Evidence map›Paper›PMID 33612899›Full record

ArticleJournal of molecular liquids2021

Rational design of potent anti-COVID-19 main protease drugs: An extensive multi-spectrum in silico approach.

Sajjad Ahmad, Yasir Waheed, Saba Ismail, Muzammil Hasan Najmi, Jawad Khaliq Ansari

Open access · greenAbstract read
In one paragraph

Article in Journal of molecular liquids, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 15% of its field
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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. In Silico Models for Anti-COVID-19 Drug Discovery: A Systematic Review.Advances in pharmacological and pharmaceutical sciences · 2023
    Review
  2. Article
  3. Article
  4. Novel Drug Design for Treatment of COVID-19: A Systematic Review of Preclinical Studies.The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2022
    Review
  5. Article
  6. Virus structure and structure-based antivirals.Current opinion in virology · 2021
    Review
  7. An overview of potential inhibitors targeting non-structural proteins 3 (PLComputational and structural biotechnology journal · 2021
    Review
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

5 authors at 2 institutions in 1 country.

Sajjad AhmadFoundation University Medical College, Foundation University Islamabad, Islambad, Pakistan.
Yasir WaheedFoundation University Medical College, Foundation University Islamabad, Islambad, Pakistan.
Saba IsmailFoundation University Medical College, Foundation University Islamabad, Islambad, Pakistan.
Muzammil Hasan NajmiFoundation University Medical College, Foundation University Islamabad, Islambad, Pakistan.
Jawad Khaliq AnsariFoundation University Medical College, Foundation University Islamabad, Islambad, Pakistan.
Foundation University Medical College · PKFoundation University Islamabad · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a novel coronavirus and the etiological agent of global pandemic coronavirus disease (COVID-19) requires quick development of potential therapeutic strategies. Computer aided drug design approaches are highly efficient in identifying promising drug candidates among an available pool of biological active antivirals with safe pharmacokinetics. The main protease (M

Indexed as

ASINEX antiviral libraryCOVID-19MD simulationMM-PBSASARS-CoV-2 MProWaterSwap

Identifiers

PMID33612899
PMCPMC7879066
OpenAlexW3131541701

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.