Mechanistic Elucidation of Protease–Substrate and Protein–Protein Interactions for Targeting Viral Infections

Viral infections represent an old threat to global health, with multiple epidemics and pandemics in the history of mankind. Despite several advances in the development of antiviral substances and vaccines, many viral species are still not targeted. Additionally, new viral species emerge, posing a menace without precedent to humans and animals and causing fatalities, disabilities, environmental harm, and economic losses. In this thesis, we present rational modeling approaches for targeting specific protease-substrate and protein-protein interactions pivotal for the viral replication cycle. Over the course of this work, antiviral research is supported beginning with the development of small molecular antiviral substances, going through the modeling of a potential immunogenic epitope for vaccine development, towards the establishment of descriptors for susceptibility of animals to a viral infection. Notably, all the research was done under scarce data availability, highlighting the predictive power of computational methods and complementarity between in-silico and in-vitro or in-vivo methods

A General, Symmetry-Based Approach for the Assembly of Proteins into Nanoscale Polyhedra.

The assembly of individual protein subunits into large-scale symmetrical structures is widespread in Nature and confers unique biological properties which have potential applications in nano-technology and medicine. While efforts to functionalize and repurpose existing protein complexes have been mainly successful, designing well-defined de novo protein complexes remains an unsolved problem. A major challenge in engineering de novo symmetrical assemblies has been to design interactions between the protein subunits so that they specifically assemble into the desired structure. Prior de novo protein cages have been developed with moderate success, but suffer from a lack of generalizability and require significant computational effort and screening of mutant fusion proteins. The design and optimization of a simple, generalizable approach to designing novel fusion proteins which assemble into cage-like structures will be the subject of this dissertation. We show that by genetically fusing a C4-symmetric coiled-coil to the C-terminus of a C3-symmetric trimeric protein via a short, flexible linker, we can assemble a well-defined 24-subunit protein cage with octahedral symmetry. The flexible nature of these assemblies alleviates the need for rigorous interface modeling, requiring only minimal computation to determine the length of the linker sequence. This is the first de novo designed symmetrical protein complex to incorporate a C4 symmetry element, and we anticipate this method can be applied to a wider variety of proteins and symmetries, which may open up a new avenue of research into designer protein cages with unique, built-in functionalities.PHDChemistryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120840/1/sciore_1.pd

Advances in Molecular Simulation

Molecular simulations are commonly used in physics, chemistry, biology, material science, engineering, and even medicine. This book provides a wide range of molecular simulation methods and their applications in various fields. It reflects the power of molecular simulation as an effective research tool. We hope that the presented results can provide an impetus for further fruitful studies

Predicting multibody assembly of proteins

textThis thesis addresses the multi-body assembly (MBA) problem in the context of protein assemblies. [...] In this thesis, we chose the protein assembly domain because accurate and reliable computational modeling, simulation and prediction of such assemblies would clearly accelerate discoveries in understanding of the complexities of metabolic pathways, identifying the molecular basis for normal health and diseases, and in the designing of new drugs and other therapeutics. [...] [We developed] F²Dock (Fast Fourier Docking) which includes a multi-term function which includes both a statistical thermodynamic approximation of molecular free energy as well as several of knowledge-based terms. Parameters of the scoring model were learned based on a large set of positive/negative examples, and when tested on 176 protein complexes of various types, showed excellent accuracy in ranking correct configurations higher (F² Dock ranks the correcti solution as the top ranked one in 22/176 cases, which is better than other unsupervised prediction software on the same benchmark). Most of the protein-protein interaction scoring terms can be expressed as integrals over the occupied volume, boundary, or a set of discrete points (atom locations), of distance dependent decaying kernels. We developed a dynamic adaptive grid (DAG) data structure which computes smooth surface and volumetric representations of a protein complex in O(m log m) time, where m is the number of atoms assuming that the smallest feature size h is [theta](r[subscript max]) where r[subscript max] is the radius of the largest atom; updates in O(log m) time; and uses O(m)memory. We also developed the dynamic packing grids (DPG) data structure which supports quasi-constant time updates (O(log w)) and spherical neighborhood queries (O(log log w)), where w is the word-size in the RAM. DPG and DAG together results in O(k) time approximation of scoring terms where k << m is the size of the contact region between proteins. [...] [W]e consider the symmetric spherical shell assembly case, where multiple copies of identical proteins tile the surface of a sphere. Though this is a restricted subclass of MBA, it is an important one since it would accelerate development of drugs and antibodies to prevent viruses from forming capsids, which have such spherical symmetry in nature. We proved that it is possible to characterize the space of possible symmetric spherical layouts using a small number of representative local arrangements (called tiles), and their global configurations (tiling). We further show that the tilings, and the mapping of proteins to tilings on arbitrary sized shells is parameterized by 3 discrete parameters and 6 continuous degrees of freedom; and the 3 discrete DOF can be restricted to a constant number of cases if the size of the shell is known (in terms of the number of protein n). We also consider the case where a coarse model of the whole complex of proteins are available. We show that even when such coarse models do not show atomic positions, they can be sufficient to identify a general location for each protein and its neighbors, and thereby restricts the configurational space. We developed an iterative refinement search protocol that leverages such multi-resolution structural data to predict accurate high resolution model of protein complexes, and successfully applied the protocol to model gp120, a protein on the spike of HIV and currently the most feasible target for anti-HIV drug design.Computer Science

Minimal training time in supervised retinal vessel segmentation

In this paper, we perform comparative analysis between different classifiers using the same experimental setup for supervised retinal vessel segmentation. The aim of this paper is to find supervised classifier that can obtain good segmentation accuracy with minimal training time. Minimizing the training time is essential when dealing with biomedical images. The more samples introduced to a learning model, the better it can adapt to the unseen data. The results indicate a trade-off between accuracy and training time can be obtained in a classifier trained by a Neural Network. When tested with a publicly available database, the learning model only requires less than 2 minutes in the learning phase and achieves overall accuracy of 94.54%

Molecular Simulation Studies on the Prion Protein Variants: Insights into the Intriguing Effects of Mutations

Prion diseases, or transmissible spongiform encephalopathies (TSE), are a group of rare fatal neurodegenerative maladies that affect humans and animals. The fundamental breakthrough in TSE research was the discovery of the "prion"\u23afproteinaceous infectious particle\u23af and the verification of the \u201cprotein-only\u201d hypothesis, which states that prions could self-propagate by converting the cellular prion protein (PrPC) into the scrapie form, PrPSc (or prions), and lead to neurodegeneration without using any nucleic acids. The concept of prions may unify neurodegenerative diseases under a common pathogenic mechanism. Indeed, growing evidence shows that TSE may share similar pathogenesis with common neurodegenerative syndromes such as Alzheimer\u2019s disease and Parkinson\u2019s disease, for which there are currently no cure. Today, PrP is one of the most studied models for protein misfolding mechanism and TSE serve as an excellent model for studying many other neurodegenerative diseases. Understanding the molecular mechanism of the PrP misfolding process may profoundly influence the development of diagnostics and effective therapies for neurodegenerative diseases in general. Investigating human (Hu) PrP TSE-linked mutations (more than 50 currently identified mutations, linked to ~15% of the cases) may be very instrumental in this respect, as it can provide hints on the molecular basis of the PrPC\u2192PrPSc conversion. These mutations cause spontaneous TSE, which are likely due to modifications in the native structure of PrPC. They are located all over the structure. Polymorphisms (i.e. non-pathogenic, naturally occurring mutations) in the PrP gene have been found to influence the etiology and neuropathology of the disease in both humans and sheep. In transgenic (Tg) mice, artificial mutations can determine the susceptibility to the infection of different prion strains. Intriguingly, mouse (Mo) PrP containing artificial mutations (denoted MoPrP chimera, hereinafter) have very different effects in vitro: some MoPrP chimera were found to resist PrPSc infection, whereas some others did not; some of the resistant MoPrP chimeras even exhibited a protective effect (known as the dominant-negative effect) over the co-expressed endogenous wild-type (WT) MoPrPC. Most mutations are located in the folded globular domain (GD) while fewer are located in the intrinsically disordered N-terminal domain (N-term). The N-term of PrPC has been suggested to serve multiple functions in vivo, which likely relies on the structural flexibility of this domain. Therefore, characterizing the structural features of the N-term is central for investigating not only the mutations in this domain, but also the physiological role of the N-term. Based on previous studies in our lab, in this thesis we first applied molecular dynamics simulations to studying the impact of all the known Hu TSE-linked mutations in HuPrPC GD. We next applied the same approach to study the GD structure of MoPrP chimeras which contain one or two residues from Hu or sheep PrP sequence. By studying these PrP variants, we aim to identify the structural determinants of the mutants that may play a role in the PrPC\u2192PrPSc conversion. Our calculations discovered that these mutants exhibit different structural features from those of the WT PrP GD mainly in two common regions that are likely the \u201chot spots\u201d in the protein misfolding process. These features can be classified into different types that are correlated to the types of mutants (i.e. pathogenic, resistant or dominant-negative), thus hinting to the molecular mechanisms of PrPSc formation and propagation. We have then predicted the structure of the entire PrP N-term and the impact of the Hu TSE-linked mutations in this domain using a novel Monte Carlo-based simulation approach, PROFASI. PROFASI has already shown to provide structural predictions in a disordered protein such as \u3b1-synuclein. Our results are consistent with available experimental data and therefore firmly allow us to provide the first overview on the structural determinants of all Hu TSE-linked mutations in PrP

Structural and Functional Studies of Proteins Involved in Antigen Processing: A Dissertation

This thesis is comprised of studies of proteins involved in class I and class II major histocompatibility complex (MHC) antigen procressing. In class I MHC processing, structural and functional studies were conducted of an aminopeptidase, ERAP1, that mediates the final step in antigen processing to understand how it is particularly suitable for cleavage of antigenic peptides for class I MHC presentation. In the class II MHC antigen presentation pathway, structural studies were conducted to characterize a fluorogenic peptide that can be used to understand peptide loading events in vivo and in real time. Also structural studies of class II MHC and peptide complexes were conducted to understand the nature of an unique C-terminal secondary structure element exhibited by an HIV derived peptide in the peptide binding groove of class II MHC. The studies discussed in this thesis provide insights into the proteins involved in the class I and class II MHC antigen presentation pathway. The endoplasmic reticulum (ER) aminopeptidase, ERAP1, is a 941 amino acid member of the M1 family of zinc metalloaminopeptidases. Unlike other aminopeptidases, ERAP1 has a length and C-terminal preference for its substrates. Interestingly, ERAP1 has been shown to trim antigenic peptides to lengths of 8 or 9 amino acids long. This length matches the length required to bind into the peptide binding groove of class I MHC molecules. In addition, ERAP1 is upregulated in the ER of cells treated with interferon gamma (IFN-γ). Knock-down of ERAP1 by siRNA results in less overall antigenic presentation during IFN-γ treatment, although the knock-down does not affect all class I MHC epitopes equally. Knock-out studies show that ERAP1 effects the antigen repertoire at the cell surface. These and other data implicate ERAP1 as an important player in class I MHC antigen presentation. A chapter of this thesis will describe the crystallographic work describing the structures of ERAP1 with an aminopeptidase inhibitor, bestatin, and ERAP1 without an inhibitor that suggest possible peptide binding site in ERAP1 that will allow it to generate suitable substrates for a subset of class I MHC alleles. Class II MHC plays a key role in the immune response by presenting antigenic peptides on CD4+ cytotoxic cell surfaces for T-cell response. The binding of peptides onto the MHC is an important step in creating an immune response. Structures of peptide bound MHC class II show conserved side chain binding pockets within the overall peptide-binding groove. In HLA-DR1, a common human class II MHC, the P1 pocket shows a preference for large hydrophobic side chains. Development of environmentally sensitive peptide analogs, that can bind into the class II MHC the same way as native peptides, can assist in visualizing the antigen binding process. A chapter in this thesis describes the crystallographic work showing that (4-DAPA)-HA can be used to study antigen-presenting processes in a cell by visualizing the changes in fluorescence of the synthesized peptide upon antigen loading. Crystallographic analysis of MHC class II, HLA-DR1, in complex with HIV gag-derived peptide, GagP16(PEVIPMFSALSEGATP), and superantigen, SEC3- 3B2, reveals the conventional polyproline conformation up to MHC binding pocket residue, P9, while the C-terminus of GagP16 adopts an unusual β- hairpin loop structure. Additionally, interactions between the leucine at P8 (LeuP8) and other residues on the loop such as ThrP16 and AlaP14 of the hairpin loop, was observed. Importantly, GagP16 requires the last 4 amino acids (P13-P16), which is part of the hairpin loop, for T-cell recognition. Understanding what dictates the C-terminal hairpin loop and the interaction motif of HLA-DR1/GagP16 complex with its TCR will provide insights on why it is important for T cell activation. A chapter in this thesis discusses the structural investigation conducted to understand the determinants of the loop at the C-terminus of GagP16 using designed peptides. It will also discuss work involving HLA-DR1 with the T cell receptor, AC25, that was cloned from T cells that are specific to HLA-DR1 in complex with the GagP16 peptide

The Conformational Universe of Proteins and Peptides: Tales of Order and Disorder

Proteins represent one of the most abundant classes of biological macromolecules and play crucial roles in a vast array of physiological and pathological processes. The knowledge of the 3D structure of a protein, as well as the possible conformational transitions occurring upon interaction with diverse ligands, are essential to fully comprehend its biological function.In addition to globular, well-folded proteins, over the past few years, intrinsically disordered proteins (IDPs) have received a lot of attention. IDPs are usually aggregation-prone and may form toxic amyloid fibers and oligomers associated with several human pathologies. Peptides are smaller in size than proteins but similarly represent key elements of cells. A few peptides are able to work as tumor markers and find applications in the diagnostic and therapeutic fields. The conformational analysis of bioactive peptides is important to design novel potential drugs acting as selective modulators of specific receptors or enzymes. Nevertheless, synthetic peptides reproducing different protein fragments have frequently been implemented as model systems in folding studies relying on structural investigations in water and/or other environments.This book contains contributions (seven original research articles and five reviews published in the journal Molecules) on the above-described topics and, in detail, it includes structural studies on globular folded proteins, IDPs and bioactive peptides. These works were conducted usingdifferent experimental methods

Antibody Discovery, Optimization, and Application: Translational Protein Engineering for Precision Medicine

Next-generation, “omics-based”, translational research is rapidly characterizing genetically determined pathophysiology at an unprecedented depth. Through the application of high-throughput sequencing technologies and advanced immune engineering methods new insights into adaptive immunity has been generated at an extraordinary rate. However, despite rapid accumulation of new scientific insight, critical gaps in our scientific understanding of antibody-mediated molecular immunity limit the number of novel antibody-based medical interventions that translate past basic scientific discovery andinto clinical application. Here, this original work directly addresses outstanding gaps in our scientific knowledge of molecular humoral immunity through the discovery, optimization, enhancement, and biophysical characterization of monoclonal antibody proteins to inform the development of new precision medicines. Experimental monoclonal antibody genes, structure, and functions are assessed using a suite of immune engineering technologies, including: natively-paired antibody heavy:light chain complementary DNA libraries, in vitro mutagenesis, recombinant DNA vectors, functional yeast-surface display, fluorescence activated cell screening, high-throughput single-cell next-generation sequencing, and advanced biophysical characterization assays to translate basic research findings into new, clinically relevant, insights. Experimental application of these technologies using functional antibody:antigen screening methods produced the discovery of a novel SARS-CoV-2 neutralizing monoclonal antibody 910-30, and delineated antibody paired heavy:light chain sequence-structure-function signatures contributing to potent SARS-CoV-2 neutralization in public antibody responses. These findings have important applications for understanding communal immunity and developing effective intervention strategies during an acute global pandemic outbreak. This work also describes translational antibody protein engineering methods used to define precise, functionally optimized, genetic sequences from template monoclonal antibodies CIS43 and VRC34.01, which target the clinically relevant pathogens plasmodium falciparum and viral HIV-1, respectively. The antibody insights gained from functional optimization experiments were used to produce improved biomolecular blueprints defining structural mechanisms and forward pathways for highly protective humoral immunity against P. falciparum and HIV-1, respectively. Altogether, the scientific outcomes from this research have immediate clinical applications for the development of therapeutic, prophylactic, diagnostic and research reagents for COVID-19, HIV/AIDS, and malaria, as well as broad impact for the development of precision medicines against diseases of clinical relevance