bioRxivBioengineeringPreprint
A De Novo Design Strategy to Convert FAcD from Dimer to Active Monomer
Ke-Wei CheniD, Cuizhen WangiD, Hui-si Huang, Xing WuiD, Jianan CheniD, Jia-He Qiu, Kin Kuan HoiiD, Tianyu SuniD, Jian‐bo WangiD, Yun‐Dong WuiD
Abstract
Enzymes largely exist in various oligomeric states, but monomeric enzymes are more conducive to industrial applications. Converting an oligomeric enzyme into an active monomer is a significant challenge. In this study, we present a de novo design strategy to convert fluoroacetate dehalogenase (FAcD) from its native dimeric form to an active monomer. Using the AI-based method ProteinMPNN, we identified critical protein-protein interaction (PPI) sites at the dimer interface. ArDCA, another AI tool, was employed to pinpoint catalytic hotspots. Six mutants, Mu1-Mu6, were designed. Molecular dynamics (MD) simulations, coupled with mass spectrometry, confirmed that these mutants form stable monomers. The pre-reaction state (PRS) model predicted that three of these mutants exhibited catalytic activity. In particular, Mu5 with 11 mutations from the wild-type, was predicted to have high catalytic activity, and was subsequently confirmed by kinetics experiment, with a kcat of 672.2 min-1 and a T5030 > 100 {degrees}C, comparable to the wild-type enzyme (kcat = 676.3 min-1, T5030 = 84 {degrees}C). Notably, the Y149M mutation increased catalytic activity nearly forty-fold, demonstrating the effectiveness of our design strategy.
- assay: protein structure
- research focus: protein design
- approach: deep learning
- approach: statistical model
- Citations
- 2
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