the currently available evidence on COVID-19 with regard to its implications for ophthalmology. DESIGN AND SETTING: Narrative review developed by a research group at Universidade Federal de Sao Paulo (UNIFESP), Sao Paulo (SP), Brazil, and at Ludwig-Maximilians-Universitat, Munich, Germany. METHODS: We searched the literature on the repercussions of COVID-19 within ophthalmological care, using the MEDLINE and LILACS databases, with the keywords "COVID-19", "ophthalmology" and "coronavirus", from January 1, 2020, to March 27, 2021. Clinical trials, meta-analysis, randomized controlled trials, reviews and systematic reviews were identified. RESULTS: We retrieved 884 references, of which 42 were considered eligible for intensive review and critical analysis. Most of the studies selected reported the evidence regarding COVID-19 and its implications for ophthalmology. CONCLUSIONS: Knowledge of eye symptoms and ocular transmission of the virus remains incomplete. New clinical trials with larger numbers of patients may answer these questions in the future. Moreover, positively, implementation of innovative changes in medicine such as telemedicine and artificial intelligence may assist in diagnosing eye diseases and in training and education for students.