生物技术通报 ›› 2025, Vol. 41 ›› Issue (7): 336-346.doi: 10.13560/j.cnki.biotech.bull.1985.2025-0008

• 研究报告 • 上一篇    下一篇

基于蛋白智能模型提升溶菌酶RPL187的热稳定性

王辉1,2(), 范灵熙2, 孙纪录1, 王苑3, 伍宁丰2, 田健3, 关菲菲2()   

  1. 1.河北农业大学食品科技学院,保定 071000
    2.中国农业科学院生物技术研究所,北京 100081
    3.中国农业科学院北京畜牧兽医研究所,北京 100193
  • 收稿日期:2025-01-04 出版日期:2025-07-26 发布日期:2025-07-22
  • 通讯作者: 关菲菲,女,博士,副研究员,研究方向 :酶蛋白分子设计及改造;E-mail: guanfeifei@caas.cn
  • 作者简介:王辉,男,硕士研究生,研究方向 :酶蛋白分子设计及改造;E-mail: asherhui0120@163.com
  • 基金资助:
    国家重点研发计划(2022YFC2104800);国家肉鸡产业技术体系(CARS-41)

Enhancing the Thermostability of Lysozyme RPL187 Based on Protein Intelligence Models

WANG Hui1,2(), FAN Ling-xi2, SUN Ji-lu1, WANG Yuan3, WU Ning-feng2, TIAN Jian3, GUAN Fei-fei2()   

  1. 1.College of Food Science and Technology, Hebei Agricultural University, Baoding 071000
    2.Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081
    3.Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193
  • Received:2025-01-04 Published:2025-07-26 Online:2025-07-22

摘要:

目的 溶菌酶可作为抑菌剂而广泛应用于食品、生物、医药等领域。但溶菌酶作为一种生物活性物质,其稳定性受温度影响较大,难以满足不同行业的需求。因此采用一种结合人工智能模型设计并筛选蛋白质突变体的改造策略,提高溶菌酶的热稳定性,扩大溶菌酶的实际应用范围。 方法 研究材料为瘤胃原虫基因组来源的溶菌酶RPL187,通过大肠杆菌异源表达蛋白质进行后续实验,利用国标法检测溶菌酶RPL187在不同温度(37、45、50、55 ℃)处理不同时间(0、1、2、4、8 h)下剩余酶比活的变化情况;基于人工智能模型生成并筛选RPL187的多点突变体,同样利用国标法检测溶菌酶突变体在不同温度处理不同时间下剩余酶比活的变化情况,并通过测定野生型与突变体Tm值、自由能、氢键数量、二级结构含量等变化进而研究热稳定性提高的机制。 结果 RPL187在37 ℃和pH 6.5条件下的酶比活为(142 000±2 000)U/mg,比蛋清溶菌酶高5倍;RPL187在37 ℃和45 ℃条件下较稳定,但随着温度升高和热处理时间延长,酶比活出现明显下降的情况,在55 ℃条件下孵育1 h,酶比活下降88%左右;为了提高RPL187的热稳定性,基于人工智能模型共筛选11个RPL187多点突变体;有7个突变体成功在大肠杆菌中可溶性表达,其中RPL187-592和RPL187-209具有抑制藤黄微球菌的活性;进一步热稳定性的检测结果显示,RPL187-592和RPL187-209在50 ℃下经热处理8 h后剩余酶比活较野生型分别高4.43倍和2.29倍,Tm值较野生型分别提高2.06 ℃和2.41 ℃,并且自由能较野生型分别降低1.57 kcal/mol和0.43 kcal/mol,表现出较野生型更稳定的构象和更高的热稳定性。与野生型相比,突变体RPL187-592的分子内氢键增加了3个,且氨基酸由亲水向疏水的转变(K2V和K137V)均有助于提高蛋白质的热稳定性;而在RPL187-209中,可能是由于氨基酸由柔性向刚性(K78P和K108P)以及由亲水向疏水(K137A)的转变而增加热稳定性。 结论 本改造策略可以有效提高蛋白质热稳定性,对于扩大溶菌酶应用范围的实际需求有着重要意义,同时也为相关研究提供可参考的依据。

关键词: 溶菌酶, 藤黄微球菌, 酶比活, 热稳定性改造, 人工智能模型

Abstract:

Objective Lysozyme may be widely used as bacteriostatic agent in food, biomedicine and other fields. However, the stability of lysozyme as a biologically active substance is greatly affected by temperature, which makes it difficult to meet the needs of different industries. Therefore, a modification strategy incorporating the use of artificial intelligence models to design and screen protein mutants was used to improve the thermostability of lysozyme and expand the practical applications of lysozyme. Method The research material is lysozyme RPL187 from rumen protozoa genome. The variation of residual enzyme activities of lysozyme RPL187 at different temperatures (37, 45, 50, and 55 ℃) for different treating times (0, 1, 2, 4, and 8 h) were detected by the national standard method through the heterologous expression of the protein in Escherichia coli. The multipoint mutant of RPL187 was generated and screened based on the AI model, and the variations of residual enzyme activities of lysozyme mutant were detected at different temperatures and different times by the national standard method. The mechanism of the improved thermostability was investigated by determining the changes in Tm value, free energy, number of hydrogen bonds, and content of secondary structure between the wild type and the mutant. Result The specific activity of the RPL187 was (142 000±2 000) U/mg at 37 ℃ and pH 6.5, which was 5 times that of egg white lysozyme. RPL187 was more stable at 37 ℃ and 45 ℃, but with the increase of temperature and the prolongation of the heat treatment time, there was a significant decrease in the specific activity of the enzyme. After incubation for 1 h at 55 ℃, the specific activity of the enzyme decreased by about 88%. In order to improve the thermostability of RPL187, a total of 11 RPL187 multipoint mutants were screened based on the artificial intelligence model; seven mutants were successfully expressed solubilistically in E. coli, among which, RPL187-592 and RPL187-209 had the inhibitory activity against Micrococcus garciniae. Further results of the thermostability assay showed that RPL187-592 and RPL187-209 were stable at 50 ℃. The residual enzyme specific activities after heat treatment at 50 ℃ for 8 h were 4.43 times and 2.29 times that of the wild type, the Tm values were 2.06 ℃ and 2.41 ℃ higher than that of the wild type, and the free energies were 1.57 kcal/mol and 0.43 kcal/mol lower than that of the wild type, which demonstrated a more stable conformation and a higher thermostability than those of the wild type. Compared with the wild type, mutant RPL187-592 showed an increase of three intramolecular hydrogen bonds and the shift of amino acids from hydrophilic to hydrophobic (K2V and K137V) both contributed to the increase in thermostability of the protein; whereas, in RPL187-209, the increase in thermostability may be due to the shift of amino acids from flexible to rigid (K78P and K108P) and from hydrophilic to hydrophobic (K137A). Conclusion This modification strategy may effectively improve the thermostability of proteins, which is of great significance for the practical needs of expanding the application range of lysozyme, and also provides a referable basis for related research.

Key words: lysozyme, Micrococcus garciniae, specific activity, thermostability modification, artificial intelligence model