Orcid Publication

Detalle de: Computational prediction of protein functional sites—Applications in biotechnology and biomedicine

Title Computational prediction of protein functional sites—Applications in biotechnology and biomedicine
Abstract

There are many computational approaches for predicting protein functional sites based on different sequence and structural features. These methods are essential to cope with the sequence deluge that is filling databases with uncharacterized protein sequences. They complement the more expensive and time-consuming experimental approaches by pointing them to possible candidate positions. In many cases they are jointly used to characterize the functional sites in proteins of biotechnological and biomedical interest and eventually modify them for different purposes. There is a clear trend towards approaches based on machine learning and those using structural information, due to the recent developments in these areas. Nevertheless, "classic" methods based on sequence and evolutionary features are still playing an important role as these features are strongly related to functionality. In this review, the main approaches for predicting general functional sites in a protein are discussed, with a focus on sequence-based approaches.

Apa Reference (2022). Computational prediction of protein functional sites—Applications in biotechnology and biomedicine. Advances in Protein Chemistry and Structural Biology, 39-57. 10.1016/bs.apcsb.2021.12.001
Doi 10.1016/bs.apcsb.2021.12.001
Publication Date 2022
Publication Type Book / chapter
Ontology Artificial Intelligence, Machine Learning in Biology, Function prediction, Biological Databases
Researchers Florencio Pazos Cabaleiro
Research Groups
Tools

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