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«Towards Classification and Functional Description of Enzymes A case study of feruloyl esterases D.B.R.K. GUPTA UDATHA Industrial Biotechnology ...»

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Thesis for the degree of Doctor of Philosophy

Towards Classification and

Functional Description of Enzymes

A case study of feruloyl esterases

D.B.R.K. GUPTA UDATHA

Industrial Biotechnology

Department of Chemical and Biological Engineering

CHALMERS UNIVERSITY OF TECHNOLOGY

Gothenburg, Sweden 2013

Towards Classification and Functional Description of Enzymes

A case study of feruloyl esterases

D.B.R.K. GUPTA UDATHA

© D.B.R.K. GUPTA UDATHA, 2013.

ISBN 978-91-7385-770-3 Doktorsavhandlingar vid Chalmers tekniska högskola Ny serie nr 3451 ISSN 0346-718X Industrial Biotechnology Department of Chemical and Biological Engineering Chalmers University of Technology SE-41296 Gothenburg Sweden Telephone: +46 (0) 31-772 1000

Cover illustration:

Scheme to functionally describe an enzyme through substrate interactions and chemical features, by D.B.R.K. Gupta Udatha Printed by Chalmers Reproservice Gothenburg, Sweden 2013 ii To my family and friends… “Touch a scientist and you touch a child” (Ray Bradbury) iii iv Preface This PhD dissertation serves as a partial fulfillment of the requirements to obtain the PhD degree at the Department of Chemical and Biological Engineering, Chalmers University of Technology, Sweden. The PhD project was carried out between 2009 and 2012, under the supervision of Professor Lisbeth Olsson. Associate Professor Gianni Panagiotou acted as co-supervisor in 2009-2011. The major part of the research work during my PhD was focused on integration of chemical informatics, biophysical characterization and protein engineering for modeling the substrate specificity of feruloyl esterases. As a guest PhD student at the Technical University of Denmark for a period of 6 months, I initiated collaboration with Associate Professor Irene Kouskoumvekaki (CBS, Computational Chemical Biology group) for the integration of bioinformatics and cheminformatics tools towards functional enzyme classification schemes.

The knowledge and expertise gained through integration of in silico- and experimental- biology was also applied to other collaborative projects (which are outside the border of my PhD project) focused on metabolic engineering and functional genomics.

My PhD project was mainly funded by the Swedish Research Council (Vetenskapsrådet) however personal scholarships partially supported my course work and conference trips.

Dasaradhi Bala Rama Krishna Gupta Udatha January 2013 v Towards Classification and Functional Description of Enzymes A case study of feruloyl esterases D.B.R.K. GUPTA UDATHA Industrial Biotechnology, Department of Chemical and Biological Engineering, Chalmers University of Technology Abstract The prediction of enzyme functionality from sequence or structure data remains a challenging task that can be best addressed by studying the structure-function relationships determined from previously available information. This thesis work was focused on developing a reliable classification and functional description for the feruloyl esterase (FAE) enzyme family, whose members’ possess both structural and catalytic promiscuity. To establish functional subgrouping of feruloyl esterases a combination of computational and experimental resources was used. The major challenge for FAEs, which often share little sequence similarity to each other and show varied substrate specificity catalyzing the conserved reaction involving an ester bond, is to represent the function in a computationally accessible format. For the analysis of FAEs with overlapping and unique specificity to individual substrates there is a need to capture the chemical function in terms of overall substrate specificity. To meet this requirements, the classification of FAEs was performed by incorporating the information of sequence properties, common-feature based pharmacophore models and the knowledge of active-residue constellations of the FAE binding pockets. Using machine learning techniques an automated descriptor-based classification system for FAEs was proposed that resulted into 12 FAE families. Based on catalytic residue constellations these families were sub-grouped into 32 functionally distinct sub-families. The biological relevance of the descriptor based classification system was validated with experimental data obtained from biochemical and biophysical characterization of FAEs. Challenges in the selection of the appropriate docking algorithm and scoring function combination for the prediction of substrate specificity of FAEs were addressed using molecular docking approaches. The evaluation of 88 docking algorithm-scoring function combinations from leading commercial docking programs for substrate specificity predictions revealed large differences in their performances that could be attributed to the differences in properties of the target proteins. Using the combination of in silico approaches and enzymology, structure-function relationships of FAEs were probed, especially in case of an exceptional Multiple Nucleophilic Elbowed Esterase (MNEE) from Sorangium cellulosum with four functionally distinct and catalytically promiscuous active-sites. Finally, this thesis demonstrates the application of structure-function relationship studies to obtain insights on the promiscuity of enzymes in their evolutionary path and to explain their structure-activity changes in immobilization based biosynthetic reactions.





Keywords: feruloyl esterases, functional classification, enzyme promiscuity, molecular docking, descriptors, pharmacophore, catalytic triad, structure-function relationship, protein evolution, enzyme immobilization vi List of Publications This thesis is based on the work described in the following publications, referred to as

Paper I-V in the text:

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PAPER VIII: D.B.R.K. Gupta Udatha, Karina M. Madsen, Lisbeth Olsson, Gianni Panagiotou (2012) Synthesis of adenosine ferulate using a multiple nucleophilic elbowed enzyme from Sorangium cellulosum. Manuscript in preparation.

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Book Chapter PAPER X: D.B.R.K. Gupta Udatha, Simon Rasmussen, Thomas Sicheritz-Pontén, Gianni Panagiotou.

Targeted metabolic engineering guided by computational analysis of

Single Nucleotide Polymorphisms (SNPs). Systems Metabolic Engineering:

Methods and Protocols, Methods in Molecular Biology, vol. 985, Springer (2013).

viii Contribution summary

A summary of my contributions to each of the above listed publications is given below:

PAPER I: Designed and performed research; analyzed data; wrote the manuscript.

PAPER II: Designed and performed research; analyzed data; wrote the manuscript.

PAPER III: Designed and performed research; analyzed data; wrote the manuscript.

PAPER IV: Designed and performed research; analyzed data; wrote the manuscript.

PAPER V: Designed and performed in silico research work; analyzed data; co-authored the manuscript.

PAPER VI: Designed and performed in silico research work; analyzed data; co-authored the manuscript.

PAPER VII: Designed and performed in silico research work; analyzed data; co-authored the manuscript.

PAPER VIII: Designed and performed research; analyzed data; co-authored the manuscript.

PAPER IX: Designed and performed in silico research work; analyzed data; co-authored the manuscript.

PAPER X: Co-authored the book chapter.

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PREFACE …………………………………………………………………………………………... v

Abstract

………………………………………………………………………………………... vi LIST OF PUBLICATIONS ………………………………………………………………………. vii Contribution summary …………………………………………………………………………….. ix INTRODUCTION ………………………………………………………………………………... 1 CHAPTER 1 Enzyme Classification ……………………………………………………………… 7

1.1 Carbohydrate Active Enzymes ……………………………………………………………........ 11

1.2 Feruloyl esterases …………………………………………………………………………...…. 13 CHAPTER 2 Approaches for Classification of Enzymes beyond EC system …………………… 19

2.1 Sequence based classification of enzymes ………………………………………………............ 21

2.2 Structure based classification of enzymes ……………………………………………………… 22

2.3 Descriptor based classification of enzymes …………………………………………………….. 23 CHAPTER 3 Substrate Specificity Predictions ………………………………………………….. 29

3.1 Challenges in selecting molecular docking programs in prediction of substrate specificities …… 33

3.2 Validation of substrate specificity predictions …………………………………………………. 37 CHAPTER 4 Enzyme structure-function relationships ………………………………………….. 43

4.1 Enzyme Classification vs Enzyme Evolution: a case study ……………………………………... 46 CONCLUSIONS …………………………………………………………………………………. 55 PERSPECTIVES ………………………………………………………………………………….. 61 ACKNOWLEDGEMENTS ……………………………………………………………………… 65 REFERENCES ……………………………………………………………………………….…… 67 PAPER I - PAPER V

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The most difficult challenge in catalysis has been solved by living organisms through harnessing the specificity and reactivity of enzymes to build and degrade diverse molecules. Enzymes, the cell’s own catalysts, are challenging to understand in detail knowing that the efficiency of enzyme catalyzed reactions can reach ~109 M-1 sec-1 (i.e.

kcat/KM) with the substrate in solution (Wolfenden & Snider, 2001). This catalytic ability of an enzyme is located in its binding pocket or cavity, called active site (Koshland, 1958) that varies among different enzymes in size, shape and the constellation of catalytically active group of amino acid residues. These structural differences in enzymes are the roots for variations in the reactions they catalyze.

The presence of diverse substrates or nutrients in the habitat drives the evolution of species by imparting selection for new functions on enzymes to metabolize or recognize nutrients or toxic compounds in the environment, hence new enzyme activities arise in species that adapt to changing environments (Hegeman & Rosenberg, 1970). In fact, the plasticity of enzymes to attain new functions in the path of evolution has allowed living organisms to flourish in diverse environments (Zalatan & Herschlag, 2009). Even though a hypothesis that has been proposed back in 1976 (Jensen, 1976) indicate that enzymes can catalyze secondary reactions in addition to the one they are evolved to catalyze, still several biochemistry books define these macromolecules as being highly specific. Along with high substrate and reaction selectivity many enzymes are known today to be able to process several substrates, a property called enzyme promiscuity (Hult & Berglund, 2007). Developments in enzymology, from an early focus on the catalytic mechanisms of individual enzymes to recent efforts to understand enzyme action in the context of dynamic and functional biological systems consisting of many interacting molecules, are continuously filling the gaps in our knowledge on the Darwinian assumption of ‘one enzyme-one function’ evolution under which every protein has evolved to perform a

–  –  –

unique function that ultimately benefits the host organism (Reymond et al., 2009;

Simon & Cravatt, 2010).

Enzymes are generally classified either based on function or sequence/structure similarity. Therefore, there are a few questions to be solved: does the functional promiscuity shown by enzymes correlates to sequence or structural promiscuity? How can enzymes with substrate promiscuity be classified to develop a toolbox for biocatalytic applications? Do promiscuous enzymes possess more than one active site or an active site with flexible catalytic residue constellations?

The work described in this thesis demonstrates ways to deal with and understand enzymes with functional promiscuity 1 (Carbonell & Faulon, 2010). I present how the combination of in silico approaches and protein biochemistry can be used to classify and explore enzyme families with functional promiscuity. Feruloyl esterases (FAEs) are taken as a case study in this thesis, as they are featured by broad substrate specificity, a property that has been exploited in biosynthetic applications (presented in CHAPTER I). The framework presented in Figure 1 was followed to study the sequence-structure-function relationships in the feruloyl esterase group of enzymes and can be applied to understand any promiscuous enzyme family. The information provided on the molecular signatures for functional sub-classification of enzymes might also be of value for enzyme engineers in designing novel biocatalysts.

The specific aims of this work are:

1) To develop novel classification schemes to group enzymes into clusters or families that reflect their substrate specificity and to develop an automated classification system for enzyme families (PAPER I).

2) To develop substrate pharmacophores for the classified enzyme families and to further experimentally validate the developed pharmacophore features (PAPER I & III).

1 Enzymes often possess the capability of functional promiscuity, i.e. to catalyze more than one reaction (catalytic promiscuity) or to show broad substrate specificity (substrate promiscuity).

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Figure 1. A combined approach of in silico biology and enzymology towards classification, structural and functional analysis of enzymes with catalytic promiscuity.



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