Chemical-informatics approach to COVID-19 drug discovery: Monte Carlo based QSAR, virtual screening and molecular docking study of some in-house molecules as papain-like protease (PLpro) inhibitors

Abstract

World Health Organization characterized novel coronavirus disease , caused by severe acute respiratory syndrome (SARS) coronavirus-2 (SARS-CoV-2) as world pandemic. This infection has been spreading alarmingly by causing huge social and economic disruption. In order to response quickly, the inhibitors already designed against different targets of previous human coronavirus infections will be a great starting point for anti-SARS-CoV-2 inhibitors. In this study, our approach integrates different ligand based drug design strategies of some in-house chemicals. The study design was composed of some major aspects: (a) classification QSAR based data mining of diverse SARS-CoV papain-like protease (PLpro) inhibitors, (b) QSAR based virtual screening (VS) to identify in-house molecules that could be effective against putative target SARS-CoV PLpro and (c) finally validation of hits through receptor-ligand interaction analysis. This approach could be used to aid in the process of COVID-19 drug discovery. It will introduce key concepts, set the stage for QSAR based screening of active molecules against putative SARS-CoV-2 PLpro enzyme. Moreover, the QSAR models reported here would be of further use to screen large database. This study will assume that the reader is approaching the field of QSAR and molecular docking based drug discovery against SARS-CoV-2 PLpro with little prior knowledge.

Protease targeted COVID-19 drug discovery and its challenges: Insight into viral main protease (Mpro) and papain-like protease (PLpro) inhibitors

“…Since the SARS-CoV-2 Mpro shares about 96% sequence similarity with SARS-CoV Mpro, previously reported SARS-CoV Mpro inhibitors may have huge prospect to show their efficacy against SARS-CoV-2 Mpro also. By May this year, we have endorsed our rational anti-viral drug design efforts through data mining and molecular docking studies 10 . In an endeavour, our research team explored the crucial structural fingerprints modulating SARS-CoV PLpro inhibitory activities by the aid of 2D-QSAR, SPCI analysis as well as Monte Carlo optimization based QSAR.…”

“…In late December 2019, the newly emerged highly contagious novel coronavirus disease 2019 (COVID-19) was identified in Humans 1 , 2 . The outburst of virus containing a single positive-stranded RNA first found to occur in Wuhan, China and was named as severe acute respiratory syndrome (SARS)-CoV-2 (SARS-CoV-2) 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 . Worldwide more than millions of cases have been registered 11 , 12 .…”

Exploring RdRp–remdesivir interactions to screen RdRp inhibitors for the management of novel coronavirus 2019-nCoV

“…Pharmaceutical companies such as Ascletis Pharma are also testing two HIV protease inhibitors (ritonavir and ASC09) to treat COVID-19 [ 7 ], while Gilead Sciences is investigating remdesivir (GS-5734), a broad-spectrum antiviral originally developed to treat Ebola virus and then dropped, which has shown significant results against coronavirus infection [ 8 ]. Academic research groups are also focusing on utilizing reported inhibitors for virtual screening analysis against different viral targets such as 3-C like protease [ 9 , 10 ], papain-like protease (PLpro) [ 11 ], etc. However, recently researchers have favoured targeting a virus-specific protein such as RdRp, noting that coronaviruses do not contain or use a reverse transcriptase [ 12 ].…”

Chemistry in Times of Artificial Intelligence

“…AI techniques have also been used to discover drugs that might be used against COVID-19 targets. [89,90]…”