Literature DB >> 25792555

Solubis: optimize your protein.

Greet De Baets1, Joost Van Durme1, Rob van der Kant2, Joost Schymkowitz2, Frederic Rousseau2.   

Abstract

MOTIVATION: Protein aggregation is associated with a number of protein misfolding diseases and is a major concern for therapeutic proteins. Aggregation is caused by the presence of aggregation-prone regions (APRs) in the amino acid sequence of the protein. The lower the aggregation propensity of APRs and the better they are protected by native interactions within the folded structure of the protein, the more aggregation is prevented. Therefore, both the local thermodynamic stability of APRs in the native structure and their intrinsic aggregation propensity are a key parameter that needs to be optimized to prevent protein aggregation.
RESULTS: The Solubis method presented here automates the process of carefully selecting point mutations that minimize the intrinsic aggregation propensity while improving local protein stability.
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Year:  2015        PMID: 25792555     DOI: 10.1093/bioinformatics/btv162

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


  4 in total

1.  ANTISOMA: A Computational Pipeline for the Reduction of the Aggregation Propensity of Monoclonal Antibodies.

Authors:  Katerina C Nastou; Eleftheria G Karataraki; Nikos C Papandreou; Anna-Isavella G Rerra; Vassiliki P Grimanelli; Ilias Maglogiannis; Stavros J Hamodrakas; Vassiliki A Iconomidou
Journal:  Adv Exp Med Biol       Date:  2020       Impact factor: 2.622

2.  Autoimmune Responses to Soluble Aggregates of Amyloidogenic Proteins Involved in Neurodegenerative Diseases: Overlapping Aggregation Prone and Autoimmunogenic regions.

Authors:  Sandeep Kumar; A Mary Thangakani; R Nagarajan; Satish K Singh; D Velmurugan; M Michael Gromiha
Journal:  Sci Rep       Date:  2016-02-29       Impact factor: 4.379

3.  Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics.

Authors:  Pin-Kuang Lai; Austin Gallegos; Neil Mody; Hasige A Sathish; Bernhardt L Trout
Journal:  MAbs       Date:  2022 Jan-Dec       Impact factor: 5.857

Review 4.  Discovery-stage identification of drug-like antibodies using emerging experimental and computational methods.

Authors:  Emily K Makowski; Lina Wu; Priyanka Gupta; Peter M Tessier
Journal:  MAbs       Date:  2021 Jan-Dec       Impact factor: 5.857

  4 in total

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