Target-Centered Drug Repurposing Predictions of Human Angiotensin-Converting Enzyme 2 (ACE2) and Transmembrane Protease Serine Subtype 2 (TMPRSS2) Interacting Approved Drugs for Coronavirus Disease 2019 (COVID-19) Treatment through a Drug-Target Interaction Deep Learning Model

Viruses
Yoonjung ChoiBo Ram Beck

Abstract

Previously, our group predicted commercially available Food and Drug Administration (FDA) approved drugs that can inhibit each step of the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using a deep learning-based drug-target interaction model called Molecule Transformer-Drug Target Interaction (MT-DTI). Unfortunately, additional clinically significant treatment options since the approval of remdesivir are scarce. To overcome the current coronavirus disease 2019 (COVID-19) more efficiently, a treatment strategy that controls not only SARS-CoV-2 replication but also the host entry step should be considered. In this study, we used MT-DTI to predict FDA approved drugs that may have strong affinities for the angiotensin-converting enzyme 2 (ACE2) receptor and the transmembrane protease serine 2 (TMPRSS2) which are essential for viral entry to the host cell. Of the 460 drugs with Kd of less than 100 nM for the ACE2 receptor, 17 drugs overlapped with drugs that inhibit the interaction of ACE2 and SARS-CoV-2 spike reported in the NCATS OpenData portal. Among them, enalaprilat, an ACE inhibitor, showed a Kd value of 1.5 nM against the ACE2. Furthermore, three of the top 30 drugs with strong affinity predict...Continue Reading

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Citations

Jun 3, 2021·Journal of Clinical Medicine·Md Mohaimenul IslamYu-Chuan Jack Li
Jul 31, 2021·Journal of Healthcare Engineering·Nishant JhaM Saravana Kumar

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Methods Mentioned

BETA
AlphaLISA
RNA-seq

Clinical Trials Mentioned

NCT04468087
NCT04381936

Software Mentioned

AutoDockTools
Open Babel
AlphaLISA
AutoDock Vina
CLUE
OpenData
gen3d
Molecule Transformer (
ACE2
TMPRSS2

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