Three-Dimensional Ideal Gas Reference State Based Energy Function

Title:Three-Dimensional Ideal Gas Reference State Based Energy Function

Volume: 12 Issue: 2

Author(s): Avdesh Mishra and Md Tamjidul Hoque*

Affiliation:

• Department of Computer Science, University of New Orleans, New Orleans, LA 70148,United States

Keywords: Decoy-set, energy function, genetic algorithm, optimization, protein structure.

Abstract: Background: Energy functions of proteins are developed to quantitatively capture the desirable features of physical interaction that determines the protein folding and structure prediction processes.

Objective: It is vital to develop an accurate energy function to discriminate native-like proteins from decoys. Along the same line, we develop an accurate energy function, which involves careful modelling of the reference state.

Method: Here we propose a novel three-dimensional ideal gas reference state based energy function, which is based on three distinct hydrophobic-hydrophilic interactions of amino acids. The three distinct group of interactions, namely hydrophobic versus hydrophilic, hydrophobic versus hydrophobic and hydrophilic versus hydrophilic are controlled via three-dimensional optimized values of alpha. Using Genetic Algorithm, we optimized the contributions of each of the three groups along with the z-score to discriminate the native from the decoys.

Results: The approach allows us to segregate the statistics, which in turn enables us to model the interactions more accurately without grossly averaging the impact as done in well-known ideal gas reference state based approach. To compute the energy scores we use a database of 4332 known protein structures obtained from the Protein Data Bank.

Conclusion: Our energy function is found to be very competitive compared to the state-of-the-art approaches, and outperforms the nearest competitor by 40.9% for the most challenging Rosetta decoy-set.

Cite this article as:

Mishra Avdesh and Hoque Tamjidul Md*, Three-Dimensional Ideal Gas Reference State Based Energy Function, Current Bioinformatics 2017; 12 (2) . https://dx.doi.org/10.2174/1574893611666161109093137

DOI https://dx.doi.org/10.2174/1574893611666161109093137	Print ISSN 1574-8936
Publisher Name Bentham Science Publisher	Online ISSN 2212-392X