Tools for Predicting Metal Binding Sites in Protein: A Review

Medhavi      Mallick; Ambarish      Sharan Vidyarthi; Shankaracharya

Abstract

The rapid growth of the Protein Data Bank (PDB) highlights a great challenge for researchers to predict the binding sites of protein for specific metal ion(s). Experimental determination of functional features of a protein is expensive, time consuming and difficult to automate. Therefore, there is a great demand of computational methods for predicting functional features of protein. This review sheds light on currently available in-silico methods including different tools and databases which are based on various information of metal ion and their binding sites (protein residue length, amino acid composition, geometrical and molecular information etc.) and determines the efficiency, speed and accuracy by using diverse algorithms which make the tools beneficial.

Keywords: Computational method, Metal binding site, Motif, PDB, Metalloprotein, Stand alone tools, Metal binding Site Predictor, GRID, CHED, MSDsite