Computational methods and tools for binding site recognition between proteins and small molecules: from classical geometrical approaches to modern machine learning strategies.


Journal

Journal of computer-aided molecular design
ISSN: 1573-4951
Titre abrégé: J Comput Aided Mol Des
Pays: Netherlands
ID NLM: 8710425

Informations de publication

Date de publication:
10 2019
Historique:
received: 01 07 2019
accepted: 11 10 2019
pubmed: 20 10 2019
medline: 29 7 2020
entrez: 20 10 2019
Statut: ppublish

Résumé

In the current "genomic era" the number of identified genes is growing exponentially. However, the biological function of a large number of the corresponding proteins is still unknown. Recognition of small molecule ligands (e.g., substrates, inhibitors, allosteric regulators, etc.) is pivotal for protein functions in the vast majority of the cases and knowledge of the region where these processes take place is essential for protein function prediction and drug design. In this regard, computational methods represent essential tools to tackle this problem. A significant number of software tools have been developed in the last few years which exploit either protein sequence information, structure information or both. This review describes the most recent developments in protein function recognition and binding site prediction, in terms of both freely-available and commercial solutions and tools, detailing the main characteristics of the considered tools and providing a comparative analysis of their performance.

Identifiants

pubmed: 31628659
doi: 10.1007/s10822-019-00235-7
pii: 10.1007/s10822-019-00235-7
doi:

Substances chimiques

Ligands 0
Proteins 0
Small Molecule Libraries 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

887-903

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Auteurs

Gabriele Macari (G)

Department of Sciences, Roma Tre University, Viale Guglielmo Marconi 446, 00146, Rome, Italy.

Daniele Toti (D)

Department of Sciences, Roma Tre University, Viale Guglielmo Marconi 446, 00146, Rome, Italy.

Fabio Polticelli (F)

Department of Sciences, Roma Tre University, Viale Guglielmo Marconi 446, 00146, Rome, Italy. fabio.polticelli@uniroma3.it.
National Institute of Nuclear Physics, Roma Tre Section, 00146, Rome, Italy. fabio.polticelli@uniroma3.it.

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Classifications MeSH