Evidence map›Paper›PMID 32081744›Full record

ReviewMethods (San Diego, Calif.)2021

The fine art of preparing membrane transport proteins for biomolecular simulations: Concepts and practical considerations.

Hana Shiref, Shana Bergman, Sophie Clivio, Michelle A Sahai

Open access · greenAbstract readReview
In one paragraph

Review in Methods (San Diego, Calif.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 36% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Microbial membrane transport proteins and their biotechnological applications.World journal of microbiology & biotechnology · 2024
    Review
  2. Article
  3. Review
  4. 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

4 authors at 3 institutions in 2 countries.

Hana ShirefDepartment of Life Sciences, University of Roehampton, London SW15 4JD, UK.
Shana BergmanDepartment of Physiology and Biophysics, Weill Cornell Medical College of Cornell University (WCMC), New York, NY 10065, USA.
Sophie ClivioHarvard University, Cambridge, MA 02138, USA.
Michelle A SahaiDepartment of Life Sciences, University of Roehampton, London SW15 4JD, UK. Electronic address: michelle.sahai@roehampton.ac.uk.
University of Roehampton · GBCornell University · USHarvard University Press · US

Funding

Genetic and Environmental Influences on AddictionT32DA039080 · NIDA · WEILL MEDICAL COLL OF CORNELL UNIV · PI Teresa A Milner · 2017 to 2026
$1.4M
NIDA NIH HHS T32 DA039080
6 · The paper itself

Abstract

Molecular dynamics (MD) simulations have developed into an invaluable tool in bimolecular research, due to the capability of the method in capturing molecular events and structural transitions that describe the function as well as the physiochemical properties of biomolecular systems. Due to the progressive development of more efficient algorithms, expansion of the available computational resources, as well as the emergence of more advanced methodologies, the scope of computational studies has increased vastly over time. We now have access to a multitude of online databases, software packages, larger molecular systems and novel ligands due to the phenomenon of emerging novel psychoactive substances (NPS). With so many advances in the field, it is understandable that novices will no doubt find it challenging setting up a protein-ligand system even before they run their first MD simulation. These initial steps, such as homology modelling, ligand docking, parameterization, protein preparation and membrane setup have become a fundamental part of the drug discovery pipeline, and many areas of biomolecular sciences benefit from the applications provided by these technologies. However, there still remains no standard on their usage. Therefore, our aim within this review is to provide a clear overview of a variety of concepts and methodologies to consider, providing a workflow for a case study of a membrane transport protein, the full-length human dopamine transporter (hDAT) in complex with different stimulants, where MD simulations have recently been applied successfully.

Indexed as

Molecular Dynamics SimulationAlgorithmsDopamine Plasma Membrane Transport ProteinsDrug DiscoveryHumansLigandsMembrane Transport ProteinsProtein BindingDopamine Plasma Membrane Transport ProteinsLigandsMembrane Transport ProteinsComputational modellingMembrane protein simulationsMolecular dockingMolecular dynamicsProtein structure preparationSmall molecule parameterization

Identifiers

PMID32081744
PMCPMC10062712
OpenAlexW3008977712

What OpenQuestion holds

Textmetadata
LicenceTDM
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.