Evidence map›Paper›PMID 33140043›Full record

ArticlebioRxiv : the preprint server for biology2020

Mechanism of ligand recognition by human ACE2 receptor.

Apurba Bhattarai, Shristi Pawnikar, Yinglong Miao

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, 2 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 1 institution in 1 country.

Apurba BhattaraiCenter for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047, USA.
Shristi PawnikarCenter for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047, USA.
Yinglong MiaoCenter for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047, USA.
University of Kansas · US

Funding

Enhanced Sampling of G-Protein-Coupled Receptor-G Protein InteractionsR01GM132572 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI MIAO, YINGLONG · 2019 to 2023
$1.5M
NIGMS NIH HHS R01 GM132572
6 · The paper itself

Abstract

Angiotensin converting enzyme 2 (ACE2) plays a key role in renin-angiotensin system regulation and amino acid homeostasis. Human ACE2 acts as the receptor for severe acute respiratory syndrome coronaviruses SARS-CoV and SARS-CoV-2. ACE2 is also widely expressed in epithelial cells of lungs, heart, kidney and pancreas. It is considered an important drug target for treating SARS-CoV-2, as well as pulmonary diseases, heart failure, hypertension, renal diseases and diabetes. Despite the critical importance, the mechanism of ligand binding to the human ACE2 receptor remains unknown. Here, we address this challenge through all-atom simulations using a novel ligand Gaussian accelerated molecular dynamics (LiGaMD) method. Microsecond LiGaMD simulations have successfully captured both binding and unbinding of the MLN-4760 inhibitor in the ACE2 receptor. In the ligand unbound state, the ACE2 receptor samples distinct Open, Partially Open and Closed conformations. Ligand binding biases the receptor conformational ensemble towards the Closed state. The LiGaMD simulations thus suggest a conformational selection mechanism for ligand recognition by the ACE2 receptor. Our simulation findings are expected to facilitate rational drug design of ACE2 against coronaviruses and other related human diseases.

Identifiers

PMID33140043
PMCPMC7605550
OpenAlexW3096971718

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.