Literature DB >> 29444233

BetaSerpentine: a bioinformatics tool for reconstruction of amyloid structures.

Stanislav A Bondarev1, Olga V Bondareva2, Galina A Zhouravleva1, Andrey V Kajava3,4,5.   

Abstract

Motivation: Numerous experimental studies have suggested that polypeptide chains of large amyloidogenic regions zig-zag in β-serpentine arrangements. These β-serpentines are stacked axially and form the superpleated β-structure. Despite this progress in the understanding of amyloid folds, the determination of their 3D structure at the atomic level is still a problem due to the polymorphism of these fibrils and incompleteness of experimental structural data. Today, the way to get insight into the atomic structure of amyloids is a combination of experimental studies with bioinformatics.
Results: We developed a computer program BetaSerpentine that reconstructs β-serpentine arrangements from individual β-arches predicted by ArchCandy program and ranks them in order of preference. It was shown that the BetaSerpentine program in combination with the experimental data can be used to gain insight into the detailed 3D structure of amyloids. It opens avenues to the structure-based interpretation and design of the experiments. Availability and implementation: BetaSerpentine webserver can be accessed through website: http://bioinfo.montp.cnrs.fr/b-serpentine. Source code is available in git.hub repository (github.com/stanislavspbgu/BetaSerpentine). Contact: stanislavspbgu@gmail.com or andrey.kajava@crbm.cnrs.fr. Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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Year:  2018        PMID: 29444233     DOI: 10.1093/bioinformatics/btx629

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  6 in total

1.  Bioinformatics Methods in Predicting Amyloid Propensity of Peptides and Proteins.

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Review 2.  Protein aggregation: in silico algorithms and applications.

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3.  Structure-based machine-guided mapping of amyloid sequence space reveals uncharted sequence clusters with higher solubilities.

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Journal:  Nat Commun       Date:  2020-07-03       Impact factor: 14.919

4.  Aggregation and Prion-Inducing Properties of the G-Protein Gamma Subunit Ste18 are Regulated by Membrane Association.

Authors:  Tatiana A Chernova; Zhen Yang; Tatiana S Karpova; John R Shanks; Natalia Shcherbik; Keith D Wilkinson; Yury O Chernoff
Journal:  Int J Mol Sci       Date:  2020-07-16       Impact factor: 5.923

5.  Bioinformatics methods for identification of amyloidogenic peptides show robustness to misannotated training data.

Authors:  Michał Burdukiewicz; Malgorzata Kotulska; Natalia Szulc; Marlena Gąsior-Głogowska; Jakub W Wojciechowski; Jarosław Chilimoniuk; Paweł Mackiewicz; Tomas Šneideris; Vytautas Smirnovas
Journal:  Sci Rep       Date:  2021-04-26       Impact factor: 4.379

Review 6.  Protein Co-Aggregation Related to Amyloids: Methods of Investigation, Diversity, and Classification.

Authors:  Stanislav A Bondarev; Kirill S Antonets; Andrey V Kajava; Anton A Nizhnikov; Galina A Zhouravleva
Journal:  Int J Mol Sci       Date:  2018-08-04       Impact factor: 5.923

  6 in total

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