Viral channel forming proteins--How to assemble and depolarize lipid membranes in silico.

Wolfgang B Fischer, Monoj Mon Kalita, Dieter Heermann

Abstract readReview

In one paragraph

Review in Biochimica et biophysica acta, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

The citrus tristeza virus p33 protein functions as a viroporin.PLoS pathogens · 2025
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

3 authors.

Wolfgang B FischerInstitute of Biophotonics, School of Biomedical Science and Engineering, National Yang-Ming University, Taipei 112, Taiwan; Biophotonics & Molecular Imaging Center (BMIRC), National Yang-Ming University, Taipei 112, Taiwan. Electronic address: wfischer@ym.edu.tw.

Monoj Mon KalitaInstitute of Biophotonics, School of Biomedical Science and Engineering, National Yang-Ming University, Taipei 112, Taiwan; Biophotonics & Molecular Imaging Center (BMIRC), National Yang-Ming University, Taipei 112, Taiwan.

Dieter HeermannInstitute of Biophotonics, School of Biomedical Science and Engineering, National Yang-Ming University, Taipei 112, Taiwan; Biophotonics & Molecular Imaging Center (BMIRC), National Yang-Ming University, Taipei 112, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viral channel forming proteins (VCPs) have been discovered in the late 70s and are found in many viruses to date. Usually they are small and have to assemble to form channels which depolarize the lipid membrane of the host cells. Structural information is just about to emerge for just some of them. Thus, computational methods play a pivotal role in generating plausible structures which can be used in the drug development process. In this review the accumulation of structural data is introduced from a historical perspective. Computational performances and their predictive power are reported guided by biological questions such as the assembly, mechanism of function and drug-protein interaction of VCPs. An outlook of how coarse grained simulations can contribute to yet unexplored issues of these proteins is given. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Indexed as

Models, ChemicalModels, MolecularComputer SimulationHydrophobic and Hydrophilic InteractionsIon ChannelsLipid BilayersViral Regulatory and Accessory ProteinsIon ChannelsLipid BilayersViral Regulatory and Accessory ProteinsCoarse grained simulationsMolecular dynamics simulationsProtein assemblyProtein structureSecondary structure predictionViral channel proteins

Identifiers

PMID26806161

DOI10.1016/j.bbamem.2016.01.018

PMCPMC7094687

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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.