Evidence map›Paper›PMID 35886905›Full record

ArticleInternational journal of molecular sciences2022

Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel.

Silvia Gervasoni, Carmine Talarico, Candida Manelfi, Alessandro Pedretti, Giulio Vistoli, Andrea R Beccari

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Approaching Pharmacological Space: Events and Components.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  3. Progress of the "Molecular Informatics" Section in 2022.International journal of molecular sciences · 2023
    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 2 institutions in 1 country.

Silvia GervasoniDipartimento di Scienze Farmaceutiche, Università degli Studi di Milano, Via Luigi Mangiagalli, 25, I-20133 Milano, Italy.ORCID 0000-0002-5731-3396
Carmine TalaricoDompé Farmaceutici SpA, EXSCALATE Labs, Via Tommaso De Amicis, 95, I-80131 Napoli, Italy.ORCID 0000-0003-4789-0955
Candida ManelfiDompé Farmaceutici SpA, EXSCALATE Labs, Via Tommaso De Amicis, 95, I-80131 Napoli, Italy.
Alessandro PedrettiDipartimento di Scienze Farmaceutiche, Università degli Studi di Milano, Via Luigi Mangiagalli, 25, I-20133 Milano, Italy.ORCID 0000-0001-5916-2029
Giulio VistoliDipartimento di Scienze Farmaceutiche, Università degli Studi di Milano, Via Luigi Mangiagalli, 25, I-20133 Milano, Italy.ORCID 0000-0002-3939-5172
Andrea R BeccariDompé Farmaceutici SpA, EXSCALATE Labs, Via Tommaso De Amicis, 95, I-80131 Napoli, Italy.ORCID 0000-0001-6830-2695
Dompé (Italy) · ITUniversity of Milan · IT

Funding

Ministero Sviluppo Economico (MISE) F/090033/01/X36
6 · The paper itself

Abstract

(1) Background: Virtual screening campaigns require target structures in which the pockets are properly arranged for binding. Without these, MD simulations can be used to relax the available target structures, optimizing the fine architecture of their binding sites. Among the generated frames, the best structures can be selected based on available experimental data. Without experimental templates, the MD trajectories can be filtered by energy-based criteria or sampled by systematic analyses. (2) Methods: A blind and methodical analysis was performed on the already reported MD run of the hTRPM8 tetrameric structures; a total of 50 frames underwent docking simulations by using a set of 1000 ligands including 20 known hTRPM8 modulators. Docking runs were performed by LiGen program and involved the frames as they are and after optimization by SCRWL4.0. For each frame, all four monomers were considered. Predictive models were developed by the EFO algorithm based on the sole primary LiGen scores. (3) Results: On average, the MD simulation progressively enhances the performance of the extracted frames, and the optimized structures perform better than the non-optimized frames (EF1% mean: 21.38 vs. 23.29). There is an overall correlation between performances and volumes of the explored pockets and the combination of the best performing frames allows to develop highly performing consensus models (EF1% = 49.83). (4) Conclusions: The systematic sampling of the entire MD run provides performances roughly comparable with those previously reached by using rationally selected frames. The proposed strategy appears to be helpful when the lack of experimental data does not allow an easy selection of the optimal structures for docking simulations. Overall, the reported docking results confirm the relevance of simulating all the monomers of an oligomer structure and emphasize the efficacy of the SCRWL4.0 method to optimize the protein structures for docking calculations.

Indexed as

Molecular Dynamics SimulationProteinsBinding SitesLigandsMolecular Docking SimulationProtein BindingLigandsProteinsconsensus modelsEFO algorithmhTRPM8LiGen softwareMD simulationssystematic samplingvirtual screening

Identifiers

PMID35886905
PMCPMC9317601
OpenAlexW4284884766

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.