Anticipating protein evolution with successor sequence predictor
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F26%3A0197679" target="_blank" >RIV/00216305:26230/26:0197679 - isvavai.cz</a>
Result on the web
<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC11927200/" target="_blank" >https://pmc.ncbi.nlm.nih.gov/articles/PMC11927200/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1186/s13321-025-00971-z" target="_blank" >10.1186/s13321-025-00971-z</a>
Alternative languages
Result language
angličtina
Original language name
Anticipating protein evolution with successor sequence predictor
Original language description
The quest to predict and understand protein evolution has been hindered by limitations on both the theoretical and the experimental fronts. Most existing theoretical models of evolution are descriptive, rather than predictive, leaving the fnal modifcations in the hands of researchers. Existing experimental techniques to help probe the evolutionary sequence space of proteins, such as directed evolution, are resource-intensive and require specialised skills. We present the successor sequence predictor (SSP) as an innovative solution. Successor sequence predictor is an in silico protein design method that mimics laboratory-based protein evolution by reconstructing a protein's evolutionary history and suggesting future amino acid substitutions based on trends observed in that history through carefully selected physicochemical descriptors. This approach enhances specialised proteins by predicting mutations that improve desired properties, such as thermostability, activity, and solubility. Successor Sequence Predictor can thus be used as a general protein engineering tool to develop practically useful proteins. The code of the Successor Sequence Predictor is provided at https://github.com/loschmidt/successor-sequence-predictor, and the design of mutations will be also possible via an easy-to-use web server https://loschmidt.chemi.muni.cz/freprotasr/.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Cheminformatics
ISSN
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e-ISSN
1758-2946
Volume of the periodical
17
Issue of the periodical within the volume
34
Country of publishing house
GB - UNITED KINGDOM
Number of pages
12
Pages from-to
1-12
UT code for WoS article
001467954700002
EID of the result in the Scopus database
2-s2.0-105000891864