Evidence map›Paper›PMID 31240406›Full record

ArticleJournal of molecular modeling2019

Molecular modeling and computational study of the chiral-dependent structures and properties of self-assembling diphenylalanine peptide nanotubes.

Vladimir S Bystrov, Pavel S Zelenovskiy, Alla S Nuraeva, Svitlana Kopyl, Olga A Zhulyabina, Vsevolod A Tverdislov

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Article in Journal of molecular modeling, 2019. 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
2.2field-weighted citation impact, top 13% 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, 31 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

6 authors at 4 institutions in 2 countries.

Vladimir S BystrovInstitute of Mathematical Problems of Biology, Keldysh Institute of Applied Mathematics, RAS, 142290, Pushchino, Moscow Region, Russia. vsbys@mail.ru.ORCID http://orcid.org/0000-0003-1487-9469
Pavel S ZelenovskiySchool of Natural Sciences and Mathematics, Ural Federal University, 620000, Ekaterinburg, Russia.
Alla S NuraevaSchool of Natural Sciences and Mathematics, Ural Federal University, 620000, Ekaterinburg, Russia.
Svitlana KopylDepartment of Physics and CICECO-Aveiro Institute of Materials, University of Aveiro, 3810-193, Aveiro, Portugal.
Olga A ZhulyabinaFaculty of Physics, Lomonosov Moscow State University, 119991, Moscow, Russia.
Vsevolod A TverdislovFaculty of Physics, Lomonosov Moscow State University, 119991, Moscow, Russia.
Lomonosov Moscow State University · RUUral Federal University · RUInstitute of Mathematical Problems of Biology · RUUniversity of Aveiro · PT

Funding

Russian Foundation for Basic Research 19-01-00519 А
6 · The paper itself

Abstract

The structure and properties of diphenylalanine (FF) peptide nanotubes (PNT) based on phenylalanine were investigated by various molecular modeling methods. The main approach employed semi-empirical quantum-chemical methods (PM3 and AM1). Ab initio, density functional theory methods and molecular mechanical approaches were also used. Both model structures and structures extracted from experimental crystallographic databases obtained by X-ray methods were examined. A comparison of optimized model structures and structures obtained by natural self-assembly revealed important differences depending on chirality: D and L. In both the cases, the effect of chirality on the results of self-assembly of FF PNT was established: PNT based on the D-FF has large condensation energy E

Indexed as

Models, MolecularMolecular ConformationAlgorithmsDensity Functional TheoryDipeptidesModels, TheoreticalNanostructuresNanotubes, PeptidePhenylalanineDipeptidesNanotubes, PeptidePhenylalaninephenylalanylphenylalanineAb initioChiralityDFTDiphenylalanineMolecular mechanicsMolecular modelingPeptide nanotubeSelf-assemblySemi-empirical methodsTopology

Identifiers

PMID31240406
OpenAlexW2953620216

What OpenQuestion holds

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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.