An in silico design algorithm has been developed to design binding ligands for protein targets of known three-dimensional structure. In this method, the binding energy of a candidate ligand is used to ascribe it a probability of binding. A sample of a virtual library of candidate ligands is then used to ascribe implicit weights to all the ligands in the library. These weights are used to obtain virtual sub-libraries which collectively carry a greater probability to bind to the target. This algorithm is presented along with validation studies on the different algorithmic components, demonstrating how optimization of the design method can be best achieved.

Semi-synthetic β-lactam antibiotics are the most prescribed class of antibiotics in the world. Chemical coupling of a β-lactam moiety with an acyl side chain has dominated the industrial production of semi-synthetic β-lactam antibiotics since their discovery in the early 1960s. Enzymatic coupling of a β-lactam moiety with an acyl side chain can be accomplished in a process that is much more environmentally benign but also results in a much lower yield. The goal of the research presented in this dissertation is to improve the enzymatic synthesis of β-lactam antibiotics via reaction engineering, medium engineering and data-drive protein engineering. Reaction engineering was employed to demonstrate that the hydrolysis of penicillin G to produce the β-lactam nucleus 6-aminopenicillanic acid (6-APA), and the synthesis of ampicillin from 6-APA and (R)-phenylglycine methyl ester ((R)-PGME), can be combined in a cascade conversion. In this work, penicillin G acylase (PGA) was utilized to catalyze the hydrolysis step, and PGA and α-amino ester hydrolase (AEH) were both studied to catalyze the synthesis step. Two different reaction configurations and various relative enzyme loadings were studied. Both configurations present a promising alternative to the current two-pot set-up which requires intermittent isolation of the intermediate, 6-APA. Medium engineering is primarily of interest in β-lactam antibiotic synthesis as a means to suppress the undesired primary and secondary hydrolysis reactions. The synthesis of ampicillin from 6-APA and (R)-PGME in the presence of ethylene glycol was chosen for study after a review of the literature. It was discovered that the transesterification product of (R)-PGME and ethylene glycol, (R)-phenylglycine hydroxyethyl ester, is transiently formed during the synthesis reactions. This never reported side reaction has the ability to positively affect yield by re-directing a portion of the consumption of (R)-PGME to an intermediate that could be used to synthesize ampicillin, rather than to an unusable hydrolysis product. Protein engineering was utilized to alter the selectivity of wild-type PGA with respect to the substituent on the alpha carbon of its substrates. Four residues were identified that had altered selectivity toward the desired product, (R)-ampicillin. Furthermore, the (R)-selective variants improved the yield from pure (R)-PGME up to 2-fold and significantly decreased the amount of secondary hydrolysis present in the reactions. Overall, we have expanded the applicability of PGA and AEH for the synthesis of semi-synthetic β-lactam antibiotics. We have shown the two enzymes can be combined in a novel one-pot cascade, which has the potential to eliminate an isolation step in the current manufacturing process. Furthermore, we have shown that the previously reported ex-situ mixed donor synthesis of ampicillin for PGA can also occur in-situ in the presence of a suitable side chain acyl donor and co-solvent. Finally, we have made significant progress towards obtaining a selective PGA that is capable of synthesizing diastereomerically pure semi-synthetic β-lactam antibiotics from racemic substrates.

The enzymatic hydrolysis of cellulose to glucose by cellulases is one of the major steps in the conversion of lignocellulosic biomass to biofuel. This hydrolysis by cellulases, a heterogeneous reaction, currently suffers from some major limitations, most importantly a dramatic rate slowdown at high degrees of conversion in the case of crystalline cellulose. Various rate-limiting factors were investigated employing experimental as well as computational studies. Cellulose accessibility and the hydrolysable fraction of accessible substrate (a previously undefined and unreported quantity) were shown to decrease steadily with conversion, while cellulose reactivity, defined in terms of hydrolytic activity per amount of actively adsorbed cellulase, remained constant. Faster restart rates were observed on partially converted cellulose as compared to uninterrupted hydrolysis rates, supporting the presence of an enzyme clogging phenomenon. Cellulose crystallinity is a major substrate property affecting the rates, but its quantification has suffered from lack of consistency and accuracy. Using multivariate statistical analysis of X-ray data from cellulose, a new method to determine the degree of crystallinity was developed. Cel7A CBD is a promising target for protein engineering as cellulose pretreated with Cel7A CBDs exhibits enhanced hydrolysis rates resulting from a reduction in crystallinity. However, for Cel7A CBD, a high throughput assay is unlikely to be developed. In the absence of a high throughput assay (required for directed evolution) and extensive knowledge of the role of specific protein residues (required for rational protein design), the mutations need to be picked wisely, to avoid the generation of inactive variants. To tackle this issue, a method utilizing the underlying patterns in the sequences of a protein family has been developed.

<p>The recent development of methods for constructing andhandling large collections (libraries) of proteins, from whichvariants with desired traits can be isolated, hasrevolutionized the field of protein engineering. Key elementsof such methods are the various ways in which the genotypes(the genes) and the phenotypes (the encoded proteins) arephysically linked during the process. In one section of thework underlying this thesis, one such technique (phagedisplay), was used to isolateand identify protein librarymembers based on their catalytic or target molecule-bindingproperties.</p><p>In a first study, phage display libraries of the lipolyticenzyme Lipolase from Thermomyces lanuginosa were constructed,the objective being to identify variants with improvedcatalytic efficiency in the presence of detergents. Toconstruct the libraries, nine positions were targeted for codonrandomization, all of which are thought to be involved in theconformational change-dependent enzyme activation that occursat water-lipid interfaces. The aim was to introduce two tothree amino acid mutations at these positions per lipase gene.After confirming that the wt enzyme could be functionallydisplayed on phage, selections with the library were performedutilizing a mechanism-based biotinylated inhibitor in thepresence of a detergent formulation. According to rhodamineB-based activity assays, the fraction of active clonesincreased from 0.2 to 90 % over three rounds of selection.Although none of the variants selected using this approachshowed increased activity, in either the presence or absence ofdetergent compared to the wild type enzyme, the resultsdemonstrated the possibility of selecting variants of theenzyme based on catalytic activity.</p><p>In the following work, phage libraries of the StaphylococcalProtein A (SPA)-derived Z-domain, constructed by randomizationof 13 surface-located positions, were used to isolate Z domainvariants (affibodies) with novel binding specificities. Astargets for selections, the parental SPA domains as well as twopreviously selected affibodies directed against two unrelatedtarget proteins were used. Binders of all three targets wereisolated with affinities (KD) in the range of 2-0.5 µM.One SPA binding affibody (Z_SPA-1) was shown to bind to each of the fivehomologous native IgG-binding domains of SPA, as well as theZdomain used as the scaffold for library constructions.Furthermore, the Z_SPA-1affibody was shown to compete with one of thenative domains of SPA for binding to the Fc part of humanantibodies, suggesting that the Z_SPA-1affibody bound to the Fc-binding surface ofthe Z domain. The majority of the affibodies isolated in theother two selections using two different affibodies as targets,showed very little or no binding to unrelated affibodies,indicating that the binding was directed to the randomizedsurface of their respective targets, analogously toanti-idiotypic antibodies.</p><p>The structure of the wild type Z domain/Z_SPA-1affibody co-complex was determined by x-raycrystallography, which confirmed the earlier findings in thatthe affibody Z_SPA-1affibody was shown to bind to the Fc bindingsurface of the Z domain. Further, both the Z domain and the Z_SPA-1affibody had very similar three helix-bundletopologies, and the interaction surface involved ten out of thethirteen randomized residues, with a central hydrophobic patchsurrounded by polar residues. In addition, the interactionsurface showed a surprisingly high shape complementarity, giventhe limited size of the library used for selections. The Z_SPA-1affibody was further investigated for use invarious biotechnological applications. In one study, the Z_SPA-1affibody was successfully recruited as a novelaffinity gene fusion partner for production, purification anddetection of cDNA-encoded recombinant proteins using anSPA-based medium for affinity chromatography. Further, the SPAbinding capability of the Z_SPA-1affibody was employed for site-specific andreversible docking of Z_SPA-1affibody-tagged reporter proteins onto an SPAfusion protein anchored to a cellulose surface via acellulose-binding moiety. These generated protein complexesresembles the architecture of so-called cellulosomes observedin cellulolytic bacteria. The results suggest it may bepossible to use anti-idiotypic affibody-binding protein pairsas modules to build other self-assembling types of proteinnetworks.</p><p><b>Keywords:</b>phage display, selection, mechanism-basedinhibitor, affinity domains, crystal structure, Staphylococcusaureus protein A, affinity chromatography, anti-idiotypicbinding pairs, affibody, combinatorial, protein engineering,lipase, cellulosome, assembly.</p>

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 78-86).

Pharmaceutical biotechnology has been emerging as a defined, increasingly important area of science dedicated to the discovery and delivery of drugs and therapies for the treatment of various human diseases. In contrast to the advancement in pharmaceutical biotechnology, current drug discovery efforts are facing unprecedented challenges. Difficulties in identifying novel drug targets and developing effective and safe drugs are closely related to the complexity of the network of interacting human proteins. Protein-protein interactions mediate virtually all cellular processes. Therefore both identification and understanding of protein-protein interactions are essential to the process of deciphering disease mechanisms and developing treatments. Unfortunately, our current knowledge and understanding of the human interactome is largely incomplete. Most of the unknown protein-protein interactions are expected to be weak and/or transient, hence are not easily identified. These unknown or uncharacterized interactions could affect the efficacy and toxicity of drug candidates, contributing to the high rate of failure. In an attempt to facilitate the ongoing efforts in drug discovery, we describe herein a series of novel methods and their applications addressing the broad topic of protein-protein interactions. We have developed a highly efficient site-specific protein cross-linking technology mediated by the genetically incorporated non-canonical amino acid L-DOPA to facilitate the identification and characterization of weak protein-protein interactions. We also established a protocol to incorporate L-DOPA into proteins in mammalian cells to enable in vivo site-specific protein cross-kinking. We then applied the DOPA-mediated cross-linking methodology to design a protein probe which can potentially serve as a diagnostic tool or a modulator of protein-protein interactions in vivo. To deliver such engineered proteins or other bioanalytical reagents into single live cells, we established a laser-assisted cellular nano-surgery protocol which would enable detailed observations of cell-to-cell variability and communication. Finally we investigated a possible experimental scheme to genetically evolve a fluorescent peptide, which has tremendous potential as a tool in cellular imaging and dynamic observation of protein-protein interactions in vivo. We aim to contribute to the discovery and development of new drugs and eventually to the overall health of our society by adding the technology above to the array of currently available bioanalytical tools. / text

Proteins are diverse polymers of covalently linked amino acids. They play a role in almost every biological process that occurs within an organism. Twenty different amino acids are genetically encoded by mammalian cells to build proteins. The sequence of these amino acids determines the protein’s final shape, structure, and function. Modern molecular cloning techniques allow for the genetic encoding and expression of mutant proteins that have one or more amino acids replaced with one of the others. The roles of individual amino acids in a protein can therefore be studied. Proteins with novel functions have also been designed or evolved using this technology. However, the genetic code is limited to the twenty natural amino acids. Nonnatural amino acids have unique side groups that not found on any of the twenty natural amino acids. They can be site-specifically incorporated using a mutant orthogonal suppressor tRNA/aminoacyl-tRNA synthetase (aaRS) pair. Each pair only allows for one type of nonnatural amino acid to be genetically encoded. This technology has resulted in the incorporation of over fifty different types of nonnatural amino acids into proteins in prokaryotic and eukaryotic cells. Unfortunately, most of these pairs are not orthogonal outside of prokaryotic systems and only a few have been developed for mammalian cells. To create more mammalian pairs a nonnatural aaRS has to be evolved and screened in a cumbersome process. In this dissertation an approach is outlined that can be used to change the orthogonality of existing nonnatural suppressor tRNA/aaRS pairs. As a result of the orthogonality change many previously unavailable pairs can be shuttled into mammalian cells. The ability to genetically encode a 21st amino acid is a powerful tool in the study and engineering of proteins. / text

B and T cells comprise the two major arms of the adaptive immune response tasked with clearing and preventing infection; molecular recognition in these cells occurs through antibodies and T cell receptors (TCRs), respectively. Highly successful therapeutics, clinical diagnostics and laboratory tools have been engineered from fragments of these parent molecules. The binding specificity, affinity and biophysical characteristics of these fragments determine their potential applications and resulting efficacies. Thus engineering desired properties into antibody and TCR fragments is a major concern of the multi-billion dollar biopharmaceutical industry. Toward this goal, we (1) designed antibody specificity using a novel computational method, (2) engineered thermoresistant Fabs by phage-based selection and (3) modulated binding kinetics for a single-chain TCR. In the first study, de novo modeling was used to generate libraries of FLAG peptide-binding single-chain antibodies. Phage-based screening identified a dominant design, and activity was confirmed after conversion to soluble Fab format. Bioinformatics analysis revealed potential areas for design process improvement. We present the first experimental validation of this in silico design method, which can be used to guide future antibody specificity engineering efforts. In the second study, the variable heavy chain of a moderately stable EE peptide-binding Fab was subjected to random mutagenesis, and variants were selected for resistance to heat inactivation. Thermoresistant clones where biophysically characterized, and structural analysis of selected mutations suggested general mechanisms of stabilization. Framework mutations conferring thermoresistance can be grafted to other antibodies in future Fab stabilization work. In the third study, TCR fragment binding kinetics for a clonotypic antibody were modulated by varying valence during phage-based selection. Binding affinity and kinetics for representative variants depended on the display format used during selection, and all TCR fragments retained binding to native pMHC antigen. This work demonstrates a general engineering platform for tuning protein-protein interactions. Using a combination of computational design and phage-based screening, we have identified antibodies and TCR fragments with improved binding properties or biophysical characteristics. The optimized variants possess a wider range of potential applications compared to their parent molecules, and we detail engineering methods likely to be useful in the engineering of many other protein-based therapeutics. / text

The development of hybridoma technology nearly forty years ago set the foundation for the use of antibodies in the life sciences. Subsequent advances in recombinant DNA technology have allowed us to adapt antibody genes to various screening systems, greatly increasing the throughput and specialized applications for which these complex biomolecules can be adapted. While selection systems are a powerful tool for discovery and evolution, they can be slow and prone to unintended biases. We see computational approaches as an efficient process for rapid discovery and engineering of antibodies. This is particularly relevant for biodefense and emerging infectious disease applications, for which time is a valuable commodity. In the first chapter of this work, we examine computational protocols for ‘supercharging’ proteins. This process resurfaces the target protein, adding charged moieties to impart specialized functions such as thermoresistance and cell penetration. Current algorithms for resurfacing proteins are static, treating each mutation as an event within a vacuum. The net result is that while several variants can be created, each must be tested experimentally to ensure the resultant protein is functional. In many cases, the designed proteins were severely impaired or incapable of folding. We hypothesize that a more dynamic approach, keeping an eye on energetics and the consequences of mutations will yield a more efficient and robust method for supercharging, successfully adding charges to proteins while minimizing deleterious effects. We continue on this theme applying the successful algorithm to supercharging antibodies for increased function. Utilizing the MS2 model biosensor system, we rationally engineer charges onto the surface of an antibody fragment, increasing thermoresistance, minimizing destabilizing effects, and in some cases actually increasing affinity. Finally, we apply next-generation sequencing approaches to the rapid discovery of antibodies directed against the Zaire Ebolavirus species. We utilize a local immunization strategy to generate a polarized antibody repertoire that is then sequenced to provide a database of antigen-specific variants. This repertoire is probed in silico and individual antibodies selected for analysis, bypassing time- and resource-consuming selection experiments. / text

Many cancers have long been known to display an absolute requirement for the amino acid methionine (L-Met). Studies have shown that in the absence of L-Met, sensitive neoplasms experience cell cycle arrest and perish. Without the metabolic deviations that characterize L-Met auxotrophs, normal cells are able to grow on precursors such as homocysteine and tolerate periods of L-Met starvation. The differential requirement for this amino acid between normal and tumor cells has been exploited through enzymatic serum degradation of L-Met by a bacterial methionine-γ-lyase (MGL). Though MGL was able to deplete L-Met to therapeutically useful levels in animal models and exert a significant cytotoxic effect on malignant cell lines in vitro and on tumor xenografts in vivo, the clinical implementation of this enzyme is hampered by its short serum half-life and potential for catastrophic immune response. In the chapters that follow, we describe the engineering of a novel human methionine degrading enzyme (hMGL) that overcomes the limitations of the bacterial therapeutic. We have shown that hMGL is capable of degrading methionine at a therapeutically useful rate and inducing extensive cell killing in a variety of neoplasms. This enzyme is expected to have low immunogenicity in patients and a high therapeutic index. We have developed a high throughput screen for methionine degrading activity that we can utilize to further engineer the enzyme based on the results of additional preclinical development. We have found that hMGL is also capable of degrading cystine to operate as a dual amino acid depletion treatment that is expected to be more potent than methionine depletion alone. Due to the wide array of neoplasms sensitive to methionine and cystine starvation, the engineered enzyme holds a great deal of promise as a unique and powerful cancer therapeutic. / text