PASSerRank: Prediction of allosteric sites with learning to rank.
learning to rank
machine learning
protein allostery
web server
Journal
Journal of computational chemistry
ISSN: 1096-987X
Titre abrégé: J Comput Chem
Pays: United States
ID NLM: 9878362
Informations de publication
Date de publication:
30 10 2023
30 10 2023
Historique:
revised:
19
06
2023
received:
02
05
2023
accepted:
10
07
2023
medline:
4
9
2023
pubmed:
10
8
2023
entrez:
10
8
2023
Statut:
ppublish
Résumé
Allostery plays a crucial role in regulating protein activity, making it a highly sought-after target in drug development. One of the major challenges in allosteric drug research is the identification of allosteric sites. In recent years, many computational models have been developed for accurate allosteric site prediction. Most of these models focus on designing a general rule that can be applied to pockets of proteins from various families. In this study, we present a new approach using the concept of Learning to Rank (LTR). The LTR model ranks pockets based on their relevance to allosteric sites, that is, how well a pocket meets the characteristics of known allosteric sites. After the training and validation on two datasets, the Allosteric Database (ASD) and CASBench, the LTR model was able to rank an allosteric pocket in the top three positions for 83.6% and 80.5% of test proteins, respectively. The model outperforms other common machine learning models with higher F1 scores (0.662 in ASD and 0.608 in CASBench) and Matthews correlation coefficients (0.645 in ASD and 0.589 in CASBench). The trained model is available on the PASSer platform (https://passer.smu.edu) to aid in drug discovery research.
Substances chimiques
Proteins
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
2223-2229Subventions
Organisme : NIH HHS
ID : 2R15GM122013
Pays : United States
Commentaires et corrections
Type : UpdateOf
Informations de copyright
© 2023 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.
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