The Hepatitis E Virus Polyproline Region Is Involved in Viral Adaptation

Genomes of hepatitis E virus (HEV), rubivirus and cutthroat virus (CTV) contain a region of high proline density and low amino acid (aa) complexity, named the polyproline region (PPR). In HEV genotypes 1, 3 and 4, it is the only region within the non-structural open reading frame (ORF1) with positive selection (4–10 codons with dN/dS>1). This region has the highest density of sites with homoplasy values >0.5. Genotypes 3 and 4 show ∼3-fold increase in homoplastic density (HD) in the PPR compared to any other region in ORF1, genotype 1 does not exhibit significant HD (p<0.0001). PPR sequence divergence was found to be 2-fold greater for HEV genotypes 3 and 4 than for genotype 1. The data suggest the PPR plays an important role in host-range adaptation. Although the PPR appears to be hypervariable and homoplastic, it retains as much phylogenetic signal as any other similar sized region in the ORF1, indicating that convergent evolution operates within the major HEV phylogenetic lineages. Analyses of sequence-based secondary structure and the tertiary structure identify PPR as an intrinsically disordered region (IDR), implicating its role in regulation of replication. The identified propensity for the disorder-to-order state transitions indicates the PPR is involved in protein-protein interactions. Furthermore, the PPR of all four HEV genotypes contains seven putative linear binding motifs for ligands involved in the regulation of a wide number of cellular signaling processes. Structure-based analysis of possible molecular functions of these motifs showed the PPR is prone to bind a wide variety of ligands. Collectively, these data suggest a role for the PPR in HEV adaptation. Particularly as an IDR, the PPR likely contributes to fine tuning of viral replication through protein-protein interactions and should be considered as a target for development of novel anti-viral drugs

The Overlap of Small Molecule and Protein Binding Sites within Families of Protein Structures

Protein–protein interactions are challenging targets for modulation by small molecules. Here, we propose an approach that harnesses the increasing structural coverage of protein complexes to identify small molecules that may target protein interactions. Specifically, we identify ligand and protein binding sites that overlap upon alignment of homologous proteins. Of the 2,619 protein structure families observed to bind proteins, 1,028 also bind small molecules (250–1000 Da), and 197 exhibit a statistically significant (p<0.01) overlap between ligand and protein binding positions. These “bi-functional positions”, which bind both ligands and proteins, are particularly enriched in tyrosine and tryptophan residues, similar to “energetic hotspots” described previously, and are significantly less conserved than mono-functional and solvent exposed positions. Homology transfer identifies ligands whose binding sites overlap at least 20% of the protein interface for 35% of domain–domain and 45% of domain–peptide mediated interactions. The analysis recovered known small-molecule modulators of protein interactions as well as predicted new interaction targets based on the sequence similarity of ligand binding sites. We illustrate the predictive utility of the method by suggesting structural mechanisms for the effects of sanglifehrin A on HIV virion production, bepridil on the cellular entry of anthrax edema factor, and fusicoccin on vertebrate developmental pathways. The results, available at http://pibase.janelia.org, represent a comprehensive collection of structurally characterized modulators of protein interactions, and suggest that homologous structures are a useful resource for the rational design of interaction modulators

Analysis of protein-RNA and protein-peptide interactions in Equine Infectious Anemia Virus (EIAV) infection

Macromolecular interactions are essential for virtually all cellular functions including signal transduction processes, metabolic processes, regulation of gene expression and immune responses. This dissertation focuses on the characterization of two important macromolecular interactions involved in the relationship between Equine Infectious Anemia Virus (EIAV) and its host cell in horse: (i) the interaction between the EIAV Rev protein and its binding site, the Rev-responsive element (RRE) and (ii) interactions between equine MHC class I molecules and epitope peptides derived from EIAV proteins.;EIAV, one of the most divergent members of the lentivirus family, has a single-stranded RNA genome and carries several regulatory and structural proteins within its viral particle. Rev is an essential EIAV regulatory encoded protein that interacts with the viral RRE, a specific binding site in the viral mRNA. Using a combination of experimental and computational methods, the interactions between EIAV Rev and RRE were characterized in detail. EIAV Rev was shown to have a bipartite RNA binding domain containing two arginine rich motifs (ARMs). The RRE secondary structure was determined and specific structural motifs that act as cis-regulatory elements for EIAV Rev-RRE interaction were identified. Interestingly, a structural motif located in the high affinity Rev binding site is well conserved in several diverse lentiviral genomes, including HIV-1.;Macromolecular interactions involved in the immune response of the horse to EIAV infection were investigated by analyzing complexes between MHC class I proteins and epitope peptides derived from EIAV Rev, Env and Gag proteins. Computational modeling results provided a mechanistic explanation for the experimental finding that a single amino acid change in the peptide binding domain of the equine MHC class I molecule differentially affects the recognition of specific epitopes by EIAV-specific CTL. Together, the findings in this dissertation provide novel insights into the strategy used by EIAV to replicate itself, and provide new details about how the host cell responds to and defends against EIAV upon the infection. Moreover, they have contributed to our understanding of the macromolecular recognition events that regulate these processes

Large margin methods for partner specific prediction of interfaces in protein complexes

2014 Spring.The study of protein interfaces and binding sites is a very important domain of research in bioinformatics. Information about the interfaces between proteins can be used not only in understanding protein function but can also be directly employed in drug design and protein engineering. However, the experimental determination of protein interfaces is cumbersome, expensive and not possible in some cases with today's technology. As a consequence, the computational prediction of protein interfaces from sequence and structure has emerged as a very active research area. A number of machine learning based techniques have been proposed for the solution to this problem. However, the prediction accuracy of most such schemes is very low. In this dissertation we present large-margin classification approaches that have been designed to directly model different aspects of protein complex formation as well as the characteristics of available data. Most existing machine learning techniques for this task are partner-independent in nature, i.e., they ignore the fact that the binding propensity of a protein to bind to another protein is dependent upon characteristics of residues in both proteins. We have developed a pairwise support vector machine classifier called PAIRpred to predict protein interfaces in a partner-specific fashion. Due to its more detailed model of the problem, PAIRpred offers state of the art accuracy in predicting both binding sites at the protein level as well as inter-protein residue contacts at the complex level. PAIRpred uses sequence and structure conservation, local structural similarity and surface geometry, residue solvent exposure and template based features derived from the unbound structures of proteins forming a protein complex. We have investigated the impact of explicitly modeling the inter-dependencies between residues that are imposed by the overall structure of a protein during the formation of a protein complex through transductive and semi-supervised learning models. We also present a novel multiple instance learning scheme called MI-1 that explicitly models imprecision in sequence-level annotations of binding sites in proteins that bind calmodulin to achieve state of the art prediction accuracy for this task

Analysis of Protein-RNA and Protein-Peptide Interactions in Equine Infectious Anemia

Macromolecular interactions are essential for virtually all cellular functions including signal transduction processes, metabolic processes, regulation of gene expression and immune responses. This dissertation focuses on the characterization of two important macromolecular interactions involved in the relationship between Equine Infectious Anemia Virus (EIAV) and its host cell in horse: (1) the interaction between the EIAV Rev protein and its binding site, the Rev-responsive element (RRE) and (2) interactions between equine MHC class I molecules and epitope peptides derived from EIAV proteins. EIAV, one of the most divergent members of the lentivirus family, has a single-stranded RNA genome and carries several regulatory and structural proteins within its viral particle. Rev is an essential EIAV regulatory encoded protein that interacts with the viral RRE, a specific binding site in the viral mRNA. Using a combination of experimental and computational methods, the interactions between EIAV Rev and RRE were characterized in detail. EIAV Rev was shown to have a bipartite RNA binding domain contain two arginine rich motifs (ARMs). The RRE secondary structure was determined and specific structural motifs that act as cis-regulatory elements for EIAV Rev-RRE interaction were identified. Interestingly, a structural motif located in the high affinity Rev binding site is well conserved in several diverse lentiviral genoes, including HIV-1. Macromolecular interactions involved in the immune response of the horse to EIAV infection were investigated by analyzing complexes between MHC class I proteins and epitope peptides derived from EIAV Rev, Env and Gag proteins. Computational modeling results provided a mechanistic explanation for the experimental finding that a single amino acid change in the peptide binding domain of the quine MHC class I molecule differentially affectes the recognitino of specific epitopes by EIAV-specific CTL. Together, the findings in this dissertation provide novel insights into the strategy used by EIAV to replicate itself, and provide new details about how the host cell responds to and defends against EIAV upon the infection. Moreover, they have contributed to the understanding of the macromolecular recognition events that regulate these processes

Novel bioinformatics tools for epitope-based peptide vaccine design

BACKGROUND T-cells are essential in the mediation of immune responses, helping clear bacteria, viruses and cancerous cells. T-cells recognise anomalies in the cellular proteome associated with infection and neoplasms through the T-cell receptor (TCR). The most common TCRs in humans, αβ TCRs, engage processed peptide epitopes presented on the major histocompatibility complex (pMHC). TCR-pMHC interaction is critical to vaccination. In this thesis I will discuss three pieces of software and outcomes derived from them that contribute to epitope-based vaccine design. RESULTS Three pieces of software were developed to help scientists study and understand T-cell responses. The first, STACEI allows users to interrogate the TCR-pMHC crystal structures. The time consuming, error-prone analysis that previously would have to be ran manually, is replaced by a single, flexible package. The second development is the introduction of general-purpose computing on the GPU (GP-GPU) in aiding the prediction of T-cell epitopes by scanning protein datasets using data derived from combinatorial peptide libraries (CPLs). Finally, I introduce RECIPIENT, a reverse vaccinology tool (RV) that combines pangenomic and population genetics methods to predict good vaccine targets across multiple pathogen samples. CONCLUSION Across this thesis, I introduce three different methods that aid the study of T-cells that will hopefully improve future vaccine design. These methods range across data types and methodologies, with methods focusing on mechanistic understanding of the TCR-pMHC binding event; the application of GP-GPU to CPLs and using microbial genomics to aid the study and understanding of antigen-specific T-cell responses. These three methods have a significant potential for further integration, especially the structural methods

Dissecting the Histone-binding Mechanism of a PHD Finger Subtype

Disordered tails of histones are critical information retrieval hub and thus, aberrations in the flow of information through these hubs are associated with a number of pathological consequences in human. Mechanism for retrieval of information from these hubs is achieved by protein-protein interaction, i.e. proteins dock onto histone tails to initiate chromatin signaling. Eukaryotes have a number of small peptide binding domains that have evolved to specifically interact with histone tails, and these domains called histone readers as they read the information encoded on histone tails. Plant homeodomain (hereafter PHD) finger, a binucleated zinc finger, family is one such histone readers. Next-generation sequencing efforts on diagnosed patient’s genomes or cancer tissues show that mutations in PHD finger, particularly a subgroup of PHD fingers, are associated with number of pathological consequences. Therefore, for future understanding of the possible mechanisms for the pathological consequences, as an initial step, detailed characterization of the binding mechanism of the PHD subtype, the PHD_nW_DD, was undertaken here. Starting with human BAZ2A (bromodomain adjacent to zinc-finger 2A), one member of the PHD_nW_DD subtype that is associated with prostate cancer was utilized to probe the effect of mutations on histone tail binding. We experimentally discovered two categories of mutations that disrupt peptide binding: (1) Type-A: positions that are in contact with the peptide and (2) Type-B: positions that are remote from the peptide-binding site (distal site). For my dissertation, I focused on understanding the biochemical basis of the effects of Type-A mutations using recombinant protein chemistry and biophysical chemistry. The peptide-anchoring residue positions of BAZ2A-PHD, interestingly, are enriched in specific type of residues in a subtype specific manner. The energetics revealed that, two non-polar amino acid residues and an Aspartate residue in the treble clef knuckle make significant contributions to the formation of the hBAZ2A-histone peptide complex as mutations at these three positions completely aborted peptide binding. The energetic contributions of the identified positions were further confirmed by mutagenesis in three members of the subtype (UHRF1-PHD, KDM5B-PHD and KAT6A-PHD) that included pairs sharing even less than 40% sequence identity with each other. Despite low sequence similarity, mutations cause similar consequences in histone H3 binding suggesting a strong similarity in the binding mechanism, and thus justifying the subtype classification

Exploring the Role of Calcium Ions in Biological Systems by Computational Prediction and Protein Engineering

Ca2+, a signal for death and life, is closely involved in the regulation of numerous important cellular events. Ca2+ carries out its function through its binding to Ca2+-receptors or Ca2+-binding proteins. The EF-hand protein, with a helix-loop-helix Ca2+-binding motif, constitutes one of the largest protein families. To facilitate our understanding of the role of Ca2+ in biological systems (denoted as calciomics) using genomic information, an improved pattern search method (http://www.chemistry.gsu.edu/faculty/Yang/Calciomics.htm) for the identification of EF-hand and EF-like Ca2+-binding proteins was developed. This fast and robust method allows us to analyze putative EF-hand proteins at the genome-wide level and further visualize the evolutionary scenario of the EF-hand protein family. This prediction method further enables us to locate a putative viral EF-hand Ca2+-binding motif within the rubella virus nonstructural protease that cleaves the nonstructural protein precursor into two active replicase components. A novel grafting approach has been used to probe the metal-binding properties of this motif by engineering the predicted 12-residue Ca2+-coordinating loop into a non-Ca2+-binding scaffold protein, CD2 domain 1. Structural and conformational studies were further performed on a purified, bacterially-expressed NS protease minimal metal-binding domain spanning the Zn2+- and EF-hand Ca2+-binding motif. It was revealed that Ca2+ binding induced local conformational changes and increased thermal stability. Furthermore, functional studies were carried out using RUB infectious cDNA clone and replicon constructs. Our studies have shown that the Ca2+ binding loop played a structural role in the NS protease and was specifically required for optimal stability under physiological conditions. In addition, we have predicted and characterized a calmodulin-binding domain in the gap junction proteins connexin43 and connexin44. Peptides encompassing the CaM binding motifs were synthesized and their ability to bind CaM was determined using various biophysical approaches. Transient expression in HeLa cells of two mutant Cx43-EYFP constructs without the putative CaM-binding site eliminated the Ca2+-dependent inhibition of gap junction permeability. These results provide the first direct evidence that CaM binds to a specific region of the ubiquitous gap junction protein Cx43 and Cx44 in a Ca2+-dependent manner, providing a molecular basis for the well-characterized Ca2+-dependent inhibition of Cx43-containing gap junctions

G-quadruplex DNA aptamers and their ligands: Structure, function and application

Highly specific and tight-binding nucleic acid aptamers have been selected against a variety of molecular targets for over 20 years. A significant proportion of these oligonucleotides display G-quadruplex structures, particularly for DNA aptamers, that enable molecular recognition of their ligands. G-quadruplex structures couple a common scaffold to varying loop motifs that act in target recognition. Here, we review DNA G-quadruplex aptamers and their ligands from a structural and functional perspective. We compare the diversity of DNA G-quadruplex aptamers selected against multiple ligand targets, and consider structure with a particular focus on dissecting the thrombin binding aptamer - thrombin interaction. Therapeutic and analytical applications of DNA G-quadruplex aptamers are also discussed. Understanding DNA G-quadruplex aptamers carries implications not only for therapeutics and diagnostics, but also in the natural biochemistry of guanine-rich nucleic acids. © 2012 Bentham Science Publishers.postprin