Evidence map›Paper›PMID 33907750›Full record

ArticlebioRxiv : the preprint server for biology2022

Identification of druggable host targets needed for SARS-CoV-2 infection by combined pharmacological evaluation and cellular network directed prioritization both in vitro and in vivo.

J J Patten, Patrick T Keiser, Deisy Gysi, Giulia Menichetti, Hiroyuki Mori, Callie J Donahue, Xiao Gan, Italo do Valle, Kathleen Geoghegan-Barek, Manu Anantpadma and 16 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 9 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

26 authors at 6 institutions in 1 country.

Giulia MenichettiORCID 0000-0001-5201-6774
Hiroyuki Mori
Italo do Valle
Kathleen Geoghegan-Barek
RuthMabel Boytz
Jacob L Berrigan
Sarah Hulsey-Stubbs
Colin O'Leary
Sallieu Jalloh
Stephen J Elledge
Deborah Anderson
Joseph Loscalzo
Marinka Zitnik
Suryaram Gummuluru
Albert-László BarabásiORCID 0000-0002-4028-3522
Boston University · USBrigham and Women's Hospital · USHarvard University · USBroad Institute · USMatTek Corporation (United States) · USNortheastern University · US

Funding

Regulatory Compliance CoreUC7AI095321 · NIAID · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Ronald O'Brien · 2014 to 2026
$159.3M
NIAID NIH HHS UC7 AI095321
6 · The paper itself

Abstract

Identification of host factors contributing to replication of viruses and resulting disease progression remains a promising approach for development of new therapeutics. Here, we evaluated 6710 clinical and preclinical compounds targeting 2183 host proteins by immunocytofluorescence-based screening to identify SARS-CoV-2 infection inhibitors. Computationally integrating relationships between small molecule structure, dose-response antiviral activity, host target and cell interactome networking produced cellular networks important for infection. This analysis revealed 389 small molecules, >12 scaffold classes and 813 host targets with micromolar to low nanomolar activities. From these classes, representatives were extensively evaluated for mechanism of action in stable and primary human cell models, and additionally against Beta and Delta SARS-CoV-2 variants and MERS-CoV. One promising candidate, obatoclax, significantly reduced SARS-CoV-2 viral lung load in mice. Ultimately, this work establishes a rigorous approach for future pharmacological and computational identification of novel host factor dependencies and treatments for viral diseases.

Identifiers

PMID33907750
PMCPMC8077576
OpenAlexW3154117841

What OpenQuestion holds

Textmetadata
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.