计算机辅助的头孢菌素C酰化酶的从头设计

项目名称： 计算机辅助的头孢菌素C酰化酶的从头设计

项目编号： No.21476123

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 数理科学和化学

项目作者： 朱玉山

作者单位： 清华大学

项目金额： 80万元

中文摘要： 本课题将以超结构建模及大系统优化为基础建立计算机辅助的酶分子从头设计计算策略，并以催化CPC水解制备7－ACA的反应过程为例设计CPC酰化酶进行实验验证。本课题在具体的建模过程中将重点研究（i）基于蛋白质三维数据库及目的反应过渡态小分子的大小、形状及简化催化约束开发骨架筛选算法及建立针对目的反应的骨架库；（ii）改进蛋白骨架上的催化残基匹配算法，匹配过程中不仅考虑催化残基的预组织还要考虑不同反应步骤之间催化残基的再组织约束；（iii）改进结合位点处的氨基酸序列选择优化算法，建立求解考虑蛋白折叠自由能最小及酶活性位点与小分子过渡态之间结合能最小的多目标优化模型。本课题将针对CPC水解反应建立蛋白骨架库及从头设计能够催化CPC水解的人工酶并进行实验验证，通过实验结果与模型计算相结合的方法探索酶分子从头设计的物理化学规律，从而为开发能够催化任意目的反应的人工酶打下理论基础。

中文关键词： 计算酶设计；全局优化；多目标优化；蛋白－配体相互作用；酰化酶

英文摘要： In this project, the computer-aided de novo design methodology for enzyme catalyst will be developed based on superstructure modeling and systems optimization, and this method will be validated using the creation of a novel cephalosporin C (CPC) acylase which catalyzes the hydrolytic reaction of CPC to produce the important pharmaceutical intermediate 7-aminocephalosporanic acid (7-ACA). The key research contents include: (i) Develop protein scaffold selection algorithm and build scaffold library for target reaction based on three-dimensional database of proteins, i.e., PDB, and the size, shape, and simplified catalytic constraints of reaction transition state; (ii) Develop improved combinatorial optimization matching algorithm to anchor catalytic residues on selected scaffolds, the novel algorithm will consider no only the pre-organized catalytic residues but also the re-organization of the catalytic residues during different steps of the reaction; (iii) Develop improved algorithm for amino acid sequence selection at binding sites which will identify the Pareto solution of the multi-objective optimization problem for sequence selection where the two minimization targets are the folding energy of protein and binding energy between active site and small molecule transition state. Finally the scaffold library for de novo design of CPC acylase will be built and the artificial enzymes endowed with activity of catalyzing the hydrolysis of CPC will be used to validate the proposed computational strategy, and this integrated way of combining experiments and modeling will help us to investigate the physio-chemical rules behind the enzyme catalysis and enhance our enzyme design capability towards arbitrary target reaction so as to create great opportunities to develop green processes to replace the chemical processes with high emission.

英文关键词： computational enzyme design;global optimization;multi-objective optimization;protein-ligand interaction;acylase