Protein-folding simulations of the hydrophobic-hydrophilic model by combining pull moves with energy landscape paving

Abstract

The energy landscape paving (ELP) method is a class of heuristic global optimization algorithm based on Monte Carlo sampling.By incorporating generation of initial conformation based on greedy strategy, conformation update mechanism based on pull moves and some heuristic off-trap strategies into the improved ELP method, we propose a new version of ELP, called ELP-pull moves. We test ELP-pull moves on both two-dimensional (2D) and three-dimensional (3D) hydrophobic-hydrophilic (HP) protein folding model. For ten 2D benchmark sequences of length ranging from 20 to 100, the proposed algorithm finds the lowest energies so far. Within the achieved results, the algorithm converges more rapidly and efficiently than the previous methods. For all ten 3D sequences with length 64, the ELP-pull moves method finds new lower energies within comparable computational times. The numerical results demonstrate our algorithm is a powerful method to study lattice protein folding model.

A novel state space representation for the solution of 2D-HP protein folding problem using reinforcement learning methods

“…Thus, in this study the reinforcement learning methods are used for the solution of the protein-folding problem in two dimensional lattice model. There exist many studies [4][5][6][7][8][9] in literature that proposed different methods for the solution of this problem, but the use of reinforcement learning methods are quite new. In [10][11][12][13], authors used the Q-learning algorithm to solve the protein folding problem in two dimensional hydrophobic-polar (2D-HP) model.…”

Finding multiple minimum-energy conformations of the hydrophobic-polar protein model via multidomain sampling

“…To further simplify the problem, coarse-grain lattice protein models are frequently used. The hydrophobic-polar (HP) model [4] is one of the most popular lattice protein models [5][6][7][8][9], as it greatly simplifies the amino acid representation and interaction. In this model, amino acids are abstracted as hydrophobic (H) or polar (P) residues, and the proteins are self-avoiding chains arranged on a simple cubic lattice.…”