AggreProt: a web server for predicting and engineering aggregation prone regions in proteins

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F24%3A00081379" target="_blank" >RIV/00159816:_____/24:00081379 - isvavai.cz</a>

Alternative codes found

RIV/00216224:14310/24:00136705 RIV/61989100:27740/24:10255789

Result on the web

<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC11223854/pdf/gkae420.pdf" target="_blank" >https://pmc.ncbi.nlm.nih.gov/articles/PMC11223854/pdf/gkae420.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1093/nar/gkae420" target="_blank" >10.1093/nar/gkae420</a>

Result language

angličtina

Original language name

AggreProt: a web server for predicting and engineering aggregation prone regions in proteins

Original language description

Recombinant proteins play pivotal roles in numerous applications including industrial biocatalysts or therapeutics. Despite the recent progress in computational protein structure prediction, protein solubility and reduced aggregation propensity remain challenging attributes to design. Identification of aggregation-prone regions is essential for understanding misfolding diseases or designing efficient protein-based technologies, and as such has a great socio-economic impact. Here, we introduce AggreProt, a user-friendly webserver that automatically exploits an ensemble of deep neural networks to predict aggregation-prone regions (APRs) in protein sequences. Trained on experimentally evaluated hexapeptides, AggreProt compares to or outperforms state-of-the-art algorithms on two independent benchmark datasets. The server provides per-residue aggregation profiles along with information on solvent accessibility and transmembrane propensity within an intuitive interface with interactive sequence and structure viewers for comprehensive analysis. We demonstrate AggreProt efficacy in predicting differential aggregation behaviours in proteins on several use cases, which emphasize its potential for guiding protein engineering strategies towards decreased aggregation propensity and improved solubility. The webserver is freely available and accessible at https://loschmidt.chemi.muni.cz/aggreprot/. Graphical Abstract

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10608 - Biochemistry and molecular biology

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

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Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Nucleic Acids Research

ISSN

0305-1048

e-ISSN

1362-4962

Volume of the periodical

52

Issue of the periodical within the volume

W1

Country of publishing house

US - UNITED STATES

Number of pages

11

Pages from-to

"W159"-"W169"

UT code for WoS article

001233323700001

EID of the result in the Scopus database

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