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Structure. 2018 Mar 6;26(3):499-512.e2. doi: 10.1016/j.str.2018.02.001.

An Augmented Pocketome: Detection and Analysis of Small-Molecule Binding Pockets in Proteins of Known 3D Structure.

Author information

1
National Mathematics Initiative, Indian Institute of Science, Bangalore 560012, India.
2
Department of Biochemistry, Indian Institute of Science, Bangalore 560012, India.
3
National Mathematics Initiative, Indian Institute of Science, Bangalore 560012, India; Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, India.
4
National Mathematics Initiative, Indian Institute of Science, Bangalore 560012, India; Department of Biochemistry, Indian Institute of Science, Bangalore 560012, India. Electronic address: nchandra@iisc.ac.in.

Abstract

Protein-ligand interactions form the basis of most cellular events. Identifying ligand binding pockets in proteins will greatly facilitate rationalizing and predicting protein function. Ligand binding sites are unknown for many proteins of known three-dimensional (3D) structure, creating a gap in our understanding of protein structure-function relationships. To bridge this gap, we detect pockets in proteins of known 3D structures, using computational techniques. This augmented pocketome (PocketDB) consists of 249,096 pockets, which is about seven times larger than what is currently known. We deduce possible ligand associations for about 46% of the newly identified pockets. The augmented pocketome, when subjected to clustering based on similarities among pockets, yielded 2,161 site types, which are associated with 1,037 ligand types, together providing fold-site-type-ligand-type associations. The PocketDB resource facilitates a structure-based function annotation, delineation of the structural basis of ligand recognition, and provides functional clues for domains of unknown functions, allosteric proteins, and druggable pockets.

KEYWORDS:

allosteric proteins; druggable proteins; ligand and binding; pocket types; pocketome; protein-ligand interactions; structural bioinformatics; structure-based annotation; structure-function relationship

PMID:
29514079
DOI:
10.1016/j.str.2018.02.001
[Indexed for MEDLINE]

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