Evidence map›Paper›PMID 33469570›Full record

ArticleChemRxiv : the preprint server for chemistry2020

Small Molecules to Destabilize the ACE2-RBD Complex: A Molecular Dynamics Study for Potential COVID-19 Therapeutics.

Meghdad Razizadeh, Mehdi Nikfar, Yaling Liu

Abstract readPreprint
In one paragraph

Article in ChemRxiv : the preprint server for chemistry, 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.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Meghdad RazizadehDepartment of Mechanical Engineering and Mechanics, Lehigh University, Bethlehem, PA 18015, USA.
Mehdi NikfarDepartment of Mechanical Engineering and Mechanics, Lehigh University, Bethlehem, PA 18015, USA.
Yaling LiuDepartment of Mechanical Engineering and Mechanics, Lehigh University, Bethlehem, PA 18015, USA.

Funding

Supplement: Hemolysis Prediction Software DevelopmentR01HL131750 · NHLBI · LEHIGH UNIVERSITY · PI LIU, YALING · 2017 to 2021
$2.2M
NHLBI NIH HHS R01 HL131750
6 · The paper itself

Abstract

The ongoing COVID-19 pandemic has infected millions of people, claimed hundreds of thousands of lives, and made a worldwide health emergency. Understanding the SARS-CoV-2 mechanism of infection is crucial in the development of potential therapeutics and vaccines. The infection process is triggered by direct binding of the SARS-CoV-2 receptor-binding domain (RBD) to the host cell receptor, Angiotensin-converting enzyme 2 (ACE2). Many efforts have been made to design or repurpose therapeutics to deactivate RBD or ACE2 and prevent the initial binding. In addition to direct inhibition strategies, small chemical compounds might be able to interfere and destabilize the meta-stable, pre-fusion complex of ACE2-RBD. This approach can be employed to prevent the further progress of virus infection at its early stages. In this study, Molecular docking is employed to analyze the binding of two chemical compounds, SSAA09E2 and Nilotinib, with the druggable pocket of the ACE2-RBD complex. The structural changes as a result of the interference with the ACE2-RBD complex are analyzed by molecular dynamics simulations. Results show that both Nilotinib and SSAA09E2 can induce significant conformational changes in the ACE2-RBD complex, intervene with the hydrogen bonds, and influence the flexibility of proteins. Moreover, essential dynamics analysis suggests that the presence of small molecules can trigger large-scale conformational changes that may destabilize the ACE2-RBD complex.

Indexed as

ACE2-RBD ComplexCOVID-19DockingMolecular DynamicsNilotinibSSAA09E2

Identifiers

PMID33469570
PMCPMC7814830

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.