Premium
Investigating the Importance of the Pocket‐estimation Method in Pocket‐based Approaches: An Illustration Using Pocket‐ligand Classification
Author(s) -
Caumes Géraldine,
Borrel Alexandre,
Abi Hussein Hiba,
Camproux AnneClaude,
Regad Leslie
Publication year - 2017
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201700025
Subject(s) - binding pocket , computer science , profiling (computer programming) , data mining , binding site , computational biology , biology , genetics , operating system
Small molecules interact with their protein target on surface cavities known as binding pockets. Pocket‐based approaches are very useful in all of the phases of drug design. Their first step is estimating the binding pocket based on protein structure. The available pocket‐estimation methods produce different pockets for the same target. The aim of this work is to investigate the effects of different pocket‐estimation methods on the results of pocket‐based approaches. We focused on the effect of three pocket‐estimation methods on a pocket‐ligand (PL) classification. This pocket‐based approach is useful for understanding the correspondence between the pocket and ligand spaces and to develop pharmacological profiling models. We found pocket‐estimation methods yield different binding pockets in terms of boundaries and properties. These differences are responsible for the variation in the PL classification results that can have an impact on the detected correspondence between pocket and ligand profiles. Thus, we highlighted the importance of the pocket‐estimation method choice in pocket‐based approaches.