关键词: 蛋白质耐热温度, 群智能算法, 人工蜂群, 粒子群优化, 氨基酸网络, 氨基酸含量

Abstract: In order to predict the protein melting temperature directly from the term of the sequence and structure of the protein, the prediction of protein melting temperature based on swarm intelligence algorithm is proposed. Using the hybrid algorithm that combines artificial bee colony and particle swarm, which optimizes the parameters of multivariate linear regression model, the paper calculates the protein melting temperature based on amino acid content. Additionally, by adding amino acid network topological properties to amino acid content, the prediction accuracy is greatly improved. For mesophilic protein, the correlation coefficient between the predicted value deviation and the real value deviation increases to 0.71, the average of prediction accuracy increases to 0.88 compared with the result using amino acid content; and the correlation coefficient increases to 0.75, the average of prediction accuracy increases to 0.91 of thermophilic protein. Amino acid network topological properties offer an innovation perspective for the prediction of protein melting temperature.

Key words: protein melting temperature, swarm intelligence algorithm, artificial bee colony, particle swarm optimization, amino acid network, amino acid content