Browsing by Subject "Structure"

This thesis concerns the use of protein structure to improve phylogenetic inference. There has been growing interest in phylogenetics as the number of available DNA and protein sequences continues to grow rapidly and demand from other scientific fields increases. It is now well understood that phylogenies should be inferred jointly with alignment through use of stochastic evolutionary models. It has not been possible, however, to incorporate protein structure in this framework. Protein structure is more strongly conserved than sequence over long distances, so an important source of information, particularly for alignment, has been left out of analyses.

I present a stochastic process model for the joint evolution of protein primary and tertiary structure, suitable for use in alignment and estimation of phylogeny. Indels arise from a classic Links model and mutations follow a standard substitution matrix, while backbone atoms diffuse in three-dimensional space according to an Ornstein-Uhlenbeck process. The model allows for simultaneous estimation of evolutionary distances, indel rates, structural drift rates, and alignments, while fully accounting for uncertainty. The inclusion of structural information enables pairwise evolutionary distance estimation on time scales not previously attainable with sequence evolution models. Ideally inference should not be performed in a pairwise fashion between proteins, but in a fully Bayesian setting simultaneously estimating the phylogenetic tree, alignment, and model parameters. I extend the initial pairwise model to this framework and explore model variants which improve agreement between sequence and structure information. The model also allows for estimation of heterogeneous rates of structural evolution throughout the tree, identifying groups of proteins structurally evolving at different speeds. In order to explore the posterior over topologies by Markov chain Monte Carlo sampling, I also introduce novel topology + alignment proposals which greatly improve mixing of the underlying Markov chain. I show that the inclusion of structural information reduces both alignment and topology uncertainty. The software is available as plugin to the package StatAlign.

Finally, I also examine limits on statistical inference of phylogeny through sequence information models. These limits arise due to the `cutoff phenomenon,' a term from probability which describes processes which remain far from their equilibrium distribution for some period of time before swiftly transitioning to stationarity. Evolutionary sequence models all exhibit a cutoff; I show how to find the cutoff for specific models and sequences and relate the cutoff explicitly to increased uncertainty in inference of evolutionary distances. I give theoretical results for symmetric models, and demonstrate with simulations that these results apply to more realistic and widespread models as well. This analysis also highlights several drawbacks to common default priors for phylogenetic analysis, I and suggest a more useful class of priors.

This dissertation explores the complex process of organizational change, applying a behavioral lens to understand change in processes, products, and search behaviors. Chapter 1 examines new practice adoption, exploring factors that predict the extent to which routines are adopted “as designed” within the organization. Using medical record data obtained from the hospital’s Electronic Health Record (EHR) system I develop a novel measure of the “gap” between routine “as designed” and routine “as realized.” I link this to a survey administered to the hospital’s professional staff following the adoption of a new EHR system and find that beliefs about the expected impact of the change shape fidelity of the adopted practice to its design. This relationship is more pronounced in care units with experienced professionals and less pronounced when the care unit includes departmental leadership. This research offers new insights into the determinants of routine change in organizations, in particular suggesting the beliefs held by rank-and-file members of an organization are critical in new routine adoption. Chapter 2 explores changes to products, specifically examining culling behaviors in the mobile device industry. Using a panel of quarterly mobile device sales in Germany from 2004-2009, this chapter suggests that the organization’s response to performance feedback is conditional upon the degree to which decisions are centralized. While much of the research on product exit has pointed to economic drivers or prior experience, these central finding of this chapter—that performance below aspirations decreases the rate of phase-out—suggests that firms seek local solutions when doing poorly, which is consistent with behavioral explanations of organizational action. Chapter 3 uses a novel text analysis approach to examine how the allocation of attention within organizational subunits shapes adaptation in the form of search behaviors in Motorola from 1974-1997. It develops a theory that links organizational attention to search, and the results suggest a trade-off between both attentional specialization and coupling on search scope and depth. Specifically, specialized unit attention to a more narrow set of problems increases search scope but reduces search depth; increased attentional coupling also increases search scope at the cost of depth. This novel approach and these findings help clarify extant research on the behavioral outcomes of attention allocation, which have offered mixed results.

Human welfare depends heavily on ecosystem services like water purification and nutrient cycling. Many of these ecosystem services, in turn, rely on reactions performed by microbes and yet remarkably little is known about how anthropogenic impacts are affecting the structure and function of microbial communities. To help address this knowledge gap, this dissertation uses field surveys and laboratory experiments to examine how watershed urbanization affects microbial communities in receiving streams. We focus on a specific functional group and its associated function - the denitrifying bacteria and denitrification. Denitrifying bacteria use reactive nitrogen and organic carbon as substrates to perform denitrification. Denitrification is one of the few ways to permanently remove reactive nitrogen from ecosystems. Since excess reactive nitrogen in water contributes to serious water quality and human health problems like toxic algal blooms and bowel cancer, denitrification in streams can be considered a valuable ecosystem service. Watershed urbanization, however, may alter the structure of denitrifying bacteria communities in ways that constrain their capacity to remove reactive nitrogen from streams.

Watershed urbanization leads to drastic changes in receiving streams, with urban streams receiving a high frequency of scouring flows, together with increased nutrient (nitrogen and carbon), contaminant (e.g., heavy metals), and thermal pollution. These changes are known to cause significant losses of sensitive insect and fish species from urban streams. Microbes like denitrifying bacteria may be similarly affected. In the first part of this dissertation, we describe results from four repeated surveys of eight central North Carolina streams affected to varying degrees by watershed urbanization. For each stream and sampling date, we characterized both overall and denitrifying bacterial communities and measured denitrification potentials. Differences in overall and denitrifying bacteria community composition were strongly associated with the urbanization gradient. Denitrification potentials, which varied widely, were not significantly associated with substrate supply. By incorporating information on the community composition of denitrifying bacteria together with substrate supply in a linear mixed-effects model, we explained 45% of the variation in denitrification potential (p < 0.001). Results suggest that 1) watershed urbanization can lead to significant changes in the composition of bacterial communities in streams and 2) such changes may have important functional consequences.

The second part of this dissertation examines how urbanization-driven changes to the structure of denitrifying bacteria communities might affect the way they respond to stress or disturbance. Some communities can resist changes to functionality in response to disturbance, potentially as a result of previous exposure and subsequent adaptation (legacy hypothesis) or high diversity (insurance hypothesis). We compare the resistance of two structurally distinct denitrifying bacteria communities to experimental disturbances in laboratory microcosms. Communities originated from either a polluted, warm urban streams or a relatively pristine, cool forest stream. In this case, the two communities had comparable compositions, but forest communities were more diverse than their urban counterparts. Urban communities experienced significant reductions in denitrification rates in response to the most severe increased pollution and temperature treatments, while forest communities were unaffected by those same treatments. These findings support the insurance, but not the legacy hypothesis and suggest that the functioning of urban streams may be more susceptible to further environmental degradation than forest streams not heavily impacted by human activities.

In the third part of this dissertation, we discuss results from a one-time survey of denitrifying bacteria communities and denitrification potentials in 49 central North Carolina streams affected to varying degrees by watershed urbanization. We use multivariate statistics and structural equation modeling to address two key questions: 1) How do different urban impacts affect the structure of denitrifying bacteria communities and 2) How do abiotic (e.g., temperature) versus biotic (denitrifying bacteria community structure) factors affect denitrification potentials in urban streams? Denitrifying bacteria community structure was strongly affected by the urban impacts measured. Community composition responded to increased temperatures, substrate supply, and contamination, while diversity responded negatively to increased temperatures and hydrologic disturbance. Moreover, increased temperatures and substrate supply had significant positive effects, while urbanization-driven changes to denitrifying bacteria community structure had significant negative effects on denitrification potential. The structural equation model captured 63% of the variation in denitrification potential among sites and highlighted the important role that microbial community structure can play in regulating ecosystem functioning. These findings provide a novel explanation for recent observations of decreasing denitrification efficiency with increasing urbanization. Ultimately, we hope findings from this dissertation will help inform more effective stream management and restoration plans and motivate ecologists to consider including microbial community structure in ecosystem models of microbe-mediated processes.

The structural plasticity conferred by conformational flexibility has increasingly been recognized as a likely determinant of function. For example, multiscale heterogeneity in the calmodulin central helix most likely helps it in binding over 100 protein targets, and a concerted motion seen in both nuclear magnetic resonance (NMR) and crystal structures of ubiquitin is proposed to underlie its functional plasticity of promiscuous binding to many different proteins with high affinity. However, flexibility is manifested in a variety of ways, depending both on the protein itself and on how it is observed. Conformational heterogeneity (the term we use for flexibility when studied by X-ray crystallography) is evident in electron density, either as fully separated peaks or as anisotropic density shapes showing fluctuation of atom groupings. Many phenomena contribute to conformational heterogeneity in crystal structures, from diverse crystal contacts to functionally relevant conformational fluctuations on a wide range of time and size scales.

In addition to ubiquitin and calmodulin, the Staphylococcus aureus virulence factor staphylococcal protein A (SpA) is an example of a highly heterogeneous protein. SpA is a major contributor to bacterial evasion of the host immune system, through high-affinity binding to host proteins such as antibodies, von Willebrand factor, and tumor necrosis factor receptor 1 (TNFR1). The protein includes five small three-helix-bundle domains (E-D-A-B-C) separated by conserved flexible linkers. Prior attempts to crystallize individual domains in the absence of a binding partner were apparently unsuccessful. There are also no previous structures of tandem domains. In this thesis, I report the high-resolution crystal structures of a single C domain (collected at both cryogenic and room temperatures), a single A domain, and two B domains connected by the conserved linker. All four apo structures exhibit extensive multiscale conformational heterogeneity, which required novel modeling protocols. Comparison of domain structures shows that helix1 orientation is especially heterogeneous, coordinated with changes in sidechain conformational networks and contacting protein interfaces.

The interaction between a SpA domain and the Fc fragment of IgG was partially elucidated previously in the crystal structure 1FC2. Although informative, the previous structure wasn't properly folded and left many substantial questions unanswered, such as a detailed description of the tertiary structure of SpA domains in complex with Fc and the structural changes that take place upon binding. In this thesis, I report the 2.3-A structure of a fully folded SpA domain in complex with Fc. My structure indicates that there are extensive structural rearrangements necessary for binding Fc, including concerted rotamer changes and coupled backbone rearrangements that lead to a difference in helix1 angle. The conformational heterogeneity of the helix1/2 interface is also eliminated in the complex, with previously poly-rotameric interfacial residues locking into single rotamer conformations. Such a loss of conformational heterogeneity upon formation of the protein-protein interface may occur in SpA and in its multiple binding partners and may be an important structural paradigm in other functionally plastic proteins.

Olfaction is one of the most primitive of our senses, and the olfactory receptors that mediate this very important chemical sense comprise the largest family of genes in the mammalian genome. It is therefore surprising that we understand so little of how olfactory receptors work. In particular we have a poor idea of what odorous chemicals are detected by most of the olfactory receptors in the genome, and for those receptors which we have paired with ligands, we know relatively little about how the structure of these ligands can either activate or inhibit the activation of these receptors. Furthermore the large repertoire of olfactory receptors, which belong to the G protein coupled receptor (GPCR) superfamily, can serve as a model to contribute to our broader understanding of GPCR- ligand binding, especially since GPCRs are important pharmaceutical targets.

In this dissertation, I explore the relationship between olfactory receptors and their ligands, both by manipulating the ligands presented to the olfactory receptors, as well as by altering the structure of the receptor itself by mutagenesis. Here we report the probable requirement of a hydrated germinal-diol form of octanal for activation of the rodent OR-I7 receptor by ligand manipulation, and the successful in vitro modeling and manipulation of ketamine binding to MOR136-1. We also report the results of a large-scale screen of 1190 human and mouse olfactory receptors for receptors activated by volatile general anesthetics, which has lead to the identification of 32 olfactory receptor-volatile general anesthetic pairs.

For all organisms, the ability to sense and react to noxious environments is fundamental to their survival. For multi-celled organisms this process generally involves a nervous system and an extensive network of signal transduction pathways. TRPV ion channels have been shown to participate in signal transduction in response to noxious stimuli. At the cellular level these channels function in sensing of mechanical, thermal, and osmotic stimuli, and at the organismal level they function in homeostasis and nociception. TRPV ion channels participate in nociceptive signal transduction via cation influx, but exactly how these channels function at a mechanistic level and lead to activation of the cell or induction of a specific behavior is elusive. Previous research has shown that the pore-forming unit of an ion channel is critical for channel regulation, gating, ion selectivity, and ion permeation. Various regulatory domains have been identified to date in the pore-forming unit of TRP channels and a clearer picture of channel gating is beginning to emerge, but less is known about ion permeation.

To better understand the specific domains that are critical to ion capture, selectivity, and permeation in TRPV channels, we investigated the function of these regions using the C. elegans TRPV channel OSM-9 in vivo, and the mammalian TRPV channel TRPV4 in heterologous cell culture. OSM-9 is the functional ortholog of mammalian TRPV4 and it is likely that critical domains identified in OSM-9 are functionally conserved in TRPV4 and play a similar role in other TRPV channels. OSM-9 is expressed in the ASH neurons and is responsible for all of the behaviors initiated by that cell. The stereotypical avoidance behavior mediated by ASH, in response to noxious stimuli, serves as a model for nociception in vertebrates. As OSM-9 is necessary for all of these behavioral responses, activation of ASH acts as a read-out for OSM-9 function.

Through targeted mutagenesis of the OSM-9 loop domains and transgenic expression directed to the ASH head sensory neurons in an osm-9 null background, we discovered a critical role for the amino acids both N- and C- terminal to the pore helix in osmotic avoidance behavior. We confirmed the existence of a selectivity filter C-terminal to the pore helix and revealed that the turret is critical for channel function, possibly as a component of the inactivation gate.

We first identified the boundaries of the selectivity filter to be M601-F609. We also determined what properties of those residues were critical to Ca2+ and Na+ selectivity. In vivo Ca2+ imaging strongly suggested that residues Y604, D605, and F609 are critical for Ca2+ entry into the cell. Patch-clamp electrophysiology of a chimeric ion channel consisting largely of rat TRPV4, but encompassing transmembranes 5 through 6 of OSM-9, revealed that OSM-9 conducts both Ca2+ and Na+. Mutation Y604G disrupted both Ca2+ and Na+ conductance, whereas mutations Y604F and Y606A increased or maintained Na+ conductance and severely reduced Ca2+ conductance, while maintaining avoidance behavior. Homology modeling of OSM-9, based on an alignment of OSM-9 to Kv1.2, suggests that Y604 and F609 serve structural roles in maintaining filter constraints. Thus, aromatic and negative residues in the OSM-9 selectivity filter are critical to ion permeation and selectivity.

Our studies involving the selectivity filter support previous research that the selectivity filter is critical for TRP channel function. We also provide evidence that the selectivity filter is critical for nocifensive animal behavior. Fewer studies, however, have investigated the TM5-pore helix linker, known as the turret. The turret is believed to function in the binding of ligands and toxins in K+ channels, and more recently was suggested to be critical for temperature sensing in TRPV1. We investigated the function of the turret residues in several sensory submodalities of the OSM-9 channel and found that all deletions tested result in channel defects, including gain- and loss-of-function phenotypes. Several charge reversal mutations in the OSM-9 turret also resulted in partial defects. The discovery of a gain-of-function mutation indicates that the turret functions in gating. When the turret is mutated in this way, the channel is unable to enter into the inactivated state, allowing continued ion influx after repeated stimulation. The loss-of-function phenotypes indicate that the secondary structure of the turret is critical to the function of the channel, and perhaps gating. These findings, combined with the observed charge-reversal defects, support the conclusion that the turret is necessary for transducing conformational changes in response to stimuli.

Our in vivo findings on the external pore forming structures increase the understanding of ion permeation in TRP channels and clarify mechanisms of activation in nociceptor neurons in vivo. Furthermore, these studies enhance our insights into evolution of mammalian nociception in view of the established functional orthology of OSM-9 and TRPV4.

Nucleic acids are subjected to many different mechanical loadings inside. These loadings could cause large deformations and conformational changes to these molecules. This is why the mechanical properties of nucleic acids are so important to their functions. Here we use a newly designed and built high-performance AFM force spectrometer, supplemented with molecular dynamics simulations and NMR spectroscopy to investigate the relationship between mechanical properties and structure of different nucleic acids.

To test the mechanical properties of nucleic acids, we successfully designed and purpose-built a single molecule puller, an instrument to physically stretch single molecules, at a fraction of the cost of a commercial AFM instrument. This instrument has similar force noise to hybrid instruments, while also exhibiting significantly lower drift, on the order of five times lower. This instrument allows the measurement of subtle transitions as a molecule is stretched. With the addition of a lock-in amplifier, we possibly could obtain better force resolution, the order of femtonewtons.

We find that helical structure does indeed have an effect on the mechanical properties of double-stranded DNA. As the A-form double helix has a shorter, wider structure compared to the B-form helix, its force spectra exhibit a shorter initial length before the overstretching force plateau, compared to B-form DNA. Contrarily, the Z-form double helix has a narrower, more extended helical structure than B-form DNA, and we see this fact manifest in the force spectra of Z-DNA, which has a longer initial length before the overstretching force plateau. Also, interestingly, we find that neither A, nor Z-DNA force spectra display the second melting force plateau. Indicating this plateau is not necessarily cause by melting of strands apart, but rather a feature of B-DNA.

To better understand the forces that stabilized these different structures, specifically base stacking, we also mechanically characterize different single-stranded helical polynucleotides using AFM based force spectroscopy. We expand on previous studies by confirming that single helical polynucleotides undergo a force transition at a force of ~20 pN as they are uncoiled, and also demonstrating, that when stretched beyond this force transition, the molecules behave differently depending on base sequence and backbone sugar. Specifically, the force spectra of poly-adenylic acid possess a linear force region, which persists to ~300 pN, after the force plateau. We also observe that poly-deoxyadenylic acid is comparatively stiffer than other polynucleotides after undergoing two force transitions. By supplementing our force spectroscopic data with MD simulations and NMR spectroscopy, we find that base stacking in adenine is quite strong, persisting above 100 pN. We find that initial helical structure, which is defined by base stacking and backbone sugar, guides the stretching pathway of the polynucleotides. This finding can possibly be extrapolated to the elasticity of double-stranded DNA.

Computational protein design aims at identifying protein mutations and conformations with desired target properties (such as increased protein stability, switch of substrate specificity, or novel function) from a vast combinatorial space of candidate solutions. The development of algorithms to efficiently and accurately solve problems in protein design has thus posed significant computational and modeling challenges. Despite the inherent hardness of protein design, a number of computational techniques have been previously developed and applied to a wide range of protein design problems. In many cases, however, the available computational protein design techniques are deficient both in computational power and modeling accuracy. Typical simplifying modeling assumptions for computational protein design are the rigidity of the protein backbone and the discretization of the protein side-chain conformations. Here, we present the derivation, proofs of correctness and complexity, implementation, and application of novel algorithms for computational protein design that, unlike previous approaches, have provably-accurate guarantees even when backbone or continuous side-chain flexibility are incorporated into the model. We also describe novel divide-and-conquer and dynamic programming algorithms for improved computational efficiency that are shown to result in speed-ups of up to several orders of magnitude as compared to previously-available techniques. Our novel algorithms are further incorporated as part of K*, a provably-accurate ensemble-based algorithm for protein-ligand binding prediction and protein design. The application of our suite of protein design algorithms to a variety of problems, including enzyme redesign and small-molecule inhibitor design, is described. Experimental validation, performed by our collaborators, of a set of our computational predictions confirms the feasibility and usefulness of our novel algorithms for computational protein design.

Nucleic acids (DNA and RNA) play essential roles in the central dogma of biology for the storage and transfer of genetic information. The unique chemical and conformational structures of nucleic acids – the double helix composed of complementary Watson-Crick base pairs, provide the structural basis to carry out their biological functions. DNA double helix can dynamically accommodate Watson-Crick and Hoogsteen base-pairing, in which the purine base is flipped by ~180° degrees to adopt syn rather than anti conformation as in Watson-Crick base pairs. There is growing evidence that Hoogsteen base pairs play important roles in DNA replication, recognition, damage or mispair accommodation and repair. Here, we constructed a database for existing Hoogsteen base pairs in DNA duplexes by a structure-based survey from the Protein Data Bank, and structural analyses based on the resulted Hoogsteen structures revealed that Hoogsteen base pairs occur in a wide variety of biological contexts and can induce DNA kinking towards the major groove. As there were documented difficulties in modeling Hoogsteen or Watson-Crick by crystallography, we collaborated with the Richardsons’ lab and identified potential Hoogsteen base pairs that were mis-modeled as Watson-Crick base pairs which suggested that Hoogsteen can be more prevalent than it was thought to be. We developed solution NMR method combined with the site-specific isotope labeling to characterize the formation of, or conformational exchange with Hoogsteen base pairs in large DNA-protein complexes under solution conditions, in the absence of the crystal packing force. We showed that there are enhanced chemical exchange, potentially between Watson-Crick and Hoogsteen, at a sharp kink site in the complex formed by DNA and the Integration Host Factor protein. In stark contrast to B-form DNA, we found that Hoogsteen base pairs are strongly disfavored in A-form RNA duplex. Chemical modifications N1-methyl adenosine and N1-methyl guanosine that block Watson-Crick base-pairing, can be absorbed as Hoogsteen base pairs in DNA, but rather potently destabilized A-form RNA and caused helix melting. The intrinsic instability of Hoogsteen base pairs in A-form RNA endows the N1-methylation as a functioning post-transcriptional modification that was known to facilitate RNA folding, translation and potentially play roles in the epitranscriptome. On the other hand, the dynamic property of DNA that can accommodate Hoogsteen base pairs could be critical to maintaining the genome stability.

Inositol Polyphosphate Multi-Kinase (IPMK, also known as ArgRIII, Arg82, and IPK2) is a central component of the inositol signaling system, catalyzing the phosphorylation of at least four different inositol polyphosphate species in vivo with in vitro activity observed for three more. Each of these IP species is sterically unique and the phosphorylation target varies between the 6'-, 3'-, or 5'-hydroxyls, classifying IPMK as a 6/3/5-kinase. The products of IPMK have been linked to multiple processes including cell cycle regulation, transcriptional control, telomere length regulation, mRNA export and various phenotypes including mouse embryonic and fly larvae development, and stress responses in plants and yeast. Linking specific IP species and cellular processes has been complicated by the inability to distinguish between the different effects of the various IP species generated by IPMK. Deletion of IPMK affects the IP populations of all its various substrates and products and therefore the role of a single IP species cannot be tracked. The goals of this work were to address the question of substrate selectivity and develop new tools to probe inositol signaling in vivo through a combination of structural, enzymatic, and genomic techniques.

The structure of Arabidopsis thaliana IPMK is reported at 2.9Å resolution and in conjunction with a new model of inositol selectivity has been used to design constructs with altered substrate profiles. In vitro and in vivo experiments have confirmed that IPMK identifies substrate inositol polyphosphate species through a recognition surface that requires phosphate groups occupy specific pockets and rejects those with axial phosphate groups in specific regions. In vivo experiments have linked specific inositol polyphosphate species to nitrogen metabolism and temperature sensitivity in yeast and established the potential for these constructs to be used to probe signaling in other organisms.

Sulfite oxidase, a metabolically important enzyme, catalyzes the physiologically critical conversion of sulfite to sulfate in the terminal step of the degradation of sulfur containing compounds. The enzyme has been the focus for much research since its discovery in the 1950's. A central question to understanding the mechanism of molybdoenzymes such as sulfite oxidase and nitrate reductase concerns the roles of active site residues and the coordination chemistry of the Mo atom in the structure and function of the enzyme. The goal of this work was directed towards the characterization and determination of the structures of active site variants of sulfite oxidase using a spectroscopic, kinetic, and protein crystallographic approach.

Earlier studies have identified a single, highly conserved cysteine residue as the donor of a covalent bond from the protein to molybdenum in sulfite oxidase and nitrate reductase. The C185S and C185A variants of chicken sulfite oxidase exhibited severely attenuated activity. Crystallographic and spectroscopic analysis of both variants revealed a change in the metal coordination, from a dioxo to a trioxo form of Mo.

Assimilatory nitrate reductase is a member of the sulfite oxidase family of molybdopterin enzymes. The crystal structure of the Mo domain of the enzyme from Pichia angusta revealed high structural homology in the active sites of nitrate reductase and sulfite oxidase. Both enzymes utilize the same form of the molybdenum cofactor and have three out of five residues conserved at the active site. Substitution of two active site residues in sulfite oxidase alters the substrate affinity of chicken SO from sulfite to nitrate, resulting in an increase of nitrate reductase activity over wild-type sulfite oxidase. Additionally we identified an additional amino acid position in sulfite oxidase that corresponds to a non-conserved position in NR that further increased NR activity. Finally, these nitrate reductase variants of sulfite oxidase were crystallized and the structures solved. This represents the first example of the transmutation of a molybdenum enzyme to change activity and substrate affinity to those of a homologous enzyme.

Eukaryotic human pathogens present a serious threat to global health, causing hundreds of millions of infections with high death rate each year. Fungi and protozoa are two major classes of eukaryotic pathogens. Fungi Cryptococcus neoformans, Candida albicans, and protozoa Plasmodium falciparum are important pathogens from these classes. Although the therapeutics treating infections caused by these species are available, the options of front-line drugs are limited and the drug resistance is emerging and spreading. Therefore, there is a need for new therapeutics. Protein prenylation catalyzed by protein farnesyltransferase (FTase) and protein geranylgeranyltransferase (GGTase) is essential to the survival of Cryptococcus neoformans, Candida albicans, and Plasmodium falciparum. The previous biophysical and biochemical studies of FTase and GGTase from these species illustrate their divergence from the human enzymes, providing opportunities to develop species specific FTase or GGTase inhibitors for treating infectious diseases.In this dissertation, we choose to target FTases from Cryptococcus neoformans, Candida albicans, and Plasmodium falciparum by repurposing and derivatizing the well-studied human FTase inhibitors. We first derivatized human FTase inhibitor L-778,123, leading to a novel compound that shows potent inhibition of Cryptococcus neoformans growth with MIC value of 3 µM. The IC50 of the compound is 130 nM in the presence of physiological concentration of phosphate. Crystal structures of the compound bound to Cryptococcus neoformans FTase (CnFTase) shows a distinct binding mode from the starting compound, explaining the inhibition mechanism. Additionally, the compound does not exhibit significant mammalian cell toxicity up to 200 µM in cell based assays. We also derivatized and evaluated another human FTase inhibitor Tipifarnib. The derivatives showed the improved antifungal activity against Cryptococcus neoformans and Candida albicans. Finally, we have developed a new system to produce Plasmodium falciparum FTase for future inhibitor development. The data present in this dissertation could advance the future development of novel treatment for infections caused by eukaryotic human pathogens. Additionally, we report two protein engineering studies. The first addresses stability and overexpression of the telomerase riboprotein complex. Here we engineered the catalytic core complex and the RNA binding domain, and evaluated the capability of using these materials for inhibitor development. In the second study, an intein was inserted into DNA polymerases to produce temperature controlled enzymes. The intein controlled DNA polymerases only showed activities after intein splicing triggered by high temperature (>60oC), enabling the capability of conducting “hot-start” reactions by themselves. We demonstrated that using intein controlled DNA polymerases could reduce the nonspecific amplifications in PCR reactions.

X-ray crystallography 3D atomic models are used in a variety of research areas to understand and manipulate protein structure. Research and application are dependent on the quality of the models. Low-resolution experimental data is a common problem in crystallography which makes solving structures and producing the reliable models that many scientists depend on difficult.

In this work, I develop new, automated tools for validation and correction of low-resolution structures. These tools are gathered under the name CaBLAM, for C-alpha Based Low-resolution Annotation Method. CaBLAM uses a unique, C-alpha-geometry-based parameter space to identify outliers in protein backbone geometry, and to identify secondary structure that may be masked by modeling errors.

CaBLAM was developed in the Python programming language as part of the Phenix crystallography suite and the open CCTBX Project. It makes use of architecture and methods available in the CCTBX toolbox. Quality-filtered databases of high-resolution protein structures, especially the Top8000, were used to construct contours of expected protein behavior for CaBLAM. CaBLAM has also been integrated into the codebase for the Richardson Lab's online MolProbity validation service.

CaBLAM succeeds in providing useful validation feedback for protein structures in the 2.5-4.0A resolution range. This success demonstrates the relative reliability of the C-alpha; trace of a protein in this resolution range. Full mainchain information can be extrapolated from the C-alpha; trace, especially for regular secondary structure elements.

CaBLAM has also informed our approach to validation for low-resolution structures. Moderation of feedback, to reduce validation overload and to focus user attention on modeling errors that are both significant and correctable, is one of our goals. CaBLAM and the related methods that have grown around it demonstrate the progress towards this goal.