Title: LMDS-based approach for efficient top-k local ligand-binding site search

Authors: Sungchul Kim; Lee Sael; Hwanjo Yu

Addresses: Department of Computer Science and Engineering, Pohang University of Science and Technology (POSTECH), Gyeongbuk, South Korea ' Department of Computer Science, Stony Brook University, Stony Brook, NY 11794-4400, USA; Department of Computer Science, SUNY Korea, Incheon, South Korea ' Department of Computer Science and Engineering, Pohang University of Science and Technology (POSTECH), Gyeongbuk, South Korea

Abstract: In this work, we propose a LMDS-based binding-site search for improving the search speed of the Patch-Surfer method. Patch-Surfer is efficient in recognition of protein-ligand binding partners, further speedup is necessary to address multiple-user access. Futher speedup is realised by exploiting Landmark Multi-Dimensional Scaling (LMDS). It computes embedding coordinates for data points based on their distances from landmark points. When selecting the landmark points, we adopt two approaches - random and greedy selection. Our method approximately retrieves top-k results and the accuracy increases as we exploit more landmark points. Although two landmark selection approaches show comparable results, the greedy selection shows the best performance when the number of landmark points is large. Using our method, the searching time is reduced up to 99% and it retrieves almost 80% of exact top-k results. Additionally, LMDS-based binding-site search+ improves the retrieval accuracy from 80% to 95% while sacrificing the speedup ratio from 99% to 90% compared to Patch-Surfer.

Keywords: structure-based function prediction; protein surface; protein-ligand binding; ligand binding pocket; 3D Zernike descriptor; binding site comparison; bioinformatics; data mining; LMDS; landmark multidimensional scaling; local ligand binding sites; ligand binding site search; random selection; greedy selection; landmark points.

DOI: 10.1504/IJDMB.2015.070066

International Journal of Data Mining and Bioinformatics, 2015 Vol.12 No.4, pp.417 - 433

Received: 02 Jul 2014
Accepted: 20 Jul 2014

Published online: 26 Jun 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article