GRSA Enhanced for Protein Folding Problem in the Case of Peptides

Juan Frausto-Solís,Juan Paulo Sánchez-Hernández,Juan J González-Barbosa,Fanny G Maldonado-Nava

doi:10.3390/axioms8040136

Abstract

Protein folding problem (PFP) consists of determining the functional three-dimensional structure of a target protein. PFP is an optimization problem where the objective is to find the structure with the lowest Gibbs free energy. It is significant to solve PFP for use in medical and pharmaceutical applications. Hybrid simulated annealing algorithms (HSA) use a kind of simulated annealing or Monte Carlo method, and they are among the most efficient for PFP. The instances of PFP can be classified as follows: (a) Proteins with a large number of amino acids and (b) peptides with a small number of amino acids. Several HSA have been positively applied for the first case, where I-Tasser has been one of the most successful in the CASP competition. PEP-FOLD3 and golden ratio simulated annealing (GRSA) are also two of these algorithms successfully applied to peptides. This paper presents an enhanced golden simulated annealing (GRSA2) where soft perturbations (collision operators), named “on-wall ineffective collision” and “intermolecular ineffective collision”, are applied to generate new solutions in the metropolis cycle. GRSA2 is tested with a dataset for peptides previously proposed, and a comparison with PEP-FOLD3 and I-Tasser is presented. According to the experimentation, GRSA2 has an equivalent performance to those algorithms.

Highlights

Protein folding problem (PFP) consists of determining the functional three-dimensional structure or native structure (NS) of a target protein
Paper, we we present present the the GRSA2
We present the GRSA2 algorithm for the protein folding problem applied to peptides

Summary

Introduction

Protein folding problem (PFP) consists of determining the functional three-dimensional structure or native structure (NS) of a target protein. This problem represents an enormous challenge for the scientific community, and there are significant advances and applications of PFP [1], this problem is far from being solved. To solve the computational problem of designing an algorithm to predict the native structure from a given amino acid sequence. The strategy for solving PFP using only information from the amino acid sequences is known as ab initio and relies on the TH of Anfinsen: This is the approach used in this paper. As we have mentioned before, there are other successful strategies; they cannot be considered as ab initio because they use additional data from the secondary structure or other fragments of proteins

Methods

Results

Conclusion