Microtubules are critically important cytoskeletal elements. Together with microtubule associated proteins (MAPs), they form the latticework on which eukaryotic life exists. Simply put, microtubules are polymers of tubulin heterodimers, which are composed of the globular proteins alpha and beta tubulin. In vivo, these monomers associate with one another to form heterodimers, which then polymerize to form microtubules. In mammals, microtubule polymerization is a temperature-dependent process with an optimum of 37°C (Detrich et al., 2000). If temperatures exceed this optimal temperature by even a few degrees, the microtubule will begin to dissemble due to denaturation of the tubulin subunit and permanent loss of both shape and function will occur. This thermal barrier seems to be consistent in most eukaryotic organisms. Two exceptions are the thermophilic red algae, Cyanidium caldarium and Cyanidioschyzon merolae. These thermophilic acidophiles have been discovered in volcanic vents around the globe from Yellow Stone Park to Italy and grow at optimal temperatures of around 55°C. These organisms have been primarily studied in the context of evolutionary biology because of their primitive characteristics. Very little is known about the molecular biology of these organisms, and certainly nothing is known about how the biochemistry of these organisms brings about the ability to survive the harsh conditions of their environment. Currently, my hypothesis concerning the thermostable tubulin expressed within these organisms is that there may be key amino acid differences in the tubulin's primary structure that confer enhanced thermostability. I am testing this hypothesis by sequencing the alpha and beta tubulin genes of Cyanidium caldarium and Cyanidioschyzon merolae, generating homology models of the tubulin dimers, and comparing these models to a known mesophilic tubulin heterodimer structure in order to identify potential structural differences. / Master of Science

The results from this work are reported into two sections listed below: <br><br> Synthesis: <br><br> Following structural classes of compounds have been designed, synthesized and studied as inhibitors of pjDHFR, RTKs and tubulin: <br> 1. 2,4-Diamino-6-(substituted-arylmethyl)pyrido[2,3-d]pyrimidines <br> 2. 4-((3-Bromophenyl)linked)-6-(substituted-benzyl)-7H-pyrrolo[2,3-d]pyrimidin-2-amines<br> 3. 6-Methyl-5-((substitutedphenyl)thio)-7H-pyrrolo[2,3-d]pyrimidin-2-amines <br> A total of 35 new compounds (excluding intermediates) were synthesized, characterized and submitted for biological evaluation. Results from these studies will be presented in due course. Bulk synthesis of the potent lead compound 170 was carried out to facilitate in vivo evaluation. <br><br> Docking Studies <br><br> Docking studies were performed using LeadIT, MOE, Sybyl or Flexx for target compounds listed above and for other compounds reported by Gangjee et al. against the following targets: <br> 1. Dihydrofolate reductase: human, P. carinii, P. jirovecii (pjDHFR) and T. gondii (tgDHFR)<br> 2. Thymidylate synthase: human (hTS) and T. gondii (tgTS)<br> 3. Receptor tyrosine kinases: VEGFR2, EGFR and PDGFR-β<br> 4. Colchicine binding site of tublulin.<br> Novel homology models were generated and validated for pjDHFR, tgDHFR, tgTS, PDGFR-β and the F36C L65P pjDHFR double mutant. The tgTS homology model generated in this study and employed to design novel inhibitors shows remarkable similarity with the recently published X-ray crystal structures. Docking studies were performed to provide a molecular basis for the observed activity of target compounds against DHFR, RTKs or tubulin. Results from these studies support structure-based and ligand-based medicinal chemistry efforts in order to improve potency and/or selectivity of analogs of the docked compounds against these targets.<br> Novel topomer CoMFA models were developed for tgTS and hTS using a set of 85 bicyclic inhibitors and for RTKs using a set of 60 inhibitors reported by Gangjee et al. The resultant models could be used to explain the potency and/or selectivity differences for selected molecules for tgTS over hTS. Topomer CoMFA maps show differences in steric and/or electronic requirements among the three RTKs, and could be used, in conjuction with other medicinal chemistry approaches, to modulate the selectivity and/or potency of inhibitors with multiple RTK inhibitory potential. Drug design efforts that involve virtual library screening using these topomer CoMFA models in conjunction with traditional medicinal chemistry techniques and docking are currently underway. / Mylan School of Pharmacy and the Graduate School of Pharmaceutical Sciences; / Medicinal Chemistry / PhD; / Dissertation;

Organic cation transporters (OCTs) play a pivotal role in the absorption, tissue distribution, and excretion of a diverse array of substances, and currently the nature of the biochemical interactions between substrate and OCTs are unknown. Therefore, identifying which amino acid residues are critical for OCT-substrate interactions is of central importance to understanding and predicting interactions between drugs and OCTs. A three-dimensional (3-D) homology model of human OCT3 was generated using the crystal structure of a high affinity phosphate transporter from Piriformospora indica (PiPT) as template, and putative binding pocket for the prototypical hOCT3 ligand 1-methyl-4-phenylpyridinium (MPP+) was identified through docking studies. Five residues, Phe36, Val40, Trp358, Glu451 and Asp478, were identified as potentially mediating hOCT3-MPP+ interactions, and confirmed through in vitro studies. Additionally, 3-D homology modeling of the functional hOCT3 mutant Val40Leu, and all non-functional hOCT3 mutants, indicated changes in binding pocket architecture consistent with weakening of ligand-transporter interactions. Docking of structurally divergent hOCT3 substrates indicated binding interactions in the same general region as that identified for MPP+, albeit with mostly unique residues. Interspecies differences were explored by generating 3-D homology models for rat and murine Oct3. Results from docking studies using compounds exhibiting vastly different binding affinities (Km or IC50) towards the OCT3/Oct3 orthologs were consistent with varying strength in ligand-transporter binding pocket interactions. Finally, a series of novel compounds exhibiting anti-depressant-like activity was screened for OCT interaction in vitro, and demonstrated significant inhibitory effects on OCTs for many of the compounds.

This research is focused on the study of the effect of mutating proline 145 to threonine on the substrate and regiospecificity of flavonol specific 3-O-glucosyltransferase (Cp3GT). While the mutant P145T enzyme did not glucosylate anthocyanidins, it did glucosylate flavanones and flavones in addition to retaining activity with flavonols. HPLC was used for product identification and showed mutant P145T glucosylated naringenin at the 7-OH position forming naringenin-7-O-glucoside and flavonols at the 3-OH position. Homology modeling and docking was done to predict the acceptor substrate recognition pattern and models were validated by experimental results. In other related work, a thrombin cleavage site was inserted into wild type Cp3GT and recombinant P145T enzyme between the enzyme and the C-myc tags in order to be able to cleave off tags. This provides the tool needed for future efforts to crystallize these proteins for structural determination.

Biological nitrogen fixation is accomplished in the bacterium Azotobacter vinelandii by means of three metalloenzymes: The molybdenum, vanadium, and iron-only nitrogenase. The knowledge regarding biological nitrogen fixation has come from studies on the Mo-dependent reaction. However, the V- and Fe-only-dependent reduction of nitrogen remains largely unknown. By using homology modeling techniques, the protein folds that contain the metal cluster active sites for the V- and Fe-only nitrogenases were constructed. The models uncovered similarities and differences existing among the nitrogenases regarding the identity of the amino acid residues lining pivotal structural features for the correct functioning of the proteins. These differences, could account for the differences in catalytic properties depicted by these enzymes. The quaternary structure of the dinitrogenases also differs. Such component in the Mo-nitrogenase is an α2β2 tetramer while for the V- an Fe-only nitrogenase is an α2β2δ2 hexamer. The latter enzymes are unable to reduce N2 in the absence of a functional δ subunit, yet they reduce H+ and the non-physiological substrate C2H2. Therefore, the δ subunit is essential for V- and Fe-only dependent nitrogen fixation by a mechanism that still remains unknown. In attempt to understand why the δ subunit is essential for V-dependent N2 reduction from a structural stand point, this work presents the strategy followed to clone the vnfG gene and purify its expression product, the δ subunit. The purified protein was subjected to crystallization trials and used to stabilize a histidine-tagged VFe protein that would otherwise purify with low Fe2+ content and poor H+ and C2H2 reduction activities. The VFe preparation was used to conduct substrate reduction assays to assess: i) The electron allocation patterns to each of the reduction products of the substrates C2H2, N2, N2H4, and N3−; and ii) Inhibition patterns among substrate and inhibitor of the nitrogenase reaction. This work also reports on the effect N2H4 and N3− has on the electron flux to the products of the C2H2 reduction. The work presented herein provides information with which to compare and contrast biological nitrogen fixation as catalyzed by the Mo- and V-nitrogenases from Azotobacter vinelandii.

La connaissance de la structure tridimensionnelle (3D) des protéines est une information capitale. Néanmoins, le nombre de protéines dont la structure 3D a été déterminée expérimentalement est cent fois plus faible que le nombre de protéines connues aujourd'hui. Cet écart ne pourra pas être comblé, car les techniques expérimentales de détermination de structure (diffraction de rayons X et résonance magnétique nucléaire) sont coûteuses et lentes (un an de travail en moyenne pour une seule protéine). Un moyen d'obtenir plus rapidement la structure 3D de protéines est de la prédire par des moyens bioinformatiques. La technique de prédiction la plus précise actuellement est la modélisation par homologie. Celle-ci est basée sur la similitude de structure entre deux protéines de séquences similaires. L'étape critique de cette méthode est l'étape d'alignement entre la séquence à modéliser et une séquence similaire de structure connue. Notre travail a consisté tout d'abord en la conception d'une nouvelle méthode d'alignement pairé très fiable. Cette méthode a ensuite été incluse dans un système automatique de modélisation par homologie: la bonne qualité des structures prédites par le système trouve en partie son origine dans le programme d'alignement utilisé. Enfin, nous avons appliqué notre système de modélisation automatique à la modélisation de toutes les protéines déduites du génome d'une bactérie pathogène étudiée dans notre unité de recherche: Brucella melitensis. Cela nous a conduit à créer une banque de données structurales et fonctionnelles consacrée au génome de cette bactérie. Cette banque de données est devenue un outil de travail indispensable pour plusieurs équipes de recherche européennes qui étudient Brucella melitensis.

Submitted by Haroudo Xavier Filho (haroudo.xavierfo@ufpe.br) on 2016-04-22T16:55:34Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertacao_SheylaSilvaLima_2015.pdf: 4958893 bytes, checksum: 21511e1c9e1a86ea210befeb33c91543 (MD5) / Made available in DSpace on 2016-04-22T16:55:34Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertacao_SheylaSilvaLima_2015.pdf: 4958893 bytes, checksum: 21511e1c9e1a86ea210befeb33c91543 (MD5) Previous issue date: 2015-02-24 / FACEPE / Ciclotídeos são uma classe de peptídeos antimicrobianos (AMPs - do inglês Antimicrobial peptide) cíclicos de plantas, compostos de, aproximadamente, 30 resíduos de aminoácidos, sendo seis cisteínas conservadas e conectadas por três pontes de dissulfeto. Sua expressão é constitutiva, tendo sua principal função na defesa vegetal contra patógenos, que podem causar perdas significativas em culturas importantes para a agricultura, como no caso da família Poaceae que apresenta destacada importância econômica no Brasil e no mundo. Nesse estudo foi conduzida uma busca por genes relacionados a ciclotídeos vegetais, disponíveis em bancos de dados de acesso restrito e público, com vistas ao isolamento e caracterização in silico desses peptídeos. Através da busca nos genomas de Hevea brasiliensis, Manihot esculenta, Ricinus communis, Sorghum bicolor e Zea mays; bem como no transcriptoma de Vigna unguiculata foi verificado que apenas o genoma de Zea mays apresentou dois possíveis genes codificadores de ciclotídeos. Assim, primers foram desenhados para o isolamento destes genes em milho. Além da espécie Z. mays, as espécies Triticum aestivum (trigo) e Secale cereale (centeio), foram utilizadas para a tentativa de isolamento a partir dos pares de primers desenhados. Foram obtidos 19 fragmentos (amplicons), sendo quatro deles (zm315, zm316, zm317, sc359) com o domínio ciclotídeo, os três primeiros de milho e o último de centeio. Essas quatro sequências foram, então, submetidas a uma caracterização in silico, para predição da estrutura secundaria, terciaria e função predita. Verificou-se que esses peptídeos apresentam as seis cisteínas conservadas, três pontes dissulfeto e o padrão de aminoácidos entre as cisteínas, similar aos encontrados em ciclotídeos. Ainda foi possível a predição de algumas propriedades físico-químicas e modelagem por homologia para as quatro proteínas, o que mostrou a qualidade e confiabilidade dos modelos. Sugere-se que dois dos ciclotídeos isolados (zm315, zm316) pertençam a uma nova classe de peptídeos lineares, mas com características de ciclotídeos. / Cyclotides are a class of cyclic antimicrobial peptides (AMPs) present on plants, composed by approximately 30 amino acid residues, including six conserved cysteines connected by three disulphide bridges. Its expression is constitutive, with main function on plant defense against pathogens, that may cause significant losses in important cultivars, as in the case of Poaceae, a family that presents economic importance for the agriculture in Brazil and worldwide. This study performed a search for genes related to plant cyclotides, available in restricted and public access databases, aimed at their in silico isolation and characterization. Searching for these peptides in Hevea brasiliensis, Manihot esculenta, Ricinus communis, Sorghum bicolor, Vigna unguiculata and Zea mays genomes, we obtained two possible genes encoding Cyclotides in Z. mays. Thus, primers were designed for the isolation of these genes in maize as well in wheat (Triticum aestivum) and rye (Secale cereale) species. We obtained 19 amplicons and four of them (zm315, zm316, zm317, sc359) presented cyclotide domain. These four sequences were then subjected to in silico characterization, for predicting their secondary and tertiary structures, as well their function. It was found that these peptides present six conserved cysteines, three disulphide bridges and the amino acid pattern between the cysteines similar to those found in cyclotides. It was also possible to predict some physical chemical properties and also building a 3D protein by homology modeling for the four peptides, presenting high quality and reliability. Our analysis indicates that two isolated cyclotides (zm315, zm316) appear to belong to a new class of linear peptides, but with cyclotide features.

Antibiotics have transformed modern medicine in manifold ways. However, the misuse and over-consumption of antibiotics or antimicrobials have led to the rise in antimicrobial resistance (AMR). Unfortunately, robust tools or techniques for the detection of potential loci responsible for AMR before it happens are lacking. The emergence of resistance even when a strain lacks known AMR genes has puzzled researchers for a long time. Clearly, there is a critical need for the development of novel approaches for uncovering yet unknown resistance elements in pathogens and advancing our understanding of emerging resistance mechanisms. To aid in the development of new tools for deciphering AMR, here we propose a machine learning (ML) based framework that provides ML models trained and tested on (1) genotypic AMR and phenotypic antimicrobial susceptibility testing (AST) data, which can predict novel resistance factors in bacterial strains that lack already implicated resistance genes; and (2) complete gene set and AST phenotypic data, which can predict the most important genetic loci involved in resistance to specific antibiotics in bacterial strains. The validation of resistance loci prioritized by our ML pipeline was performed using homology modeling and in silico molecular docking.

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