Evidence map›Paper›PMID 41413356›Full record

ArticleJournal of computer-aided molecular design2025

Chasing allosteric inhibition of the SARS-CoV-2 PLpro via molecular dynamics simulations with flooding fragments (MDFFr).

Jason Pattis, Khaled Elokely, Eleonora Gianti

Abstract read
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In one paragraph

Article in Journal of computer-aided molecular design, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

3 authors.

Jason PattisInstitute for Computational Molecular Science, Temple University, Philadelphia, PA, 19122, USA.
Khaled ElokelyDivision of Pharmaceutical Sciences, School of Pharmacy, College of Heath Sciences, University of Wyoming, Laramie, WY, 82071-2000, USA. kelokely@uwyo.edu.
Eleonora GiantiDepartment of Chemistry and Biochemistry, Queens College, City University of New York (CUNY), 65-30 Kissena Blvd., Flushing, NY, 11367, USA. Eleonora.Gianti@qc.cuny.edu.

Funding

RF Research Foundation and the City University of New York (CUNY) Queens College Startup fundsUniversity of Wyoming (UWYO) and School of Pharmacy (SOP) Startup funds
6 · The paper itself

Abstract

The SARS-CoV-2 papain-like protease (PLpro) represents a crucial therapeutic target due to its dual role in viral polyprotein processing and suppression of host immune responses through de-ubiquitination and de-ISGylation activities. To identify novel allosteric druggable sites on PLpro, we developed a molecular dynamics approach with flooding fragments (MDFFr), which extends a previously established method –Molecular Dynamics flooding– enabling broader applicability across biological targets. Using MDFFr, we evaluated interactions of known phenolic inhibitors with SARS-CoV-2 PLpro and identified several biologically significant sites, encompassing allosteric hotspots, cryptic pockets, and regions involved in protein–protein interactions. Our simulations not only confirmed experimentally characterized binding sites, including fragment-binding and protein–protein interaction regions for ubiquitin and ISG15 (Interferon-Stimulated Gene 15), but also uncovered previously unrecognized hotspots for further investigation. These results establish MDFFr as a suitable approach for physics-based druggability assessment of biological targets using only protein 3D structure, while providing detailed insights into fragment-protein interactions at both druggable sites and protein–protein interfaces. These findings also unveil new opportunities for allosteric inhibition of PLpro, potentially advancing therapeutic strategies against SARS-CoV-2 and other coronavirus-related diseases. Furthermore, by using “real” drug-like fragments (rather than standard cosolvent “probes”), MDFFr enhances translational relevance and directly informs drug repurposing and ligand discovery efforts.

Indexed as

Antiviral AgentsBetacoronavirusCoronavirus 3C ProteasesCoronavirus Papain-Like ProteasesMolecular Dynamics SimulationSARS-CoV-2Allosteric RegulationAllosteric SiteBinding SitesCytokinesHumansPhenolsProtein BindingUbiquitinUbiquitinsAntiviral AgentsCoronavirus 3C ProteasesCoronavirus Papain-Like ProteasesCytokinesISG15 protein, humanpapain-like protease, SARS-CoV-2PhenolsUbiquitinUbiquitinsBinding site identificationCosolvent mappingFlooding simulationsMolecular dynamics simulationsProtein–protein interaction sitesSites of allosteric modulation

Identifiers

What Socratic 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 Socratic graph.