Evidence map›Paper›PMID 29052792›Full record

ArticleJournal of computer-aided molecular design2018

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling.

Soumendranath Bhakat, Emil Åberg, Pär Söderhjelm

Open access · hybridAbstract read
In one paragraph

Article in Journal of computer-aided molecular design, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 26% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

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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 at 1 institution in 1 country.

Soumendranath BhakatDivision of Biophysical Chemistry, Lund University, Chemical Center, P. O. B. 124, 22100, Lund, Sweden.
Emil ÅbergDivision of Biophysical Chemistry, Lund University, Chemical Center, P. O. B. 124, 22100, Lund, Sweden.
Pär SöderhjelmDivision of Biophysical Chemistry, Lund University, Chemical Center, P. O. B. 124, 22100, Lund, Sweden. par.soderhjelm@bpc.lu.se.ORCID 0000-0001-6938-7803
Lund University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.

Indexed as

Drug DesignMolecular Docking SimulationBinding SitesDatabases, ProteinDrug DiscoveryHumansLigandsMolecular Dynamics SimulationProtein BindingProtein ConformationReceptor, Farnesoid X-ActivatedReceptors, Cytoplasmic and NuclearLigandsReceptor, Farnesoid X-ActivatedReceptors, Cytoplasmic and NuclearD3RDockingMD simulationPose predictionProtein–ligand bindingReconnaissance metadynamics

Identifiers

PMID29052792
PMCPMC5767213
OpenAlexW2766832305

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.