Evidence map›Paper›PMID 33551661›Full record

ArticleSaudi journal of biological sciences2021

Computational drug screening against the SARS-CoV-2 Saudi Arabia isolates through a multiple-sequence alignment approach.

Pooi Ling Mok, Avin Ee-Hwan Koh, Aisha Farhana, Abdullah Alsrhani, Mohammad Khursheed Alam, Subbiah Suresh Kumar

Abstract read
In one paragraph

Article in Saudi journal of biological sciences, 2021. 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

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.

Pooi Ling MokDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, P.O. Box 2014, Sakaka, Al-Jawf Province, Saudi Arabia.
Avin Ee-Hwan KohDepartment of Biomedical Sciences, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia.
Aisha FarhanaDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, P.O. Box 2014, Sakaka, Al-Jawf Province, Saudi Arabia.
Abdullah AlsrhaniDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, P.O. Box 2014, Sakaka, Al-Jawf Province, Saudi Arabia.
Mohammad Khursheed AlamDepartment of Orthodontics, College of Dentistry, Jouf University, P.O. Box 2014, Sakaka, Al-Jawf Province, Saudi Arabia.
Subbiah Suresh KumarGenetics and Regenerative Medicine Research Centre, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 is a rapidly emerging infectious disease caused by the SARS-CoV-2 virus currently spreading throughout the world. To date, there are no specific drugs formulated for it, and researchers around the globe are racing against the clock to investigate potential drug candidates. The repurposing of existing drugs in the market represents an effective and economical strategy commonly utilized in such investigations. In this study, we used a multiple-sequence alignment approach for preliminary screening of commercially-available drugs on SARS-CoV sequences from the Kingdom of Saudi Arabia (KSA) isolates. The viral genomic sequences from KSA isolates were obtained from GISAID, an open access repository housing a wide variety of epidemic and pandemic virus data. A phylogenetic analysis of the present 164 sequences from the KSA provinces was carried out using the MEGA X software, which displayed high similarity (around 98%). The sequence was then analyzed using the VIGOR4 genome annotator to construct its genomic structure. Screening of existing drugs was carried out by mining data based on viral gene expressions from the ZINC database. A total of 73 hits were generated. The viral target orthologs were mapped to the SARS-CoV-2 KSA isolate sequence by multiple sequence alignment using CLUSTAL OMEGA, and a list of 29 orthologs with purchasable drug information was generated. The results showed that the SARS CoV replicase polyprotein 1a had the highest sequence similarity at 79.91%. Through ZINC data mining, tanshinones were found to have high binding affinities to this target. These compounds could be ideal candidates for SARS-CoV-2. Other matches ranged between 27 and 52%. The results of this study would serve as a significant endeavor towards drug discovery that would increase our chances of finding an effective treatment or prevention against COVID19.

Indexed as

CoronavirusCOVID-19Multiple sequence alignmentSaudi ArabiaTanshinones

Identifiers

PMID33551661
PMCPMC7845492

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.