Evidence map›Paper›PMID 39086396›Full record

ArticleFrontiers in pharmacology2024

Identifying plant-derived antiviral alkaloids as dual inhibitors of SARS-CoV-2 main protease and spike glycoprotein through computational screening.

Ramsha Yamin, Iqra Ahmad, Hira Khalid, Asia Perveen, Sumra Wajid Abbasi, Umar Nishan, Sheheryar Sheheryar, Arlindo Alencar Moura, Sarfraz Ahmed, Riaz Ullah and 3 more

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

13 authors.

Ramsha Yamin *Department of Biochemistry, Bahauddin Zakariya University, Multan, Pakistan.
Iqra Ahmad *Department of Biochemistry, Bahauddin Zakariya University, Multan, Pakistan.
Hira KhalidDepartment of Biochemistry, Bahauddin Zakariya University, Multan, Pakistan.
Asia PerveenDepartment of Biochemistry, Bahauddin Zakariya University, Multan, Pakistan.
Sumra Wajid AbbasiDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, Pakistan.
Umar NishanDepartment of Chemistry, Kohat University of Science & Technology, Kohat, Pakistan.
Sheheryar SheheryarDepartment of Animal Science, Federal University of Ceara, Fortaleza, Brazil.
Arlindo Alencar MouraDepartment of Animal Science, Federal University of Ceara, Fortaleza, Brazil.
Sarfraz AhmedWellman Centre for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Riaz UllahDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Essam A AliDepartment of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Mohibullah ShahDepartment of Biochemistry, Bahauddin Zakariya University, Multan, Pakistan.
Suvash Chandra OjhaDepartment of Infectious Diseases, The Affiliated Hospital of Southwest Medical University, Luzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 is currently considered the ninth-deadliest pandemic, spreading through direct or indirect contact with infected individuals. It has imposed a consistent strain on both the financial and healthcare resources of many countries. To address this challenge, there is a pressing need for the development of new potential therapeutic agents for the treatment of this disease. To identify potential antiviral agents as novel dual inhibitors of SARS-CoV-2, we retrieved 404 alkaloids from 12 selected medicinal antiviral plants and virtually screened them against the renowned catalytic sites and favorable interacting residues of two essential proteins of SARS-CoV-2, namely, the main protease and spike glycoprotein. Based on docking scores, 12 metabolites with dual inhibitory potential were subjected to drug-likeness, bioactivity scores, and drug-like ability analyses. These analyses included the ligand-receptor stability and interactions at the potential active sites of target proteins, which were analyzed and confirmed through molecular dynamic simulations of the three lead metabolites. We also conducted a detailed binding free energy analysis of pivotal SARS-CoV-2 protein inhibitors using molecular mechanics techniques to reveal their interaction dynamics and stability. Overall, our results demonstrated that 12 alkaloids, namely, adouetine Y, evodiamide C, ergosine, hayatinine, (+)-homoaromoline, isatithioetherin C, N,alpha-L-rhamnopyranosyl vincosamide, pelosine, reserpine, toddalidimerine, toddayanis, and zanthocadinanine, are shortlisted as metabolites based on their interactions with target proteins. All 12 lead metabolites exhibited a higher unbound fraction and therefore greater distribution compared with the standards. Particularly, adouetine Y demonstrated high docking scores but exhibited a nonspontaneous binding profile. In contrast, ergosine and evodiamide C showed favorable binding interactions and superior stability in molecular dynamics simulations. Ergosine demonstrated exceptional performance in several key pharmaceutical metrics. Pharmacokinetic evaluations revealed that ergosine exhibited pronounced bioactivity, good absorption, and optimal bioavailability. Additionally, it was predicted not to cause skin sensitivity and was found to be non-hepatotoxic. Importantly, ergosine and evodiamide C emerged as superior drug candidates for dual inhibition of SARS-CoV-2 due to their strong binding affinity and drug-like ability, comparable to known inhibitors like N3 and molnupiravir. This study is limited by its

Indexed as

alkaloidsmain proteaseSARS-CoV-2secondary metabolitesspike glycoprotein

Identifiers

PMID39086396
PMCPMC11288853

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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.