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Norton-Baker B, Denton MCR, Murphy NP, Fram B, Lim S, Erickson E, Gauthier NP, Beckham GT. Enabling high-throughput enzyme discovery and engineering with a low-cost, robot-assisted pipeline. Sci Rep 2024; 14:14449. [PMID: 38914665 PMCID: PMC11196671 DOI: 10.1038/s41598-024-64938-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Accepted: 06/14/2024] [Indexed: 06/26/2024] Open
Abstract
As genomic databases expand and artificial intelligence tools advance, there is a growing demand for efficient characterization of large numbers of proteins. To this end, here we describe a generalizable pipeline for high-throughput protein purification using small-scale expression in E. coli and an affordable liquid-handling robot. This low-cost platform enables the purification of 96 proteins in parallel with minimal waste and is scalable for processing hundreds of proteins weekly per user. We demonstrate the performance of this method with the expression and purification of the leading poly(ethylene terephthalate) hydrolases reported in the literature. Replicate experiments demonstrated reproducibility and enzyme purity and yields (up to 400 µg) sufficient for comprehensive analyses of both thermostability and activity, generating a standardized benchmark dataset for comparing these plastic-degrading enzymes. The cost-effectiveness and ease of implementation of this platform render it broadly applicable to diverse protein characterization challenges in the biological sciences.
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Grants
- DE-SC0022024 U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), Genomic Science Program
- DE-SC0022024 U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), Genomic Science Program
- DE-SC0022024 U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), Genomic Science Program
- DE-SC0022024 U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), Genomic Science Program
- DE-SC0022024 U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), Genomic Science Program
- DE-AC36-08GO28308 Advanced Materials and Manufacturing Technologies Office (AMMTO)
- DE-AC36-08GO28308 Advanced Materials and Manufacturing Technologies Office (AMMTO)
- DE-AC36-08GO28308 Advanced Materials and Manufacturing Technologies Office (AMMTO)
- DE-AC36-08GO28308 Advanced Materials and Manufacturing Technologies Office (AMMTO)
- U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Bioenergy Technologies Office (BETO)
- Bio-Optimized Technologies to keep Thermoplastics out of Landfills and the Environment (BOTTLE) Consortium
- Dana-Farber Cancer Institute
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Affiliation(s)
- Brenna Norton-Baker
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, CO, USA
- BOTTLE Consortium, Golden, CO, USA
- Agile BioFoundry, Emeryville, CA, USA
| | - Mackenzie C R Denton
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, CO, USA
- BOTTLE Consortium, Golden, CO, USA
| | - Natasha P Murphy
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, CO, USA
- BOTTLE Consortium, Golden, CO, USA
| | - Benjamin Fram
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Samuel Lim
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Erika Erickson
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, CO, USA
- BOTTLE Consortium, Golden, CO, USA
| | - Nicholas P Gauthier
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA.
| | - Gregg T Beckham
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, CO, USA.
- BOTTLE Consortium, Golden, CO, USA.
- Agile BioFoundry, Emeryville, CA, USA.
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2
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Weinstein JJ, Saikia C, Karbat I, Goldenzweig A, Reuveny E, Fleishman SJ. One-shot design elevates functional expression levels of a voltage-gated potassium channel. Protein Sci 2024; 33:e4995. [PMID: 38747377 PMCID: PMC11094769 DOI: 10.1002/pro.4995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 04/03/2024] [Accepted: 04/05/2024] [Indexed: 05/19/2024]
Abstract
Membrane proteins play critical physiological roles as receptors, channels, pumps, and transporters. Despite their importance, however, low expression levels often hamper the experimental characterization of membrane proteins. We present an automated and web-accessible design algorithm called mPROSS (https://mPROSS.weizmann.ac.il), which uses phylogenetic analysis and an atomistic potential, including an empirical lipophilicity scale, to improve native-state energy. As a stringent test, we apply mPROSS to the Kv1.2-Kv2.1 paddle chimera voltage-gated potassium channel. Four designs, encoding 9-26 mutations relative to the parental channel, were functional and maintained potassium-selective permeation and voltage dependence in Xenopus oocytes with up to 14-fold increase in whole-cell current densities. Additionally, single-channel recordings reveal no significant change in the channel-opening probability nor in unitary conductance, indicating that functional expression levels increase without impacting the activity profile of individual channels. Our results suggest that the expression levels of other dynamic channels and receptors may be enhanced through one-shot design calculations.
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Affiliation(s)
- Jonathan Jacob Weinstein
- Department of Biomolecular SciencesWeizmann Institute of ScienceRehovotIsrael
- Present address:
Scala Biodesign LtdTel AvivIsrael
| | - Chandamita Saikia
- Department of Biomolecular SciencesWeizmann Institute of ScienceRehovotIsrael
- Present address:
Institute for BiochemistryUniversity of LübeckLübeckGermany
| | - Izhar Karbat
- Department of Biomolecular SciencesWeizmann Institute of ScienceRehovotIsrael
| | | | - Eitan Reuveny
- Department of Biomolecular SciencesWeizmann Institute of ScienceRehovotIsrael
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3
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Daffern N, Johansson KE, Baumer ZT, Robertson NR, Woojuh J, Bedewitz MA, Davis Z, Wheeldon I, Cutler SR, Lindorff-Larsen K, Whitehead TA. GMMA Can Stabilize Proteins Across Different Functional Constraints. J Mol Biol 2024; 436:168586. [PMID: 38663544 DOI: 10.1016/j.jmb.2024.168586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 04/16/2024] [Accepted: 04/17/2024] [Indexed: 05/06/2024]
Abstract
Stabilizing proteins without otherwise hampering their function is a central task in protein engineering and design. PYR1 is a plant hormone receptor that has been engineered to bind diverse small molecule ligands. We sought a set of generalized mutations that would provide stability without affecting functionality for PYR1 variants with diverse ligand-binding capabilities. To do this we used a global multi-mutant analysis (GMMA) approach, which can identify substitutions that have stabilizing effects and do not lower function. GMMA has the added benefit of finding substitutions that are stabilizing in different sequence contexts and we hypothesized that applying GMMA to PYR1 with different functionalities would identify this set of generalized mutations. Indeed, conducting FACS and deep sequencing of libraries for PYR1 variants with two different functionalities and applying a GMMA analysis identified 5 substitutions that, when inserted into four PYR1 variants that each bind a unique ligand, provided an increase of 2-6 °C in thermal inactivation temperature and no decrease in functionality.
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Affiliation(s)
- Nicolas Daffern
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO 80305, USA
| | - Kristoffer E Johansson
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Zachary T Baumer
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO 80305, USA
| | | | - Janty Woojuh
- Department of Botany and Plant Sciences, University of California, Riverside, USA
| | - Matthew A Bedewitz
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO 80305, USA
| | - Zoë Davis
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO 80305, USA
| | - Ian Wheeldon
- Department of Chemical and Environmental Engineering, University of California, Riverside, USA; Institute for Integrative Genome Biology, University of California, Riverside, Riverside, CA, USA
| | - Sean R Cutler
- Department of Botany and Plant Sciences, University of California, Riverside, USA; Institute for Integrative Genome Biology, University of California, Riverside, Riverside, CA, USA; Center for Plant Cell Biology, University of California, Riverside, Riverside, CA, USA
| | - Kresten Lindorff-Larsen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Timothy A Whitehead
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO 80305, USA.
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4
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Ertelt M, Meiler J, Schoeder CT. Combining Rosetta Sequence Design with Protein Language Model Predictions Using Evolutionary Scale Modeling (ESM) as Restraint. ACS Synth Biol 2024; 13:1085-1092. [PMID: 38568188 PMCID: PMC11036486 DOI: 10.1021/acssynbio.3c00753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 02/16/2024] [Accepted: 03/20/2024] [Indexed: 04/20/2024]
Abstract
Computational protein sequence design has the ambitious goal of modifying existing or creating new proteins; however, designing stable and functional proteins is challenging without predictability of protein dynamics and allostery. Informing protein design methods with evolutionary information limits the mutational space to more native-like sequences and results in increased stability while maintaining functions. Recently, language models, trained on millions of protein sequences, have shown impressive performance in predicting the effects of mutations. Assessing Rosetta-designed sequences with a language model showed scores that were worse than those of their original sequence. To inform Rosetta design protocols with language model predictions, we added a new metric to restrain the energy function during design using the Evolutionary Scale Modeling (ESM) model. The resulting sequences have better language model scores and similar sequence recovery, with only a minor decrease in the fitness as assessed by Rosetta energy. In conclusion, our work combines the strength of recent machine learning approaches with the Rosetta protein design toolbox.
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Affiliation(s)
- Moritz Ertelt
- Institute
for Drug Discovery, University Leipzig Medicine
Faculty, Liebigstr. 19, D-04103 Leipzig, Germany
- Center
for Scalable Data Analytics and Artificial Intelligence ScaDS.AI, D-04105 Leipzig, Germany
| | - Jens Meiler
- Institute
for Drug Discovery, University Leipzig Medicine
Faculty, Liebigstr. 19, D-04103 Leipzig, Germany
- Center
for Scalable Data Analytics and Artificial Intelligence ScaDS.AI, D-04105 Leipzig, Germany
- Department
of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United
States
- Center
for Structural Biology, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Clara T. Schoeder
- Institute
for Drug Discovery, University Leipzig Medicine
Faculty, Liebigstr. 19, D-04103 Leipzig, Germany
- Center
for Scalable Data Analytics and Artificial Intelligence ScaDS.AI, D-04105 Leipzig, Germany
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5
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Dai C, Tian JX, Chen YF, Ni YH, Cui L, Cao HX, Song LL, Xu SY, Wang YJ, Zheng YG. Computer-aided design to enhance the stability of aldo-keto reductase KdAKR. Biotechnol J 2024; 19:e2300637. [PMID: 38472092 DOI: 10.1002/biot.202300637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 01/29/2024] [Accepted: 02/02/2024] [Indexed: 03/14/2024]
Abstract
The aldo-keto reductase (AKR) KdAKR from Kluyvermyces dobzhanskii can reduce t-butyl 6-chloro-(5S)-hydroxy-3-oxohexanoate ((5S)-CHOH) to t-butyl 6-chloro-(3R,5S)-dihydroxyhexanoate ((3R,5S)-CDHH), which is the key chiral intermediate of rosuvastatin. Herein, a computer-aided design that combined the use of PROSS platform and consensus design was employed to improve the stability of a previously constructed mutant KdAKRM6 . Experimental verification revealed that S196C, T232A, V264I and V45L produced improved thermostability and activity. The "best" mutant KdAKRM10 (KdAKRM6 -S196C/T232A/V264I/V45L) was constructed by combining the four beneficial mutations, which displayed enhanced thermostability. Its T50 15 and Tm values were increased by 10.2 and 10.0°C, respectively, and half-life (t1/2 ) at 40°C was increased by 17.6 h. Additionally, KdAKRM10 demonstrated improved resistance to organic solvents compared to that of KdAKRM6 . Structural analysis revealed that the increased number of hydrogen bonds and stabilized hydrophobic core contributed to the rigidity of KdAKRM10 , thus improving its stability. The results validated the feasibility of the computer-aided design strategy in improving the stability of AKRs.
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Affiliation(s)
- Chen Dai
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, P. R. China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, P. R. China
| | - Jia-Xin Tian
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, P. R. China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, P. R. China
| | - Yu-Feng Chen
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, P. R. China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, P. R. China
| | - Yue-Han Ni
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, P. R. China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, P. R. China
| | - Lei Cui
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, P. R. China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, P. R. China
| | - Hai-Xing Cao
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, P. R. China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, P. R. China
| | - Lin-Lin Song
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, P. R. China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, P. R. China
| | - Shen-Yuan Xu
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, P. R. China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, P. R. China
| | - Ya-Jun Wang
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, P. R. China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, P. R. China
| | - Yu-Guo Zheng
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, P. R. China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, P. R. China
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6
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Yang J, Li FZ, Arnold FH. Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering. ACS CENTRAL SCIENCE 2024; 10:226-241. [PMID: 38435522 PMCID: PMC10906252 DOI: 10.1021/acscentsci.3c01275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 12/26/2023] [Accepted: 01/16/2024] [Indexed: 03/05/2024]
Abstract
Enzymes can be engineered at the level of their amino acid sequences to optimize key properties such as expression, stability, substrate range, and catalytic efficiency-or even to unlock new catalytic activities not found in nature. Because the search space of possible proteins is vast, enzyme engineering usually involves discovering an enzyme starting point that has some level of the desired activity followed by directed evolution to improve its "fitness" for a desired application. Recently, machine learning (ML) has emerged as a powerful tool to complement this empirical process. ML models can contribute to (1) starting point discovery by functional annotation of known protein sequences or generating novel protein sequences with desired functions and (2) navigating protein fitness landscapes for fitness optimization by learning mappings between protein sequences and their associated fitness values. In this Outlook, we explain how ML complements enzyme engineering and discuss its future potential to unlock improved engineering outcomes.
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Affiliation(s)
- Jason Yang
- Division
of Chemistry and Chemical Engineering, California
Institute of Technology, Pasadena, California 91125, United States
| | - Francesca-Zhoufan Li
- Division
of Biology and Biological Engineering, California
Institute of Technology, Pasadena, California 91125, United States
| | - Frances H. Arnold
- Division
of Chemistry and Chemical Engineering, California
Institute of Technology, Pasadena, California 91125, United States
- Division
of Biology and Biological Engineering, California
Institute of Technology, Pasadena, California 91125, United States
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7
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Radley E, Davidson J, Foster J, Obexer R, Bell EL, Green AP. Engineering Enzymes for Environmental Sustainability. ANGEWANDTE CHEMIE (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2023; 135:e202309305. [PMID: 38516574 PMCID: PMC10952289 DOI: 10.1002/ange.202309305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Indexed: 03/23/2024]
Abstract
The development and implementation of sustainable catalytic technologies is key to delivering our net-zero targets. Here we review how engineered enzymes, with a focus on those developed using directed evolution, can be deployed to improve the sustainability of numerous processes and help to conserve our environment. Efficient and robust biocatalysts have been engineered to capture carbon dioxide (CO2) and have been embedded into new efficient metabolic CO2 fixation pathways. Enzymes have been refined for bioremediation, enhancing their ability to degrade toxic and harmful pollutants. Biocatalytic recycling is gaining momentum, with engineered cutinases and PETases developed for the depolymerization of the abundant plastic, polyethylene terephthalate (PET). Finally, biocatalytic approaches for accessing petroleum-based feedstocks and chemicals are expanding, using optimized enzymes to convert plant biomass into biofuels or other high value products. Through these examples, we hope to illustrate how enzyme engineering and biocatalysis can contribute to the development of cleaner and more efficient chemical industry.
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Affiliation(s)
- Emily Radley
- Department of Chemistry & Manchester Institute of Biotechnology The University of Manchester 131 Princess Street Manchester M1 7DN UK
| | - John Davidson
- Department of Chemistry & Manchester Institute of Biotechnology The University of Manchester 131 Princess Street Manchester M1 7DN UK
| | - Jake Foster
- Department of Chemistry & Manchester Institute of Biotechnology The University of Manchester 131 Princess Street Manchester M1 7DN UK
| | - Richard Obexer
- Department of Chemistry & Manchester Institute of Biotechnology The University of Manchester 131 Princess Street Manchester M1 7DN UK
| | - Elizabeth L Bell
- Renewable Resources and Enabling Sciences Center National Renewable Energy Laboratory Golden CO USA
- BOTTLE Consortium Golden CO USA
| | - Anthony P Green
- Department of Chemistry & Manchester Institute of Biotechnology The University of Manchester 131 Princess Street Manchester M1 7DN UK
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8
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Radley E, Davidson J, Foster J, Obexer R, Bell EL, Green AP. Engineering Enzymes for Environmental Sustainability. Angew Chem Int Ed Engl 2023; 62:e202309305. [PMID: 37651344 PMCID: PMC10952156 DOI: 10.1002/anie.202309305] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 08/23/2023] [Accepted: 08/24/2023] [Indexed: 09/02/2023]
Abstract
The development and implementation of sustainable catalytic technologies is key to delivering our net-zero targets. Here we review how engineered enzymes, with a focus on those developed using directed evolution, can be deployed to improve the sustainability of numerous processes and help to conserve our environment. Efficient and robust biocatalysts have been engineered to capture carbon dioxide (CO2 ) and have been embedded into new efficient metabolic CO2 fixation pathways. Enzymes have been refined for bioremediation, enhancing their ability to degrade toxic and harmful pollutants. Biocatalytic recycling is gaining momentum, with engineered cutinases and PETases developed for the depolymerization of the abundant plastic, polyethylene terephthalate (PET). Finally, biocatalytic approaches for accessing petroleum-based feedstocks and chemicals are expanding, using optimized enzymes to convert plant biomass into biofuels or other high value products. Through these examples, we hope to illustrate how enzyme engineering and biocatalysis can contribute to the development of cleaner and more efficient chemical industry.
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Affiliation(s)
- Emily Radley
- Department of Chemistry & Manchester Institute of BiotechnologyThe University of Manchester131 Princess StreetManchesterM1 7DNUK
| | - John Davidson
- Department of Chemistry & Manchester Institute of BiotechnologyThe University of Manchester131 Princess StreetManchesterM1 7DNUK
| | - Jake Foster
- Department of Chemistry & Manchester Institute of BiotechnologyThe University of Manchester131 Princess StreetManchesterM1 7DNUK
| | - Richard Obexer
- Department of Chemistry & Manchester Institute of BiotechnologyThe University of Manchester131 Princess StreetManchesterM1 7DNUK
| | - Elizabeth L. Bell
- Renewable Resources and Enabling Sciences CenterNational Renewable Energy LaboratoryGoldenCOUSA
- BOTTLE ConsortiumGoldenCOUSA
| | - Anthony P. Green
- Department of Chemistry & Manchester Institute of BiotechnologyThe University of Manchester131 Princess StreetManchesterM1 7DNUK
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9
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Zhang MF, Xie WL, Chen C, Li CX, Xu JH. Computational redesign of taxane-10β-hydroxylase for de novo biosynthesis of a key paclitaxel intermediate. Appl Microbiol Biotechnol 2023; 107:7105-7117. [PMID: 37736790 DOI: 10.1007/s00253-023-12784-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/27/2023] [Accepted: 09/07/2023] [Indexed: 09/23/2023]
Abstract
Paclitaxel (Taxol®) is the most popular anticancer diterpenoid predominantly present in Taxus. The core skeleton of paclitaxel is highly modified, but researches on the cytochrome P450s involved in post-modification process remain exceedingly limited. Herein, the taxane-10β-hydroxylase (T10βH) from Taxus cuspidata, which is the third post-modification enzyme that catalyzes the conversion of taxadiene-5α-yl-acetate (T5OAc) to taxadiene-5α-yl-acetoxy-10β-ol (T10OH), was investigated in Escherichia coli by combining computation-assisted protein engineering and metabolic engineering. The variant of T10βH, M3 (I75F/L226K/S345V), exhibited a remarkable 9.5-fold increase in protein expression, accompanied by respective 1.3-fold and 2.1-fold improvements in turnover frequency (TOF) and total turnover number (TTN). Upon integration into the engineered strain, the variant M3 resulted in a substantial enhancement in T10OH production from 0.97 to 2.23 mg/L. Ultimately, the titer of T10OH reached 3.89 mg/L by fed-batch culture in a 5-L bioreactor, representing the highest level reported so far for the microbial de novo synthesis of this key paclitaxel intermediate. This study can serve as a valuable reference for further investigation of other P450s associated with the artificial biosynthesis of paclitaxel and other terpenoids. KEY POINTS: • The T10βH from T. cuspidata was expressed and engineered in E. coli unprecedentedly. • The expression and activity of T10βH were improved through protein engineering. • De novo biosynthesis of T10OH was achieved in E. coli with a titer of 3.89 mg/L.
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Affiliation(s)
- Mei-Fang Zhang
- State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing, East China University of Science and Technology, Shanghai, 200237, People's Republic of China
| | - Wen-Liang Xie
- State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing, East China University of Science and Technology, Shanghai, 200237, People's Republic of China
| | - Cheng Chen
- State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing, East China University of Science and Technology, Shanghai, 200237, People's Republic of China
| | - Chun-Xiu Li
- State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing, East China University of Science and Technology, Shanghai, 200237, People's Republic of China
| | - Jian-He Xu
- State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing, East China University of Science and Technology, Shanghai, 200237, People's Republic of China.
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10
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Xu SY, Zhou L, Xu Y, Hong HY, Dai C, Wang YJ, Zheng YG. Recent advances in structure-based enzyme engineering for functional reconstruction. Biotechnol Bioeng 2023; 120:3427-3445. [PMID: 37638646 DOI: 10.1002/bit.28540] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 07/27/2023] [Accepted: 08/15/2023] [Indexed: 08/29/2023]
Abstract
Structural information can help engineer enzymes. Usually, specific amino acids in particular regions are targeted for functional reconstruction to enhance the catalytic performance, including activity, stereoselectivity, and thermostability. Appropriate selection of target sites is the key to structure-based design, which requires elucidation of the structure-function relationships. Here, we summarize the mutations of residues in different specific regions, including active center, access tunnels, and flexible loops, on fine-tuning the catalytic performance of enzymes, and discuss the effects of altering the local structural environment on the functions. In addition, we keep up with the recent progress of structure-based approaches for enzyme engineering, aiming to provide some guidance on how to take advantage of the structural information.
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Affiliation(s)
- Shen-Yuan Xu
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
| | - Lei Zhou
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
| | - Ying Xu
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
| | - Han-Yue Hong
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
| | - Chen Dai
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
| | - Ya-Jun Wang
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
| | - Yu-Guo Zheng
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- Engineering Research Center of Bioconversion and Biopurification of the Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, People's Republic of China
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11
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Musil M, Jezik A, Horackova J, Borko S, Kabourek P, Damborsky J, Bednar D. FireProt 2.0: web-based platform for the fully automated design of thermostable proteins. Brief Bioinform 2023; 25:bbad425. [PMID: 38018911 PMCID: PMC10685400 DOI: 10.1093/bib/bbad425] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 10/25/2023] [Accepted: 11/01/2023] [Indexed: 11/30/2023] Open
Abstract
Thermostable proteins find their use in numerous biomedical and biotechnological applications. However, the computational design of stable proteins often results in single-point mutations with a limited effect on protein stability. However, the construction of stable multiple-point mutants can prove difficult due to the possibility of antagonistic effects between individual mutations. FireProt protocol enables the automated computational design of highly stable multiple-point mutants. FireProt 2.0 builds on top of the previously published FireProt web, retaining the original functionality and expanding it with several new stabilization strategies. FireProt 2.0 integrates the AlphaFold database and the homology modeling for structure prediction, enabling calculations starting from a sequence. Multiple-point designs are constructed using the Bron-Kerbosch algorithm minimizing the antagonistic effect between the individual mutations. Users can newly limit the FireProt calculation to a set of user-defined mutations, run a saturation mutagenesis of the whole protein or select rigidifying mutations based on B-factors. Evolution-based back-to-consensus strategy is complemented by ancestral sequence reconstruction. FireProt 2.0 is significantly faster and a reworked graphical user interface broadens the tool's availability even to users with older hardware. FireProt 2.0 is freely available at http://loschmidt.chemi.muni.cz/fireprotweb.
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Affiliation(s)
- Milos Musil
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic
- Department of Information Systems, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic
- International Clinical Research Centre, St. Anne’s University Hospital Brno, Brno, Czech Republic
| | - Andrej Jezik
- Department of Information Systems, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic
| | - Jana Horackova
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic
| | - Simeon Borko
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic
- Department of Information Systems, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic
- International Clinical Research Centre, St. Anne’s University Hospital Brno, Brno, Czech Republic
| | - Petr Kabourek
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic
- International Clinical Research Centre, St. Anne’s University Hospital Brno, Brno, Czech Republic
| | - Jiri Damborsky
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic
- International Clinical Research Centre, St. Anne’s University Hospital Brno, Brno, Czech Republic
| | - David Bednar
- Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic
- International Clinical Research Centre, St. Anne’s University Hospital Brno, Brno, Czech Republic
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12
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Kouba P, Kohout P, Haddadi F, Bushuiev A, Samusevich R, Sedlar J, Damborsky J, Pluskal T, Sivic J, Mazurenko S. Machine Learning-Guided Protein Engineering. ACS Catal 2023; 13:13863-13895. [PMID: 37942269 PMCID: PMC10629210 DOI: 10.1021/acscatal.3c02743] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/20/2023] [Indexed: 11/10/2023]
Abstract
Recent progress in engineering highly promising biocatalysts has increasingly involved machine learning methods. These methods leverage existing experimental and simulation data to aid in the discovery and annotation of promising enzymes, as well as in suggesting beneficial mutations for improving known targets. The field of machine learning for protein engineering is gathering steam, driven by recent success stories and notable progress in other areas. It already encompasses ambitious tasks such as understanding and predicting protein structure and function, catalytic efficiency, enantioselectivity, protein dynamics, stability, solubility, aggregation, and more. Nonetheless, the field is still evolving, with many challenges to overcome and questions to address. In this Perspective, we provide an overview of ongoing trends in this domain, highlight recent case studies, and examine the current limitations of machine learning-based methods. We emphasize the crucial importance of thorough experimental validation of emerging models before their use for rational protein design. We present our opinions on the fundamental problems and outline the potential directions for future research.
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Affiliation(s)
- Petr Kouba
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech
Republic
- Czech Institute
of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Jugoslavskych partyzanu 1580/3, 160 00 Prague 6, Czech Republic
- Faculty of
Electrical Engineering, Czech Technical
University in Prague, Technicka 2, 166 27 Prague 6, Czech Republic
| | - Pavel Kohout
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech
Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, 656 91 Brno, Czech Republic
| | - Faraneh Haddadi
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech
Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, 656 91 Brno, Czech Republic
| | - Anton Bushuiev
- Czech Institute
of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Jugoslavskych partyzanu 1580/3, 160 00 Prague 6, Czech Republic
| | - Raman Samusevich
- Czech Institute
of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Jugoslavskych partyzanu 1580/3, 160 00 Prague 6, Czech Republic
- Institute
of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo nám. 2, 160 00 Prague 6, Czech Republic
| | - Jiri Sedlar
- Czech Institute
of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Jugoslavskych partyzanu 1580/3, 160 00 Prague 6, Czech Republic
| | - Jiri Damborsky
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech
Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, 656 91 Brno, Czech Republic
| | - Tomas Pluskal
- Institute
of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo nám. 2, 160 00 Prague 6, Czech Republic
| | - Josef Sivic
- Czech Institute
of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Jugoslavskych partyzanu 1580/3, 160 00 Prague 6, Czech Republic
| | - Stanislav Mazurenko
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, 625 00 Brno, Czech
Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, 656 91 Brno, Czech Republic
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13
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Kunka A, Marques SM, Havlasek M, Vasina M, Velatova N, Cengelova L, Kovar D, Damborsky J, Marek M, Bednar D, Prokop Z. Advancing Enzyme's Stability and Catalytic Efficiency through Synergy of Force-Field Calculations, Evolutionary Analysis, and Machine Learning. ACS Catal 2023; 13:12506-12518. [PMID: 37822856 PMCID: PMC10563018 DOI: 10.1021/acscatal.3c02575] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 08/24/2023] [Indexed: 10/13/2023]
Abstract
Thermostability is an essential requirement for the use of enzymes in the bioindustry. Here, we compare different protein stabilization strategies using a challenging target, a stable haloalkane dehalogenase DhaA115. We observe better performance of automated stabilization platforms FireProt and PROSS in designing multiple-point mutations over the introduction of disulfide bonds and strengthening the intra- and the inter-domain contacts by in silico saturation mutagenesis. We reveal that the performance of automated stabilization platforms was still compromised due to the introduction of some destabilizing mutations. Notably, we show that their prediction accuracy can be improved by applying manual curation or machine learning for the removal of potentially destabilizing mutations, yielding highly stable haloalkane dehalogenases with enhanced catalytic properties. A comparison of crystallographic structures revealed that current stabilization rounds were not accompanied by large backbone re-arrangements previously observed during the engineering stability of DhaA115. Stabilization was achieved by improving local contacts including protein-water interactions. Our study provides guidance for further improvement of automated structure-based computational tools for protein stabilization.
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Affiliation(s)
- Antonin Kunka
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Brno 601 77, Czech Republic
- International
Clinical Research Center, St. Anne’s University Hospital, Brno 601 77, Czech Republic
| | - Sérgio M. Marques
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Brno 601 77, Czech Republic
- International
Clinical Research Center, St. Anne’s University Hospital, Brno 601 77, Czech Republic
| | - Martin Havlasek
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Brno 601 77, Czech Republic
| | - Michal Vasina
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Brno 601 77, Czech Republic
- International
Clinical Research Center, St. Anne’s University Hospital, Brno 601 77, Czech Republic
| | - Nikola Velatova
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Brno 601 77, Czech Republic
| | - Lucia Cengelova
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Brno 601 77, Czech Republic
| | - David Kovar
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Brno 601 77, Czech Republic
- International
Clinical Research Center, St. Anne’s University Hospital, Brno 601 77, Czech Republic
| | - Jiri Damborsky
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Brno 601 77, Czech Republic
- International
Clinical Research Center, St. Anne’s University Hospital, Brno 601 77, Czech Republic
| | - Martin Marek
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Brno 601 77, Czech Republic
- International
Clinical Research Center, St. Anne’s University Hospital, Brno 601 77, Czech Republic
| | - David Bednar
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Brno 601 77, Czech Republic
- International
Clinical Research Center, St. Anne’s University Hospital, Brno 601 77, Czech Republic
| | - Zbynek Prokop
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Brno 601 77, Czech Republic
- International
Clinical Research Center, St. Anne’s University Hospital, Brno 601 77, Czech Republic
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14
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Weinstein JY, Martí-Gómez C, Lipsh-Sokolik R, Hoch SY, Liebermann D, Nevo R, Weissman H, Petrovich-Kopitman E, Margulies D, Ivankov D, McCandlish DM, Fleishman SJ. Designed active-site library reveals thousands of functional GFP variants. Nat Commun 2023; 14:2890. [PMID: 37210560 DOI: 10.1038/s41467-023-38099-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 04/13/2023] [Indexed: 05/22/2023] Open
Abstract
Mutations in a protein active site can lead to dramatic and useful changes in protein activity. The active site, however, is sensitive to mutations due to a high density of molecular interactions, substantially reducing the likelihood of obtaining functional multipoint mutants. We introduce an atomistic and machine-learning-based approach, called high-throughput Functional Libraries (htFuncLib), that designs a sequence space in which mutations form low-energy combinations that mitigate the risk of incompatible interactions. We apply htFuncLib to the GFP chromophore-binding pocket, and, using fluorescence readout, recover >16,000 unique designs encoding as many as eight active-site mutations. Many designs exhibit substantial and useful diversity in functional thermostability (up to 96 °C), fluorescence lifetime, and quantum yield. By eliminating incompatible active-site mutations, htFuncLib generates a large diversity of functional sequences. We envision that htFuncLib will be used in one-shot optimization of activity in enzymes, binders, and other proteins.
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Affiliation(s)
| | - Carlos Martí-Gómez
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | - Rosalie Lipsh-Sokolik
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Shlomo Yakir Hoch
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Demian Liebermann
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Reinat Nevo
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Haim Weissman
- Department of Molecular Chemistry and Materials Science, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | | | - David Margulies
- Department of Chemical and Structural Biology, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Dmitry Ivankov
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - David M McCandlish
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel.
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15
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Engelberger F, Zakary JD, Künze G. Guiding protein design choices by per-residue energy breakdown analysis with an interactive web application. Front Mol Biosci 2023; 10:1178035. [PMID: 37228581 PMCID: PMC10204868 DOI: 10.3389/fmolb.2023.1178035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 04/26/2023] [Indexed: 05/27/2023] Open
Abstract
Recent developments in machine learning have greatly facilitated the design of proteins with improved properties. However, accurately assessing the contributions of an individual or multiple amino acid mutations to overall protein stability to select the most promising mutants remains a challenge. Knowing the specific types of amino acid interactions that improve energetic stability is crucial for finding favorable combinations of mutations and deciding which mutants to test experimentally. In this work, we present an interactive workflow for assessing the energetic contributions of single and multi-mutant designs of proteins. The energy breakdown guided protein design (ENDURE) workflow includes several key algorithms, including per-residue energy analysis and the sum of interaction energies calculations, which are performed using the Rosetta energy function, as well as a residue depth analysis, which enables tracking the energetic contributions of mutations occurring in different spatial layers of the protein structure. ENDURE is available as a web application that integrates easy-to-read summary reports and interactive visualizations of the automated energy calculations and helps users selecting protein mutants for further experimental characterization. We demonstrate the effectiveness of the tool in identifying the mutations in a designed polyethylene terephthalate (PET)-degrading enzyme that add up to an improved thermodynamic stability. We expect that ENDURE can be a valuable resource for researchers and practitioners working in the field of protein design and optimization. ENDURE is freely available for academic use at: http://endure.kuenzelab.org.
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16
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Zelnik ID, Mestre B, Weinstein JJ, Dingjan T, Izrailov S, Ben-Dor S, Fleishman SJ, Futerman AH. Computational design and molecular dynamics simulations suggest the mode of substrate binding in ceramide synthases. Nat Commun 2023; 14:2330. [PMID: 37087500 PMCID: PMC10122649 DOI: 10.1038/s41467-023-38047-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 04/13/2023] [Indexed: 04/24/2023] Open
Abstract
Until now, membrane-protein stabilization has relied on iterations of mutations and screening. We now validate a one-step algorithm, mPROSS, for stabilizing membrane proteins directly from an AlphaFold2 model structure. Applied to the lipid-generating enzyme, ceramide synthase, 37 designed mutations lead to a more stable form of human CerS2. Together with molecular dynamics simulations, we propose a pathway by which substrates might be delivered to the ceramide synthases.
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Affiliation(s)
- Iris D Zelnik
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Beatriz Mestre
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Jonathan J Weinstein
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Tamir Dingjan
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Stav Izrailov
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Shifra Ben-Dor
- Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Anthony H Futerman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel.
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17
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Rosace A, Bennett A, Oeller M, Mortensen MM, Sakhnini L, Lorenzen N, Poulsen C, Sormanni P. Automated optimisation of solubility and conformational stability of antibodies and proteins. Nat Commun 2023; 14:1937. [PMID: 37024501 PMCID: PMC10079162 DOI: 10.1038/s41467-023-37668-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Accepted: 03/24/2023] [Indexed: 04/08/2023] Open
Abstract
Biologics, such as antibodies and enzymes, are crucial in research, biotechnology, diagnostics, and therapeutics. Often, biologics with suitable functionality are discovered, but their development is impeded by developability issues. Stability and solubility are key biophysical traits underpinning developability potential, as they determine aggregation, correlate with production yield and poly-specificity, and are essential to access parenteral and oral delivery. While advances for the optimisation of individual traits have been made, the co-optimization of multiple traits remains highly problematic and time-consuming, as mutations that improve one property often negatively impact others. In this work, we introduce a fully automated computational strategy for the simultaneous optimisation of conformational stability and solubility, which we experimentally validate on six antibodies, including two approved therapeutics. Our results on 42 designs demonstrate that the computational procedure is highly effective at improving developability potential, while not affecting antigen-binding. We make the method available as a webserver at www-cohsoftware.ch.cam.ac.uk.
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Affiliation(s)
- Angelo Rosace
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
- Master in Bioinformatics for Health Sciences, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
- Institute for Research in Biomedicine (IRB), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - Anja Bennett
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
- Department of Mammalian Expression, Global Research Technologies, Novo Nordisk A/S, Novo Nordisk Park 1, 2760, Måløv, Denmark
- BRIC, Faculty of Health and Medical Sciences, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Marc Oeller
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
| | - Mie M Mortensen
- Department of Purification Technologies, Global Research Technologies, Novo Nordisk A/S, Novo Nordisk Park 1, 2760, Måløv, Denmark
- Faculty of Engineering and Science, Department of Biotechnology, Chemistry and Environmental Engineering, University of Aalborg, Fredrik Bajers Vej 7H, 9220, Aalborg, Denmark
| | - Laila Sakhnini
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
- Department of Biophysics and Injectable Formulation 2, Global Research Technologies, Novo Nordisk A/S, Måløv, 2760, Denmark
| | - Nikolai Lorenzen
- Department of Biophysics and Injectable Formulation 2, Global Research Technologies, Novo Nordisk A/S, Måløv, 2760, Denmark
| | - Christian Poulsen
- Department of Mammalian Expression, Global Research Technologies, Novo Nordisk A/S, Novo Nordisk Park 1, 2760, Måløv, Denmark
| | - Pietro Sormanni
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK.
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18
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Malbranke C, Bikard D, Cocco S, Monasson R, Tubiana J. Machine learning for evolutionary-based and physics-inspired protein design: Current and future synergies. Curr Opin Struct Biol 2023; 80:102571. [PMID: 36947951 DOI: 10.1016/j.sbi.2023.102571] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 01/29/2023] [Accepted: 02/07/2023] [Indexed: 03/24/2023]
Abstract
Computational protein design facilitates the discovery of novel proteins with prescribed structure and functionality. Exciting designs were recently reported using novel data-driven methodologies that can be roughly divided into two categories: evolutionary-based and physics-inspired approaches. The former infer characteristic sequence features shared by sets of evolutionary-related proteins, such as conserved or coevolving positions, and recombine them to generate candidates with similar structure and function. The latter approaches estimate key biochemical properties, such as structure free energy, conformational entropy, or binding affinities using machine learning surrogates, and optimize them to yield improved designs. Here, we review recent progress along both tracks, discuss their strengths and weaknesses, and highlight opportunities for synergistic approaches.
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Affiliation(s)
- Cyril Malbranke
- Laboratory of Physics of the Ecole Normale Supérieure, PSL Research, CNRS UMR 8023, Sorbonne Université, Université de Paris, Paris, France; Institut Pasteur, Université Paris Cité, CNRS UMR 6047, Synthetic Biology, 75015 Paris, France.
| | - David Bikard
- Institut Pasteur, Université Paris Cité, CNRS UMR 6047, Synthetic Biology, 75015 Paris, France
| | - Simona Cocco
- Laboratory of Physics of the Ecole Normale Supérieure, PSL Research, CNRS UMR 8023, Sorbonne Université, Université de Paris, Paris, France
| | - Rémi Monasson
- Laboratory of Physics of the Ecole Normale Supérieure, PSL Research, CNRS UMR 8023, Sorbonne Université, Université de Paris, Paris, France
| | - Jérôme Tubiana
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
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19
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Shanbhag AP. Stairway to Stereoisomers: Engineering Short- and Medium-Chain Ketoreductases To Produce Chiral Alcohols. Chembiochem 2023; 24:e202200687. [PMID: 36640298 DOI: 10.1002/cbic.202200687] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 01/14/2023] [Accepted: 01/14/2023] [Indexed: 01/15/2023]
Abstract
The short- and medium-chain dehydrogenase/reductase superfamilies are responsible for most chiral alcohol production in laboratories and industries. In nature, they participate in diverse roles such as detoxification, housekeeping, secondary metabolite production, and catalysis of several chemicals with commercial and environmental significance. As a result, they are used in industries to create biopolymers, active pharmaceutical intermediates (APIs), and are also used as components of modular enzymes like polyketide synthases for fabricating bioactive molecules. Consequently, random, semi-rational and rational engineering have helped transform these enzymes into product-oriented efficient catalysts. The rise of newer synthetic chemicals and their enantiopure counterparts has proved challenging, and engineering them has been the subject of numerous studies. However, they are frequently limited to the synthesis of a single chiral alcohol. The study attempts to defragment and describe hotspots of engineering short- and medium-chain dehydrogenases/reductases for the production of chiral synthons.
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Affiliation(s)
- Anirudh P Shanbhag
- Department of Biophysics, Molecular Biology and Bioinformatics, University of Calcutta, Kolkata, 700009, India.,Bugworks Research India Pvt. Ltd., C-CAMP, National Centre for Biological Sciences (NCBS-TIFR), Bellary Road, Bangalore, 560003, India
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20
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Aung T, Grubbe WS, Nusbaum RJ, Mendoza JL. Recent and future perspectives on engineering interferons and other cytokines as therapeutics. Trends Biochem Sci 2023; 48:259-273. [PMID: 36241490 PMCID: PMC9974544 DOI: 10.1016/j.tibs.2022.09.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 09/13/2022] [Accepted: 09/14/2022] [Indexed: 11/12/2022]
Abstract
As crucial mediators and regulators of our immune system, cytokines are involved in a broad range of biological processes and are implicated in various disease pathologies. The field of cytokine therapeutics has gained much momentum from the maturation of conventional protein engineering methodologies such as structure-based designs and/or directed evolution, which is further aided by the advent of in silico protein designs and characterization. Just within the past 5 years, there has been an explosion of proof-of-concept, preclinical, and clinical studies that utilize an armory of protein engineering methods to develop cytokine-based drugs. Here, we highlight the key engineering strategies undertaken by recent studies that aim to improve the pharmacodynamic and pharmacokinetic profile of interferons and other cytokines as therapeutics.
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Affiliation(s)
- Theint Aung
- Department of Chemistry, The University of Chicago, Chicago, IL 60637, USA
| | - William S Grubbe
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL 60637, USA
| | - Rebecca J Nusbaum
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL 60637, USA
| | - Juan L Mendoza
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL 60637, USA; Department of Biochemistry and Molecular Biophysics, The University of Chicago, Chicago, IL 60637, USA.
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21
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Dolan JP, Cosgrove SC, Miller GJ. Biocatalytic Approaches to Building Blocks for Enzymatic and Chemical Glycan Synthesis. JACS AU 2023; 3:47-61. [PMID: 36711082 PMCID: PMC9875253 DOI: 10.1021/jacsau.2c00529] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 11/16/2022] [Accepted: 11/17/2022] [Indexed: 06/17/2023]
Abstract
While the field of biocatalysis has bloomed over the past 20-30 years, advances in the understanding and improvement of carbohydrate-active enzymes, in particular, the sugar nucleotides involved in glycan building block biosynthesis, have progressed relatively more slowly. This perspective highlights the need for further insight into substrate promiscuity and the use of biocatalysis fundamentals (rational design, directed evolution, immobilization) to expand substrate scopes toward such carbohydrate building block syntheses and/or to improve enzyme stability, kinetics, or turnover. Further, it explores the growing premise of using biocatalysis to provide simple, cost-effective access to stereochemically defined carbohydrate materials, which can undergo late-stage chemical functionalization or automated glycan synthesis/polymerization.
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22
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Barber-Zucker S, Mateljak I, Goldsmith M, Kupervaser M, Alcalde M, Fleishman SJ. Designed High-Redox Potential Laccases Exhibit High Functional Diversity. ACS Catal 2022; 12:13164-13173. [PMID: 36366766 PMCID: PMC9638991 DOI: 10.1021/acscatal.2c03006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 09/29/2022] [Indexed: 11/29/2022]
Abstract
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White-rot fungi secrete an impressive repertoire of high-redox
potential laccases (HRPLs) and peroxidases for efficient oxidation
and utilization of lignin. Laccases are attractive enzymes for the
chemical industry due to their broad substrate range and low environmental
impact. Since expression of functional recombinant HRPLs is challenging,
however, iterative-directed evolution protocols have been applied
to improve their expression, activity, and stability. We implement
a rational, stabilize-and-diversify strategy to two HRPLs that we
could not functionally express. First, we use the PROSS stability-design
algorithm to allow functional expression in yeast. Second, we use
the stabilized enzymes as starting points for FuncLib active-site
design to improve their activity and substrate diversity. Four of
the FuncLib-designed HRPLs and their PROSS progenitor exhibit substantial
diversity in reactivity profiles against high-redox potential substrates,
including lignin monomers. Combinations of 3–4 subtle mutations
that change the polarity, solvation, and sterics of the substrate-oxidation
site result in orders of magnitude changes in reactivity profiles.
These stable and versatile HRPLs are a step toward generating an effective
lignin-degrading consortium of enzymes that can be secreted from yeast.
The stabilize-and-diversify strategy can be applied to other challenging
enzyme families to study and expand the utility of natural enzymes.
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Affiliation(s)
- Shiran Barber-Zucker
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7600001, Israel
| | - Ivan Mateljak
- Department of Biocatalysis, Institute of Catalysis, CSIC, Cantoblanco, Madrid 28049, Spain
- EvoEnzyme S.L., Parque Científico de Madrid, C/Faraday, 7, Campus de Cantoblanco, Madrid 28049, Spain
| | - Moshe Goldsmith
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7600001, Israel
| | - Meital Kupervaser
- Nancy and Stephen Grand Israel National Center for Personalized Medicine, Weizmann Institute of Science, Rehovot 7600001, Israel
| | - Miguel Alcalde
- Department of Biocatalysis, Institute of Catalysis, CSIC, Cantoblanco, Madrid 28049, Spain
| | - Sarel J. Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7600001, Israel
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23
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Thieker DF, Maguire JB, Kudlacek ST, Leaver‐Fay A, Lyskov S, Kuhlman B. Stabilizing proteins, simplified: A Rosetta-based webtool for predicting favorable mutations. Protein Sci 2022; 31:e4428. [PMID: 36173174 PMCID: PMC9490798 DOI: 10.1002/pro.4428] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Revised: 08/06/2022] [Accepted: 08/21/2022] [Indexed: 11/07/2022]
Abstract
Many proteins have low thermodynamic stability, which can lead to low expression yields and limit functionality in research, industrial and clinical settings. This article introduces two, web-based tools that use the high-resolution structure of a protein along with the Rosetta molecular modeling program to predict stabilizing mutations. The protocols were recently applied to three genetically and structurally distinct proteins and successfully predicted mutations that improved thermal stability and/or protein yield. In all three cases, combining the stabilizing mutations raised the protein unfolding temperatures by more than 20°C. The first protocol evaluates point mutations and can generate a site saturation mutagenesis heatmap. The second identifies mutation clusters around user-defined positions. Both applications only require a protein structure and are particularly valuable when a deep multiple sequence alignment is not available. These tools were created to simplify protein engineering and enable research that would otherwise be infeasible due to poor expression and stability of the native molecule.
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Affiliation(s)
- David F. Thieker
- Department of Biochemistry and BiophysicsUniversity of North Carolina School of MedicineChapel HillNorth CarolinaUSA
| | - Jack B. Maguire
- Department of Biochemistry and BiophysicsUniversity of North Carolina School of MedicineChapel HillNorth CarolinaUSA
| | - Stephan T. Kudlacek
- Department of Biochemistry and BiophysicsUniversity of North Carolina School of MedicineChapel HillNorth CarolinaUSA
| | - Andrew Leaver‐Fay
- Department of Biochemistry and BiophysicsUniversity of North Carolina School of MedicineChapel HillNorth CarolinaUSA
| | - Sergey Lyskov
- Department of Chemical and Biomolecular EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Brian Kuhlman
- Department of Biochemistry and BiophysicsUniversity of North Carolina School of MedicineChapel HillNorth CarolinaUSA
- Lineburger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
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24
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Glycine Substitution of Residues with Unfavored Dihedral Angles Improves Protein Thermostability. Catalysts 2022. [DOI: 10.3390/catal12080898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Single mutations that can substantially enhance stability are highly desirable for protein engineering. However, it is generally rare for this kind of mutant to emerge from directed evolution experiments. This study used computational approaches to identify hotspots in a diacylglycerol-specific lipase for mutagenesis with functional hotspot and sequence consensus strategies, followed by ∆∆G calculations for all possible mutations using the Rosetta ddg_monomer protocol. Single mutants with significant ∆∆G changes (≤−2.5 kcal/mol) were selected for expression and characterization. Three out of seven tested mutants showed a significantly enhanced thermostability, with Q282W and A292G in the catalytic pocket and D245G located on the opposite surface of the protein. Remarkably, A292G increased the T5015 (the temperature at which 50% of the enzyme activity was lost after a 15 min of incubation) by ~7 °C, concomitant with a twofold increase in enzymatic activity at the optimal reaction temperature. Structural analysis showed that both A292 and D245 adopted unfavored dihedral angles in the wild-type (WT) enzyme. Substitution of them by glycine might release a steric strain to increase the stability. In sum, substitution by glycine might be a promising strategy to improve protein thermostability.
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25
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Precision materials: Computational design methods of accurate protein materials. Curr Opin Struct Biol 2022; 74:102367. [DOI: 10.1016/j.sbi.2022.102367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Revised: 02/22/2022] [Accepted: 02/28/2022] [Indexed: 11/23/2022]
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26
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Barber-Zucker S, Mindel V, Garcia-Ruiz E, Weinstein JJ, Alcalde M, Fleishman SJ. Stable and Functionally Diverse Versatile Peroxidases Designed Directly from Sequences. J Am Chem Soc 2022; 144:3564-3571. [PMID: 35179866 PMCID: PMC8895400 DOI: 10.1021/jacs.1c12433] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
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White-rot fungi secrete a repertoire
of high-redox potential oxidoreductases
to efficiently decompose lignin. Of these enzymes, versatile peroxidases
(VPs) are the most promiscuous biocatalysts. VPs are attractive enzymes
for research and industrial use but their recombinant production is
extremely challenging. To date, only a single VP has been structurally
characterized and optimized for recombinant functional expression,
stability, and activity. Computational enzyme optimization methods
can be applied to many enzymes in parallel but they require accurate
structures. Here, we demonstrate that model structures computed by
deep-learning-based ab initio structure prediction
methods are reliable starting points for one-shot PROSS stability-design
calculations. Four designed VPs encoding as many as 43 mutations relative
to the wildtype enzymes are functionally expressed in yeast, whereas
their wildtype parents are not. Three of these designs exhibit substantial
and useful diversity in their reactivity profiles and tolerance to
environmental conditions. The reliability of the new generation of
structure predictors and design methods increases the scale and scope
of computational enzyme optimization, enabling efficient discovery
and exploitation of the functional diversity in natural enzyme families
directly from genomic databases.
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Affiliation(s)
- Shiran Barber-Zucker
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7600001, Israel
| | - Vladimir Mindel
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7600001, Israel
| | - Eva Garcia-Ruiz
- Department of Biocatalysis, Institute of Catalysis, CSIC, Cantoblanco, Madrid 28094, Spain
| | - Jonathan J Weinstein
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7600001, Israel
| | - Miguel Alcalde
- Department of Biocatalysis, Institute of Catalysis, CSIC, Cantoblanco, Madrid 28094, Spain
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7600001, Israel
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27
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Orlando M, Fortuna S, Oloketuyi S, Bajc G, Goldenzweig A, de Marco A. CDR1 Composition Can Affect Nanobody Recombinant Expression Yields. Biomolecules 2021; 11:biom11091362. [PMID: 34572576 PMCID: PMC8465892 DOI: 10.3390/biom11091362] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 09/10/2021] [Accepted: 09/13/2021] [Indexed: 01/03/2023] Open
Abstract
The isolation of nanobodies from pre-immune libraries by means of biopanning is a straightforward process. Nevertheless, the recovered candidates often require optimization to improve some of their biophysical characteristics. In principle, CDRs are not mutated because they are likely to be part of the antibody paratope, but in this work, we describe a mutagenesis strategy that specifically addresses CDR1. Its sequence was identified as an instability hot spot by the PROSS program, and the available structural information indicated that four CDR1 residues bound directly to the antigen. We therefore modified the loop flexibility with the addition of an extra glycine rather than by mutating single amino acids. This approach significantly increased the nanobody yields but traded-off with moderate affinity loss. Accurate modeling coupled with atomistic molecular dynamics simulations enabled the modifications induced by the glycine insertion and the rationale behind the engineering design to be described in detail.
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Affiliation(s)
- Marco Orlando
- Department of Biotechnology and Life Sciences, University of Insubria, Via J. H. Dunant 3, 21100 Varese, Italy;
| | - Sara Fortuna
- Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via L. Giorgieri 1, 34127 Trieste, Italy;
| | - Sandra Oloketuyi
- Lab of Environmental and Life Sciences, University of Nova Gorica, Vipavska cesta 13, Rožna Dolina, 5000 Nova Gorica, Slovenia;
| | - Gregor Bajc
- Department of Biology, Biotechnical Faculty, University of Ljubljana, Večna pot 111, 1000 Ljubljana, Slovenia;
| | - Adi Goldenzweig
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel;
| | - Ario de Marco
- Lab of Environmental and Life Sciences, University of Nova Gorica, Vipavska cesta 13, Rožna Dolina, 5000 Nova Gorica, Slovenia;
- Correspondence: ; Tel.: +386-(05)-3315295
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28
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Heath RS, Ruscoe RE, Turner NJ. The beauty of biocatalysis: sustainable synthesis of ingredients in cosmetics. Nat Prod Rep 2021; 39:335-388. [PMID: 34879125 DOI: 10.1039/d1np00027f] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Covering: 2015 up to July 2021The market for cosmetics is consumer driven and the desire for green, sustainable and natural ingredients is increasing. The use of isolated enzymes and whole-cell organisms to synthesise these products is congruent with these values, especially when combined with the use of renewable, recyclable or waste feedstocks. The literature of biocatalysis for the synthesis of ingredients in cosmetics in the past five years is herein reviewed.
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Affiliation(s)
- Rachel S Heath
- Manchester Institute of Biotechnology, Department of Chemistry, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
| | - Rebecca E Ruscoe
- Manchester Institute of Biotechnology, Department of Chemistry, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
| | - Nicholas J Turner
- Manchester Institute of Biotechnology, Department of Chemistry, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
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