Protein Language Model‐Guided Engineering of a 2,3‐Butanediol Dehydrogenase for the Enantioselective Synthesis of Cyclic α ‐Hydroxy Ketones
Source abstract
Abstract
ABSTRACT (2 R ,3 R )‐butanediol dehydrogenases (BDHs) are promising catalysts for the production of α ‐hydroxy ketones, which are highly valuable compounds in the synthesis of fine chemicals and pharmaceuticals. However, (2 R ,3 R )‐BDHs display limited stereoselectivity, thus restricting wider applications. In this study, we engineered a (2 R ,3 R )‐BDH from Bacillus subtilis ( Bs BDH) to enhance and invert its stereoselectivity toward 1,2‐cyclohexanediol (1,2‐CHD) for the production of chiral 2‐hydroxycyclohexanone. The hot spots 115, 118, 293 of Bs BDH were initially identified using the protein language model ESM‐1v. Subsequently, to obtain a stable scaffold to engineer stereoselectivity, we devised a strategy of position analysis and source search, achieving a true‐positive rate of 88.2% in designing thermostable single variants. Furthermore, iterative saturation mutagenesis was applied to the hot spots of the thermostable variant 6M2, and obtained a trans ‐CHD preference variant LTF ( ee > 99%) and a cis ‐CHD preference variant 10M ( ee > 99%). Several high‐activity variants were also obtained, including 6M2/F115C/L118F and 6M2/F115L/L118M, which demonstrated the activity improvements toward 25 substrates, with the highest enhancement reaching 5183.1‐fold. Additionally, molecular dynamics (MD) simulations and the incorporation of non‐canonical amino acids (ncAAs) were utilized to elucidate the mechanisms underlying the variants. The engineered Bs BDH variants exhibit promising potential for the biocatalytic production of α ‐hydroxyketones.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Enzyme Catalysis and Immobilization · Microbial Metabolic Engineering and Bioproduction · Biochemical Acid Research Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Bioengineering College of Chemical and Biological Engineering Zhejiang University Hangzhou China
ZJU‐Hangzhou Global Scientific and Technological Innovation Centre Hangzhou China
Zhejiang Key Laboratory of Intelligent Manufacturing for Functional Chemicals ZJU‐Hangzhou Global Scientific and Technological Innovation Centre Zhejiang University Hangzhou China
Funding
National Natural Science Foundation of China
References (68)
Show source-provided references
1. 10.1039/c2cs35046g10.1039/c2cs35046g ↗
2. 10.1016/j.bmc.2003.10.01710.1016/j.bmc.2003.10.017 ↗
3. 10.1016/S0960‐894X(02)01058‐210.1016/S0960‐894X(02)01058‐2 ↗
4. 10.1021/ar900196n10.1021/ar900196n ↗
5. 10.1016/j.tetasy.2006.06.02310.1016/j.tetasy.2006.06.023 ↗
6. 10.1039/D4GC00827H10.1039/D4GC00827H ↗
7. 10.1021/jm970065l10.1021/jm970065l ↗
8. 10.3390/molecules2514319710.3390/molecules25143197 ↗
9. 10.1002/1521‐3773(20020517)41:10<1743::AID‐ANIE1743>3.0.CO;2‐Q10.1002/1521‐3773(20020517)41:10<1743::AID‐ANIE1743>3.0.CO;2‐Q ↗
10. 10.1002/anie.20035308510.1002/anie.200353085 ↗
11. 10.1002/slct.20230179110.1002/slct.202301791 ↗
12. 10.1002/cctc.20230170710.1002/cctc.202301707 ↗
13. 10.1016/j.cbpa.2013.02.01710.1016/j.cbpa.2013.02.017 ↗
14. 10.1016/j.gresc.2022.05.01110.1016/j.gresc.2022.05.011 ↗
15. 10.1002/ejoc.20160022810.1002/ejoc.201600228 ↗
16. 10.1016/j.copbio.2004.06.00210.1016/j.copbio.2004.06.002 ↗
17. 10.1002/ejoc.20030033810.1002/ejoc.200300338 ↗
18. 10.1016/j.tetasy.2004.06.04810.1016/j.tetasy.2004.06.048 ↗
19. 10.1016/0957‐4166(96)00272‐810.1016/0957‐4166(96)00272‐8 ↗
20. 10.1002/anie.20221508810.1002/anie.202215088 ↗
21. 10.1021/jacs.3c0145610.1021/jacs.3c01456 ↗
22. 10.1021/acscatal.4c0176610.1021/acscatal.4c01766 ↗
23. 10.1021/acscatal.1c0067810.1021/acscatal.1c00678 ↗
24. 10.1021/acscatal.4c0467610.1021/acscatal.4c04676 ↗
25. 10.1002/cbic.20230029010.1002/cbic.202300290 ↗
26. 10.1016/j.ijbiomac.2024.13644310.1016/j.ijbiomac.2024.136443 ↗
27. 10.1016/j.jbiotec.2016.12.01610.1016/j.jbiotec.2016.12.016 ↗
28. 10.1016/j.jbiotec.2017.07.02010.1016/j.jbiotec.2017.07.020 ↗
29. 10.1016/j.tibtech.2022.01.00810.1016/j.tibtech.2022.01.008 ↗
30. 10.1016/j.ijbiomac.2024.13141510.1016/j.ijbiomac.2024.131415 ↗
31. 10.1186/s13068‐020‐01820‐x10.1186/s13068‐020‐01820‐x ↗
32. 10.1039/C7CY00169J10.1039/C7CY00169J ↗
33. 10.1002/adsc.20130030110.1002/adsc.201300301 ↗
34. 10.1021/cs501611310.1021/cs5016113 ↗
35. 10.1007/s00253‐013‐4959‐x10.1007/s00253‐013‐4959‐x ↗
36. 10.1128/AEM.02998‐1010.1128/AEM.02998‐10 ↗
37. 10.1007/s12033‐021‐00308‐910.1007/s12033‐021‐00308‐9 ↗
38. 10.1074/jbc.M00303520010.1074/jbc.M003035200 ↗
39. 10.1016/j.bcab.2019.10137210.1016/j.bcab.2019.101372 ↗
40. 10.1016/j.bbagen.2023.13032610.1016/j.bbagen.2023.130326 ↗
41. 10.1021/acs.chemrev.1c0026010.1021/acs.chemrev.1c00260 ↗
42. 10.1016/j.biotechadv.2022.10792610.1016/j.biotechadv.2022.107926 ↗
43. 10.1021/cbe.4c0001210.1021/cbe.4c00012 ↗
44. 10.1002/anie.20050274610.1002/anie.200502746 ↗
45. 10.1002/anie.20060279510.1002/anie.200602795 ↗
46. 10.1038/nature1994610.1038/nature19946 ↗
47. 10.1093/nar/gky41710.1093/nar/gky417 ↗
48. 10.1016/j.csbj.2018.01.00210.1016/j.csbj.2018.01.002 ↗
49. 10.1002/prot.2292110.1002/prot.22921 ↗
50. 10.1093/bioinformatics/btz18410.1093/bioinformatics/btz184 ↗
51. 10.1038/ncomms633010.1038/ncomms6330 ↗
52. 10.1016/j.molcel.2016.06.01210.1016/j.molcel.2016.06.012 ↗
53. 10.1016/j.apcata.2013.06.02310.1016/j.apcata.2013.06.023 ↗
54. 10.1021/bi035271b10.1021/bi035271b ↗
55. 10.1016/j.jinorgbio.2017.07.02210.1016/j.jinorgbio.2017.07.022 ↗
56. 10.1039/b418040b10.1039/b418040b ↗
57. 10.3390/molecules2004715610.3390/molecules20047156 ↗
58. J.Meier R.Rao andR.Verkuil “Language Models Enable Zero‐Shot Prediction of the Effects of Mutations on Protein Function ” in35th Annual Conference on Neural Information Processing Systems(NeurIPS 2021).10.1101/2021.07.09.450648 ↗
59. 10.1016/j.biotechadv.2013.10.01210.1016/j.biotechadv.2013.10.012 ↗
60. 10.1093/bioadv/vbae10310.1093/bioadv/vbae103 ↗
61. 10.1093/bioinformatics/btl15810.1093/bioinformatics/btl158 ↗
62. 10.1021/cbe.5c0003310.1021/cbe.5c00033 ↗
63. 10.1021/acs.chemrev.4c0013610.1021/acs.chemrev.4c00136 ↗
64. 10.1038/s41586‐024‐07487‐w10.1038/s41586‐024‐07487‐w ↗
65. 10.1002/jcc.2335410.1002/jcc.23354 ↗
66. 10.1016/j.softx.2015.06.00110.1016/j.softx.2015.06.001 ↗
67. 10.1002/jcc.2306710.1002/jcc.23067 ↗
68. 10.1002/wcms.6610.1002/wcms.66 ↗