Evidence map›Paper›PMID 38050479›Full record

ArticleIn silico pharmacology2024

Exploring the viral protease inhibitor space driven by consensus scoring-based virtual screening.

Mamona Mushtaq, Sehrish Naz, Sajda Ashraf, Robert J Doerksen, Mohammad Nur-E-Alam, Zaheer Ul-Haq

Open access · greenAbstract read
In one paragraph

Article in In silico pharmacology, 2024. 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
0.2field-weighted citation impact, top 42% of its field
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 citations in OpenAlex.

  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

6 authors at 4 institutions in 3 countries.

Mamona MushtaqDr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270 Pakistan.
Sehrish NazDr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270 Pakistan.
Sajda AshrafDr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270 Pakistan.
Robert J DoerksenDepartment of BioMolecular Sciences, University of Mississippi, Oxford, MS 38677 USA.
Mohammad Nur-E-AlamDepartment of Pharmacognosy, College of Pharmacy, King Saud University, 11451 Riyadh, Saudi Arabia.
Zaheer Ul-HaqDr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270 Pakistan.
International Center for Chemical and Biological Sciences · PKKing Saud University · SAUniversity of Karachi · PKUniversity of Mississippi · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dengue fever presents a major health concern, and the lack of an effective vaccine or definite therapeutic regimen has led the research community to identify safe-by-design potential targets for drug discovery. Since the association of the NS2B co-factor with the protease domain of NS3 is imperative for the catalytic activity of the enzyme complex, inhibitors blocking their interaction could provide an alternative strategy to combat the dengue virus. In this context, the present study is aimed at exploring computer-assisted modeling of significant physicochemical features required for the inhibition of the dengue virus protease complex. First of all, alanine scanning was utilized to map hot spot residues critical for the association of the two subunits, NS2B and NS3pro, by studying their energy profiles. Then, consensus score-based virtual screening was performed to search through the commercially available chemical datasets. After screening, 1,575 small molecules were moved forward into docking studies to investigate their interactions with crucial interfacial residues (i.e., Tyr23, Lys26, Phe46, and Leu58), with only 233 molecules passing that stage. The top 30 molecules were selected based on a detailed profile of intermolecular interactions. After that, the top five molecules were selected for detailed mechanistic studies via molecular dynamics simulations followed by subsequent binding free energy calculations, principal component analysis in conjunction with free energy landscape. To the best of our knowledge, this is the first systematic and comprehensive investigation to identify protein-protein interaction blockers against the target protein at such a large scale, using integrated computational tools. Our results highlight the enhanced stability and good binding affinities towards the target protein of these compounds, which might act as new scaffolds for NS2B-NS3 protease inhibition. Future studies will be directed to explore the detailed atomistic-based structural and energetic framework of the mutation-induced affinity change between the protease domain of the DENV-2 NS3 protein and its cofactor NS2B. The detailed insight in turn might suggest precise and focused targeted points for the structure-based drug design but the computational cost may be a challenge. Graphical abstract: Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-023-00174-0.

Indexed as

Alanine scanningBinding free energy calculationsConsensus score-based virtual screeningDengue virus proteaseFree energy landscapeMolecular dynamics simulationPrincipal component analysisProtein–protein interaction inhibitor

Identifiers

PMID38050479
PMCPMC10693542
OpenAlexW4389274959

What OpenQuestion 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 OpenQuestion graph.