PocketAlign A Novel Algorithm for Aligning Binding Sites in Protein Structures

Abstract

A fundamental task in bioinformatics involves a transfer of knowledge from one protein molecule onto another by way of recognizing similarities. Such similarities are obtained at different levels, that of sequence, whole fold, or important substructures. Comparison of binding sites is important to understand functional similarities among the proteins and also to understand drug cross-reactivities. Current methods in literature have their own merits and demerits, warranting exploration of newer concepts and algorithms, especially for large-scale comparisons and for obtaining accurate residue-wise mappings. Here, we report the development of a new algorithm, PocketAlign, for obtaining structural superpositions of binding sites. The software is available as a web-service at http://proline.physics.iisc.ernet.in/pocketalign/. The algorithm encodes shape descriptors in the form of geometric perspectives, supplemented by chemical group classification. The shape descriptor considers several perspectives with each residue as the focus and captures relative distribution of residues around it in a given site. Residue-wise pairings are computed by comparing the set of perspectives of the first site with that of the second, followed by a greedy approach that incrementally combines residue pairings into a mapping. The mappings in different frames are then evaluated by different metrics encoding the extent of alignment of individual geometric perspectives. Different initial seed alignments are computed, each subsequently extended by detecting consequential atomic alignments in a three-dimensional grid, and the best 500 stored in a database. Alignments are then ranked, and the top scoring alignments reported, which are then streamed into Pymol for visualization and analyses. The method is validated for accuracy and sensitivity and benchmarked against existing methods. An advantage of PocketAlign, as compared to some of the existing tools available for binding site comparison in literature, is that it explores different schemes for identifying an alignment thus has a better potential to capture similarities in ligand recognition abilities. PocketAlign, by finding a detailed alignment of a pair of sites, provides insights as to why two sites are similar and which set of residues and atoms contribute to the similarity.

Myoglobin structure and function: A multiweek biochemistry laboratory project

“…Over six 3-h laboratory periods, the students isolate Mb from muscle tissue, spectroscopically characterize the oxidation state of its heme moiety and its ligand binding, analyze the protein's structure via molecular modeling programs, and track its thermal denaturation with FTIR. We have expanded and combined previously described experiments [29232], and also updated procedures to reflect changes in the availability of structure analysis software like PyMOL [2,37,38]. This project has the advantage of fulfilling two sometimes disparate goals in laboratory curriculum development: It introduces students to a wide variety of biochemical techniques, while at the same time organizing the project around a central, biologically relevant theme.…”

PLIC: protein–ligand interaction clusters

“…Here we present a database providing the Protein Data Bank (PDB)-scale information of all similar binding sites for each protein–ligand complex. In-house tools, PocketMatch (12) and PocketAlign (13), have been used to obtain clusters of similar binding sites from the PDB. The PocketMatch algorithm represents a binding site in a frame-invariant manner by considering both shape and chemical nature of the amino acid.…”

Identification of Ligand Templates using Local Structure Alignment for Structure-Based Drug Design

“…Common subgraphs of maximal alignment in a pair of the local structures are then detected to superpose the structures. PocketAlign 18 uses shape descriptors, which encode local structures using Cα atoms, to perform residue-wise pairing. The residue pairs are combined into a mapping to obtain an optimal alignment.…”