Evidence map›Paper›PMID 32817950›Full record

ArticlebioRxiv : the preprint server for biology2020

Discovery of COVID-19 Inhibitors Targeting the SARS-CoV2 Nsp13 Helicase.

Mark Andrew White, Wei Lin, Xiaodong Cheng

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 18 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Mark Andrew WhiteSealy Center for Structural Biology and Molecular Biophysics, The University of Texas Medical Branch, Galveston, TX 77555, USA.
Wei LinDepartment of Integrative Biology & Pharmacology, University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Xiaodong ChengDepartment of Integrative Biology & Pharmacology, University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
The University of Texas Health Science Center at Houston · USThe University of Texas Medical Branch at Galveston · US

Funding

Preclinical Development of Novel Rickettsiosis Therapeutics Targeting EPAC1R01AI111464 · NIAID · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI CHENG, XIAODONG, WALKER, DAVID H · 2014 to 2018
$6.5M
Exchange Protein directly Activated by cAMP (EPAC): Structure, Function and TherapeuticsR35GM122536 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI CHENG, XIAODONG · 2017 to 2021
$1.9M
NIAID NIH HHS R01 AI111464NIGMS NIH HHS R35 GM122536
6 · The paper itself

Abstract

The raging COVID-19 pandemic caused by SARS-CoV2 has infected millions of people and killed several hundred thousand patients worldwide. Currently, there are no effective drugs or vaccines available for treating coronavirus infections. In this study, we have focused on the SARS-CoV2 helicase (Nsp13), which is critical for viral replication and the most conserved non-structural protein within the coronavirus family. Using homology modeling and molecular dynamics approaches, we generated structural models of the SARS-CoV2 helicase in its apo- and ATP/RNA-bound conformations. We performed virtual screening of ~970,000 chemical compounds against the ATP binding site to identify potential inhibitors. Herein, we report docking hits of approved human drugs targeting the ATP binding site. Importantly, two of our top drug hits have significant activity in inhibiting purified recombinant SARS-CoV-2 helicase, providing hope that these drugs can be potentially repurposed for the treatment of COVID-19.

Identifiers

PMID32817950
PMCPMC7430582
OpenAlexW3048874199

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.