Prediction of Enzyme Mutant Activity Using Computational Mutagenesis and Incremental Transduction

Wet laboratory mutagenesis to determine enzyme activity changes is expensive and time consuming. This paper expands on standard one-shot learning by proposing an incremental transductive method (T2bRF) for the prediction of enzyme mutant activity during mutagenesis using Delaunay tessellation and 4-body statistical potentials for representation. Incremental learning is in tune with both eScience and actual experimentation, as it accounts for cumulative annotation effects of enzyme mutant activity over time. The experimental results reported, using cross-validation, show that overall the incremental transductive method proposed, using random forest as base classifier, yields better results compared to one-shot learning methods. T2bRF is shown to yield 90% on T4 and LAC (and 86% on HIV-1). This is significantly better than state-of-the-art competing methods, whose performance yield is at 80% or less using the same datasets

Optimization of Recombination Methods and Expanding the Utility of Penicillin G Acylase

Protein engineering can be performed by combinatorial techniques (directed evolution) and data-driven methods using machine-learning algorithms. The main characteristic of directed evolution (DE) is the application of an effective and efficient screen or selection on a diverse mutant library. As it is important to have a diverse mutant library for the success of DE, we compared the performance of DNA-shuffling and recombination PCR on fluorescent proteins using sequence information as well as statistical methods. We found that the diversity of the libraries DNA-shuffling and recombination PCR generates were dependent on type of skew primers used and sensitive to nucleotide identity levels between genes. DNA-shuffling and recombination PCR produced libraries with different crossover tendencies, suggesting that the two protocols could be used in combination to produce better libraries. Data-driven protein engineering uses sequence, structure and function data along with analyzed empirical activity information to guide library design. Boolean Learning Support Vector Machines (BLSVM) to identify interacting residues in fluorescent proteins and the gene templates were modified to preserve interactions post recombination. By site-directed mutagenesis, recombination and expression experiments, we validated that BLSVM can be used to identify interacting residues and increase the fraction of active proteins in the library. As an extension to the above experiments, DE was applied on monomeric Red Fluorescent Proteins to improve its spectral characteristics and structure-guided protein engineering was performed on penicillin G acylase (PGA), an industrially relevant catalyst, to change its substrate specificity.Ph.D.Committee Chair: Bommarius, Andreas; Committee Member: Hu, Wei-Shou; Committee Member: Lee, Jay; Committee Member: Lutz, Stefan; Committee Member: Prausnitz, Mar

Connectable Components for Protein Design

Protein design requires reusable, trustworthy, and connectable parts in order to scale to complex challenges. The recent explosion of protein structures stored within the Protein Data Bank provides a wealth of small motifs we can harvest, but we still lack tools to combine them into larger proteins. Here I explore two approaches for connecting reusable protein components on two different length scales. On the atomic scale, I build an interactive search engine for connecting chemical fragments together. Protein fragments built using this search engine recapitulate native-like protein assemblies that can be integrated into existing protein scaffolds using backbone search engines such as MaDCaT. On the protein domain scale, I quantitatively dissect structural variations in two-component systems in order to extract general principles for engineering interfacial flexibility between modular four-helix bundles. These bundles exhibit large scissoring motions where helices move towards or away from the bundle axis and these motions propagate across domain boundaries. Together, these two approaches form the beginnings of a multiscale methodology for connecting reusable protein fragments where there is a constant interplay and feedback between design of atomic structure, secondary structure, and tertiary structure. Rapid iteration, visualization, and search glue these diverse length scales together into a cohesive whole

Improving flavonoid production in Saccharomyces cerevisiae using synthetic biology tools

Flavonoids are plant secondary metabolites and represent one of the largest classes of natural products. Due to their health-beneficial properties, they have found potential applications in foods, beverages, cosmetics, and pharmaceuticals. Currently, their production is based on extraction from plant material. However, the low abundance of flavonoids in nature hinders efficient extraction and purification, thus inhibiting their market expansion. Chemical synthesis, although possible, relies on the use of harmful chemicals, harsh operating conditions, and high energy consumption.Metabolic engineering of microorganisms to develop so-called “microbial cell factories” has gained increasing attention as a more efficient and sustainable way to produce a variety of chemicals – including flavonoids. Saccharomyces cerevisiae (baker’s yeast) is one of the most well-studied and widely applied eukaryotic organisms for this endeavor. The fact that yeast shares cellular similarities to plants makes it a suitable host for the heterologous expression of flavonoid biosynthetic pathways. In this thesis, I present our efforts to improve the production of flavonoids in S. cerevisiae through the development and application of several synthetic biology tools. First, transcription factor-based biosensors for the isoflavonoid genistein and the flavonoid precursor p-coumaroyl-CoA were established. The latter sensor was used to devise a dynamic regulation strategy for the production of naringenin, a central flavanone and precursor for many flavanone derivatives. Cell growth was improved and naringenin titers were increased significantly. Next, a malonate assimilation pathway was implemented in yeast to enhance the supply of malonyl-CoA, an important precursor for all flavonoid compounds. By expressing a heterologous malonate transporter and malonyl-CoA synthetase, I constructed strains able to grow on externally supplied malonate. The malonate transporter was further evolved through targeted in vivo mutagenesis and beneficial mutations were identified through growth-based enrichment under selective conditions. Lastly, the production of the dihydrochalcone phloretin was explored. Its biosynthesis was accompanied by substantial byproduct formation and product degradation in the yeast cultivation medium. Different strategies, including enzyme scaffolding and antioxidant supplementation, were investigated to improve yeast-based production.Taken together, I addressed some significant challenges within microbial flavonoid production and showcased how synthetic biology tools may overcome these obstacles

Investigation of the Function and Regulation of ABC Transporters

The copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the authorATP-Binding-Cassette (ABC) transporters are primary active pumps that typically couple the binding and hydrolysis of ATP to the translocation of compounds across cellular membranes. Some, like ABCB1, ABCC1 and ABCC3, are polyspecific and can efflux clinically important drugs which may contribute to their therapeutic failure. In this study I have investigated (1) the mechanism of ABC transporter function, (2) studied the potential for regulation by ubiquitin ligases (both using ABCB1 as a model), and (3) tested the involvement of ABCC1 and ABCC3 in autocrine signalling in cancer. (1) In 1966, Jardetzky et. al [1] proposed that membrane pumps function by exposing their ligand-binding pocket alternately on different sides of the membrane. For ABC transporters, this coupling of the aspect and affinity of the ligand-binding cavities of the two transmembrane domains (TMDs) to the ATP catalytic cycle of the two nucleotide-binding domains (NBDs) is fundamental to the transport mechanism but is poorly understood at the molecular level. Structure data suggest signals are transduced through intracellular loops of the TMDs which slot into grooves on the top surface of the NBDs. At the base of these grooves is the Q-loop. By analysing the function of Q-loop mutants in combination with ligand binding cavity mutants I have discovered that the Q-loops are crucial to the transport cycle and that they are required to couple ligand binding to conformational changes at the NBDs necessary to drive the transporter into an inward closed state. 4 (2) ABCB1 is known to be a key component of chemical barrier separating the circulation from the cerebrospinal fluid. It has also been reported to transport β-amyloid across the lumenal membrane and into the circulation. Loss of ABCB1 from the barrier with age has therefore been suggested to play a role in Alzheimer’s Disease. The ubiquitin ligase Nedd4-1 has been implicated in the post-translational regulation of ABCB1 abundance in cells. Here, I report that ABCB1 can be ubiquitinated by Nedd4-1 in vitro and identify the residues modified (by mass spectrometry). (3) Lysophosphatidylinositol (LPI) is an autocrine metabolite produced by cancer cells that binds to the G-protein coupled transmembrane receptor GPR55 on the surface of cells. Stimulation of GPR55 activates a signalling cascade that induces proliferation and metastases of the cancer cells. How LPI is released from the cells was not known. In this study I show that ABCC1 and ABCC3, which are known to be expressed in ovarian and pancreatic cancers, can transport LPI into inside-out vesicles suggesting a new role for these “drug resistance” transporters in cancer biology

Stability-mediated epistasis constrains the evolution of an influenza protein.

John Maynard Smith compared protein evolution to the game where one word is converted into another a single letter at a time, with the constraint that all intermediates are words: WORD→WORE→GORE→GONE→GENE. In this analogy, epistasis constrains evolution, with some mutations tolerated only after the occurrence of others. To test whether epistasis similarly constrains actual protein evolution, we created all intermediates along a 39-mutation evolutionary trajectory of influenza nucleoprotein, and also introduced each mutation individually into the parent. Several mutations were deleterious to the parent despite becoming fixed during evolution without negative impact. These mutations were destabilizing, and were preceded or accompanied by stabilizing mutations that alleviated their adverse effects. The constrained mutations occurred at sites enriched in T-cell epitopes, suggesting they promote viral immune escape. Our results paint a coherent portrait of epistasis during nucleoprotein evolution, with stabilizing mutations permitting otherwise inaccessible destabilizing mutations which are sometimes of adaptive value. DOI:http://dx.doi.org/10.7554/eLife.00631.001

Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics

This book is a collection of original research articles in the field of computer-aided drug design. It reports the use of current and validated computational approaches applied to drug discovery as well as the development of new computational tools to identify new and more potent drugs

Structural phylogeny by profile extraction and multiple superimposition using electrostatic congruence as a discriminator

Phylogenetic analysis of proteins using multiple sequence alignment (MSA) assumes an underlying evolutionary relationship in these proteins which occasionally remains undetected due to considerable sequence divergence. Structural alignment programs have been developed to unravel such fuzzy relationships. However, none of these structure based methods have used electrostatic properties to discriminate between spatially equivalent residues. We present a methodology for MSA of a set of related proteins with known structures using electrostatic properties as an additional discriminator (STEEP). STEEP first extracts a profile, then generates a multiple structural superimposition providing a consolidated spatial framework for comparing residues and finally emits the MSA. Residues that are aligned differently by including or excluding electrostatic properties can be targeted by directed evolution experiments to transform the enzymatic properties of one protein into another. We have compared STEEP results to those obtained from a MSA program (ClustalW) and a structural alignment method (MUSTANG) for chymotrypsin serine proteases. Subsequently, we used PhyML to generate phylogenetic trees for the serine and metallo-β-lactamase superfamilies from the STEEP generated MSA, and corroborated the accepted relationships in these superfamilies. We have observed that STEEP acts as a functional classifier when electrostatic congruence is used as a discriminator, and thus identifies potential targets for directed evolution experiments. In summary, STEEP is unique among phylogenetic methods for its ability to use electrostatic congruence to specify mutations that might be the source of the functional divergence in a protein family. Based on our results, we also hypothesize that the active site and its close vicinity contains enough information to infer the correct phylogeny for related proteins

Dissecting molecular mechanisms of disease in the wheat pathogen, Parastagonospora nodorum

Dissecting molecular mechanisms of disease in the wheat pathogen, Parastagonospora nodorum Parastagonospora nodorum is a wheat specific pathogen that causes annual losses to the Australian wheat industry in excess of $100 million AUD. This necrotrophic fungus kills the host tissue generating necrotic lesions within which fruiting bodies develop, spreading spores and continuing the disease cycle. This polycyclic infection cycle leads to field epidemics resulting in the losses to growers. Sporulation and virulence are the two crucial aspects for disease development in the P. nodorum-wheat pathosystem and form the basis of this project. A forward genetics approach was employed to discover novel mechanisms by which P. nodorum facilitates infection on wheat. A library of random P. nodorum insertion mutants was generated, and subsequently screened for gain and loss of virulence phenotypes on non-susceptible and susceptible wheat cultivars. From a library of 950 transformants seven displayed a consistent avirulent phenotype on the susceptible wheat cultivar. To identify the disrupted loci leading to avirulence, genomes of the seven avirulent P. nodorum strains were sequenced elucidating a Catechol-1,2-dioxygenase and a Copper dependent amine oxidase. To complement the virulence investigation, a combined transcriptomics and metabolomics approach was employed to decipher sporulation in this pathogen. This is of particular interest as the canonical sporulation pathways in other, model fungi, were previously shown to be not applicable in P. nodorum. A differential gene analysis of fungal material collected at critical developmental time points identified several key genes involved in initiating a sporulation cascade. Notably, a WetA homolog was identified, along with an uncharacterised Aquaporin-like protein and a Pr1-like protein. Metabolomics and subsequent sporulation assays revealed a polyamine pathway plays an integral role in initiating and coordinating asexual development of P. nodorum

Simulations of Chemical Catalysis

This dissertation contains simulations of chemical catalysis in both biological and heterogeneous contexts. A mixture of classical, quantum, and hybrid techniques are applied to explore the energy profiles and compare possible chemical mechanisms both within the context of human and bacterial enzymes, as well as exploring surface reactions on a metal catalyst. A brief summary of each project follows. Project 1 — Bacterial Enzyme SpvC The newly discovered SpvC effector protein from Salmonella typhimurium interferes with the host immune response by dephosphorylating mitogen-activated protein kinases (MAPKs) with a -elimination mechanism. The dynamics of the enzyme substrate complex of the SpvC effector is investigated with a 3.2 ns molecular dynamics simulation, which reveals that the phosphorylated peptide substrate is tightly held in the active site by a hydrogen bond network and the lysine general base is positioned for the abstraction of the alpha hydrogen. The catalysis is further modeled with density functional theory (DFT) in a truncated active-site model at the B3LYP/6-31 G(d,p) level of theory. The truncated model suggested the reaction proceeds via a single transition state. After including the enzyme environment in ab initio QM/MM studies, it was found to proceed via an E1cB-like pathway, in which the carbanion intermediate is stabilized by an enzyme oxyanion hole provided by Lys104 and Tyr158 of SpvC. Project 2 — Human Enzyme CDK2 Phosphorylation reactions catalyzed by kinases and phosphatases play an indispensable role in cellular signaling, and their malfunctioning is implicated in many diseases. Ab initio quantum mechanical/molecular mechanical studies are reported for the phosphoryl transfer reaction catalyzed by a cyclin-dependent kinase, CDK2. Our results suggest that an active-site Asp residue, rather than ATP as previously proposed, serves as the general base to activate the Ser nucleophile. The corresponding transition state features a dissociative, metaphosphate-like structure, stabilized by the Mg(II) ion and several hydrogen bonds. The calculated free-energy barrier is consistent with experimental values. Project 3 — Bacterial Enzyme Anthrax Lethal Factor In this dissertation, we report a hybrid quantum mechanical and molecular mechanical study of the catalysis of anthrax lethal factor, an important first step in designing inhibitors to help treat this powerful bacterial toxin. The calculations suggest that the zinc peptidase uses the same general base-general acid mechanism as in thermolysin and carboxypeptidase A, in which a zinc-bound water is activated by Glu687 to nucleophilically attack the scissile carbonyl carbon in the substrate. The catalysis is aided by an oxyanion hole formed by the zinc ion and the side chain of Tyr728, which provide stabilization for the fractionally charged carbonyl oxygen. Project 4 — Methanol Steam Reforming on PdZn alloy Recent experiments suggested that PdZn alloy on ZnO support is a very active and selective catalyst for methanol steam reforming (MSR). Plane-wave density functional theory calculations were carried out on the initial steps of MSR on both PdZn and ZnO surfaces. Our calculations indicate that the dissociation of both methanol and water is highly activated on \ufb02at surfaces of PdZn such as (111) and (100), while the dissociation barriers can be lowered significantly by surface defects, represented here by the (221), (110), and (321) faces of PdZn. The corresponding processes on the polar Zn-terminated ZnO(0001) surfaces are found to have low or null barriers. Implications of these results for both MSR and low temperature mechanisms are discussed