Evidence map›Paper›PMID 39707350›Full record

ArticleVirology journal2024

Targeting SARS-CoV-2 main protease: a comprehensive approach using advanced virtual screening, molecular dynamics, and in vitro validation.

Smbat Gevorgyan, Hamlet Khachatryan, Anastasiya Shavina, Sajjad Gharaghani, Hovakim Zakaryan

Abstract read
In one paragraph

Article in Virology journal, 2024. 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
–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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Integrated Evaluation ofPharmaceuticals (Basel, Switzerland) · 2026
    Article
  5. Article
  6. Review
  7. 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

5 authors.

Smbat GevorgyanLaboratory of Antiviral Drug Discovery. Institute of Molecular Biology of National Academy of Sciences, 0014, Yerevan, Armenia. smbatg@denovosciences.ai.
Hamlet KhachatryanLaboratory of Antiviral Drug Discovery. Institute of Molecular Biology of National Academy of Sciences, 0014, Yerevan, Armenia.
Anastasiya ShavinaLaboratory of Antiviral Drug Discovery. Institute of Molecular Biology of National Academy of Sciences, 0014, Yerevan, Armenia.
Sajjad GharaghaniDenovo Sciences Inc, 0060, Yerevan, Armenia.
Hovakim ZakaryanLaboratory of Antiviral Drug Discovery. Institute of Molecular Biology of National Academy of Sciences, 0014, Yerevan, Armenia.

Funding

Higher Education and Science Committee MESCS of Republic of Armenia 23LCG-1F014
6 · The paper itself

Abstract

The COVID-19 pandemic, driven by the SARS-CoV-2 virus, necessitates the development of effective therapeutics. The main protease of the virus, Mpro, is a key target due to its crucial role in viral replication. Our study presents a novel approach combining ligand-based pharmacophore modeling with structure-based advanced virtual screening to identify potential inhibitors of Mpro. We screened around 200 million compounds using this integrated methodology, resulting in a shortlist of promising compounds. These were further scrutinized through molecular dynamics simulations, revealing their interaction dynamics with Mpro. Subsequent in vitro assays using the Mpro enzyme identified two compounds exhibiting significant micromolar inhibitory activity. These findings provide valuable scaffolds for the development of advanced therapeutics targeting Mpro. The comprehensive nature of our approach, spanning computational predictions to experimental validations, offers a robust pathway for rapid and efficient identification of potential drug candidates against COVID-19.

Indexed as

Antiviral AgentsCoronavirus 3C ProteasesMolecular Dynamics SimulationProtease InhibitorsSARS-CoV-2COVID-19COVID-19 Drug TreatmentDrug Evaluation, PreclinicalHumansMolecular Docking SimulationAntiviral AgentsCoronavirus 3C ProteasesProtease Inhibitors

Identifiers

PMID39707350
PMCPMC11662536

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.