NAC4ED: A high-throughput computational platform for the rational design of enzyme activity and substrate selectivity

Chuanxi Zhang , Yinghui Feng , Yiting Zhu , Lei Gong , Hao Wei , Lujia Zhang

mLife ›› 2024, Vol. 3 ›› Issue (4) : 505 -514.

PDF
mLife ›› 2024, Vol. 3 ›› Issue (4) : 505 -514. DOI: 10.1002/mlf2.12154
METHOD

NAC4ED: A high-throughput computational platform for the rational design of enzyme activity and substrate selectivity

Author information +
History +
PDF

Abstract

In silico computational methods have been widely utilized to study enzyme catalytic mechanisms and design enzyme performance, including molecular docking, molecular dynamics, quantum mechanics, and multiscale QM/MM approaches. However, the manual operation associated with these methods poses challenges for simulating enzymes and enzyme variants in a high-throughput manner. We developed the NAC4ED, a high-throughput enzyme mutagenesis computational platform based on the “near-attack conformation” design strategy for enzyme catalysis substrates. This platform circumvents the complex calculations involved in transition-state searching by representing enzyme catalytic mechanisms with parameters derived from near-attack conformations. NAC4ED enables the automated, high-throughput, and systematic computation of enzyme mutants, including protein model construction, complex structure acquisition, molecular dynamics simulation, and analysis of active conformation populations. Validation of the accuracy of NAC4ED demonstrated a prediction accuracy of 92.5% for 40 mutations, showing strong consistency between the computational predictions and experimental results. The time required for automated determination of a single enzyme mutant using NAC4ED is 1/764th of that needed for experimental methods. This has significantly enhanced the efficiency of predicting enzyme mutations, leading to revolutionary breakthroughs in improving the performance of high-throughput screening of enzyme variants. NAC4ED facilitates the efficient generation of a large amount of annotated data, providing high-quality data for statistical modeling and machine learning. NAC4ED is currently available at http://lujialab.org.cn/software/.

Keywords

high-throughput screening / near-attack conformation / protein engineering / rational design

Cite this article

Download citation ▾
Chuanxi Zhang,Yinghui Feng,Yiting Zhu,Lei Gong,Hao Wei,Lujia Zhang. NAC4ED: A high-throughput computational platform for the rational design of enzyme activity and substrate selectivity. mLife, 2024, 3(4): 505-514 DOI:10.1002/mlf2.12154

登录浏览全文

4963

注册一个新账户 忘记密码

References

RIGHTS & PERMISSIONS

2024 The Author(s). mLife published by John Wiley & Sons Australia, Ltd on behalf of Institute of Microbiology, Chinese Academy of Sciences.

AI Summary AI Mindmap
PDF

0

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/