PSSRDBModel- Protein 3D structure prediction server based on the secondary structure informations

Abstract

Abstract The 3D structure of a protein is highly depended on its sequence. In the absence of an experimentally determined structure, comparative or homology modeling can provide a useful 3D model for a protein that is related to at least one known protein structure (template). Comparative modeling predicts the 3D structure of a given protein sequence (target) primarily based on its alignment with one or more proteins of known structure (templates). However, the sequence similarities below 25% (twilight zone) are not considered for modeling. In this scenario, we have emphasized approach to predict the 3D structure by considering the similarity of secondary structural elements and their consensus. We have developed a database with Protein secondary structure representative database (PSSRD) that holds the secondary structure information. In this work we have designed a PSSRDBModel server that can model the proteins by selecting the template by considering the templates secondary structure element information and Medical subject heading (MeSH) terms. The modeling server at PSSRDB is based on the sequence homology based on the target-template alignment and MeSH terms and uses MODELLER algorithm.