C1, SAP and ZiCo: structural studies of three metal‑binding proteins from a crystallographic perspective

Atomic resolution models of proteins are crucial for understanding their biological mechanisms and provide insights into the relationship between protein sequence and structure. Many protein structures incorporate metal ions, exploiting their unique chemistry as reaction centres or for structural stability. This thesis describes the progress made towards solving the structures of three such metal-binding proteins by means of X-ray crystallography. Complement component C1 is a large protein complex that initiates the first line of immune defence and requires calcium for structural stability. Fragments of C1 have already been solved at high resolution, but there are no accurate models of the assembled complex. In this work, a new method for purifying intact C1 from human serum was developed and the purified complex was characterised by various methods. Finally, attempts were made to crystallise native human C1 with a view to obtaining high-resolution structures of the entire complex. Serum amyloid P is another serum protein, also thought to be involved in the immune response. It is often found associated with amyloid deposits, although SAP binds a variety of ligands in a calcium-dependent manner. While the structure of SAP has been determined, its physiological function is still not fully understood. SAP was purified using established methods and its ligand-binding properties were investigated under various conditions using dynamic light scattering, in an attempt to gather more information about the possible function of this molecule. Finally, ZiCo is a small peptide that was designed to switch between a multimeric coiled coil and a monomeric zinc finger fold on binding zinc. The system has been characterised extensively in solution, but high-resolution structures are required to validate the design. ZiCo was crystallised and diffraction data were collected. The structure of the peptide was partially solved, indicating that the multimeric form of the ZiCo peptide is indeed a trimeric coiled coil

Combinatorial Design Of Virtual Sialic Acid Analogues Against Influenza A Hemagglutinin Using Structure And Fragment Based Approaches

In this study molecular modeling techniques were used to design databases of virtual SA analogues by a single substitution at either of C2, C5 or C6 positions of SA scaffold. Dalam kajian ini, kaedah pemodelan molekul telah digunakan untuk mereka bentuk pangkalan data analog maya SA dengan penggantian tunggal sama ada pada kedudukan C2, C5 atau C6 rangka SA

Computational approaches to virtual screening in human central nervous system therapeutic targets

In the past several years of drug design, advanced high-throughput synthetic and analytical chemical technologies are continuously producing a large number of compounds. These large collections of chemical structures have resulted in many public and commercial molecular databases. Thus, the availability of larger data sets provided the opportunity for developing new knowledge mining or virtual screening (VS) methods. Therefore, this research work is motivated by the fact that one of the main interests in the modern drug discovery process is the development of new methods to predict compounds with large therapeutic profiles (multi-targeting activity), which is essential for the discovery of novel drug candidates against complex multifactorial diseases like central nervous system (CNS) disorders. This work aims to advance VS approaches by providing a deeper understanding of the relationship between chemical structure and pharmacological properties and design new fast and robust tools for drug designing against different targets/pathways. To accomplish the defined goals, the first challenge is dealing with big data set of diverse molecular structures to derive a correlation between structures and activity. However, an extendable and a customizable fully automated in-silico Quantitative-Structure Activity Relationship (QSAR) modeling framework was developed in the first phase of this work. QSAR models are computationally fast and powerful tool to screen huge databases of compounds to determine the biological properties of chemical molecules based on their chemical structure. The generated framework reliably implemented a full QSAR modeling pipeline from data preparation to model building and validation. The main distinctive features of the designed framework include a)efficient data curation b) prior estimation of data modelability and, c)an-optimized variable selection methodology that was able to identify the most biologically relevant features responsible for compound activity. Since the underlying principle in QSAR modeling is the assumption that the structures of molecules are mainly responsible for their pharmacological activity, the accuracy of different structural representation approaches to decode molecular structural information largely influence model predictability. However, to find the best approach in QSAR modeling, a comparative analysis of two main categories of molecular representations that included descriptor-based (vector space) and distance-based (metric space) methods was carried out. Results obtained from five QSAR data sets showed that distance-based method was superior to capture the more relevant structural elements for the accurate characterization of molecular properties in highly diverse data sets (remote chemical space regions). This finding further assisted to the development of a novel tool for molecular space visualization to increase the understanding of structure-activity relationships (SAR) in drug discovery projects by exploring the diversity of large heterogeneous chemical data. In the proposed visual approach, four nonlinear DR methods were tested to represent molecules lower dimensionality (2D projected space) on which a non-parametric 2D kernel density estimation (KDE) was applied to map the most likely activity regions (activity surfaces). The analysis of the produced probabilistic surface of molecular activities (PSMAs) from the four datasets showed that these maps have both descriptive and predictive power, thus can be used as a spatial classification model, a tool to perform VS using only structural similarity of molecules. The above QSAR modeling approach was complemented with molecular docking, an approach that predicts the best mode of drug-target interaction. Both approaches were integrated to develop a rational and re-usable polypharmacology-based VS pipeline with improved hits identification rate. For the validation of the developed pipeline, a dual-targeting drug designing model against Parkinson’s disease (PD) was derived to identify novel inhibitors for improving the motor functions of PD patients by enhancing the bioavailability of dopamine and avoiding neurotoxicity. The proposed approach can easily be extended to more complex multi-targeting disease models containing several targets and anti/offtargets to achieve increased efficacy and reduced toxicity in multifactorial diseases like CNS disorders and cancer. This thesis addresses several issues of cheminformatics methods (e.g., molecular structures representation, machine learning, and molecular similarity analysis) to improve and design new computational approaches used in chemical data mining. Moreover, an integrative drug-designing pipeline is designed to improve polypharmacology-based VS approach. This presented methodology can identify the most promising multi-targeting candidates for experimental validation of drug-targets network at the systems biology level in the drug discovery process

A novel bioactive nano-composite: synthesis and characterisation with potential use as dental restorative material

PhDIt is desirable for a dental restorative material to have bioactive and bonding properties. This study focuses on the synthesis of a covalently-linked polyurethane/nanohydroxyapatite (PU/nHA) composite and evaluates its chemical, physical, thermal and biochemical characteristics. nHA powder was produced from the sol-gel and novel composite material was chemically prepared by utilising solvent polymerisation. The resulting composites were analysed by chemical, thermal, and mechanical characterisations and electrospun to form fibre mats. The composites were hydrolytically degraded in deionised water and phosphate buffer solution (PBS) and were analysed. Bioactive behaviour was determined in modified-simulated body fluid. The bioadhesion with dentine was analysed in distilled water and artificial saliva. Cell growth and proliferation was measured and number of adhering bacteria was determined and serial dilution followed by plating for colony forming units per disc. Spectral analyses showed the grafted isocyanate and ether peaks on nHA indicating that urethane linkage was established. Covalent-linkage between nHA and PU were found in this novel composite with no silane agent. The physical and thermal properties were enhanced by nHA. These composites had high resistance toward hydrolysis and little degradation was observed. Bioadhesion and bioactivity analysis showed the composite adhered firmly on the tooth surface (dentine) and bond strength was similar to existing obturating material. Higher nHA content composite showed a thicker layer of adhesion. Cells were proliferated although at a lower rate of growth compared to PU, whereas, there was reduction in bacteria adhering to the grafted composite compared to PU. With its low bacterial adhesion and biocompatibility it may provide a promising solution to reduce infections. The electrospun nano-fibres were successfully developed and revealed no loose nHA particles. Hence, this novel composite has the potential to be used as a bioactive dental restorative material

Synthesis and characterization of Benzo-[1,8]-naphthyridine-4(1H)-ones, Benzo[b]pyrazolo-[5,1-f][1,6]-naphthyridines, Benzo-[4',5']-imidazo-[1',2':1,2]-pyrido-[4,3-b]indoles and fluorinated arenes

Domino amination/conjugate addition reactions have been used to synthesize a new class of 4-quinolones. An efficient route for the synthesis of benzo[b]pyrazolo[5,1-f][1,6]naphthyridines via silver triflate-catalyzed one-pot tandem reactions has also been developed which proceeds with good functional group tolerance under mild conditions with high efficiency and excellent selectivity. A high yielding route for the synthesis of fluorinated arenes, which are difficult to obtain, has been developed by direct acyl-alkylation of benzyne.Domino Aminierungs- / Michael-Typ-Reaktionen wurden verwendet, um eine neue Klasse von 4-Chinolonen zu synthetisieren. Weiterhin wurde ein effizienter Weg zur Synthese von Benzo[b]pyrazolo[5,1-f][1,6]Naphthyridine über Silbertriflat-katalysierte Eintopf-Tandem-Reaktionen entwickelt, die mit guter Toleranz gegenüber funktionellen Gruppen, unter milden Bedingungen, mit hoher Effizienz und ausgezeichneter Selektivität verlaufen. Fluorierte Aromaten, die anderweitig schwer zu erhalten sind, wurden erstmals durch direkte Acyl-Alkylierung von Benz-in hergestellt

Potassium Channel KcsA and Its Lipid Environment

There is a general lack of atomic resolution data of mobile regions of membrane proteins embedded in lipid bilayers. As an inherently complex system, few techniques can capture information about the mobile portions of an otherwise immobilized protein. The nature of crystallography and solid-state NMR relies on structural rigidity. Solution-state NMR relies on overall mobility of a protein for resolution. In the middle regime, there are few solutions to study these systems. The inward-rectifying, pH-gated potassium channel KcsA from Streptomyces lividans makes an excellent model for the development of methods to study mobile regions of membrane proteins. Of its 160 residues, more than a third are in extracellular do- mains and are not typically captured by solid-state NMR or crystallographic techniques. These pages present evidence that KcsA’s C-terminus is highly mobile and becomes increasingly dynamic when the protein is at low pH and high K+ concen- tration, where the channel is known to be active. By applying proton-detected, high-resolution magic angle spinning NMR (HR-MAS) to fractionally deuterated KcsA, previously unattainable correlations are collected and new resonance assignments are made, demonstrating the utility of the technique. The lipid environment is well known to regulate the function of KcsA in particular and membrane proteins in general. It is generally assumed that reconstituting KcsA into a synthetic phospholipid membranes provides the protein a well-defined environment. Data is presented here which shows that KcsA co-purifies with phosphoglycerol lipids from the E. coli membrane and that these molecules are 13C enriched in the course of isotopically labeling KcsA. Further, significant hydrolysis of both co- purifying and synthetic lipids occurs under ordinary experimental conditions. These findings demand that routine analysis of samples must include verification of the chemical integrity of lipids. Finally, the feasibility of applying dynamic nuclear polarization-enhanced NMR (DNP) to KcsA is investigated as a means of elucidating information about its termini. Although KcsA is known to enhance poorly by DNP, data presented here show that this is not an intrinsic property of the protein but rather an effect of the matrix in which KcsA is investigated. The use of a 15N-enriched free amino acid dissolved into buffers used for DNP is shown to be a powerful diagnostic internal standard

Biophysical characterisation of domain 1 of rat CD2

CD2, a glycoprotein found on the T-lymphocyte, plays an important role in mediating the adhesion of T-lymphocytes to its accessory and target cells. The ligand-binding surface of CD2, which is located on the N-terminal domain of CD2 (CD2d1), has an unusually high proportion of charged residues. The ionic interactions of these charged residues are though to play a significant role in defining the ligand-specificity and binding affinity of CD2 with its ligands CD48 and CD58. The determination of the electrostatic properties of these proteins can therefore contribute to our understanding of the structure-activity relationships for these adhesion complexes. In this thesis, the biophysical characterisation of the electrostatic properties of CD2d1 is described. The principal method used for the investigation is nuclear magnetic resonance (NMR) which permit the accurate determination of the ionisation constants of all the individual acidic residues. The characterisation of the binding interaction involved site-directed mutagenesis of these residues on the binding surface. In addition, the dynamic properties of CD2d1 are also investigated by NMR relaxation experiments. The significance of the finding are discussed The pH titration of CD2d1 revealed a glutamate (Glu41) on the binding surface that has an anomalously high pka. This anomalous pka has an extensive effect on the chemical shift that suggests protein self-association mediated by this residue. This self-association was confirmed by relaxation analysis, and the CD2 was shown to dimerise with a very low affinity, but this dimerisation is nevertheless highly specific and has a pronounced effect on the relaxation parameters. The results indicated that CD2 dimerisation is maximal when Glu41 is protonated and Glu29 is deprotonated. The implication of the findings to the analysis of dynamics by NMR in discussed, and the significance of the observations to recent structural and functional analyses of rat CD2 interaction with CD48 is also examined

Chemical probes of surface layer biogenesis in Clostridium difficile

The bacterium Clostridium difficile is responsible for recent epidemics of gastroenteritis and currently causes over twice as many deaths per year as the other major hospital ‘superbug’, MRSA. Since the bacterium is resistant to conventional antibiotics there is an urgent need to develop novel therapies. C. difficile secretes a family of proteins that are held in place on the cell wall by non-covalent forces, producing a proteinaceous coat (the surface layer or S-layer) that surrounds the entire cell. These S-layer proteins (SLPs) are immunogenic in humans and play a role in binding to host cells. Synthesis of the C. difficile S-layer involves site-specific proteolytic cleavage of the SlpA precursor by an as yet unidentified C. difficile protease. Identification of the protease that processes SlpA has proven challenging, due in part to a lack of established genetic tools in C. difficle. Here the development of novel chemical probes that can disrupt S-layer formation by inhibiting the protease are described, and found to be powerful chemical proteomic tools for both protease identification and exploring the process of S-layer formation. Screening and inhibition experiments were first performed to identify novel synthetic irreversible protease inhibitors combining an electrophilic warhead with a specific sequence element matching the SlpA cleavage. These compound series were shown to possess structure-dependent activity, and inhibited cultures were also more sensitive to lysozyme-induced cell lysis, suggesting that correct processing and assembly of the S-layer is important for cell envelope integrity. Optimised inhibitors were further developed into ‘activity-based probes’ (ABPs) carrying an affinity tag, and were successfully used to isolate and identify de novo the key protease involved in cleavage of SlpA, Cwp84, using a combination of different labelling and proteomics approaches. These probes also permitted identification of Cwp84 activity across a wide range of clinical strains. In later work, the scope of the warhead element was explored in more detail, and the potential antibacterial effects of the inhibitors were investigated in both wild type and genetically engineered strains. Finally, the contributions of this work in terms of both chemical technology and C. difficile biology are critically assessed

A Comprehensive Model and Modulation of Cellular Signaling Involved in Early Mammary Development and Aggressive Cancer Using a Novel Recombinant Protein of the G3 Domain of Laminin-5

The mammary gland is a unique and specialized epidermal organ; mammary organogenesis begins in the embryo but is not fully complete until puberty. As such, formation of the mammary gland depends on temporally and spatially regulated developmental steps that require coordination of multiple biological and cell signaling processes; many of which have parallels with cancer development. Research describing the events that occur between birth and puberty is lacking and little is known about human breast development of youth. Since mammary gland development requires a coordinated balance between cell growth, proliferation, and apoptosis, it is critical to understand which signaling pathways are utilized to relay developmental signals, and how these pathways and their targets interact and cooperate with age. Additionally, interactions between integrin molecules and their laminin ligands, especially Laminin-5 (Ln-5; also known as Laminin-332), regulate multiple facets of both embryonic development and tumor growth, invasion, and metastasis. α6β4 integrin serves as a marker to detect distant metastases in the early stages of specific malignancies and β4 integrin overexpression has been found in basal-like breast cancers, correlating with aggressiveness to institute a prognostic β4 signature that increases with tumor grade. The mechanism α6β4 integrin utilizes to modulate oncogenic signaling through association with Ln-5 molecules in the ECM is the basis for the recombinant protein (rG3, the third of five G domains of Ln-5) produced for the work reported in this dissertation. Here, it is shown there are specific transcriptional differences and a unique interaction of a gene set over time that contributes to postnatal mammary gland development, and this model clearly shares similarities and signaling pathways with oncogenic development. Especially important are pathways of the adaptive and innate immunities, ECM remodeling and integrin interactions, and extrinsic and intrinsic TP53-mediated apoptosis, greater understanding of which could lead to early detection of potential tumorigenic growth and identification of potential treatment avenues. Presented is a comprehensive model of early mammary development along with several panels of biomarkers that possess a role in normal mammary development, are involved in aggressive cancers, and are affected by apoptosis induced by rG3 treatment. rG3 has proven to be a valuable tool to study apoptotic pathways and the crosstalk among those pathways

Mass Spectrometry-Based Proteomics for Studying Microbial Physiology from Isolates to Communities

With the advent of whole genome sequencing, a new era of biology was ushered in allowing for “systems-biology” approaches to characterizing microbial systems. The field of systems biology aims to catalogue and understand all of the biological components, their functions, and all of their interactions in a living system as well as communities of living systems. Systems biology can be considered an attempt to measure all of the components of a living system and then produce a data-driven model of the system. This model can then be used to generate hypotheses about how the system will respond to perturbations, which can be tested experimentally. The first step in the process is the determination of a microbial genome. This process has, to a large extent, been fully developed, with hundreds of microbial genome sequences completed and hundreds more being characterized at a breathtaking pace. The developments of technologies to use this information and to further probe the functional components of microbes at a global level are currently being developed. The field of gene expression analysis at the transcript level is one example; it is now possible to simultaneously measure and compare the expression of thousands of mRNA products in a single experiment. The natural extension of these experiments is to simultaneously measure and compare the expression of all the proteins present in a microbial system. This is the field of proteomics. With the development of electrospray ionization, rapid tandem mass spectrometry and database-searching algorithms, mass spectrometry (MS) has become the leader in the attempts to decipher proteomes. This research effort is very young and many challenges still exist. The goal of the work described here was to build a state-of-the-art robust MS-based proteomics platform for the characterization of microbial proteomes from isolates to communities. The research presented here describes the successes and challenges of this objective. Proteome analyses of the metal-reducing bacteria Shewanella oneidensis and the metabolically versatile bacteria Rhodopseudomonas palustris are given as examples of the power of this technology to elucidate proteins important to different metabolic states at a global level. The analysis of microbial proteomes from isolates is only the first step of the challenge. In nature, microbial species do not act alone but are always found in mixtures with other species where their intricate interactions are critical for survival. These studies conclude with some of the first efforts to develop methodologies to measure proteomes of simple controlled mixtures of microbial species and then present the first attempt at measuring the proteome of a natural microbial community, a biofilm from an acid mine drainage system. This microbial system illustrates life at the extreme of nature where life not only exists but flourishes in very acidic conditions with high metal concentrations and high temperatures. The technologies developed through these studies were applied to the first deep characterization of a microbial community proteome, the deciphering of the expressed proteome of the acid mine drainage biofilm. The research presented here has led to development of a state-of-the-art robust proteome pipeline, which can now be applied to the proteome analysis of any microbial isolate for a sequenced species. The first steps have also been made toward developing methodologies to characterize microbial proteomes in their natural environments. These developments are key to integrating proteome technologies with genome and transcriptome technologies for global characterizations of microbial species at the systems level. This will lead to understanding of microbial physiology from a global view where instead of analyzing one gene or protein at a time, hundreds of genes/proteins will be interrogated in microbial species as the adapt and survive in the environment