Evidence map›Paper›PMID 41652160›Full record

ReviewAdvances in experimental medicine and biology2026

Advanced Computational Methods in Protein Simulations: A Case Study of Enhanced Sampling Applied to Membrane Transporters.

Jonathan D Colburn, Simon M Lichtinger, Philip C Biggin

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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.

Jonathan D ColburnStructural Bioinformatics and Computational Biochemistry, Department of Biochemistry, University of Oxford, Oxford, England.
Simon M LichtingerStructural Bioinformatics and Computational Biochemistry, Department of Biochemistry, University of Oxford, Oxford, England.
Philip C BigginStructural Bioinformatics and Computational Biochemistry, Department of Biochemistry, University of Oxford, Oxford, England. philip.biggin@bioch.ox.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We review the use of state-of-the-art enhanced sampling techniques in molecular dynamics (MD) simulations. We briefly introduce the principles and practical considerations underlying the application of these methods, making reference to recent reviews, and then discuss their application to membrane transporters as case studies. Our discussion is structured around the respective method employed and the biological problem case in question. We categorise the latter on a conceptual basis primarily into 'conformational change' problems which encompass alternating access and other related intra-protein motions and inter-molecular 'interactions' problems, which relate to ligands, proteins or allosteric modulators. Lastly, we consider future developments that we anticipate in this field, including the increasing prominence of machine learning techniques used in combination with MD, and make some recommendations with regard to standardised reporting to improve reproducibility and transferability.

Indexed as

Computational BiologyMembrane Transport ProteinsMolecular Dynamics SimulationHumansLigandsMachine LearningProtein ConformationLigandsMembrane Transport ProteinsAlternating accessEnhanced samplingMembrane transportersMolecular dynamics

Identifiers

PMID41652160

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.