To predict protein structure based on HydrophobicPolar model(HP model) in two-dimensional space is called 2D HP protein folding problem. Ant Colony Optimization(ACO), which is inspired by the foraging behavior of ants, is a popular heuristic approach for solving combinatorial optimization problems. This paper presents a method of solving the 2D HP protein folding problem by parallel ACO algorithm. Each ant colony is able to search the best solution guided by the shared pheromone matrix which accumulates the good experience achieved by previous populations. The shared pheromone matrix can integrate all the search knowledge found by parallel colonies. Experimental results show that the parallel implementation performs better comparing with the other ACO solutions.
De novo assembly of a Chinese soybean genome SCIENCE CHINA Life Sciences 61, 871 (2018); Dynamic strategy based parallel ant colony optimization on GPUs for TSPs SCIENCE CHINA Information Sciences 60, 068102 (2017);. RESEARCH PAPER. SCIENCE CHINA Information Sciences
Sidechain prediction is an important subproblem of protein design and structure prediction. Construction of rotamer library is the basis for protein sidechain prediction because it provides the basic searching space for prediction. However, the state-of-the-art rotamer libraries focus on the statistical information of individual amino acids, ignoring the direct affection of its adjacent amino acids. This article presents a sequence-and backbone-dependent rotamer library. Both the conformation information of adjacent amino acids and torsion angle of the current residue are taken into account to construct a sequence-and backbone-dependent library by HMM. Evaluation on all 13 free modeling targets of CASP8 based on our rotamer library is conducted. Comparing with side-chain prediction based on the state-of-the-art rotamer library, our library outperforms the sidechain prediction accuracy on all the test targets to a certain extent.
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