Enhanced hybrid search algorithm for protein structure prediction using the 3D-HP lattice model

Abstract

The problem of protein structure prediction in the hydrophobic-polar (HP) lattice model is the prediction of protein tertiary structure. This problem is usually referred to as the protein folding problem. This paper presents a method for the application of an enhanced hybrid search algorithm to the problem of protein folding prediction, using the three dimensional (3D) HP lattice model. The enhanced hybrid search algorithm is a combination of the particle swarm optimizer (PSO) and tabu search (TS) algorithms. Since the PSO algorithm entraps local minimum in later evolution extremely easily, we combined PSO with the TS algorithm, which has properties of global optimization. Since the technologies of crossover and mutation are applied many times to PSO and TS algorithms, so enhanced hybrid search algorithm is called the MCMPSO-TS (multiple crossover and mutation PSO-TS) algorithm. Experimental results show that the MCMPSO-TS algorithm can find the best solutions so far for the listed benchmarks, which will help comparison with any future paper approach. Moreover, real protein sequences and Fibonacci sequences are verified in the 3D HP lattice model for the first time. Compared with the previous evolutionary algorithms, the new hybrid search algorithm is novel, and can be used effectively to predict 3D protein folding structure. With continuous development and changes in amino acids sequences, the new algorithm will also make a contribution to the study of new protein sequences.

An Adaptive Discrete Brain Storm Algorithm Solves 3D Protein Structure Prediction

“…BSO-HP method was compared with other methods to exhibit the strength of the method. Table XIII presents the comparison between theBSO-HP method with MCMPSO-TS [28], HGA-PSO [29], and TPPSO [27] based on reaching the optimal solution. MCMPSO-TS method was tested on p1, p2, p3, p4, p5, p6, p8, p10, and p11 and focused on the small HP lengths.…”

Soft Computing Techniques for the Protein Folding Problem on High Performance Computing Architectures

“…In order to avoid local minima, two different techniques named random-walk (based on the pull moves defined in [195] and relay-restart are defined. Another appealing approach on 3D HP lattices is proposed in [201] where authors develop an hybrid search algorithm that combines an enhanced particle swarm algorithm with an enhanced tabu search algorithm. The former appends the operation of crossover (single-point and two-point crossover) whereas the latter adds the operation of mutation.…”

Constraint-handling through multi-objective optimization: The hydrophobic-polar model for protein structure prediction

“…The prediction of protein structures based on the HP model represents a hard combinatorial optimization problem which has been proved to be NP-complete [3,4]. An extensive literature exists on the use of metaheuristic approaches to address this problem, including genetic algorithms [23,24], memetic and hybrid algorithms [25][26][27], tabu search [28], ant colony optimization [29,30], immune-based algorithms [8,31], particle swarm optimization [32,33], differential evolution [9,34], estimation of distribution algorithms [35,36], artificial plant optimization [37], and firefly-inspired algorithms [38].…”