Evidence map›Paper›PMID 40430346›Full record

ArticleMolecules (Basel, Switzerland)2025

Molecular Recognition of SARS-CoV-2 Mpro Inhibitors: Insights from Cheminformatics and Quantum Chemistry.

Adedapo Olosunde, Xiche Hu

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Adedapo OlosundeDepartment of Chemistry and Biochemistry, University of Toledo, Toledo, OH 43606, USA.ORCID 0000-0002-3933-832X
Xiche HuDepartment of Chemistry and Biochemistry, University of Toledo, Toledo, OH 43606, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV-2 main protease (Mpro), essential for viral replication, remains a prime target for antiviral drug design against COVID-19 and related coronaviruses. In this study, we present a systematic investigation into the molecular determinants of Mpro inhibition using an integrated approach combining large-scale data mining, cheminformatics, and quantum chemical calculations. A curated dataset comprising 963 high-resolution structures of Mpro-ligand complexes-348 covalent and 615 non-covalent inhibitors-was mined from the Protein Data Bank. Cheminformatics analysis revealed distinct physicochemical profiles for each inhibitor class: covalent inhibitors tend to exhibit higher hydrogen bonding capacity and sp

Indexed as

Antiviral AgentsCheminformaticsCoronavirus 3C ProteasesProtease InhibitorsSARS-CoV-2COVID-19COVID-19 Drug TreatmentHumansHydrogen BondingLigandsProtein BindingQuantum Theory3C-like proteinase, SARS-CoV-2Antiviral AgentsCoronavirus 3C ProteasesLigandsProtease InhibitorsCH–π interactionscovalent and non-covalent inhibitorshydrogen bondingmolecular recognitionquantum mechanicsrational drug designSARS-CoV-2 main protease (Mpro)π–π stacking interactions

Identifiers

PMID40430346
PMCPMC12114402

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.