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Deep Learning-Based Prediction of Enzyme Optimal pH and Design of Point Mutations to Improve Acid Resistance.

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Τίτλος: Deep Learning-Based Prediction of Enzyme Optimal pH and Design of Point Mutations to Improve Acid Resistance.
Συγγραφείς: Qiu S; Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, United Kingdom., Wang NK; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Life Sciences and Health Engineering, Jiangnan University, Wuxi 214122, PR China.; Yixing Institute of Food and Biotechnology Co. Ltd, Yixing 214200, PR China., Lu Y; Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, United Kingdom.; Oxford E-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford OX1 3QG, United Kingdom., Gong JS; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Life Sciences and Health Engineering, Jiangnan University, Wuxi 214122, PR China.; Yixing Institute of Food and Biotechnology Co. Ltd, Yixing 214200, PR China., Shi JS; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Life Sciences and Health Engineering, Jiangnan University, Wuxi 214122, PR China.; Yixing Institute of Food and Biotechnology Co. Ltd, Yixing 214200, PR China., Yang A; Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, United Kingdom.
Πηγή: ACS synthetic biology [ACS Synth Biol] 2025 Dec 19; Vol. 14 (12), pp. 4897-4906. Date of Electronic Publication: 2025 Nov 21.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: American Chemical Society Country of Publication: United States NLM ID: 101575075 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2161-5063 (Electronic) Linking ISSN: 21615063 NLM ISO Abbreviation: ACS Synth Biol Subsets: MEDLINE
Imprint Name(s): Original Publication: Washington, D.C. : American Chemical Society, c2012-
Ιατρικοί όροι (MeSH): Point Mutation*/genetics , Deep Learning*, Pyrococcus horikoshii/enzymology ; Pyrococcus horikoshii/genetics ; Hydrogen-Ion Concentration
Περίληψη: An accurate deep learning predictor of enzyme optimal pH is essential to quantitatively describe how pH influences the enzyme catalytic activity. CatOpt, developed in this study, outperformed existing predictors of enzyme optimal pH (RMSE = 0.833 and R2 = 0.479), and could provide good interpretability with informative residue attention weights. The classification of acidophilic and alkaliphilic enzymes and prediction of enzyme optimal pH shifts caused by point mutations showcased the capability of CatOpt as an effective computational tool for identifying enzyme pH preferences. Furthermore, a single point mutation designed with the guidance of CatOpt successfully enhanced the activity of Pyrococcus horikoshii diacetylchitobiose deacetylase at low pH (pH = 4.5/5.5) by approximately 7%, suggesting that CatOpt is a promising in silico enzyme design tool for pH-dependent enzyme activities.
References: J Mol Biol. 1993 May 20;231(2):459-74. (PMID: 8510157)
PLoS Comput Biol. 2012;8(11):e1002761. (PMID: 23133364)
Meat Sci. 2008 Oct;80(2):545-9. (PMID: 22063364)
BMC Bioinformatics. 2020 Nov 10;21(1):512. (PMID: 33167861)
PLoS One. 2013 Oct 09;8(10):e75726. (PMID: 24130738)
ACS Synth Biol. 2024 Sep 20;13(9):3013-3021. (PMID: 39197156)
Toxins (Basel). 2024 Dec 13;16(12):. (PMID: 39728798)
Indian J Microbiol. 2022 Mar;62(1):96-102. (PMID: 35068609)
J Biotechnol. 2017 Nov 10;261:194-206. (PMID: 28438579)
Science. 2023 Mar 17;379(6637):1123-1130. (PMID: 36927031)
Arch Biochem Biophys. 1999 Mar 15;363(2):349-55. (PMID: 10068458)
Protein Sci. 2009 Mar;18(3):569-78. (PMID: 19241384)
J Theor Biol. 2015 Jan 21;365:197-203. (PMID: 25452135)
Bioresour Technol. 2021 May 1;334:125241. (PMID: 33964814)
Nucleic Acids Res. 2023 Jan 6;51(D1):D523-D531. (PMID: 36408920)
Nat Biotechnol. 2017 Nov;35(11):1026-1028. (PMID: 29035372)
Curr Opin Biotechnol. 2002 Aug;13(4):345-51. (PMID: 12323357)
Appl Environ Microbiol. 2019 Aug 14;85(17):. (PMID: 31253675)
Bioinformatics. 2022 Mar 28;38(7):1995-2002. (PMID: 35043942)
Biochim Biophys Acta. 1978 Aug 7;525(2):314-24. (PMID: 28774)
Bioresour Bioprocess. 2022 May 16;9(1):54. (PMID: 38647756)
Curr Opin Struct Biol. 2025 Apr;91:103004. (PMID: 39983412)
Biotechnol Lett. 2022 Mar;44(3):473-483. (PMID: 35072843)
Cell Syst. 2017 Dec 27;5(6):538-541. (PMID: 29284126)
Brief Bioinform. 2025 Mar 04;26(2):. (PMID: 40079266)
J Am Chem Soc. 2014 Jun 18;136(24):8496-9. (PMID: 24842060)
Brief Bioinform. 2023 Nov 22;25(1):. (PMID: 38189538)
Brief Bioinform. 2024 Jul 25;25(5):. (PMID: 39129365)
Biotechnol Bioeng. 2022 Apr;119(4):1115-1128. (PMID: 35067915)
Biophys Chem. 2021 Jul;274:106591. (PMID: 33895555)
Nat Commun. 2023 Dec 11;14(1):8211. (PMID: 38081905)
Contributed Indexing: Keywords: acid resistance; deep learning; enzyme engineering; enzyme optimal pH; self-attention; sequence-based prediction
Entry Date(s): Date Created: 20251121 Date Completed: 20251219 Latest Revision: 20260513
Update Code: 20260513
PubMed Central ID: PMC12723737
DOI: 10.1021/acssynbio.5c00679
PMID: 41269167
Βάση Δεδομένων: MEDLINE
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  Data: Deep Learning-Based Prediction of Enzyme Optimal pH and Design of Point Mutations to Improve Acid Resistance.
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  Data: <searchLink fieldCode="AU" term="%22Qiu+S%22">Qiu S</searchLink>; Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, United Kingdom.<br /><searchLink fieldCode="AU" term="%22Wang+NK%22">Wang NK</searchLink>; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Life Sciences and Health Engineering, Jiangnan University, Wuxi 214122, PR China.; Yixing Institute of Food and Biotechnology Co. Ltd, Yixing 214200, PR China.<br /><searchLink fieldCode="AU" term="%22Lu+Y%22">Lu Y</searchLink>; Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, United Kingdom.; Oxford E-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford OX1 3QG, United Kingdom.<br /><searchLink fieldCode="AU" term="%22Gong+JS%22">Gong JS</searchLink>; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Life Sciences and Health Engineering, Jiangnan University, Wuxi 214122, PR China.; Yixing Institute of Food and Biotechnology Co. Ltd, Yixing 214200, PR China.<br /><searchLink fieldCode="AU" term="%22Shi+JS%22">Shi JS</searchLink>; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Life Sciences and Health Engineering, Jiangnan University, Wuxi 214122, PR China.; Yixing Institute of Food and Biotechnology Co. Ltd, Yixing 214200, PR China.<br /><searchLink fieldCode="AU" term="%22Yang+A%22">Yang A</searchLink>; Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, United Kingdom.
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  Data: <searchLink fieldCode="JN" term="%22101575075%22">ACS synthetic biology</searchLink> [ACS Synth Biol] 2025 Dec 19; Vol. 14 (12), pp. 4897-4906. <i>Date of Electronic Publication: </i>2025 Nov 21.
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  Data: <searchLink fieldCode="MM" term="%22Point+Mutation%22">Point Mutation*</searchLink>/<searchLink fieldCode="MM" term="%22Point+Mutation+genetics%22">genetics</searchLink> <br /><searchLink fieldCode="MM" term="%22Deep+Learning%22">Deep Learning*</searchLink><br /><searchLink fieldCode="MH" term="%22Pyrococcus+horikoshii%22">Pyrococcus horikoshii</searchLink>/<searchLink fieldCode="MH" term="%22Pyrococcus+horikoshii+enzymology%22">enzymology</searchLink> ; <searchLink fieldCode="MH" term="%22Pyrococcus+horikoshii%22">Pyrococcus horikoshii</searchLink>/<searchLink fieldCode="MH" term="%22Pyrococcus+horikoshii+genetics%22">genetics</searchLink> ; <searchLink fieldCode="MH" term="%22Hydrogen-Ion+Concentration%22">Hydrogen-Ion Concentration</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: An accurate deep learning predictor of enzyme optimal pH is essential to quantitatively describe how pH influences the enzyme catalytic activity. CatOpt, developed in this study, outperformed existing predictors of enzyme optimal pH (RMSE = 0.833 and R<superscript>2</superscript> = 0.479), and could provide good interpretability with informative residue attention weights. The classification of acidophilic and alkaliphilic enzymes and prediction of enzyme optimal pH shifts caused by point mutations showcased the capability of CatOpt as an effective computational tool for identifying enzyme pH preferences. Furthermore, a single point mutation designed with the guidance of CatOpt successfully enhanced the activity of Pyrococcus horikoshii diacetylchitobiose deacetylase at low pH (pH = 4.5/5.5) by approximately 7%, suggesting that CatOpt is a promising in silico enzyme design tool for pH-dependent enzyme activities.
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  Label: References
  Group: RefInfo
  Data: J Mol Biol. 1993 May 20;231(2):459-74. (PMID: <searchLink fieldCode="PM" term="%228510157%22">8510157)</searchLink><br />PLoS Comput Biol. 2012;8(11):e1002761. (PMID: <searchLink fieldCode="PM" term="%2223133364%22">23133364)</searchLink><br />Meat Sci. 2008 Oct;80(2):545-9. (PMID: <searchLink fieldCode="PM" term="%2222063364%22">22063364)</searchLink><br />BMC Bioinformatics. 2020 Nov 10;21(1):512. (PMID: <searchLink fieldCode="PM" term="%2233167861%22">33167861)</searchLink><br />PLoS One. 2013 Oct 09;8(10):e75726. (PMID: <searchLink fieldCode="PM" term="%2224130738%22">24130738)</searchLink><br />ACS Synth Biol. 2024 Sep 20;13(9):3013-3021. (PMID: <searchLink fieldCode="PM" term="%2239197156%22">39197156)</searchLink><br />Toxins (Basel). 2024 Dec 13;16(12):. (PMID: <searchLink fieldCode="PM" term="%2239728798%22">39728798)</searchLink><br />Indian J Microbiol. 2022 Mar;62(1):96-102. (PMID: <searchLink fieldCode="PM" term="%2235068609%22">35068609)</searchLink><br />J Biotechnol. 2017 Nov 10;261:194-206. (PMID: <searchLink fieldCode="PM" term="%2228438579%22">28438579)</searchLink><br />Science. 2023 Mar 17;379(6637):1123-1130. (PMID: <searchLink fieldCode="PM" term="%2236927031%22">36927031)</searchLink><br />Arch Biochem Biophys. 1999 Mar 15;363(2):349-55. (PMID: <searchLink fieldCode="PM" term="%2210068458%22">10068458)</searchLink><br />Protein Sci. 2009 Mar;18(3):569-78. (PMID: <searchLink fieldCode="PM" term="%2219241384%22">19241384)</searchLink><br />J Theor Biol. 2015 Jan 21;365:197-203. (PMID: <searchLink fieldCode="PM" term="%2225452135%22">25452135)</searchLink><br />Bioresour Technol. 2021 May 1;334:125241. (PMID: <searchLink fieldCode="PM" term="%2233964814%22">33964814)</searchLink><br />Nucleic Acids Res. 2023 Jan 6;51(D1):D523-D531. (PMID: <searchLink fieldCode="PM" term="%2236408920%22">36408920)</searchLink><br />Nat Biotechnol. 2017 Nov;35(11):1026-1028. (PMID: <searchLink fieldCode="PM" term="%2229035372%22">29035372)</searchLink><br />Curr Opin Biotechnol. 2002 Aug;13(4):345-51. (PMID: <searchLink fieldCode="PM" term="%2212323357%22">12323357)</searchLink><br />Appl Environ Microbiol. 2019 Aug 14;85(17):. (PMID: <searchLink fieldCode="PM" term="%2231253675%22">31253675)</searchLink><br />Bioinformatics. 2022 Mar 28;38(7):1995-2002. (PMID: <searchLink fieldCode="PM" term="%2235043942%22">35043942)</searchLink><br />Biochim Biophys Acta. 1978 Aug 7;525(2):314-24. (PMID: <searchLink fieldCode="PM" term="%2228774%22">28774)</searchLink><br />Bioresour Bioprocess. 2022 May 16;9(1):54. (PMID: <searchLink fieldCode="PM" term="%2238647756%22">38647756)</searchLink><br />Curr Opin Struct Biol. 2025 Apr;91:103004. (PMID: <searchLink fieldCode="PM" term="%2239983412%22">39983412)</searchLink><br />Biotechnol Lett. 2022 Mar;44(3):473-483. (PMID: <searchLink fieldCode="PM" term="%2235072843%22">35072843)</searchLink><br />Cell Syst. 2017 Dec 27;5(6):538-541. (PMID: <searchLink fieldCode="PM" term="%2229284126%22">29284126)</searchLink><br />Brief Bioinform. 2025 Mar 04;26(2):. (PMID: <searchLink fieldCode="PM" term="%2240079266%22">40079266)</searchLink><br />J Am Chem Soc. 2014 Jun 18;136(24):8496-9. (PMID: <searchLink fieldCode="PM" term="%2224842060%22">24842060)</searchLink><br />Brief Bioinform. 2023 Nov 22;25(1):. (PMID: <searchLink fieldCode="PM" term="%2238189538%22">38189538)</searchLink><br />Brief Bioinform. 2024 Jul 25;25(5):. (PMID: <searchLink fieldCode="PM" term="%2239129365%22">39129365)</searchLink><br />Biotechnol Bioeng. 2022 Apr;119(4):1115-1128. (PMID: <searchLink fieldCode="PM" term="%2235067915%22">35067915)</searchLink><br />Biophys Chem. 2021 Jul;274:106591. (PMID: <searchLink fieldCode="PM" term="%2233895555%22">33895555)</searchLink><br />Nat Commun. 2023 Dec 11;14(1):8211. (PMID: <searchLink fieldCode="PM" term="%2238081905%22">38081905)</searchLink>
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