CoMOGrad and PHOG: From Computer Vision to Fast and Accurate Protein Tertiary Structure Retrieval

TL;DR

This paper introduces fast and accurate protein structure retrieval methods inspired by computer vision techniques, utilizing novel features and Euclidean distance to improve performance on large databases.

Contribution

It presents new protein retrieval features based on co-occurrence matrices and PHOG, adapted from computer vision, enhancing speed and accuracy over existing methods.

Findings

Superior accuracy demonstrated in experiments

Faster retrieval times compared to previous methods

Features effectively capture structural information

Abstract

Due to the advancements in technology number of entries in the structural database of proteins are increasing day by day. Methods for retrieving protein tertiary structures from this large database is the key to comparative analysis of structures which plays an important role to understand proteins and their function. In this paper, we present fast and accurate methods for the retrieval of proteins from a large database with tertiary structures similar to a query protein. Our proposed methods borrow ideas from the field of computer vision. The speed and accuracy of our methods comes from the two newly introduced features, the co-occurrence matrix of the oriented gradient and pyramid histogram of oriented gradient and from the use of Euclidean distance as the distance measure. Experimental results clearly indicate the superiority of our approach in both running time and accuracy. Our method is readily available for use from this website: http://research.buet.ac.bd:8080/Comograd/.