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The photosynthetic reaction center is a type of pigment-protein complex found widely in photosynthetic bacteria, algae and higher plants. Its function is to convert the energy of sunlight into a chemical form that can be used to support other life processes. The high efficiency and structural simplicity make the bacterial

The photosynthetic reaction center is a type of pigment-protein complex found widely in photosynthetic bacteria, algae and higher plants. Its function is to convert the energy of sunlight into a chemical form that can be used to support other life processes. The high efficiency and structural simplicity make the bacterial reaction center a paradigm for studying electron transfer in biomolecules. This thesis starts with a comparison of the primary electron transfer process in the reaction centers from the Rhodobacter shperoides bacterium and those from its thermophilic homolog, Chloroflexus aurantiacus. Different temperature dependences in the primary electron transfer were found in these two type of reaction centers. Analyses of the structural differences between these two proteins suggested that the excess surface charged amino acids as well as a larger solvent exposure area in the Chloroflexus aurantiacus reaction center could explain the different temperature depenence. The conclusion from this work is that the electrostatic interaction potentially has a major effect on the electron transfer. Inspired by these results, a single point mutant was designed for Rhodobacter shperoides reaction centers by placing an ionizable amino acid in the protein interior to perturb the dielectrics. The ionizable group in the mutation site largely deprotonated in the ground state judging from the cofactor absorption spectra as a function of pH. By contrast, a fast charge recombination assoicated with protein dielectric relaxation was observed in this mutant, suggesting the possibility that dynamic protonation/deprotonation may be taking place during the electron transfer. The fast protein dielectric relaxation occuring in this mutant complicates the electron transfer pathway and reduces the yield of electron transfer to QA. Considering the importance of the protein dielectric environment, efforts have been made in quantifying variations of the internal field during charge separation. An analysis protocol based on the Stark effect of reaction center cofactor spectra during charge separation has been developed to characterize the charge-separated radical field acting on probe chromophores. The field change, monitored by the dynamic Stark shift, correlates with, but is not identical to, the electron transfer kinetics. The dynamic Stark shift results have lead to a dynamic model for the time-dependent dielectric that is complementary to the static dielectric asymmetry observed in past steady state experiments. Taken together, the work in this thesis emphasizes the importance of protein electrostatics and its dielectric response to electron transfer.
ContributorsGuo, Zhi (Author) / Woodbury, Neal W (Thesis advisor) / Lindsay, Stuart M (Committee member) / Ross, Robert (Committee member) / Ozkan, Banu S (Committee member) / Moore, Thomas A. (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Enzymes which regulate the metabolic reactions for sustaining all living things, are the engines of life. The discovery of molecules that are able to control enzyme activity is of great interest for therapeutics and the biocatalysis industry. Peptides are promising enzyme modulators due to their large chemical diversity and the

Enzymes which regulate the metabolic reactions for sustaining all living things, are the engines of life. The discovery of molecules that are able to control enzyme activity is of great interest for therapeutics and the biocatalysis industry. Peptides are promising enzyme modulators due to their large chemical diversity and the existence of well-established methods for library synthesis. Microarrays represent a powerful tool for screening thousands of molecules, on a small chip, for candidates that interact with enzymes and modulate their functions. In this work, a method is presented for screening high-density arrays to discover peptides that bind and modulate enzyme activity. A viscous polyvinyl alcohol (PVA) solution was applied to array surfaces to limit the diffusion of product molecules released from enzymatic reactions, allowing the simultaneous measurement of enzyme activity and binding at each peptide feature. For proof of concept, it was possible to identify peptides that bound to horseradish peroxidase (HRP), alkaline phosphatase (APase) and â-galactosidase (â-Gal) and substantially alter their activities by comparing the peptide-enzyme binding levels and bound enzyme activity on microarrays. Several peptides, selected from microarrays, were able to inhibit â-Gal in solution, which demonstrates that behaviors selected from surfaces often transfer to solution. A mechanistic study of inhibition revealed that some of the selected peptides inhibited enzyme activity by binding to enzymes and inducing aggregation. PVA-coated peptide slides can be rapidly analyzed, given an appropriate enzyme assay, and they may also be assayed under various conditions (such as temperature, pH and solvent). I have developed a general method to discover molecules that modulate enzyme activity at desired conditions. As demonstrations, some peptides were able to promote the thermal stability of bound enzyme, which were selected by performing the microarray-based enzyme assay at high temperature. For broad applications, selected peptide ligands were used to immobilize enzymes on solid surfaces. Compared to conventional methods, enzymes immobilized on peptide-modified surfaces exhibited higher specific activities and stabilities. Peptide-modified surfaces may prove useful for immobilizing enzymes on surfaces with optimized orientation, location and performance, which are of great interest to the biocatalysis industry.
ContributorsFu, Jinglin (Author) / Woodbury, Neal W (Thesis advisor) / Johnston, Stephen A. (Committee member) / Ghirlanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2010
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Description
Peptides offer great promise as targeted affinity ligands, but the space of possible peptide sequences is vast, making experimental identification of lead candidates expensive, difficult, and uncertain. Computational modeling can narrow the search by estimating the affinity and specificity of a given peptide in relation to a predetermined protein

Peptides offer great promise as targeted affinity ligands, but the space of possible peptide sequences is vast, making experimental identification of lead candidates expensive, difficult, and uncertain. Computational modeling can narrow the search by estimating the affinity and specificity of a given peptide in relation to a predetermined protein target. The predictive performance of computational models of interactions of intermediate-length peptides with proteins can be improved by taking into account the stochastic nature of the encounter and binding dynamics. A theoretical case is made for the hypothesis that, because of the flexibility of the peptide and the structural complexity of the target protein, interactions are best characterized by an ensemble of possible bound configurations rather than a single “lock and key” fit. A model incorporating these factors is proposed and evaluated. A comprehensive dataset of 3,924 peptide-protein interface structures was extracted from the Protein Data Bank (PDB) and descriptors were computed characterizing the geometry and energetics of each interface. The characteristics of these interfaces are shown to be generally consistent with the proposed model, and heuristics for design and selection of peptide ligands are derived. The curated and energy-minimized interface structure dataset and a relational database containing the detailed results of analysis and energy modeling are made publicly available via a web repository. A novel analytical technique based on the proposed theoretical model, Virtual Scanning Probe Mapping (VSPM), is implemented in software to analyze the interaction between a target protein of known structure and a peptide of specified sequence, producing a spatial map indicating the most likely peptide binding regions on the protein target. The resulting predictions are shown to be superior to those of two other published methods, and support the validity of the stochastic binding model.
ContributorsEmery, Jack Scott (Author) / Pizziconi, Vincent B (Thesis advisor) / Woodbury, Neal W (Thesis advisor) / Guilbeau, Eric J (Committee member) / Stafford, Phillip (Committee member) / Taylor, Thomas (Committee member) / Towe, Bruce C (Committee member) / Arizona State University (Publisher)
Created2010
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Description
Protein-surface interactions, no matter structured or unstructured, are important in both biological and man-made systems. Unstructured interactions are more difficult to study with conventional techniques due to the lack of a specific binding structure. In this dissertation, a novel approach is employed to study the unstructured interactions between proteins and

Protein-surface interactions, no matter structured or unstructured, are important in both biological and man-made systems. Unstructured interactions are more difficult to study with conventional techniques due to the lack of a specific binding structure. In this dissertation, a novel approach is employed to study the unstructured interactions between proteins and heterogonous surfaces, by looking at a large number of different binding partners at surfaces and using the binding information to understand the chemistry of binding. In this regard, surface-bound peptide arrays are used as a model for the study. Specifically, in Chapter 2, the effects of charge, hydrophobicity and length of surface-bound peptides on binding affinity for specific globular proteins (&beta-galactosidase and &alpha1-antitrypsin) and relative binding of different proteins were examined with LC Sciences peptide array platform. While the general charge and hydrophobicity of the peptides are certainly important, more surprising is that &beta-galactosidase affinity for the surface does not simply increase with the length of the peptide. Another interesting observation that leads to the next part of the study is that even very short surface-bound peptides can have both strong and selective interactions with proteins. Hence, in Chapter 3, selected tetrapeptide sequences with known binding characteristics to &beta-galactosidase are used as building blocks to create longer sequences to see if the binding function can be added together. The conclusion is that while adding two component sequences together can either greatly increase or decrease overall binding and specificity, the contribution to the binding affinity and specificity of the individual binding components is strongly dependent on their position in the peptide. Finally, in Chapter 4, another array platform is utilized to overcome the limitations associated with LC Sciences. It is found that effects of peptide sequence properties on IgG binding with HealthTell array are quiet similar to what was observed with &beta-galactosidase on LC Science array surface. In summary, the approach presented in this dissertation can provide binding information for both structured and unstructured interactions taking place at complex surfaces and has the potential to help develop surfaces covered with specific short peptide sequences with relatively specific protein interaction profiles.
ContributorsWang, Wei (Author) / Woodbury, Neal W (Thesis advisor) / Liu, Yan (Committee member) / Chaput, John (Committee member) / Arizona State University (Publisher)
Created2014