Evidence map›Paper›PMID 34906319›Full record

ReviewDrug discovery today. Technologies2021

Proteomics advances towards developing SARS-CoV-2 therapeutics using in silico drug repurposing approaches.

Amrita Mukherjee, Ayushi Verma, Surbhi Bihani, Ananya Burli, Krishi Mantri, Sanjeeva Srivastava

Abstract readReview
In one paragraph

Review in Drug discovery today. Technologies, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Amrita MukherjeeDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.
Ayushi VermaDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.
Surbhi BihaniDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.
Ananya BurliDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.
Krishi MantriDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.
Sanjeeva SrivastavaDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India. Electronic address: sanjeeva@iitb.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Standing amidst the COVID-19 pandemic, we have faced major medical and economic crisis in recent times which remains to be an unresolved issue till date. Although the scientific community has made significant progress towards diagnosis and understanding the disease; however, effective therapeutics are still lacking. Several omics-based studies, especially proteomics and interactomics, have contributed significantly in terms of identifying biomarker panels that can potentially be used for the disease prognosis. This has also paved the way to identify the targets for drug repurposing as a therapeutic alternative. US Food and Drug Administration (FDA) has set in motion more than 500 drug development programs on an emergency basis, most of them are focusing on repurposed drugs. Remdesivir is one such success of a robust and quick drug repurposing approach. The advancements in omics-based technologies has allowed to explore altered host proteins, which were earlier restricted to only SARS-CoV-2 protein signatures. In this article, we have reviewed major contributions of proteomics and interactomics techniques towards identifying therapeutic targets for COVID-19. Furthermore, in-silico molecular docking approaches to streamline potential drug candidates are also discussed.

Indexed as

COVID-19Drug RepositioningAntiviral AgentsHumansMolecular Docking SimulationPandemicsProteomicsSARS-CoV-2Antiviral Agents

Identifiers

PMID34906319
PMCPMC8222565

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.