Protein Engineering Handbook E-Book
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- Herausgeber: Wiley-VCH
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Unparalleled in size and scope, this new major reference integrates academic and industrial knowledge into a single resource, allowing for a unique overview of the entire field. Adopting a systematic and practice-oriented approach, and including a wide range of technical and methodological information, this highly accessible handbook is an invaluable 'toolbox' for any bioengineer. In two massive volumes, it covers the full spectrum of current concepts, methods and application areas.
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Seitenzahl: 1921
Veröffentlichungsjahr: 2012
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Contents
Cover
Title page
Copyright page
Preface
List of Contributors
Chapter 1: Guidelines for the Functional Analysis of Engineered and Mutant Enzymes
1.1 Introduction
1.2 Steady-State Kinetics
1.3 Enzyme Assays and the Acquisition of Initial Velocity Data
1.4 Steady-State Kinetic Parameters and Their Interpretation
1.5 Concluding Remarks
References
Chapter 2: Engineering Enantioselectivity in Enzyme-Catalyzed Reactions
2.1 Introduction
2.2 Molecular Basis for Enantioselectivity
2.3 Qualitative Predictions of Enantioselectivity
2.4 Protein Engineering to Increase or Reverse Enantioselectivity
2.5 Concluding Remarks
References
Chapter 3: Mechanism and Catalytic Promiscuity: Emerging Mechanistic Principles for Identification and Manipulation of Catalytically Promiscuous Enzymes
3.1 Introduction
3.2 Calculation of Rate Accelerations
3.3 Catalytic Features and Their Propensity for Promiscuity
3.4 Steric Effects and Structural Constriction in the Active Site: Product Promiscuity
3.5 Medium Effects in Enzyme Active Sites
3.6 Conclusions
References
Chapter 4: Φ-Value Analysis of Protein Folding Transition States
4.1 Introduction
4.2 Theoretical Principles of Protein Engineering
4.3 Guidelines for the Determination of Accurate Φ-Values
4.4 Conclusions
Acknowledgments
References
Chapter 5: Protein Folding and Solubility: Pathways and High-Throughput Assays
5.1 Introduction
5.2 Biosynthesis of Natural Proteins in Bacteria
5.3 Biosynthesis of de novo-Designed Proteins in Bacteria
5.4 Combinatorial Strategies for Assaying Protein Folding in Bacteria
5.5 Structural Genomics
5.6 Protein-Misfolding Diseases
5.7 Future Directions
References
Chapter 6: Protein Dynamics and the Evolution of Novel Protein Function
6.1 Introduction
6.2 Physical Background
6.3 Experimental Studies of Protein Dynamics
6.4 Experimental Techniques
6.5 Case Study: Protein Dynamics and the Evolution of Molecular Recognition within the Immune System
6.6 Implications for Protein Engineering
References
Chapter 7: Gaining Insight into Enzyme Function through Correlation with Protein Motions
7.1 Introduction
7.2 Experimental Investigation of Enzyme Dynamics during Catalysis
7.3 Future Challenges
Acknowledgments
References
Chapter 8: Structural Frameworks Suitable for Engineering
8.1 Introduction
8.2 Choice of Protein Scaffold in Engineering: General Considerations
8.3 Examples of Engineered Structural Frameworks in Natural Evolution
8.4 Summary
References
Chapter 9: Microbes and Enzymes: Recent Trends and New Directions to Expand Protein Space
9.1 Introduction
9.2 Protein Complexity of Microbial Communities through Metagenomics
9.3 Important Methodological Developments in Metagenomics
9.4 Metagenomic Analysis of Whole-Metagenome Sequences: Shotgun Sequencing and Pyrosequencing
9.5 Bottlenecks in the Discovery of ‘Natural’ Proteins
9.6 Conclusions to Metagenomics for Gene Discovery: The Limits of ‘Natural’ Protein Diversity
9.7 Directed Molecular Evolution for Creating ‘Artificial’ Protein Diversity
9.8 Generation of Diversity in vitro
9.9 Semi-Rational Approaches: Saturation Mutagenesis
9.10 The Development of Efficient Screening Methods
9.11 Metagenomic DNA Shuffling: Increasing Protein Complexity by Combining ‘Natural’ and ‘Artificial’ Diversity
Acknowledgments
References
Chapter 10: Inteins in Protein Engineering
10.1 Introduction
10.2 Expressed Protein Ligation
10.3 Protein trans-Splicing
10.4 Cyclization of Proteins
10.5 Protein cis-Splicing and Cleaving
10.6 Potential Future Uses in Protein Engineering
References
Chapter 11: From Prospecting to Product–Industrial Metagenomics Is Coming of Age
11.1 Prospecting for Novel Templates
11.2 Sample Generation: Access to the Metagenome
11.3 Sequence-Based Screening
11.4 Activity-Based Screening
11.5 Metagenomics–the Industrial Perspective
References
Chapter 12: Computational Protein Design
12.1 Introduction
12.2 Methods of Computational Protein Design
12.3 Computationally Designed Proteins
12.4 Outlook
Acknowledgments
References
Chapter 13: Assessing and Exploiting the Persistence of Substrate Ambiguity in Modern Protein Catalysts
13.1 Quantitative Description of Enzyme Specificity
13.2 Models of Enzyme Specificity
13.3 Advantages and Disadvantages of Specificity
13.4 Substrate Ambiguity as a Mechanism for Elaborated Metabolic Potential
13.5 Experimental Approaches to Detect Ambiguity
13.6 General Comments on Overexpression Libraries and Genetic Selections
13.7 Challenges and Prospects for the Future
References
Chapter 14: Designing Programmable Protein Switches
14.1 Introduction
14.2 Engineering Allostery
14.3 A Fundamental Experimental Challenge
14.4 A Different Approach: Creation of Internal Sequence Repeats
14.5 Engineering a Conundrum
14.6 Advantages of Sequence Duplications, and Possible Future Applications
Acknowledgments
References
Chapter 15: The Cyclization of Peptides and Proteins with Inteins
15.1 Introduction
15.2 Protein Cyclization
15.3 Cyclization of Peptides
15.4 Conclusions
References
Chapter 16: A Method for Rapid Directed Evolution
16.1 Introduction
16.2 Focused Libraries Generated by Saturation Mutagenesis
16.3 Iterative Saturation Mutagenesis
16.4 Conclusions
References
Chapter 17: Evolution of Enantioselective Bacillus subtilis Lipase
17.1 Introduction
17.2 Directed Evolution of Enantioselective Lipase from Bacillus subtilis
17.3 Directed Evolution by Error-Prone PCR
17.4 Complete Site-Saturation Mutagenesis
17.5 Conclusions
References
Chapter 18: Circular Permutation of Proteins
18.1 Introduction
18.2 Evolution of Circular Permutations in Nature
18.3 Artificial Circular Permutations
18.4 Circular Permutation and Protein Engineering
18.5 Perspective
Acknowledgments
References
Chapter 19: Incorporating Synthetic Oligonucleotides via Gene Reassembly (ISOR): A Versatile Tool for Generating Targeted Libraries
19.1 Introduction
19.2 Materials
19.3 Methods
19.4 Notes
Acknowledgments
References
Chapter 20: Protein Engineering by Structure-Guided SCHEMA Recombination
20.1 Introduction
20.2 Examples of Chimeric Libraries Designed Using the SCHEMA Algorithm
20.3 Conclusions
References
Chapter 21: Chimeragenesis in Protein Engineering
21.1 Introduction
21.2 Experimental Aspects of the SCRATCHY Protocol
21.3 Future Trends in Chimeragenesis
21.4 Conclusions
Acknowledgments
References
Chapter 22: Protein Generation Using a Reconstituted System
22.1 Introduction
22.2 The PURE System
22.3 Current Applications
22.4 Prospective Research
22.5 Concluding Remarks
References
Chapter 23: Equipping in vivo Selection Systems with Tunable Stringency
23.1 Genetic Selection in Directed Evolution Experiments
23.2 Inducible Promoters for Controlling Selection Stringency
23.3 Controlling Catalyst Concentration
23.4 Controlling Substrate Concentrations
23.5 Perspectives
References
Chapter 24: Protein Engineering by Phage Display
24.1 Introduction
24.2 The State of the Art
24.3 Practical Considerations
24.4 Conclusions and Future Challenges
References
Chapter 25: Screening Methodologies for Glycosidic Bond Formation
25.1 Introduction
25.2 Glycosynthases
25.3 Glycosyltransferases
25.4 Protocol and Practical Considerations for Using HTS Methodology in the Directed Evolution of STs
25.5 Challenges and Prospects of GT Engineering
References
Chapter 26: Yeast Surface Display in Protein Engineering and Analysis
26.1 Review
26.2 Protocols and Practical Considerations
26.3 The Future of Yeast Surface Display
Abbreviations
Acknowledgments
References
Chapter 27: In Vitro Compartmentalization (IVC) and Other High-Throughput Screens of Enzyme Libraries
27.1 Introduction
27.2 The Fundamentals of High-Throughput Screens and Selections
27.3 Enzyme Selections by Phage-Display
27.4 HTS of Enzymes Using Cell-Display and FACS
27.5 Other FACS-Based Enzyme Screens
27.6 In vivo Genetic Screens and Selections
27.7 In vitro Compartmentalization (IVC)
27.8 IVC in Double Emulsions
27.9 What’s Next?
27.10 Experimental Details
Acknowledgments
References
Chapter 28: Colorimetric and Fluorescence-Based Screening
28.1 Introduction
28.2 Enzyme-Coupled Assays
28.3 Fluorogenic and Chromogenic Substrates
28.4 Chemosensors and Biosensors
28.5 Enzyme Fingerprinting with Multiple Substrates
28.6 Conclusions
Acknowledgments
References
Chapter 29: Confocal and Conventional Fluorescence-Based High Throughput Screening in Protein Engineering
29.1 General Aspects
29.2 Fluorescence
29.3 Hardware and Instrumentation
29.4 Practical Considerations and Screening Protocol
29.5 Challenges and Future Directions
Abbreviations
Acknowledgments
References
Chapter 30: Alteration of Substrate Specificity and Stereoselectivity of Lipases and Esterases
30.1 Introduction
30.2 Background of Protein Engineering Methods
30.3 Assay Systems
30.4 Examples
30.5 Conclusions
References
Chapter 31: Altering Enzyme Substrate and Cofactor Specificity via Protein Engineering
31.1 Introduction
31.2 Specific Examples
31.3 Challenges and Future Prospects
Acknowledgments
References
Chapter 32: Protein Engineering of Modular Polyketide Synthases
32.1 Introduction
32.2 Polyketide Biosynthesis and Engineering
32.3 Engineering and Characterization Techniques
32.4 The Path Forward
Abbreviations
References
Chapter 33: Cyanophycin Synthetases
33.1 Introduction
33.2 Occurrence of Cyanophycin Synthetases
33.3 General Features
33.4 Reaction Mechanism
33.5 Substrate Specificity
33.6 Primary Structure Analysis
33.7 Enzyme Engineering
33.8 Biotechnical Applications
Acknowledgments
References
Chapter 34: Biosynthetic Pathway Engineering Strategies
34.1 Introduction
34.2 Initial Pathway Design
34.3 Optimization of the Precursor Supply
34.4 Engineering of Control Loops
34.5 Engineering of Alternative Precursor Routes
34.6 Balancing Gene Expression Levels and Activities of Metabolic Enzymes
34.7 Metabolic Network Integration and Optimization
34.8 Engineering Pathways for the Production of Diverse Compounds
34.9 Future Perspectives
Abbreviations
References
Chapter 35: Natural Polyester-Related Proteins: Structure, Function, Evolution and Engineering
35.1 Introduction
35.2 Enzymes Related to the Synthesis and Degradation of PHA
35.3 Structure-Based Engineering of PHA Synthase and Monomer-Supplying Enzymes
35.4 Directed Evolution of PHA Synthases
35.5 Structure–Function Relationship of PHA Depolymerases
35.6 Application of PHA-Protein Binding Affinity
35.7 Perspectives
References
Chapter 36: Bioengineering of Sequence-Repetitive Polypeptides: Synthetic Routes to Protein-Based Materials of Novel Structure and Function
36.1 Introduction
36.2 Block Copolymers as Targets for Materials Design
36.3 Strategies for the Construction of Synthetic Genes Encoding Sequence-Repetitive Polypeptides
36.4 A Hybrid Approach to the Controlled Assembly of Complex Architectures of Sequence-Repetitive Polypeptides
36.5 Future Outlook
Acknowledgments
References
Chapter 37: Silk Proteins – Biomaterials and Bioengineering
37.1 Silk Protein Polymers – An Overview
37.2 Silk Protein Polymers – Methods of Preparation
37.3 Silk Protein Polymers – Future Perspectives and Challenges
Acknowledgments
References
Index
Further Reading
Cox, M. M., Phillips, G. N. (eds.)
Handbook of Proteins
Structure, Function and Methods. 2 Volume Set2008HardcoverISBN: 978-0-470-06098-8
Miller, L. W. (eds.)
Probes and Tags to Study Biomolecular Function2008HardcoverISBN: 978-3-527-31566-6
Lengauer, T. (ed.)
Bioinformatics – From Genomes to Therapies2007HardcoverISBN: 978-3-527-31278-8
Schreiber, S. L., Kapoor, T., Wess, G. (eds.)
Chemical Biology
From Small Molecules to Systems Biology and Drug Design2007HardcoverISBN: 978-0-470-84984-2
Aehle, W. (ed.)
Enzymes in Industry
Production and Applications2007HardcoverISBN: 978-3-527-31689-2
Meyers, R. A. (ed.)
Proteins
From Analytics to Structural Genomics2006HardcoverISBN: 978-3-527-31608-3
The Editors
Prof. Dr. Stefan LutzDept. of ChemistryEmory University1515 Dickey DriveAtlanta GA 30322USA
Prof. Dr. Uwe T. BornscheuerDept. of Biotechnology and Enzyme CatalysisInstitute of BiochemistryGreifswald UniversityFelix-Hausdorff-Str. 417487 Greifswald
All books published by Wiley-VCH are carefully produced. Nevertheless, authors, editors, and publisher do not warrant the information contained in these books, including this book, to be free of errors. Readers are advised to keep in mind that statements, data, illustrations, procedural details or other items may inadvertently be inaccurate.
Library of Congress Card No.: applied for
British Library Cataloguing-in-Publication DataA catalogue record for this book is available from the British Library.
Bibliographic information published by the Deutsche NationalbibliothekThe Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available on the Internet at <http://dnb.d-nb.de>.
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
All rights reserved (including those of translation into other languages). No part of this book may be reproduced in any form – by photoprinting, microfilm, or any other means – nor transmitted or translated into a machine language without written permission from the publishers. Registered names, trademarks, etc. used in this book, even when not specifically marked as such, are not to be considered unprotected by law.
ISBN: 978-3-527-31850-6
Preface
Protein engineering is pursued by scientists from many different disciplines. Chemists, biochemists, biologists, and engineers alike are engaged in tailoring enzymes. As diverse as their intellectual background is their motivation to do so, varying from a desire to understand the fundamentals of biocatalysis such as the intimate relationship of structure, dynamics and function to questions of evolution, from a need to adjust enzyme properties for industrial processes to the challenge of generating novel proteins for therapeutic and biomedical applications. To meet their objectives, researchers are using highly creative and innovative approaches to introduce beneficial changes to enzymes, focusing on – among other properties – greater activity, altered substrate specificity, improved enantioselectivity, and increased stability.
As a field of research, protein engineering has made significant contributions towards a better understanding of the physical and chemical properties of proteins. In return, it has benefited from advances in traditional areas of biochemistry and biophysics. Insights into the role of protein structure from x-ray crystallography and NMR spectroscopy experiments have been rapidly growing and, together with clever mechanistic studies by enzymologists, have greatly contributed towards a better rationale for function. Separately, the emerging appreciation for protein dynamics, as well as the implementation of single-molecule studies has given us an intimate look at the performance of not just bulk catalyst but individual molecules as they move along the reaction coordinate. Paralleling advances in our understanding of the fundamentals, the last two decades have brought three paradigm shifts on the technological side of protein engineering. Starting with the introduction of the polymerase chain reaction and recombinant gene technology, progress in the field has empowered researchers to manipulate amino acid sequences in a relatively straightforward fashion and obtain vast quantities of selected polypeptides in heterologous expression systems. Next, the recreation of protein evolution processes in the laboratory, using random mutagenesis and in vitro recombination techniques, has opened up exciting and powerful new opportunities for protein engineers in all disciplines. Lastly, the recent development of predictive computer algorithms has added an important new tool, complementing experimental approaches by guiding the design and, in some cases, allowing for complete de novo construction of enzymes.
Capturing these exciting developments, Volume 1 of this book series focuses on fundamental aspects of protein engineering. While the opening chapter by Edmondson defines some of the terminology related to the characterization of engineered enzymes and the comparison to its natural parents, the contributions of Kazlauskas, Hollfelder and Miller concentrate on the active site, exploring enantioselectivity and substrate promiscuity. An often neglected yet critical aspect of protein engineering is folding of the polypeptide chain. While Fersht highlights the application of protein engineering for the studies of the folding process, DeLisa recapitulates some of the strategies to identify properly folded proteins. Along the same line, protein dynamics is another largely overlooked aspect of protein engineering. The contribution by Romesberg introduces a series of spectrophotometric techniques to capture protein motion while the article by Pelletier summarizes recent findings by NMR spectroscopy and x-ray crystallography. In one example for putting protein folding and dynamics data to work in the context of enzyme engineering, Sagermann presents a simple yet elegant method to explore and exploit conformational changes for creating functional protein switches.
Giving thought to the observation that not all proteins are equally suitable for laboratory evolution, Höcker provides a more practical perspective on the selection of protein frameworks as starting points for enzyme engineering. New activity and promising templates for engineering can also be found in the vastness of the metagenome. Many new opportunities in this emerging research area are discussed in the chapters by Ferrer and Eck. Separately, the contributions by Wood and Horswill review the utilization of intein sequences as protein engineering tools. Finally, the application of computational methods to guide protein engineering and de novo design is examined in the section by Saven.
In Volume 2, mutagenesis and shuffling strategies for generating libraries are described in the contributions by Reetz, Jäger and Tawfik while computational and experimental tools for chimeragenesis are reviewed in the chapters by Arnold and Lutz. Less conventional but highly useful, Ostermeier discusses the impact of circular permutation on the structure and function of proteins.
As library generation represents only half the challenge in directed evolution, effective methods for searching the often substantial library diversity are necessary. Such screening or selection protocols are commonly performed in vivo or with the help of display systems as reported by Hilvert, Withers, Soumillion and Wittrup. The combination of such systems with spectroscopic assays offers a highly versatile screening strategy as outlined by Reymond and Coco. Alternatively, Ueda and Tawfik describe elegant in vitro strategies for library analysis. More product-oriented, Zhao and Bornscheuer discuss the application of protein engineering towards altering substrate and cofactor specificity, as well as enantioselectivity in individual enzymes. These strategies are not limited to single-enzyme systems. The chapters by Khosla, Steinbüchel, and Schmidt-Dannert demonstrate their application towards the manipulation of entire pathways. Similarly, protein engineering also offers new opportunities for tailoring biomaterials as described in the contributions of Taguchi, Conticello and Kaplan.
In summary, this book series attempts to capture some of the diverse interests and approaches in protein engineering, reflecting the many different disciplines and individual motivations and objectives in this area. We hope that it offers solutions to existing protein engineering problems and inspires new ideas to tackle the challenges in the field. In today’s fast-moving world, it is unrealistic to expect an all-inclusive, up-to-date collection of knowledge and methods in any printed media. The current research literature is a more appropriate source for the latest hypotheses and technology. Aiming for scientists new to the field, we instead emphasize a review of the basics in the field, as well as introduce selected new and promising strategies for protein engineering. We hope that this will provide readers with a comprehensive overview of this highly interdisciplinary research topic. For the experienced protein engineer, the book series might offer some new inspiration as well.
A book project such as this would never succeed without the wonderful support of many individuals that inspired, encouraged, and assisted in its assembly. In addition to thanking all of the authors for their efforts, we would like to acknowledge our colleagues and students at Emory University and the University of Greifswald for their advice in managing such a project, as well as their willingness to review and proof-read the pages that make up the two volumes. Finally, our special thanks also extend to the people at Wiley Publisher, namely Dr. Frank Weinreich and Dr. Heike Nöthe for their editorial assistants, as well as Claudia Zschernitz and Nele Denzau for their help during the printing stage of the books.
Atlanta/Greifswald, July 2008
Stefan Lutz & Uwe T. Bornscheuer
List of contributors
Amir AharoniDepartment of Life Science andthe NIBNUniversity of Ben Gurion in theNegevPOB [email protected]
Miguel AlcaldeCSIC, Institute of CatalysisDept. of Applied Biocatalysis28049 MadridSpain
Jennifer N. AndexerInstitute of Molecular EnzymeTechnologyHeinrich-Heine-UniversityDüsseldorfResearch Centre Jülich52426 JülichGermany
Frances H. ArnoldDivision of Chemistry and ChemicalEngineeringCalifornia Institute of Technology210-411200 E California BlvdPasadenaCA [email protected]
Ana BeloquiCSIC, Institute of CatalysisDept. of Applied Biocatalysis28049 MadridSpain
Blaise R. BolesDepartment of Internal MedicRoy J. and Lucille A. Carver College ofMedicineUniversity of Iowa 440 EMBRIowa CityIA 52242USA
Uwe T. BornscheuerDepartment of Biotechnology andEnzyme CatalysisInstitute of BiochemistryGreifswald UniversityFelix-Hausdorff-Str. 417487 [email protected]
Dominique BöttcherDepartment of Biotechnology andEnzyme CatalysisInstitute of BiochemistryGreifswald UniversityFelix-Hausdorff-Str. 417487 GreifswaldGermany
Martina CarboneDivision of Chemistry andChemical EngineeringCalifornia Institute of Technology210-411200 E California BlvdPasadenaCA [email protected]
Peggy CebeDepartment of PhysicsTufts UniversityScience and Technology CenterRoom 2084 Colby StreetMedfordMA 02155USA
Alice Y. ChenDepartment of Chemical EngineeringStanford UniversityStauffer III381 North-South MallStanfordCA 94305USA
Wayne M. CocoDIREVO Biotech AGNattermannalle 150829 [email protected]
Vincent P. ConticelloDepartment of ChemistryEmory University1515 Dickey DriveAtlantaGA [email protected]
Matthew P. DeLisa120 Olin HallDepartment of Chemical andBiomolecular EngineeringCornell UniversityIthacaNY [email protected]
Kevin K. DesaiDepartment of Chemistry andBiochemistryThe Florida State University213 Dittmer LaboratoryTallahasseeFL 32306-4390USA
Matthew DeSienoDepartment of Chemical andBiomolecular EngineeringUniversity of Illinois atUrbana-Champaign600 South Mathews AvenueUrbanaIL 61801USA
Nicolas DoucetUniversité de Montré alDépartement de biochimieCP 6128Succursale Centre-VilleMontréalQuébecH3C 3J7 Canada
Jing DuDepartment of Chemical andBiomolecular EngineeringUniversity of Illinois atUrbana-Champaign600 South Mathews AvenueUrbanaIL 61801USA
Jürgen EckB-R-A-I-N AGDarmstaedter Straße 34-3664673 ZwingenbergGermany
Dale E. EdmondsonDepartments of Biochemistryand ChemistryEmory UniversityAtlantaGA 30322-4098USA
Thorsten EggertInstitute of Molecular EnzymeTechnologyHeinrich-Heine-University DüsseldorfResearch Centre Jülich52426 JülichGermanyPresent addressevocatal GmbHMerowingerplatz 1a40225 DüsseldorfGermany
Neil FergusonMedical Research Council Centre forProtein EngineeringHills RoadCambridge CB2 0QHUnited KingdomandCambridge UniversityChemical LaboratoryLensfield RoadCambridge CB2 1EWUnited Kingdom
Manuel FerrerCSIC, Institute of CatalysisDept. of Applied Biocatalysis28049 [email protected]
Alan R. FershtMedical Research Council Centre forProtein EngineeringHills RoadCambridge CB2 0QHUnited KingdomandCambridge UniversityChemical LaboratoryLensfield RoadCambridge CB2 1EWUnited [email protected]
Adam C. Fisher120 Olin HallDepartment of Chemical andBiomolecular EngineeringCornell UniversityIthacaNY 14853USA
Susanne A. FunkeInstitute of Molecular EnzymeTechnologyHeinrich-Heine-UniversityDüsseldorfResearch Centre Jülich52426 JülichGermanyPresent addressInstitute of Neuroscience andBiophysics, Molecular BiophysicsResearch Center Jülich52426 JülichGermany
Esther GaborB-R-A-I-N AGDarmstaedter Straße 34-3664673 ZwingenbergGermany
Giovanni GaddaDepartments of Chemistry andBiologyGeorgia State UniversityThe Center for Biotechnology andDrug DesignAtlantaGA 30302-4098USA
Alison R. GilliesDepartment of Chemical EngineeringPrinceton UniversityPrincetonNJ 08544USA
Peter N. GolyshinDivision of MicrobiologyHZI-Helmholtz Centre for InfectionResearch38124 BraunschweigGermanyandDepartment of Biological SciencesUniversity of WalesBangor LL57 2DGUnited Kingdom
Benjamin J. HackelMassachusetts Institute of TechnologyBuilding E19-56350 Ames StreetCambridgeMA 02142USA
Ulrich HauptsDIREVO Biotech AGNattermannalle 150829 CologneGermany
Asael HermanDepartment of Biological ChemistryWeizmann Institute of ScienceRehovot 76100Israel
andDepartment of PathologyUniversity of Washington School ofMedicineHSB K-058, BOX 357 705SeattleWA 98195-7705USA
Oliver HesseDIREVO Biotech AGNattermannalle 150829 CologneGermany
Donald HilvertLaboratory of Organic ChemistryE.T.H. ZurichAltwiesenstrasse 64CH-8093 [email protected]
Birte HöckerMax-Planck-Institute forDevelopmental BiologySpemannstrasse 3572076 Tü[email protected]
Florian HollfelderUniversity of CambridgeDepartment of BiochemistryCambridge CB2 1GAUnited [email protected]
Alexander R. HorswillDepartment of MicrobiologyRoy J. and Lucille A. CarverCollege of Medicine431 Newton Rd540 F. EcksteinMedicinal Research BuildingUniversity of IowaIowa CityIA [email protected]
Karl-Erich JaegerInstitute of Molecular EnzymeTechnologyHeinrich-Heine-University DüsseldorfResearch Centre Jülich52426 JülichGermany
Stefanie JonasUniversity of CambridgeDepartment of BiochemistryCambridge CB2 1GAUnited Kingdom
Manu KanwarDepartment of Chemical andBiomolecular EngineeringJohns Hopkins University3400 N. Charles St.BaltimoreMD 21218-2681USA
David. L. KaplanDepartment of BiomedicalEngineeringTufts UniversityMedfordMA 02155USA
Peter KastLaboratory of Organic ChemistryE.T.H. ZurichAltwiesenstrasse 64CH-8093 ZurichSwitzerland
Romas KazlauskasDepartment of Biochemistry,Molecular Biologyand Biophysics, and The BiotechnologyInstitute,University of Minnesota1479 Gortner AvenueSaint PaulMN 55108USA
Chaitan KhoslaDepartments of ChemicalEngineering, Chemistry andBiochemistryStanford University, Keck 337StanfordCA [email protected]
Andreas C. KleebLaboratory of Organic ChemistryE.T.H. ZurichAltwiesenstrasse 64CH-8093 ZurichSwitzerland
Marco LandwehrDivision of Chemistry andChemical EngineeringCalifornia Institute of Technology210-411200 E California BlvdPasadenaCA 91125USA
Yougen LiDivision of Chemistry and ChemicalEngineeringCalifornia Institute of Technology210-411200 E California BlvdPasadenaCA 91125USA
Klaus LiebetonB-R-A-I-N AGDarmstaedter Straße 34-3664673 ZwingenbergGermany
Stefan LutzDepartment of ChemistryEmory University1515 Dickey DriveAtlantaGA [email protected]
Thomas J. Mansell120 Olin HallDepartment of Chemical andBiomolecular EngineeringCornell UniversityIthacaNY 14853USA
Glenna E. MeisterDepartment of Chemical andBiomolecular EngineeringJohns Hopkins University3400 N. Charles St.BaltimoreMD 21218-2681USA
Guido MeurerB-R-A-I-N AGDarmstaedter Straße 34-3664673 ZwingenbergGermany
Michelle MeyerDivision of Chemistry andChemical EngineeringCalifornia Institute of Technology210-411200 E California BlvdPasadenaCA 91125USA
Brian G. MillerDepartment of Chemistry andBiochemistryThe Florida State University213 Dittmer LaboratoryTallahasseeFL [email protected]
Philippe MinardLaboratoire de Modelisation etIngénierie des ProtéinesInstitut de Biochimie etBiophysique Moléculaire etCellulaireUniversité Paris-Sud-Bat. 43091405 OrsayFrance
Martin NeuenschwanderLaboratory of Organic ChemistryE.T.H. ZurichAltwiesenstrasse 64CH-8093 ZurichSwitzerland
Frank NiehausB-R-A-I-N AGDarmstaedter Straße 34-3664673 ZwingenbergGermany
Marc OstermeierDepartment of Chemical and Biomolecular EngineeringJohns Hopkins University3400 N. Charles St.BaltimoreMD [email protected]
Melissa PattersonDepartment of ChemistryEmory University1515 Dickey DriveAtlantaGA 30322USA
Sonha C. PayneDepartment of ChemistryEmory University1515 Dickey DriveAtlantaGA 30322USA
Joelle N. PelletierUniversité de MontréalDépartement de chimie &Département de biochimieCP 6128Succursale Centre-VilleMontréalQuébecH3C 3J7 [email protected]
Alexander PisarchikDepartment of Biochemistry,Molecular Biology and BiophysicsUniversity of Minnesota1479 Gortner AvenueSt. PaulMN 55108USA
Manfred T. ReetzMax-Planck-Institut fürKohlenforschungKaiser-Wilhelm-Platz 145470 Mülheim an der [email protected]
Jean-Louis ReymondUniversity of BerneDepartment of Chemistry andBiochemistryFreiestrasse 33012 [email protected]
Floyd E. RomesbergThe Scripps Research InstituteDepartment of Chemistry10550 N. Torrey Pines RoadLa [email protected]
Gloria Saab-RinconDepartmento de IngenieriaCelular y Biocatalisis Instituto deBiotecnologia UniversidadNacional Autonoma de MexicoApdo Postal 510-3 CueernavacaMorelos 62250Mexico
Martin SagermannDepartment of Chemistry andBiochemistry andInterdepartmental Program inBiomolecular Science and EngineeringUniversity of California Santa BarbaraSanta Barbara 4649 B PSB NorthCalifornia [email protected]
Jeffery G. SavenDepartment of ChemistryUniversity of Pennsylvania231 South 34th StreetPhiladelphiaPA [email protected]
Marlen SchmidtDepartment of Biotechnology andEnzyme CatalysisInstitute of BiochemistryGreifswald UniversityFelix-Hausdorff-Str. 417487 GreifswaldGermany
Claudia Schmidt-DannertDepartment of Biochemistry,Molecular Biology and BiophysicsUniversity of Minnesota1479 Gortner AvenueSt. PaulMN [email protected]
Patrice SoumiIlionLaboratoire d’Ingénierie desProtéines et des PeptidesInstitut des Sciences de la VieUniversité catholique de LouvainPlace Croix du Sud 4-5, bte 31348 [email protected]
Alexander SteinbüchelInstitut für Molekulare Mikrobiologieund Biotechnologie derWestfälischenWilhelms-UniversitätCorrensstraße 348149 Mü[email protected]
Anna SteinleInstitut für MolekulareMikrobiologie und Biotechnologieder WestfälischenWilhelms-UniversitätCorrensstraße 348149 MünsterGermany
Michael StrerathDIREVO Biotech AGNattermannalle 150829 CologneGermany
Seiichi TaguchiDivision of Biotechnology andMacromolecular ChemistryGraduate School of EngineeringHokkaido UniversityN13W8, Kita-kuSapporo [email protected]
Dan S. TawfikDepartment of Biological ChemistryWeizmann Institute of ScienceUllmann BldgRoom 201aPO BOX 26Rehovot [email protected]
Megan C. ThielgesThe Scripps Research InstituteDepartment of Chemistry10550 N. Torrey Pines RoadLa JollaCaliforniaUSA
Manuela TraniDepartment of ChemistryEmory University1515 Dickey DriveAtlantaGA 30322USA
Takeharu TsugeDepartment of Innovative and EngineeredMaterialsTokyo Institute of Technology4529 NagatsutaMidori-kuYokohama 226-8502Japan
Takuya UedaDepartment of Medical GenomeSciencesGraduate School of Frontier SciencesThe University of TokyoFSB-4015-1-5 KashiwanohaKashiwaChiba [email protected]
Agathe UrvoasLaboratoire de Modelisation etIngénierie des ProtéinesInstitut de Biochimie et BiophysiqueMoléculaire et CellulaireUniversité Paris-Sud-Bat. 43091405 OrsayFrance
Peter J. WallaTechnische UniversitätBraunschweigInstitute for Physical andTheoretical ChemistryDept. for Biophysical ChemistryHans-Sommerstr. 1038106 BrunswickGermanyandMax-Planck-Institute for BiophysicalChemistryAm Faßberg 1137077 GöttingenGermany
Xiaoqin WangDepartment of BiomedicalEngineeringTufts UniversityScience Technic Center4 Colby StreetMedfordMA 02155USA
Stephen G. WithersDepartment of ChemistryUniversity of British Columbia2036 Main MallVancouverBritish Columbia V6T 1Z1Canada
K. Dane WittrupMassachusetts Institute of TechnologyBuilding E19-55177 Massachusettes AveCambridgeMA [email protected]
David W. WoodDepartment of Chemical EngineeringandDepartment of Molecular BiologyPrinceton UniversityPrincetonNJ [email protected]
Bei-Wen YingDepartment of BioinformaticEngineeringGraduate School of InformationScience and TechnologyOsaka University2-1 YamadaokaSuitaOsaka 565-0871Japan
Wayne YuThe Scripps Research InstituteDepartment of Chemistry10550 N. Torrey Pines RoadLa JollaCaliforniaUSA
Huimin ZhaoDepartments of Chemical andBiomolecular Engineering,Chemistry and BioengineeringUniversity of Illinois atUrbana-Champaign600 South Mathews AvenueUrbanaIL [email protected]
Jörg ZimmermannThe Scripps Research InstituteDepartment of Chemistry10550 N. Torrey Pines RoadLa JollaCaliforniaUSA
Miren ZumárragaCSIC, Institute of CatalysisDept. of Applied Biocatalysis28049 MadridSpain
Chapter 1
Guidelines for the Functional Analysis of Engineered and Mutant Enzymes
Dale E. Edmondson and Giovanni Gadda
1.1 Introduction
The basic goal of protein engineering is the creation of altered forms of a known enzyme catalyst that exhibits one or more of the following properties:
An increased catalytic function relative to the parent enzyme.
An altered substrate specificity or stereospecificity, such that the engineered protein is capable of catalyzing the conversion of substrates differing from the specific substrate of its parent form.
An increased stability to the environment that is required for it to catalyze the specific function required.
An analysis of all of these desired properties of the engineered protein requires detailed studies of its catalytic properties, which involve the delineation of the steady-state kinetic behavior of the mutant protein. This chapter deals with topics ranging from the acquisition of data, the analysis of the kinetic data acquired, and the interpretations and conclusions that may be inferred from those data. This chapter is not meant to be a reiteration of chapters and textbooks on enzyme kinetic approaches that are either classics in the field or have been recently published. Rather, it is meant for readers who have attended a basic biochemistry course in which enzyme kinetics is only cursorily presented. Hopefully, this chapter will fill a gap between an introductory level and the more rigorous treatments of the subject which are written for readers well versed in the field. The aim here is to describe approaches that the authors have used over their careers in order to provide a readable and useful ‘road map’ for those colleagues and students who have either not been exposed to this area of enzymology, are just entering the field, or have not had time to ‘wade through’ those texts that have been published in the area of enzyme kinetics [1, 2]. This chapter is organized as follows: a review of steady-state kinetic equations, consideration of assay procedures, interpretation of basic kinetic parameters, the effect of pH on enzyme kinetic parameters, and an introduction to enzymes catalyzing reactions that require two substrates.
1.2 Steady-State Kinetics
In order to appreciate the rest of the topics covered in this chapter, a brief review of the steady-state kinetic approach and the parameters of enzyme-catalyzed reactions is in order. The basic equation describing enzyme catalysis is the Michaelis–Menten equation:
(1.1)
where kcat (units of time−1) is the enzyme turnover number, which is defined as the maximum number of substrate molecules converted to products per active site per unit of time (with units of a first-order rate constant). Km (units of concentration) is defined as the concentration of substrate where half the maximal activity (kcat) is observed. The term vo defines the initial, zero-order rate of the reaction (with units of concentration of product-time−1), the value of which depends hyperbolically on the substrate concentration.
The requirements for the valid application of the Michaelis–Menten equation are the following:
These requirements are readily fulfilled when enzymes catalyzing the transformations of small molecules are studied. Problems arise, however, when Michaelis–Menten kinetic equations are applied to enzymes catalyzing the transformations of large macromolecules, such as other proteins or polynucleotides. The lack of fulfillment of any of the three requirements summarized above prevents the valid application of the Michaelis–Menten equation, and requires the application of other, specialized kinetic approaches that are dependent on the nature of the system examined.
Under conditions in which the concentration of substrate is significantly smaller than the Km value (normally at least 10-fold smaller), the Michaelis–Menten equation simplifies to that designated in Equation 1.2.
(1.2)
In this form the novel kinetic parameter is kcat/Km [with units of (conc. of substrate)−1 time−1], which is often referred to as a measure of ‘catalytic efficiency’ of the engineered enzyme under study. In this condition, the initial velocity is linearly dependent on the substrate concentration and the slope of this linear relation is kcat/Km, which has the units of a second-order rate constant.
1.3 Enzyme Assays and the Acquisition of Initial Velocity Data
1.3.1 Biological Sample Appropriate for Assay
1.3.2 Enzymatic Assays
The quantitative determination of enzymatic activity is a diverse topic and boils down to an exercise in analytical chemistry. In general, enzyme assays can be divided into two approaches; a discontinuous assay and a continuous assay. The difference is that the former approach is more tedious while the latter is more convenient, allowing the rapid acquisition of kinetic data, and is applicable for the use of high-throughput assay techniques. In both approaches, every effort should be made to develop methodology for monitoring the formation of product as a function of time rather than the decrease in the concentration of substrate concentrations. Basic to this question is one of accuracy. In the case of product formation, one begins with a ‘zero’ concentration and ends up with a finite amount of product formed. Therefore, one is looking at a difference (with respect to time) of a finite numerical value versus a zero value. In the case where one observes substrate loss as a function of time, the difference in determinations of substrate concentrations then involves differences in two rather large numbers, with the result being a difference in concentration of substrate that incorporates the errors involved in the analytical determinations of the amount of substrate present at various time periods in the assay. The conclusion from this discussion is that, whenever possible, it is preferable to assay the activity of enzymes by product analysis rather than by substrate analysis.
In the discontinuous enzyme assay, aliquots are removed from the incubation mixture of enzyme plus substrate at various times and product formation is determined by separation techniques that range from solvent extraction to chromatographic separations such as high-performance liquid chromatography (HPLC). The advantage of radiochemical tagging of substrate so that product concentrations are readily determined (e.g. 14C labeling at a nonlabile position) is readily apparent, although the execution of this approach requires a source of radiolabeled material of a known specific activity, which may not always be possible. Alternatives to radiolabeling procedures include mass spectrometry (MS) or gas chromatography (GC) if the products of the reaction can be made volatile, either inherently or by suitable derivatization. Most often there exist specific absorption spectral or optical rotation properties of the product that allow its quantitative determination on separation from substrate.
A fundamental issue that requires care when using a discontinuous assay (also referred to as an ‘end-point’ assay) for the determination of enzymatic activity is that of the linearity of product formation (or substrate depletion) with time at the initial stages of the reaction. This is an essential methodological aspect that is required when steady-state kinetic approaches are applied, as the observed rate of the enzymatic reaction under study is given by the slope of the tangent line to the progress curve of the reaction in a plot of (product) versus time–that is, a line that in a discontinuous assay is given by only two points. To ensure that product formation is linear over time, one must therefore repeat the assay under the same experimental conditions and determine the concentration of product at several time points during the course of the reaction–a sometimes tedious, but absolutely required, procedure. Failure to do so can invariably result in an underestimation of the enzymatic activity due to the time point selected for the quantification of the concentration of product not being in the linear portion of the progress curve of the enzymatic assay, as illustrated in the example of Figure 1.1.
Figure 1.1 Plot of initial rate of product formation with time in an enzyme assay run under zero-order conditions. Line 1 shows the nonlinear appearance of product with time, which is analyzed by the drawing of a tangent (----) to the initial rate of product formation. Line 2 shows a linear rate of product formation with time.
The continuous enzyme assay is usually performed by monitoring the changes in absorption or fluorescent spectral properties associated with product formation in the catalytic reaction. The initial rates are determined continuously and the increase in product concentration quantified as a function of time, using the above-described spectral approaches.
Figure 1.2 Reaction scheme for the coupled enzyme assay for the detection of hydrogen peroxide using Amplex Red/horseradish peroxidase.
Continuous assays can also be followed by the use of electrochemical detection of substrate and/or products. Common electrodes used include the polarographic Clark electrode for the detection of O2, and glass electrodes for the detection of H+ liberated in hydrolytic reactions. The O2 electrodes suffer from a lack of sensitivity, membrane instability, and functionality over a limited temperature range. In addition, the investigator is dealing with the problem of measuring small differences in O2 concentration by subtraction of two relatively large numerical values, which limits the precision of the measurement. Some of these problems can be overcome by the use of O2 probes which utilize the quenching of a bound fluorophore by paramagnetic ground-state O2 in solution. Care should be exercised to determine that fluorophore fluorescence is not quenched by solution components in addition to dissolved O2.
1.3.3 Analysis of Initial Rate Data
Once protocols are established for the measurement of initial velocity data, the investigator then determines the effect of substrate concentration on the initial rate of the enzymatic reaction. As most enzymes require two substrates, typically one substrate is kept at a fixed concentration while the concentration of the other substrate is varied. The data are plotted using the well known Michaelis–Menten equation (Equation 1.1), which exhibits a hyperbolic dependence of rate (vo) on [S] (Figure 1.3):
The most accurate method of determining the parameters kcat and Km is to fit the hyperbolic relationship by nonlinear fits using commonly available commercial software programs such as Origin, KaleidaGraph or SigmaPlot, all of which are available for use on most personal computers. The data required are initial rates at substrate concentrations ranging from 0.2- to 5-fold the Km value of the enzyme for the substrate, ideally with an equal number of data points below and above the Km value. Under these conditions, the investigator can determine accurate values for kcat, Km and kcat/Km for the engineered enzyme of interest. Linearization of the data using the popular Lineweaver–Burk plot (1/vo versus 1/[S] provides kcat, Km and kcat/Km values, which are less accurate as the method accentuates uncertainty by giving disproportionate weight to the least accurate data (i.e. low vo values at low concentrations of substrate). A more accurate linear plot, which provides a more balanced representation of the data, is the Hanes plot ([S]/vo versus [S]). For a detailed discussion of the various linear plotting methods, the reader is referred to a very readable treatment by Cornish-Bowden [1]. In the event that the investigator encounters a situation where the solubility of the substrate prevents the use of substrate concentrations required for saturation of the enzyme (i.e. one cannot reach kcat conditions), both linear and nonlinear fits of the data break down and lead to inaccurate kcat values (and consequently Km values). Under these conditions the investigator can only determine kcat/Km values for the enzyme by using Equation 1.2, and must restrain from reporting artifactual kcat and Km values. In opposite instances where the Km value is too small to be accurately determined, the investigator can only determine the kcat values, and must refrain from reporting artifactual kcat/Km and Km values.
1.3.4 Determination of Functional Catalytic Site Concentrations
The definitive determination of kcat relies on measuring the concentration of functional catalytic sites used in the catalytic assays. This is not a trivial point in the analysis of recombinant engineered enzymes, as purified preparations may contain an unknown fraction of protein molecules that may not be correctly folded or may not contain the native cofactor (if one is required for catalysis). Simply determining the protein concentration and assuming there to be one catalytic site per mole of enzyme is not sufficient for the correct determination of kcat values. The most direct approach to determine the concentration of functional enzyme is a titration with an irreversible mechanism-based inhibitor that forms a covalent bond to a residue in the active site [7]. This approach is the most practical one for a wide range of enzymes utilizing small-molecule substrates. Assuming that there is no partitioning between turnover and covalent labeling, one simply ‘titrates’ a solution of recombinant enzyme and determines the active sites concentration from a plot of residual activity versus amount of inhibitor added [8]. In cases where the catalyzed turnover can compete with covalent labeling, one can use a radiolabeled inhibitor and determine covalent incorporation by the amount of radiolabeling on precipitation of theenzyme under denaturing conditions. If no radiolabeled inhibitor is available, and no absorption or fluorescent spectral changes associated with covalent inhibitor incorporation are detectable, the level of covalent inhibitor incorporation can be determined using high-resolution, quantitative electrospray ionization mass spectrometry, where the increase in molecular weight of the enzyme on covalent modification is monitored and the ratio of enzyme inhibitor complex to the amount of unlabeled enzyme can be determined [9, 10]. However, the latter approach is not easily performed in most laboratories, and requires personnel and equipment that are highly specialized.
If working with enzymes that contain redox-active cofactors, the level of functional enzyme is readily determined by the level of cofactor reduction that occurs rapidly on the anaerobic addition of a reducing substrate. This approach is commonly used with flavoenzymes and metalloenzymes where the metal or flavin coenzyme undergoes a redox change on substrate addition which can be followed by UV-visible absorption spectroscopy in the absence of an oxidizing agent such as O2.
1.4 Steady-State Kinetic Parameters and Their Interpretation
After the efforts involved in expressing and purifying the engineered enzymes and the accurate determination of their steady-state kinetic properties, one is left with three numbers: kcat, Km and kcat/Km, as quantitative measures of their functional properties. The value of kcat is the rate of overall turnover in the reaction catalyzed, and is useful to compare the functional properties of the engineered protein with that of the wild-type enzyme. The catalytic turnover number has the units of t−1, and is usually expressed in min−1 or s−1. The value of kcat is a composite of all of the kinetic steps involved in catalysis at saturating concentrations of the substrates, and its value is dependent on the value of the reaction step that is the slowest in enzyme turnover and therefore constitutes the rate-limiting step in catalysis. This rate-limiting reaction need not necessarily involve a step involved in the chemical transformation of the substrate to product, but may be given by the rate of product release from the catalytic site. The goal of most enzyme engineering studies is to alter the substrate specificity of the mutated enzyme or to increase the kcat value. Therefore, the investigator should measure the kcat values for wild-type and mutant enzymes with the native substrate as well as with the desired specific substrate, with the caution that the rate-limiting step in catalysis observed with the native enzyme may be different for the engineered or mutant form.
The value of Km is defined as the substrate concentration where kcat/2 occurs, and is expressed in terms of concentration (usually mM or μM). Only in special cases is it a measure of substrate binding affinity to the enzyme (i.e. Kd). In the simplest instance of an irreversible enzyme-catalyzed reaction with a single substrate, the Km will reflect the enzyme-binding affinity for the substrate only when the rate of the chemical step is significantly slower than both the rates of dissociation of the substrate and the product from the catalytic site. (For an in-depth discussion of this topic, the reader is referred to Ref [3] and [4].) The special case described above would require extensive kinetic studies of both mutant and wild-type enzymes for verification, which is usually beyond the research goals of most enzyme engineering laboratories. One of the most extensively studied enzymes that details the effect of mutations and ‘double mutations’ on the rates of individual kinetic steps and conformational equilibria as related to catalysis is the enzyme dihydrofolate reductase (DHFR). The extensive data and references to the individual studies on this enzyme are well summarized in a review by Miller and Benkovic [11].
The steady-state kinetic value that one sees most often in the literature on engineered or mutant proteins is that of kcat/Km as a measure of the catalytic efficiency of the enzyme and a measure of its catalytic usefulness relative to wild-type, other mutant forms of the enzyme, or of other biological sources of the same catalyst. The term kcat/Km has the units of a second-order rate constant (e.g. M−1s−1) (see Equation 1.2). Northrop has written a valuable discussion of the term kcat/Km and its use in our understanding of relative catalytic efficiencies [12, 13]. In accord with his arguments, this term represents a ‘capture rate’ of the enzyme for its substrate, as this value represents all of the kinetic steps up to and including the first irreversible step in catalysis. In the simplest case of a reversible enzymatic reaction with one substrate, the kinetic parameters can be visualized as shown in Equation 1.3. The kinetic terms comprising kcat are given in Equation 1.4, which reduces to Equation 1.5 when the chemical step is fully rate-limiting in turnover, and reduces to Equation 1.6 when product release is rate-limiting.
(1.3)
(1.4)
(1.5)
(1.6)
The expression for kcat/Km is given in Equation 1.7.
(1.7)
In the situation where the chemical step is irreversible in catalysis, the expression describing this situation is shown in Equation 1.8. The expression for kcat in this case is the same as in the previous case, and shown in Equations 1.4–1.6. The expression for kcat/Km does differ from the above case, as shown in Equation 1.9.
(1.8)
(1.9)
In contrast, kcat represents all of the reaction steps in the catalytic cycle with the exclusion of the substrate-binding steps (as the substrate concentration is saturating), and is limited by the step which is rate-limiting in catalysis (i.e. the total rate of catalytic turnover can be no faster than the slowest step in the reaction sequence). Most commonly, kcat values are determined by the rate of product release (Equation 1.6), but in some instances are determined by the rate of the chemical transformation step in the enzyme reaction (Equation 1.5). It should be noted that kcat values represent rates when all of the catalytic binding sites are saturated with substrate, and therefore relative substrate binding steps cannot be included in the their comparative values.
1.4.1 pH-Dependence of Steady-State Kinetic Parameters
Generally, a key aspect in studying enzyme catalytic properties is to determine the influence of pH on kinetic parameters. In comparing wild-type and mutant enzyme activities, it is important to verify whether or not the mutation has altered pH–activity profiles. For correct comparison of mutant and wild-type catalytic activities, the data should be acquired over a pH range where kinetic parameters investigated are pH-independent in order to avoid artifactual complications in the interpretation of the kinetic data. The variation of kcat with pH generally reflects alterations in the ionization state of essential amino acid residues in the active site that participate in catalysis. The variation of kcat/Km with pH may reflect either substrate binding (pKa values due to either substrate or amino acid group at the binding site) or amino acid residues essential in the chemical step in catalysis. The point here is that engineering an enzyme may result in expected or unexpected alterations in the pKa of the amino acid side chains involved in substrate binding or in the chemical step in catalysis. Therefore, pH-dependent catalytic characterization is an essential component of the characterization of engineered enzymes. The additional information obtained also would include pKa values for the participating amino acid residues, which are easily obtained from visual inspection and fitting of pH-profile data with the appropriate equations.
1.4.2 Analysis of Two-Substrate Enzymes
A general survey of known enzymes shows that a large majority of them catalyze reactions utilizing two substrates. The principal pathways discussed in most introductory biochemistry textbooks are the ternary complex mechanism (where both substrates or both products are bound to the enzyme catalytic site) or the binary or Ping-Pong mechanism (where only one substrate or product is bound at the catalytic site at any time during the catalytic reaction) (see Figure 1.4).
Figure 1.4 Two-substrate, two-product enzyme reaction pathway scheme depicting a binary (Ping-Pong) complex mechanism in the top loop and a ternary complex mechanism in the bottom loop. A and B are the two substrates for the catalyzed reaction. P and Q denote the two products formed.
It follows, therefore, that enzyme engineering might alter kinetic steps such that a two-substrate enzyme could follow a pathway different from that of the wild-type enzyme. The simplest case would be an alteration in the rate constant for release of the first product, resulting in reaction of the second substrate with the enzyme prior to release of the first product (or vice versa). It is therefore incumbent on the investigator not to assume retention of kinetic pathway on enzyme alteration but rather to verify whether any changes in fact did occur. This is readily shown by the variation of rates with different concentrations of both substrates to determine whether binary or ternary complex formation occurs through visual inspection (and fitting with the appropriate equations) of shapes of Lineweaver–Burk plots at different concentrations of the second substrate. The finding of intersecting Lineweaver–Burk plots demonstrates ternary complex behavior. If the plots are parallel, such behavior is suggestive of binary complex (or Ping-Pong) behavior, but does not unequivocally prove it as there are numerous examples in the literature of enzymes exhibiting parallel Lineweaver–Burk plots that, on further investigation, are shown to function by a ternary complex mechanism.
1.5 Concluding Remarks
The object of this chapter is to assist the protein engineer in the task of determining the functional properties of newly engineered enzymes. This task is not a trivial one, and in many instances represents far more effort and time than that spent on the construction of mutants and their expression. If the investigator adheres to the guidelines for the assay, accumulation of steady-state kinetic properties and their interpretations, as discussed in this chapter, then he or she should feel confident in further concepts and interpretations relevant to the field of enzyme engineering in which they are involved. The reader is also referred to excellent chapters dealing with more specialized aspects of the kinetic properties of enzyme systems in three volumes of Methods in Enzymology [14–16].
References
1 Cornish-Bowden, A. (2004) Fundamentals of Enzyme Kinetics, 3rd edn, Portland Press, London.
2 Cook, P.F.and Cleland, W.W. (2007) Enzyme Kinetics and Mechanism, Garland Science Publishing, New York.
3 Rudolph, F.B., Baughes, B.W.and Beissner, R.S. (1979) Methods in Enzymology, Part A, 63, Academic Press, New York, pp. 22–42.
4 Zhou, M., Diwu, Z., Panchuk-Voloshina, N.and Hougland, R.P. (1997) Analytical Biochemistry, 253, 162–8.
5 Zhou, M.and Panchuk-Voloshina, N. (1997) Analytical Biochemistry, 253, 169–74.
6 Holt, A.and Palcic, M. (2006) Nature Protocols, 1, 2498–505.
7 Seiler, N., Jung, M.J.and Koch-Weser, J. (1978) Enzyme-Activated Irreversible Inhibitors, Elsevier Pub. Co., Amsterdam.
8 Fowler, C.J., Wiberg, A., Oreland, L.and Wimblad, B. (1980) Neurochemical Research, 5, 697–708.
9 O’Farrell, N., Kreiner, M., Moore, B.D.and Parker, M.C. (2006) Biotechnology and Bioengineering, 95, 767–71.
10 Hubálek, F., Pohl, J.and Edmondson, D.E. (2003) The Journal of Biological Chemistry, 278, 28612–8.
11 Miller, G.P.and Benkovic, S.J. (1998) Chemistry and Biology, 5, R105–13.
12 Northrop, D.B. (1998) Journal of Chemical Education, 75, 1153–7.
13 Northrop, D.B. (1999) Enzyme Mechanisms, Vol. 27 (eds P.A. Frey and D.B. Northrup), IOS Press, Amsterdam, pp. 250–63.
14 Purich, D.(ed.) (1979) Methods in Enzymology, Part A, 63, Academic Press, New York.
15 Purich, D.(ed.) (1980) Methods in Enzymology, Part B, 64, Academic Press, New York.
16 Purich, D.(ed.) (1982) Methods in Enzymology, Part C, 87, Academic Press, New York.
Chapter 2
Engineering Enantioselectivity in Enzyme-Catalyzed Reactions
Romas Kazlauskas
2.1 Introduction
Enantioselective enzyme reactions are enzyme-catalyzed reactions that discriminate between enantiomeric substrates or products. For example, the kinetic resolution of a lactam is an enantioselective enzyme reaction (see Scheme 2.1). The lactamase catalyzes the hydrolysis of the (+)-lactam, leaving the unreacted (−)-lactam in high enantiomeric purity [1]. This (−)-lactam serves as the starting material for the synthesis of carbocyclic nucleosides such as abacavir. The enantioselectivity for this reaction is >400, which means that the (+)-lactam reacts more than 400 times faster than the (−)-enantiomer.
Scheme 2.1 Lactamase-catalyzed kinetic resolution of 2-azabicyclo(2.2.1)hept-5-en-3one (lactam) yields an enantiopure intermediate for synthesis of abacavir, an anti-AIDS drug.
This chapter focuses on the use of protein engineering to increase enzyme enantioselectivity, and also provides a review of our current understanding of enantioselectivity and successes in protein engineering. The focus is on unnatural substrates such as the lactam shown in Scheme 2.1, because organic synthesis requires such reactions for the manufacture of pharmaceutical intermediates and fine chemicals. At this point, enantioselective inhibition, which is an important consideration in drug design, will not be considered because it involves only binding and not a chemical reaction.
Natural enzyme-catalyzed metabolic reactions may show very high selectivity because natural selection favors more efficient metabolic reactions. For example, L-lactate dehydrogenase from Bacillus stearothermophilus favors L-lactate over D-lactate by a ratio of more than 25000:1 [2]. The evolutionary reason for this high enantioselectivity is probably not to discriminate against D-lactate, which is the end product of anaerobic metabolism where the formation of either enantiomer fulfills the biochemical role. The high enantioselectivity is most likely the byproduct of evolving a highly efficient catalyst for L-lactate. A catalyst perfectly fitted for L-lactate will be a poor fit for D-lactate.
As enzyme-catalyzed reactions involving unnatural substrates have not faced any evolutionary pressure, their enantioselectivities vary widely. Although the lactam example in Scheme 2.1 shows excellent enantioselectivity, many examples demonstrate minimal enantioselectivity. For synthetic use, the enantioselectivity should be >50, although values as low as 20 may be synthetically useful if the product is very valuable and there are no alternative routes.
Enantioselective enzyme reactions can be either kinetic resolutions or enantioselective syntheses
