Cavity Versus Ligand Shape Descriptors: Application to Urokinase Binding Pockets
Author(s) -
Natacha Cerisier,
Leslie Regad,
Dhoha Triki,
AnneClaude Camproux,
Michel Petitjean
Publication year - 2017
Publication title -
journal of computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.585
H-Index - 95
eISSN - 1557-8666
pISSN - 1066-5277
DOI - 10.1089/cmb.2017.0061
Subject(s) - ligand (biochemistry) , biological system , computational biology , biology , biophysics , chemistry , crystallography , genetics , receptor
We analyzed 78 binding pockets of the human urokinase plasminogen activator (uPA) catalytic domain extracted from a data set of crystallized uPA-ligand complexes. These binding pockets were computed with an original geometric method that does NOT involve any arbitrary parameter, such as cutoff distances, angles, and so on. We measured the deviation from convexity of each pocket shape with the pocket convexity index (PCI). We defined a new pocket descriptor called distributional sphericity coefficient (DISC), which indicates to which extent the protein atoms of a given pocket lie on the surface of a sphere. The DISC values were computed with the freeware PCI. The pocket descriptors and their high correspondences with ligand descriptors are crucial for polypharmacology prediction. We found that the protein heavy atoms lining the urokinases binding pockets are either located on the surface of their convex hull or lie close to this surface. We also found that the radii of the urokinases binding pockets and the radii of their ligands are highly correlated (r = 0.9).
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