Abstract
Depicting a ligand-receptor complex via Interaction Fingerprints has been shown to be both a viable data visualization and an analysis tool. The spectrum of its applications ranges from simple visualization of the binding site through analysis of molecular dynamics runs, to the evaluation of the homology models and virtual screening. Here we present a novel tool derived from the Structural Interaction Fingerprints providing a detailed and unique insight into the interactions between receptor and specific regions of the ligand (grouped into pharmacophore features) in the form of a matrix, a 2D-SIFt descriptor. The provided implementation is easy to use and extends the python library, allowing the generation of interaction matrices and their manipulation (reading and writing as well as producing the average 2D-SIFt). The library for handling the interaction matrices is available via repository http://bitbucket.org/zchl/sift2d.
Highlights
Structural Interaction Fingerprints (SIFts), as described by Deng et al.[1], comprise a method for encrypting protein–ligand interactions in the form of a bit string
The study revealed the populations of residue positions belonging to the Secondary Binding Pockets (SBPs) [38], spanning TM2 (2 × 60, 2 × 63) and TM7 (7 × 34, 7 × 35 and 7 × 41) and being the extension of the Orthosteric Binding Site (OBS)
Secondary binding pockets play a role in subtype selectivity, as the SBP residues are less conserved
Summary
Structural Interaction Fingerprints (SIFts), as described by Deng et al.[1], comprise a method for encrypting protein–ligand interactions in the form of a bit string. A collection of individual interaction matrices can be averaged into a profile, providing a generalized overview of the binding mode and, concomitantly, of the common pharmacophore features of the interacting ligands. This paper presents the python library for generating and manipulation of the 2D-SIFt descriptor along with two case studies, demonstrating key advantages of extending classical interaction fingerprints: rapid binding site description by means of an averaged descriptor, and the identification of key residues for binding of different types of ligands.
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