<p>Living cells are controlled by proteins and genes that interact through complex molecular pathways to achieve a specific function. Therefore, determination of protein-protein interaction is fundamental for the understanding of the cell’s lifecycle and functions. The function of a protein is also largely determined by its interactions with other proteins. The amount of protein-protein interaction data available has multiplied by the emergence of large-scale technologies for detecting them, but the drawback of such measures is the relatively high amount of noise present in the data. It is time consuming to experimentally determine protein-protein interactions and therefore the aim of this project is to create a computational method that predicts interactions with high sensitivity and specificity. Semantic similarity measures were applied across the Gene Ontology terms assigned to proteins in S. cerevisiae to predict protein-protein interactions. Three semantic similarity measures were tested to see which one performs best in predicting such interactions. Based on the results, a method that predicts function of proteins in connection with connectivity was devised. The results show that semantic similarity is a useful measure for predicting protein-protein interactions.</p>

Title from title page of PDF (University of Missouri--St. Louis, viewed February 22, 2010). Includes bibliographical references.

Thesis (M.S.)--Mississippi State University. Department of Chemistry. / Title from title screen. Includes bibliographical references.

Noncovalent factors, such as shape complementarity and electrostatic driving forces, almost exclusively cause the affinity and specificity for which two or more biological macromolecules organize into a functioning complex. The human oncoprotein p21Ras (Ras) and a structurally identical but functionally distant analog, Rap1A (Rap), exhibit high selectivity and specificity when binding to downstream effector proteins that cannot be explained through structural analysis alone. Both Ras and Rap bind to Ral guanine nucleotide dissociation stimulator (RalGDS) with affinities that differ tenfold instigating diverse cellular functions; it is hypothesized that this specificity of RalGDS to discriminate between GTPases is largely electrostatic in nature. To investigate this hypothesis, electrostatic fields at the binding interface between mutants of RalGDS bound to Rap or Ras are measured using vibrational Stark effect (VSE) spectroscopy, in which spectral shifts of a probe oscillator’s energy is related directly to that probe’s local electrostatic environment and measured by Fourier transform infrared spectroscopy (FTIR). After calibration, the probe is inserted into a known position in RalGDS where it becomes a highly local, sensitive, and directional reporter of fluctuations of the protein’s electrostatic field caused by structural or chemical perturbations of the protein. The thiocyanate (SCN) vibrational spectroscopic probe was systematically incorporated throughout the binding interface of RalGDS. Changes in the absorption energy of the thiocyanate probe upon binding were directly related to the change of the strength of the local electrostatic field in the immediate vicinity of the probe, thereby creating a comprehensive library of the binding interactions between Ras-RalGDS and Rap-RalGDS. The measured SCN absorption energy on the monomeric protein was compared with solvent-accessible surface area (SASA) calculations with the results highlighting the complex structural and electrostatic nature of protein-water interface. Additional SASA studies of the nine RalGDS mutants that bind to Ras or Rap verified that experimentally measured thiocyanate absorption energies are negatively correlated with exposure to water at the protein-water interface. By changing the solvent composition, we confirmed that the cyanocysteine residues that are more exposed to solvent experienced a large difference in absorption energy. These studies reinforce the hypothesis that differences in the electrostatic environment at the binding interfaces of Ras and Rap are responsible for discriminating binding partners. / text

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

Protein-protein interactions are of great importance to a number of essential biological processes including cell cycle regulation, cell-cell interactions, DNA replication, transcription and translation. Thus, an understanding of protein-protein interactions is critical for understanding many facets of cell function. Unfortunately, the tools and methods currently in use to identify and study protein-protein interactions focus largely on high affinity, stable interactions. However, the majority of the protein-protein interactions involved in regulatory processes have weak affinities and are transient in nature. Therefore, it is important to develop new biotechnology capable of detecting weak and/or transient protein-protein interactions in vivo. Here, we describe four new methods that allow for the identification and study of weak and/or transient protein-protein interactions in vivo. First, we developed a rapid method to convert Escherichia coli orthogonal tRNA/synthetase pairs into an orthogonal system for mammalian cells in order to site-specifically incorporate unnatural amino acids into any gene of interest using stop codon suppression. This method will allow the expression and purification of proteins that carry normally transient post-translational modifications. Second, we successfully employed site-specific unnatural amino acid incorporation to chemically cross-link a known homodimer, Sortase A, in vivo. Third, we developed a novel tetracycline repressor-based mammalian two-hybrid system and successfully detected homo- and hetero-dimers that are known to have weak binding constants. Finally, a synthetic antibody (termed a synbody) that binds weakly to the SH3 domain of the proto-oncogene Abelson tyrosine kinase was developed. The synbody can potentially be used as a first generation drug and/or biomarker. We hope that the methods developed in this dissertation will enable the scientific community to better understand weak/transient protein-protein interactions in vivo. / text

published_or_final_version / Chemistry / Doctoral / Doctor of Philosophy

Tight junctions, as zones of close contact between epithelial and endothelial cells, form a physical barrier as one of the first host defense strategies that prevent the intrusion of pathogens across epithelia and endothelia. Recently, an interaction between the Severe Acute Respiratory Syndrome-Coronavirus (SARS-CoV) envelope protein (E) and PALS1, a member of the CRB tight junction complex, was identified in the Virus-Host Interaction group at HKU-Pasteur Research Centre (Teoh et al, 2010). In this report, I present in vitro data which helps to better understand how this protein-protein interaction could interfere with the formation and maintenance of tight junctions at the apical domain of epithelial cells. In previous research, the interaction between E and PALS1 was identified through a yeast two-hybrid screen and confirmed in vitro. A PDZ-binding motif (PBM) was identified at the C-terminal end of E, which interacts with the PDZ domain of PALS1. The objective of my research was to further enhance the knowledge of this interaction by studying the effect of E expression on PALS1 localization and tight junction structure in epithelial cells. I have shown that expression of E is associated with a partial relocalization of PALS1 to the Golgi compartment. Also, I discovered that when wild-type E, E(wt), was expressed in the MDCKII cell model, the time required for tight junction formation was extended to 6-8 hours, while normal cells only required two hours. Interestingly, expression of the E protein with a deletion of the PBM, E(ΔPBM) did not affect the timing of tight junction formation. This finding indicates that the PBM plays a critical role in the process of alteration of tight junctions mediated by E, most likely through its interaction with PALS1. Furthermore, the localization pattern of E was altered when its PBM was deleted. In the MDCKII model, E(wt) located, as expected, at membranes of the Golgi compartment, whereas E(ΔPBM) had a diffused distribution in the cytosol. This observation suggests that the PBM acts as a localization signal for the E protein to the Golgi region, which is the assembly site of the virus. Finally, to examine the role of the PBM in the context of the whole virus, I participated in the production of SARS-CoV recombinant viruses, with mutations in the PBM of E. Though this work is still in progress, the use of these viruses should help to delineate the role of E PBM in SARS-CoV induced pathogenesis in vitro and ultimately in vivo. / published_or_final_version / Pathology / Master / Master of Philosophy

The functional aspects of proteins are largely dictated by highly selective protein- protein and protein-ligand interactions, even in situations of high structural homology, where electrostatic factors are the major contributors to selectivity. The vibrational Stark effect (VSE) allows us to measure electrostatic fields in complex environments, such as proteins, by the introduction of a vibrational chromophore whose vibrational absorption energy is linearly sensitive to changes in the local electrostatic field. The works presented here seek to computationally quantify electrostatic fields measured via VSE, with the eventual goal of being able to quantitatively predict electrostatic fields, and therefore Stark shifts, for any given protein-interaction. This is done using extensive molecular dynamics in the Amber03 and AMOEBA force fields to generate large ensembles the GTPase Rap1a docked to RalGDS and [superscript p]²¹Ras docked to RalGDS. We discuss how side chain orientations contribute to the differential binding of different mutations of Rap1a binding to RalGDS, where it was found that a hydrogen-bonding pocket is disrupted by the mutation of position 31 from lysine to glutamic acid. We then show that multi-dimensional umbrella sampling of the probe orientations yields a wider range of accessible structures, increasing the quality of the ensembles generated. A large variety of methods for calculating electrostatic fields are presented, with Poisson- Boltzmann electrostatics yielding the most consistent, reliable results. Finally, we explore using AMOEBA for both ensemble-generation as well as the electrostatic description of atoms for field calculations, where early results suggest that the electrostatic field due to the induce dipole moment of the probe is responsible for predicting qualitatively correct Stark shifts.

Microarray technology has revolutionized the field of molecular biology by offering an efficient and cost effective platform for the simultaneous quantification of thousands of genes or even entire genomes in a single experiment. Unlike southern blotting, which is restricted to the measurement of one gene at-a-time, microarrays offer biologists with the opportunity to carry out genome-wide experiments in order to help them gain a systems level understanding of cell regulation and control. The application of bioinformatics in the milieu of gene expression analysis has attracted a great deal of attention in the recent past due to specific algorithms and software solutions that attempt to illustrate complex multidimensional microarray data in a biologically coherent fashion so that it can be understood by the biologist. This has given rise to some exciting prospects for deciphering microarray data, by helping us refine our comprehension pertinent to the underlying physiological dynamics of disease. Although much progress is being made in the development of specialized bioinformatics software pipelines with the purpose of decoding large volumes of gene expression data in the context of systems biology, several loopholes exist. Perhaps most notable of these loopholes is the fact that there is an increasing demand for software solutions that specialize in automating the comparison of multiple gene expression profiles, derived from microarray experiments sharing a common biological theme. This is no doubt an important challenge, since common genes across different biological conditions having similar expression patterns are likely to be involved in the same biological process and hence, may share the same regulatory signatures. The potential benefits of this in refining our understanding of the physiology of disease are undeniable. The research presented in this thesis provides a systematic walkthrough of a series of software pipelines developed for the purpose of streamlining gene expression analysis in a systems biology context. Firstly, we present BiSAn, a software tool that deciphers expression data from the perspective of transcriptional regulation. Following this, we present Genome Interaction Analyzer (GIA), which analyzes microarray data in the integrative framework of transcription factor binding sites, protein-protein interactions and molecular pathways. The final contribution is a software pipeline called MicroPath, which analyzes multiple sets of gene expression profiles and attempts to extract common regulatory signatures that may be implicating the biological question.