Three-finger toxins (3FTX) are a group of peptides that affect multiple receptor types. One group of proteins affected by 3FTX are nicotinic acetylcholine receptors (nAChR). Structural information on how neurotoxins interact with nAChR is limited and is confined to a small group of neurotoxins. Therefore, in silico methods are valuable in understanding the interactions between 3FTX and different nAChR subtypes, but there are no established protocols to model 3FTX–nAChR interactions. We followed a homology modeling and protein docking protocol to address this issue and tested its success on three different systems. First, neurotoxin peptides co-crystallized with acetylcholine binding protein (AChBP) were re-docked to assess whether Rosetta protein–protein docking can reproduce the native poses. Second, experimental data on peptide binding to AChBP was used to test whether the docking protocol can qualitatively distinguish AChBP-binders from non-binders. Finally, we docked eight peptides with known α7 and muscle-type nAChR binding properties to test whether the protocol can explain the differential activities of the peptides at the two receptor subtypes. Overall, the docking protocol predicted the qualitative and some specific aspects of 3FTX binding to nAChR with reasonable success and shed light on unknown aspects of 3FTX binding to different receptor subtypes.

Although computational structure prediction has had great successes in recent years, it regularly fails to predict the interactions of large protein complexes with residue-level accuracy, or even the correct orientation of the protein partners. The performance of computational docking can be notably enhanced by incorporating experimental data from structural biology techniques. A rapid method to probe protein-protein interactions is hydrogen-deuterium exchange mass spectrometry (HDX-MS). HDX-MS has been increasingly used for epitope-mapping of antibodies (Abs) to their respective antigens (Ags) in the past few years. In this paper, we review the current state of HDX-MS in studying protein interactions, specifically Ab-Ag interactions, and how it has been used to inform computational structure prediction calculations. Particularly, we address the limitations of HDX-MS in epitope mapping and techniques and protocols applied to overcome these barriers. Furthermore, we explore computational methods that leverage HDX-MS to aid structure prediction, including the computational simulation of HDX-MS data and the combination of HDX-MS and protein docking. We point out challenges in interpreting and incorporating HDX-MS data into Ab-Ag complex docking and highlight the opportunities they provide to build towards a more optimized hybrid method, allowing for more reliable, high throughput epitope identification.

L'étude structurale de l'interactome cellulaire peut conduire à des découvertes intéressantes sur les bases moléculaires de certaines pathologies. La modélisation par homologie et l'amarrage de protéines ("protein docking") sont deux approches informatiques pour modéliser la structure tri-dimensionnelle (3D) d'une interaction protéine-protéine (PPI). Des études précédentes ont montré que ces deux approches donnent de meilleurs résultats quand des données expérimentales sur les PPIs sont prises en compte. Cependant, les données PPI ne sont souvent pas disponibles sous une forme facilement accessible, et donc ne peuvent pas être re-utilisées par les algorithmes de prédiction. Cette thèse présente une approche systématique fondée sur l'extraction de connaissances pour représenter et manipuler les données PPI disponibles afin de faciliter l'analyse structurale de l'interactome et d'améliorer les algorithmes de prédiction par la prise en compte des données PPI. Les contributions majeures de cette thèse sont de : (1) décrire la conception et la mise en oeuvre d'une base de données intégrée KBDOCK qui regroupe toutes les interactions structurales domaine-domaine (DDI); (2) présenter une nouvelle méthode de classification des DDIs par rapport à leur site de liaison dans l'espace 3D et introduit la notion de site de liaison de famille de domaines protéiques ("domain family binding sites" ou DFBS); (3) proposer une classification structurale (inspirée du système CATH) des DFBSs et présenter une étude étendue sur les régularités d'appariement entre DFBSs en terme de structure secondaire; (4) introduire une approche systématique basée sur le raisonnement à partir de cas pour modéliser les structures 3D des complexes protéiques à partir des DDIs connus. Une interface web (http://kbdock.loria.fr) a été développée pour rendre accessible le système KBDOCK / Understanding how the protein interactome works at a structural level could provide useful insights into the mechanisms of diseases. Comparative homology modelling and ab initio protein docking are two computational methods for modelling the three-dimensional (3D) structures of protein-protein interactions (PPIs). Previous studies have shown that both methods give significantly better predictions when they incorporate experimental PPI information. However, in general, PPI information is often not available in an easily accessible way, and cannot be re-used by 3D PPI modelling algorithms. Hence, there is currently a need to develop a reliable framework to facilitate the reuse of PPI data. This thesis presents a systematic knowledge-based approach for representing, describing and manipulating 3D interactions to study PPIs on a large scale and to facilitate knowledge-based modelling of protein-protein complexes. The main contributions of this thesis are: (1) it describes an integrated database of non-redundant 3D hetero domain interactions; (2) it presents a novel method of describing and clustering DDIs according to the spatial orientations of the binding partners, thus introducing the notion of "domain family-level binding sites" (DFBS); (3) it proposes a structural classification of DFBSs similar to the CATH classification of protein folds, and it presents a study of secondary structure propensities of DFBSs and interaction preferences; (4) it introduces a systematic case-base reasoning approach to model on a large scale the 3D structures of protein complexes from existing structural DDIs. All these contributions have been made publicly available through a web server (http://kbdock.loria.fr)

Computationally driven drug design/discovery efforts generally rely on accurate assessment of the forces that guide the molecular recognition process. HINT (Hydropathic INTeraction) is a natural force field, derived from experimentally determined partition coefficients that quantifies all non-bonded interactions in the biological environment, including hydrogen bonding, electrostatic and hydrophobic interactions, and the energy of desolvation. The overall goal of this work is to apply the HINT-based atomic level description of molecular systems to biologically important proteins, to better understand their biochemistry – a key step in exploiting them for therapeutic purposes. This dissertation discusses the results of three diverse projects: i) structural modeling of human sphingosine kinase 2 (SphK2, a novel anticancer target) and binding mode determination of an isoform selective thiazolidine-2,4-dione (TZD) analog; ii) structural modeling of human cytomegalorvirus (HCMV) alkaline nuclease (AN) UL98 (a novel antiviral target) and subsequent virtual screening of its active site; and iii) explicit treatment of interfacial waters during protein-protein docking process using HINT-based computational tools. SphK2 is a key regulator of the sphingosine-rheostat, and its upregulation /overexpression has been associated with cancer development. We report structural modeling studies of a novel TZD-analog that selectively inhibits SphK2, in a HINT analysis that identifies the key structural features of ligand and protein binding site responsible for isoform selectivity. The second aim was to build a three-dimensional structure of a novel HCMV target – AN UL98, to identify its catalytically important residues. HINT analysis of the interaction of 5’ DNA end at its active site is reported. A parallel aim to perform in silico screening with a site-based pharmacophore model, identified several novel hits with potentially desirable chemical features for interaction with UL98 AN. The majority of current protein-protein docking algorithms fail to account for water molecules involved in bridging interactions between partners, mediating and stabilizing their association. HINT is capable of reproducing the physical and chemical properties of such waters, while accounting for their energetic stabilizing contributions. We have designed a solvated protein-protein docking protocol that explicitly models the Relevant bridging waters, and demonstrate that more accurate results are obtained when water is not ignored.

L'étude structurale de l'interactome cellulaire peut conduire à des découvertes intéressantes sur les bases moléculaires de certaines pathologies. La modélisation par homologie et l'amarrage de protéines ("protein docking") sont deux approches informatiques pour modéliser la structure tri-dimensionnelle (3D) d'une interaction protéine-protéine (PPI). Des études précédentes ont montré que ces deux approches donnent de meilleurs résultats quand des données expérimentales sur les PPIs sont prises en compte. Cependant, les données PPI ne sont souvent pas disponibles sous une forme facilement accessible, et donc ne peuvent pas être re-utilisées par les algorithmes de prédiction. Cette thèse présente une approche systématique fondée sur l'extraction de connaissances pour représenter et manipuler les données PPI disponibles afin de faciliter l'analyse structurale de l'interactome et d'améliorer les algorithmes de prédiction par la prise en compte des données PPI. Les contributions majeures de cette thèse sont de : (1) décrire la conception et la mise en oeuvre d'une base de données intégrée KBDOCK qui regroupe toutes les interactions structurales domaine-domaine (DDI); (2) présenter une nouvelle méthode de classification des DDIs par rapport à leur site de liaison dans l'espace 3D et introduit la notion de site de liaison de famille de domaines protéiques ("domain family binding sites" ou DFBS); (3) proposer une classification structurale (inspirée du système CATH) des DFBSs et présenter une étude étendue sur les régularités d'appariement entre DFBSs en terme de structure secondaire; (4) introduire une approche systématique basée sur le raisonnement à partir de cas pour modéliser les structures 3D des complexes protéiques à partir des DDIs connus. Une interface web (http://kbdock.loria.fr) a été développée pour rendre accessible le système KBDOCK. Le système KBDOCK couvre plus de 2,700 hetero DDIs non-redondantes correspondant à 1,439 DFBSs localisés sur 947 domaines Pfam distincts. KBDOCK a permis de réaliser plusieurs études étendues. Par exemple, KBDOCK a été utilisé pour montrer que: (1) après de 70% de familles de domaines protéiques n'ont qu'un seul DFBS et les autres familles en ont un petit nombre seulement, ce qui suggère que les DDIs re-utilisent souvent les mêmes sites de liaison; (2) plus de 80% de DFBSs interagissent avec une seule famille de domaines protéiques et les autres DFBSs interagissent avec un petit nombre de familles, ce qui indique que la plupart des DFBSs sont principalement monogames dans leur interactions avec les autres domaines protéiques; (3) les DFBSs impliqués dans des interactions présentent des régularités en terme de structure secondaire, ce qui pourrait servir comme un descripteur complémentaire dans la prédiction d'interaction; (4) lorsque les domaines re-utilisent leur DFBS, le docking orienté vient améliorer les prédictions. Ainsi, KBDOCK constitue une ressource unifiée qui permet d'enrichir les connaissances sur l'interactome structural.

Thrombosis is the most important pathological process underlying many cardiovascular diseases, which are responsible for high mortality worldwide. In this theses the computer-aided design of new anti-thrombotic agents able to inhibit two types of receptors located on the surface of the platelets has been applied. The first one - αIIbβ3 - is responsible for the interaction of activated platelets with fibrinogen to form clots, whereas the second one - thromboxane A2 - is responsible for platelet activation by one of agonists excreted by activated platelets. To achieve this, different types of models have been developed using experimentally available information and structure of protein-ligand complexes. This concerns: QSAR models, structure-based and ligand-based 3D pharmacophore models, 2D pharmacophore models, shape-based and molecular field-based models. The ensemble of the developed models were used in virtual screening. This study resulted in suggestion of new potential antagonists of αIIbβ3 and thromboxane A2 receptors. Suggested antagonists of αIIbβ3 able to bind either open or closed form of the receptor have been synthesized and tested experimentally. Experiments show that they display high activity; moreover some of theoretically designed compounds are more efficient than Tirofiban - the commercialized drug molecule. The recommended antagonists of thromboxane A2 receptor have been already synthesized but biological tests have not been completed yet.

Macromolecular assemblies such as the ribosome, spliceosome, polymerases are imperative for cellular functions. The current understanding of these important machineries and many other assemblies at the molecular level is poor. The lack of structural data for many macromolecular assemblies further causes a bottleneck in understanding the cellular processes and the various disease manifestations. Hence, it is essential to characterize the structures and molecular architectures of these macromolecular assemblies. Though the number of 3-D structures for individual proteins structures or domains in the Protein Data Bank (PDB) is growing, the number of structures deposited for macromolecular assemblies is relatively poor. Hence, apart from the use of experimental techniques for characterizing macromolecular assembly structures, the use of computational techniques would help in supplementing the growth of macromolecular assembly structures. This thesis deals with the use of integrative approaches where computational methods are combined with experimental data to model and understand the mechanistic features of macromolecular assemblies with a special focus on a sub-complex of the spliceosome machinery. Chapter 1 of this thesis provides an introduction to protein-protein interactions and macromolecular assemblies. Further, the modelling of macromolecular assemblies using integrative methods are discussed, with a subsequent introduction to the spliceosome machinery. In chapter 2, modelling studies were performed on the proteins involved in the general amino acid control mechanism, which is triggered in yeast under amino acid starvation conditions. The proteins involved in the study were Gcn1, a ribosome binding protein and the RWD-domain containing proteins Gcn2, Yih1, Gir2 and Mtc5. From laboratory experiments it is known that in order for Gcn2 activation, an eIF2α kinase, its RWD-domain has to bind to Gcn1 and the residue Arg-2259 is important for this interaction. As the 3-D structure for the Gcn1 region containing Arg-2259 is not currently available, its 3-D structure was inferred using fold recognition and comparative modelling techniques. Further, in order to understand the Gcn2 RWD domain-Gcn1 molecular interaction, a complex structure was inferred by using a restrained protein-protein docking procedure. As the proteins, Yih1 and Gir2 are known to bind to Gcn1 using their RWD-domains, first the structures of the RWD-domain containing proteins including Mtc5 were inferred using a Gcn2 RWD domain NMR structure. Additionally, the Gcn1-Gcn2 complex was used to build a set of complexes to explain the binding of other RWD domain containing proteins Yih1, Gir2 and Mtc5. The important molecular interactions were obtained on analysing the interacting residues in these complexes. Thus, the Gcn1-Gcn2 interaction at the molecular level has been proposed for the first time. Future experiments guided by the protein-protein complex models and the proposed set of mutations should provide an understanding about the critical molecular interactions involved in the general amino acid control mechanism. Chapter 3 describes an integrative approach that was used to decipher a pseudo-atomic model of the closed form of human SF3b complex. SF3b is a multi-protein complex containing seven components – p14, SF3b49, SF3b155, SF3b145, SF3b130, SF3b14b and SF3b10. It recognizes the branch point adenosine in the pre-mRNA as part of U2 snRNP or U11/U12 di-snRNP in the spliceosome. Although, the cryo-EM map for human SF3b complex has been available for more than a decade, the structure and relative spatial arrangement of all components in the complex are not yet known. The integrative modelling approach used here involved utilizing structural data in the form of available X-ray and NMR structures, fold recognition and comparative modelling as well as currently available experimental datasets, along with the available cryo-EM density map to provide a model with high structural coverage. Hence, the molecular architecture of closed form human SF3b complex was derived that can now provide insights into the functioning of SF3b in splicing. This might also help the future high resolution structure determination efforts of the entire human spliceosome machinery In chapter 4, the molecular architecture of the closed form of SF3b complex obtained from the use of integrative modelling approach (Chapter 3) is extensively discussed. The structure-function relationships for some of the SF3b components based on the pseudo-atomic model has also been provided. In addition, the extreme flexibility associated with some of the SF3b components based on dynamics analysis has also been examined. Further, using an existing U11/U12 di-snRNP cryo-EM map and the closed form SF3b complex pseudo-atomic model, an open form of the SF3b complex was modelled and the component structures were fit into it. Hence, it was found that the transition between closed and open forms is primarily caused by a flap containing the HEAT repeat protein, SF3b155. This Protein is also known to harbour cancer causing mutations and has the potential to affect the Closed to open transition as well as SF3b complex structure and stability. Thus, this provides a framework for the future understanding of the closed to open transition in SF3b functioning within the spliceosome. Chapter 5 builds upon the integrative modelling approach (Chapter 3) that proposed the molecular architecture of the closed form of human SF3b complex and an open form of SF3b that was derived due to a flap opening of the closed form and which might help in accommodating RNA and other trans-acting factors within the U11/U12 di-snRNP (Chapter 4). In the current chapter, the SF3b open form and its interaction with the RNA elements is studied. The 5' end of U12 snRNA and its interaction with pre-mRNA in branch point duplex was modelled guided by the open form of SF3b that provided the necessary structural constraints and the RNA model is topologically consistent with the existing biochemical data. Further, utilizing the SF3b opens form-RNA model and the existing experimental knowledge, an extensive discussion has been provided on how the architecture of SF3b acts as a scaffold for U12 snRNA: pre-mRNA branch point duplex formation as well as its potential implications for branch point adenosine recognition fidelity. Moreover, the reasons for SF3b to be defined as a “fuzzy” complex - a complex with highly flexible folded regions along with intrinsically disordered regions is also discussed. Hence, the current work adds to the excellent developments made previously and deepens the understanding of the structure-function relationship of the human SF3b complex in the context of the spliceosome machinery. In chapter 6, a methodology has been proposed for the use of evolutionary conservation of protein-protein interfacial residues in multiple protein cryo-EM density based fitting of the protein components in the low-resolution density maps of multi-protein assemblies. First, the methodology was tested on a dataset of simulated density maps generated at four different resolutions -10, 15, 20 and 25 Å. On utilizing the evolutionary conservation scores obtained from multiple sequence alignments to score the fitted complexes, it was found that there was a decrease in the conservation scores when compared to that of the crystal structures, which were used to generate the simulated density maps. Further, the assessment of the multiple protein density fitting technique to align the actual protein-protein interface residues correctly using a performance metric called F-measure showed there was a decrease in performance as the resolutions became poorer. Hence, based on evolutionary conservations scores as well as F-measure the decrease in conservation scores or performance was found to be mainly due to the errors associated with the fitting process. Subsequently, a refinement methodology was designed involving the use of conservation scores, which improved the accuracy of the fitted models and the same, was observed in an experimental cryo-EM density test case of RyR1-FKBP12 complex. Hence, the conservation information acts as an effective filter to distinguish the incorrectly fitted structures and improves the accuracy of the fitting of the protein structures in the density maps. Thus, one can incorporate the conserved surface residues information in the current density fitting tools to reduce ambiguity and improve the accuracy of the macromolecular assembly structures determined using cryo-EM. In the concluding chapter 7, the learnings on the structural and mechanistic features of protein assemblies obtained from the use of computational techniques and integration of experimental datasets is discussed. In chapter 2, the modelling of a binary macromolecular complex such as the Gcn1-Gcn2 complex was performed using computational structure prediction strategies to understand the molecular basis of its interaction. Due to the potential inaccuracies which can exist in computational modelling, the chapters 3 to 5 dealt with the use of integrative approaches, primarily guided by the cryo-EM map, in order to decipher the molecular architecture of the human SF3b complex in the closed and open forms as well as its contribution for branch point adenosine recognition. Based on the extensive experience gained in modelling of assemblies using cryo-EM data in the previous chapters, a new method has been proposed on the use of evolutionary conservation information to improve the accuracy of cryo-EM density based fitting. Hence, these studies have provided strategies for modelling macromolecular assemblies as well as a deeper understanding of its mechanistic features.

L'ingénierie enzymatique est un outil très avantageux dans l'industrie biotechnologique. Elle permet d'adapter les enzymes à une activité ou à une condition de réaction spécifique. En outre, elle peut permettre de déchiffrer les éléments clés qui ont facilité leur modification. Bien que l'ingénierie enzymatique soit largement pratiquée, elle comporte encore plusieurs goulets d'étranglement. Certains de ces goulets d'étranglement sont techniques, comme le développement de méthodologies pour la création de banques de mutations ciblées ou la réalisation de criblages à haut débit, et d'autres sont conceptuels, comme le déchiffrage des caractéristiques clés pertinentes d'une protéine cible pour la réussite d'un projet d'ingénierie. Parmi ces défis, l'épistasie intra-génique, ou la non-additivité des effets phénotypiques des mutations, est une caractéristique qui entrave grandement la prévisibilité. L'amélioration de l'ingénierie enzymatique nécessite une approche multidisciplinaire qui inclut une meilleure compréhension des relations structure-fonction-évolution. Cette thèse vise à contribuer à l'avancement de l'ingénierie enzymatique en étudiant deux systèmes modèles. Premièrement, des variantes dynamiques de la ß-lactamase TEM-1 ont été choisies pour étudier le lien entre la dynamique des protéines et l'évolution. La ß-lactamase TEM-1 a été largement caractérisée dans la littérature, ce qui s'est traduit par des connaissances approfondies sur son mécanisme de réaction, ses caractéristiques structurelles et son évolution. Les variantes de la ß-lactamase TEM-1 utilisées comme système modèle dans cette thèse ont été largement caractérisées, montrant une dynamique accrue à l'échelle temporelle pertinente pour la catalyse (µs à ms) mais maintenant la reconnaissance du substrat. Dans cette thèse, l'évolution in vitro de ces variantes dynamiques a été réalisée par des cycles itératifs de mutagenèse et de sélection aléatoires pour permettre une exploration impartiale du paysage de ‘fitness’. Nous démontrons que la présence de ces mouvements particuliers au début de l'évolution a permis d'accéder à des voies de mutations connues. De plus, des interactions épistatiques connues ont été introduites dans les variantes dynamiques. Leur caractérisation in silico et cinétique a révélé que les mouvements supplémentaires sur l'échelle de temps de la catalyse ont permis d'accéder à des conformations conduisant à une fonction améliorée, comme dans le TEM-1 natif. Dans l'ensemble, nous démontrons que l'évolution de la b-lactamase TEM-1 vers une nouvelle fonction est compatible avec divers mouvements à l'échelle de temps µs à ms. Il reste à savoir si cela peut se traduire par d'autres enzymes ayant un potentiel biotechnologique. Deuxièmement, la lipase Cal-A, pertinente sur le plan industriel, a été choisie pour identifier les caractéristiques qui pourraient faciliter son ingénierie. La lipase Cal-A présente des caractéristiques telles que la polyvalence du substrat et une grande stabilité thermique et réactivité qui la rendent attrayante pour la modification des triglycérides ou la synthèse de molécules pertinentes dans les industries alimentaire et pharmaceutique. Contrairement à TEM-1, la plupart des études d'évolution in vitro de la lipase Cal-A ont été réalisées dans un but industriel, avec une exploration limitée de l'espace de mutation. Par conséquent, les caractéristiques qui définissent la fonction de la lipase Cal-A restent insaisissables. Dans cette thèse, nous faisons état de la mutagenèse ciblée de la lipase Cal-A, confirmant l'existence d'une région clé pour la reconnaissance du substrat. Cela a été fait en combinant une nouvelle méthodologie de création de bibliothèque basée sur l'assemblage Golden-gate avec une visualisation structurelle basée sur des scripts pour identifier et cartographier les mutations sélectionnées dans la structure 3D. La caractérisation et la déconvolution de deux des plus aptes ont révélé l'existence d'une épistasie dans l'évolution de la lipase Cal-A vers une nouvelle fonction. Dans l'ensemble, nous démontrons que l’identification d'une variété de propriétés suite à la mutagenèse ciblée peut grandement améliorer la connaissance d'une enzyme. Cette information peut être appliquée pour améliorer l'efficacité de l'ingénierie dirigée. / Enzyme engineering is a tool with great utility in the biotechnological industry. It allows to tailor enzymes to a specific activity or reaction condition. In addition, it can allow to decipher key elements that facilitated their modification. While enzyme engineering is extensively practised, it still entails several bottlenecks. Some of these bottlenecks are technical such as the development of methodologies for creating targeted mutational libraries or performing high-throughput screening and some are conceptual such as deciphering the key relevant features in a target protein for a successful engineering project. Among these challenges, intragenic epistasis, or the non-additivity of the phenotypic effects of mutations, is a feature that greatly hinders predictability. Improving enzyme engineering needs a multidisciplinary approach that includes gaining a better understanding of structure-function-evolution relations. This thesis seeks to contribute in the advancement of enzyme engineering by investigating two model systems. First, dynamic variants of TEM-1 ß-lactamase were chosen to investigate the link between protein dynamics and evolution. TEM-1 ß-lactamase has been extensively characterized in the literature, which has translated into extensive knowledge on its reaction mechanism, structural features and evolution. The variants of TEM-1 ß-lactamase used as model system in this thesis had been extensively characterized, showing increased dynamics at the timescale relevant to catalysis (µs to ms) but maintaining substrate recognition. In this thesis, in vitro evolution of these dynamic variants was done by iterative rounds of random mutagenesis and selection to allow an unbiased exploration of the fitness landscape. We demonstrate that the presence of these particular motions at the outset of evolution allowed access to known mutational pathways. In addition, known epistatic interactions were introduced in the dynamic variants. Their in silico and kinetic characterization revealed that the additional motions on the timescale of catalysis allowed access to conformations leading to enhanced function, as in native TEM-1. Overall, we demonstrate that the evolution of TEM-1 b-lactamase toward new function is compatible with diverse motions at the µs to ms timescale. Whether this can be translated to other enzymes with biotechnological potential remains to be explored. Secondly, the industrially relevant Cal-A lipase was chosen to identify features that could facilitate its engineering. Cal-A lipase presents characteristics such as substrate versatility and high thermal stability and reactivity that make it attractive for modification of triglycerides or synthesis of relevant molecules in the food and pharmaceutical industries. Contrary to TEM-1, most in vitro evolution studies of Cal-A lipase have been done towards an industrially-specified goal, with limited exploration of mutational space. As a result, features that define function in Cal-A lipase remain elusive. In this thesis, we report on focused mutagenesis of Cal-A lipase, confirming the existence of a key region for substrate recognition. This was done by combining a novel library creation methodology based on Golden-gate assembly with script-based structural visualization to identify and map the selected mutations into the 3D structure. The characterization and deconvolution of two of the fittest revealed the existence of epistasis in the evolution of Cal-A lipase towards new function. Overall, we demonstrate that mapping a variety of properties following mutagenesis targeted to specific regions can greatly improve knowledge of an enzyme that can be applied to improve the efficiency of directed engineering.