Evidence map›Paper›PMID 28847523›Full record

ReviewBiochimica et biophysica acta. Proteins and proteomics2017

Computational membrane biophysics: From ion channel interactions with drugs to cellular function.

Williams E Miranda, Van A Ngo, Laura L Perissinotti, Sergei Yu Noskov

Open access · greenAbstract readReview
In one paragraph

Review in Biochimica et biophysica acta. Proteins and proteomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

7 citing papers in PubMed, 16 citations in OpenAlex.

  1. Alchemical Free Energy Calculations on Membrane-Associated Proteins.Journal of chemical theory and computation · 2023
    Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Review
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 1 institution in 1 country.

Williams E MirandaCentre for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada.
Van A NgoCentre for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada.
Laura L PerissinottiCentre for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada.
Sergei Yu NoskovCentre for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada. Electronic address: snoskov@ucalgary.ca.
University of Calgary · CA

Funding

In silico Safety PharmacologyR01HL128537 · NHLBI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CLANCY, COLLEEN E, SANTANA, LUIS F · 2016 to 2024
$5.7M
NHLBI NIH HHS R01 HL128537NIH HHS R01HL128537-01A1
6 · The paper itself

Abstract

The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

Indexed as

Molecular Dynamics SimulationThermodynamicsAnimalsHumansIon ChannelsLipid BilayersNeurotransmitter AgentsIon ChannelsLipid BilayersNeurotransmitter AgentsIntegral membrane proteinsKinetic cell modelsMarkov State ModelsMolecular dynamics simulationsProtein-ligand interactions

Identifiers

PMID28847523
PMCPMC5764198
OpenAlexW2746356305

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.