A existência de uma maior variedade de aminoácidos codificados pelo código genético tem estimado estudos sobre os mecanismos de síntese, reconhecimento e incorporação desses resíduos nas cadeias polipeptídicas nascentes. Um exemplo é a via de incorporação de selenocisteína evento cotraducional dirigido pelo códon UGA. Em bactérias, essa via conta com uma complexa maquinaria molecular composta por: Selenocisteína Sintase (SelA), Fator de Elongação Específico de Reconhecimento (SelB), Selenofosfato Sintetase (SelD), tRNA específico (SelC ou tRNAsec), sequência específica no mRNA (Sequência de Inserção de Selenocisteínas - SECIS) e Aminoacil tRNA Sintetase (aaRS). Pelo fato do selênio ter uma toxicidade elevada em ambientes celulares, é fundamental a compreensão do mecanismo catalítico e razão estequiométrica na formação dos complexos da via na etapa de incorporação junto ao tRNAsec, bem como sua caracterização estrutural foram os objetivos deste trabalho. A proteína SelA foi expressa e purificada para utilização em análises envolvendo microscopia de força atômica, microscopia eletrônica de transmissão com contraste negativo e em gelo vítreo foram realizadas nos complexos SelA e SelA-tRNAsec, visando obter um modelo estrutural e a razão estequiométrica dos complexos. A fim de compreender o mecanismo de passagem do selênio, ensaios de anisotropia de fluorescência e de microcalorimetria, corroborados pelas análises de troca de hidrogênio-deutério acoplado a espectrometria de massa e espectroscopia de infravermelho, elucidaram a formação e estequiometria do complexo ternário SelAtRNA sec-SelD. Tentativas de cristalização e análises cristalográficas também foram realizadas, no entanto, sem sucesso. Com os resultados obtidos foi possível propor que o reconhecimento de SelD e, consequentemente, a entrega do selenofosfato, seja uma etapa crucial da via de incorporação de selenocisteínas. / The existence of a greate variety of amino acids encoded by the genetic code has stimulated the study of the mechanisms of synthesis, recognition and incorporation of these residues in the nascent polypeptide chains. An example of genetic code expansion is the selenocysteine incorporation pathway an event cotraducional by the UGA codon. In bacteria, this pathway has a complex molecular machinery comprised: Selenocysteine Synthase (SelA), Specific Elongation Factor (SelB), Selenophosphate Synthetase (SelD), tRNA-specific (SelC or tRNAsec), Specific mRNA Sequence (SElenocysteine Insertion Sequence - SECIS) and Aminoacyl tRNA Synthetase (aaRS). Because selenium has high toxicity in cellular environments; it is essential for cell survival the association of this compound with proteins, in this case, selenoprotens and the associated proteins involved in the selenocysteine synthesis. Therfore the understanding of the catalytic mechanism, stoichiometric ratio, protein complex formation with the tRNAsec, and its structural characterization were the objectives of this work. The SelA protein was expressed and purified to used in analyzes involving atomic force microscopy, transmission electron microscopy with negative stain and in vitreous ice were performed in the complex SelA and SelA-tRNAsec in order to obtain a structural model of the complex and the stoichiometric ratio of its components. To study the selenium association with protein of the synthesis pathway, fluorescence anisotropy assays and isothermal titration calorimetry corroborated by the analysis hydrogen-deuterium exchange coupled to mass spectrometry and infrared spectroscopy were employed.Crystallization attempts were made and preliminary crystallographic analyzes were also performed, however, so far unsuccessfuly. The results obtained were possible to develop the hypothesis about the SelD recognition and, consenquently, the selenophosphate delivery, a crucial stage of the selenocysteine incorporation pathway.

Orientador: Fabio Cesar Gozzo / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Quimica / Made available in DSpace on 2018-08-13T13:49:01Z (GMT). No. of bitstreams: 1 Iglesias_AmadeuHoshi_D.pdf: 8088319 bytes, checksum: 8f6da7c324d46a34a7ce5354e6670443 (MD5) Previous issue date: 2009 / Resumo: A Espectrometria de Massas (MS) é hoje a principal técnica de caracterização de estrutura primária de proteínas devido às vantagens intrínsecas da técnica. As técnicas de cross-linking e footprinting visam desfrutar de tais vantagens para obtenção de informações estruturais de complexos protéicos. Nesse projeto foram realizados estudos de fragmentação de peptídeos contendo como cross-linker o DSS, reagente mais utilizado para esse propósito. Os mecanismos de fragmentação foram propostos baseados na dissociação de peptídeos modelos sintetizados para gerar espécies que mimetizassem experimentos com proteínas. Esses estudos permitiram a identificação de íons marcadores, que foram posteriormente utilizados em experimentos de Varredura de Íons Precursores para auxiliar na detecção de peptídeos modificados. Para realização dos experimentos de footprinting, foi desenvolvida uma linha de luz no LNLS. Posteriormente, foi proposto um novo método de quantificação de cinética de oxidação baseado nos dados de LC-MS, levando em consideração todos os produtos de oxidação formados. Esses métodos foram utilizados no estudo de interação das proteínas Tif34 e Tif35 do fator de iniciação de tradução de Saccharomyces cerevisiae. Os resultados obtidos indicam que Tif34 apresenta dois possíveis sítios de interação para a proteína Tif35 / Abstract: Mass Spectrometry (MS) is the most important tool for analyses related to protein primary structure. Cross-Linking and footprinting aim to bring those advantages to gain insights in the spatial structure of protein complexes. In this work the fragmentation of peptides containing DSS, the most used cross-linker, was studied. Fragmentation mechanisms were proposed based on the dissociation of model peptides which were synthesized in order to generate species that would resemble species found in experiments with proteins. Diagnostic ions were identified which allowed the use of Precursor Ion Scan to detect those species. In order to perform footprinting experiments, a new beamline was developed at the LNLS. A new method for quantitation of oxidation kinetics was developed based on LC-MS analysis, which considers every single oxidation product that can be generated. Those methods were thereafter used in the study of the interaction between Tif34 and Tif35, proteins which compose a translation initiation factor of Saccharomyces cerevisiae. The results indicate that Tif34 presents two different sites for the interaction with Tif35 / Doutorado / Quimica Organica / Doutor em Ciências

Orientadores: Everson Alves Miranda, Pedro de Alcântara Pessôa Filho / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química / Made available in DSpace on 2018-08-24T01:51:47Z (GMT). No. of bitstreams: 1 Hirata_GiseleAtsukoMedeiros_D.pdf: 4140620 bytes, checksum: 01025f5b18791e6b6698c34eea1dcda4 (MD5) Previous issue date: 2013 / Resumo: O segundo coeficiente virial osmótico, B22, tem sido considerado um preditor para o processo de cristalização. Uma faixa relativamente estreita de valores negativos de B22, -1x10-4 a -8x10-4 mL.mol/g2, é ideal à formação de cristais de acordo com George e Wilson (1994). Essa faixa de valores de B22 é denominada de "janela de cristalização", sendo utilizada para classificar condições adequadas de solvente à formação de cristais. Para valores maiores que -1x10-4 mL.mol/g2, a interação proteína-proteína não é suficientemente forte para a cristalização e nenhuma fase sólida é formada, enquanto para valores menores que -8x10-4 mL.mol/g2, as interações proteína-proteína são muito intensas e precipitados amorfos são formados. Dessa forma, os valores de B22 se tornaram um critério de seleção para a cristalização de proteínas, uma vez que esse coeficiente pode ser determinado por diversos métodos. Este trabalho teve como objetivo determinar experimentalmente diagramas de fases de proteínas (lisozima, insulina suína e bovina) e identificar nesses diagramas, através de análise dos valores do B22, as condições nas quais ocorre a formação de precipitado amorfo, cristalino ou outras fases (por exemplo, fase líquida). O "salting-out" foi o método escolhido para precipitar as proteínas, pois é considerado um dos mais simples e importantes métodos para induzir a cristalização. O sal volátil carbamato de amônio foi o agente de "salting-out" escolhido. As técnicas de espalhamento de luz estático (SLS) e cromatografia de auto-interação (SIC) foram usadas para determinar os valores de B22 para as proteínas em diferentes soluções aquosas de sal a 15 e 25 °C. O fenômeno de "salting-out" foi observado nos diagramas para as três proteínas estudadas. Valores negativos de B22 e altos valores da constante de "salting-out" - entre 1,07 a 3,77 kg/mol - confirmaram que o sal volátil carbamato de amônio empregado neste estudo é um bom agente precipitante. Os valores do B22 para a insulina suína (-250x10-4 a -18x10-4 mol.ml/g2 a 25 °C e -187x10-4 a -45,2x10-4 mol.ml/g2 a 15 °C) e insulina bovina (-999x10-4 a 6,7x10-4 mol.ml/g2 a 25 °C e -533x10-4 a -16,7x10-4 mol.ml/g2 a 15 °C) indicaram a precipitação, o que também foi confirmado pelos ensaios de cristalização. Já para a lisozima, obteve-se formação de cristais independente do valor de B22 encontrado (-20,4x10-4 a -3,6x10-4 mol.ml/g2 a 25 °C e -400x10-4 a -14,4x10-4 mol.ml/g2 a 15 °C). Além disso, os modelos teóricos disponíveis na literatura utilizados para a obtenção de uma estimativa do parâmetro B22 são adequados e válidos para as condições em que a medida experimental não é possível, podendo ser aplicados para o sistema proteína/sal volátil. Dessa forma, este trabalho mostrou que não existe uma "janela de cristalização universal" válida para todos os sistemas e o uso do sal volátil carbamato de amônio como agente de cristalização é uma alternativa ao uso de sais convencionais. / Abstract: The osmotic second virial coefficient, B22, has been used as a predictor of crystallization. A relatively narrow range of negative B22 values, -1x10-4 to -8x10-4 mL.mol/g2, is the ideal range for crystal formation according to George and Wilson (1994). This range, referred to as the "crystallization slot", has been used to classify suitable conditions under which proteins will assemble into crystals. For B22 values greater than -1x10-4 mL.mol/g2, the protein-protein interaction is very weak and no solid phase is formed, while for values less than -8x10-4 mL.mol/g2, the protein-protein interactions are very intense and amorphous precipitates are formed. Thus, the B22 value has become a selection criterion for protein crystallization, since this coefficient can be determined by various methods. This study aimed to determine the experimental phase diagrams for proteins (lysozyme and bovine and porcine insulin) and to identify those diagram conditions under which amorphous precipitate, crystals or other phases (for example, liquid phase) are formed, based on the values of B22. The salting-out method to precipitate proteins was chosen because it is considered one of the simplest and most important methods to induce crystallization. The volatile salt ammonium carbamate was chosen as the salting-out agent. Traditional static light scattering (SLS) and the novel self-interaction chromatography (SIC) technique were used to determine B22 values for the proteins in different aqueous salt solutions at 15 and 25 °C. The salting-out phenomenon was observed in the phase diagrams for the three proteins studied. Negative B22 values and high values of the salting-out constant - between 1.07 to 3.77 kg/mole (Cohn, 1925) - confirmed that ammonium carbamate was a good precipitant agent. The B22 values for porcine (-250x10-4 to -18x10-4 mol.ml/g2 at 25 °C and -187x10-4 to -45.2 x10-4 mol.ml/g2 at 15 °C) and bovine (-999x10-4 to 6.7x10-4 mol.ml/g2 at 25 °C and -533x10-4 to -16.7x10-4 mol.ml/g2 at 15 °C) insulin indicated precipitation that was confirmed experimentally. However, lysozyme was obtained as crystals, regardless of the B22 values found (-20.4x10-4 to -3.6 x10-4 mol.ml/g2 at 25 °C and -14.4x10-4 to -400x10-4 mol.ml/g at 15 °C). In addition, thermodynamic models available in the literature and suitable for the conditions under which experimental measurements were done provided a good fit to the data. Thus, this work showed that there is no universal "crystallization slot" applicable to all systems and that for crystallization agent, volatile salt ammonium carbamate can serve as an alternative to conventional salts. / Doutorado / Desenvolvimento de Processos Biotecnologicos / Doutora em Engenharia Quimica

HSP70 is one of the most important families of molecular chaperone that regulate the folding and transport of client proteins in an ATP dependent manner. The ATPase activity of HSP70 is stimulated through an interaction with its family of HSP40 co-chaperones. There is evidence to suggest that specific partnerships occur between the different HSP40 and HSP70 isoforms. While some of the residues involved in the interaction are known, many of the residues governing the specificity of HSP40-HSP70 partnerships are not precisely defined. It is not currently possible to predict which HSP40 and HSP70 isoforms will interact. We attempted to use bioinformatics to identify residues involved in the specificity of the interaction between the J domain from HSP40 and the ATPase domain from the HSP70 isoforms from humans. A total of 49 HSP40 and 13 HSP70 sequences from humans were retrieved and used for subsequent analyses. The HSP40 J domains and HSP70 ATPase domains were extracted using python scripts and classified according to the subcellular localization of the proteins using localization prediction programs. Motif analysis was carried out using the full length HSP40 proteins and Multiple Sequence Alignment (MSA) was performed to identify conserved residues that may contribute to the J domain – ATPase domain interactions. Phylogenetic inference of the proteins was also performed in order to study their evolutionary relationship. Homology models of the J domains and ATPase domains were generated. The corresponding models were docked using HADDOCK server in order to analyze possible putative interactions between the partner proteins using the Protein Interactions Calculator (PIC). The level of residue conservation was found to be higher in Type I and II HSP40 than in Type III J proteins. While highly conserved residues on helixes II and III could play critical roles in J domain interactions with corresponding HSP70s, conserved residues on helixes I and IV seemed to be significant in keeping the J domain in its right orientation for functional interactions with HSP70s. Our results also showed that helixes II and III formed the interaction interface for binding to HSP70 ATPase domain as well as the linker residues. Finally, data based docking procedures, such as applied in this study, could be an effective method to investigate protein-protein interactions complex of biomolecules.

Abstract DNA replication is a process in which a cell duplicates its genome before cell division, and must proceed accurately and in organized manner to guarantee maintenance of the integrity of the genetic information. DNA polymerases are enzymes that catalyse the synthesis of the new DNA strand by utilizing the parental strand as a template. In addition to chromosomal replication, DNA synthesis and therefore DNA polymerases are also needed in other processes like DNA repair and DNA recombination. The DNA polymerase is an essential DNA polymerase in eukaryotes and is required for chromosomal DNA replication. It has also been implicated in DNA repair, recombination, and in transcriptional and cell cycle control. The regulation of the human enzyme was explored by analysing its expression, phosphorylation and protein-protein interactions. Expression of both the A and B subunits of the human DNA polymerase ε was strongly growth-regulated. After serum-stimulation of quiescent fibroblasts, the steady-state mRNA levels were up-regulated at least 5-fold. In actively cycling cells, however, the steady-state mRNA and protein levels fluctuated less than 2-fold, being highest in G1/S phase. The promoter of the B subunit gene was analysed in detail. The 75 bp core promoter was essentially dependent on the Sp1 transcription factor. Furthermore, mitogenic control of the promoter required an intact E2F binding element, and binding of E2F2, E2F4 and p107 was demonstrated in vitro. A down-regulation element, located immediately downstream from the core promoter, bound E2F1, NF-1 and pRb transcription factors. A model of the promoter function is presented. Topoisomerase IIβ binding protein 1 (TopBP1) was found to be associated with human DNA polymerase ε. TopBP1 contains eight BRCT domains and is homologous to Saccharomyces cerevisiae Dpb11, Schizosaccharomyces pombe Cut5, Drosophila melanogaster Mus101 and the human Breast Cancer susceptibility protein 1 (BRCA1). TopBP1 is a phosphoprotein, whose expression is induced at the G1/S border and is required for chromosomal DNA replication. It co-localizes in S phase with BRCA1 into discrete foci, which do not represent sites of ongoing DNA replication. However, if DNA is damaged or replication is blocked in S phase cells, TopBP1 and BRCA1 re-localize into proliferating cell nuclear antigen (PCNA) containing foci that represent stalled replication forks. Finally, phosphorylation of DNA polymerase ε was described and at least three immunologically distinct and differentially phosphorylated forms were shown to exist. Phosphorylation is on serine and threonine residues and shows a cell cycle dependent fluctuation, but is not affected by DNA damage or by inhibition of DNA replication. BRCA1 co-immunoprecipitates with a hypophosphorylated form of DNA polymerase ε. In contrast, TopBP1 was shown to be associated with a hyperphosphorylated form.

Philosophiae Doctor - PhD / Supervised machine learning approaches have been applied successfully to the prediction of protein-protein interactions (PPIs) within a single organism, i.e., intra-species predictions. However, because of the absence of large amounts of experimentally validated PPIs data for training and testing, fewer studies have successfully applied these techniques to host-pathogen PPI, i.e., inter-species comparisons. Among the host-pathogen studies, most of them have focused on human-virus interactions and specifically human-HIV PPI data. Additional improvements to machine learning techniques and feature sets are important to improve the classification accuracy for host-pathogen protein-protein interactions prediction. The primary aim of this bioinformatics thesis was to develop a binary classifier with an appropriate feature set for host-pathogen protein-protein interaction prediction using published human-Hepatitis C virus PPI, and to test the model on available host-pathogen data for human-Bacillus anthracis PPI. Twelve different feature sets were compared to find the optimal set. The feature selection process reveals that our novel quadruple feature (a subsequence of four consecutive amino acid) combined with sequence similarity and human interactome network properties (such as degree, cluster coefficient, and betweenness centrality) were the best set. The optimal feature set outperformed those in the relevant published material, giving 95.9% sensitivity, 91.6% specificity and 89.0% accuracy. Using our optimal features set, we developed a neural network model to predict PPI between human-Mycobacterium tuberculosis. The strategy is to develop a model trained with intra-species PPI data and extend it to inter-species prediction. However, the lack of experimentally validated PPI data between human-Mycobacterium tuberculosis (Mtuberculosis), leads us to first assess the feasibility of using validated intra-species PPI data to build a model for inter-species PPI. In this model we used human intra-species PPI combined with Bacillus anthracis intra-species data to develop a binary classification model and extend the model for human-Bacillus anthracis inter-species prediction. Thus, we test our hypotheses on known human-Bacillus anthracis PPI data and the result shows good performance with 89.0% as average accuracy. The same approach was extended to the prediction of PPI between human-Mycobacterium tuberculosis. The predicted human-M-tuberculosis PPI data were further validated using functional enrichment of experimentally verified secretory proteins in M-tuberculosis, cellular compartment analysis and pathway enrichment analysis. Results show that five of the M-tuberculosis secretory proteins within an infected host macrophage that correspond to the mycobacterial virulent strain H37Rv were extracted from the human-M- tuberculosis PPI dataset predicted by our model. Finally, a web server was created to predict PPIs between human and Mycobacterium tuberculosis which is available online at URL:http://hppredict.sanbi.ac.za. In summary, the concepts, techniques and technologies developed as part of this thesis have the potential to contribute not only to the understanding PPI analysis between human and Mycobacterium tuberculosis, but can be extended to other pathogens. Further materials related to this study are available at ftp://ftp.sanbi.ac.za/machine learning. / National Research Foundation (NRF) and SANBI

Philosophiae Doctor - PhD / To ameliorate Hepatitis C Virus (HCV) therapeutic and diagnostic challenges requires robust intervention strategies, including approaches that leverage the plethora of rich data published in biomedical literature to gain greater understanding of HCV pathobiological mechanisms. The multitudes of metadata originating from HCV clinical trials as well as low and high-throughput experiments embedded in text corpora can be mined as data sources for the implementation of HCV-specific resources. HCV-customized resources may support the generation of worthy and testable hypothesis and reveal potential research clues to augment the pursuit of efficient diagnostic biomarkers and therapeutic targets. This research thesis report the development of two freely available HCV-specific web-based resources: (i) Dragon Exploratory System on Hepatitis C Virus (DESHCV) accessible via http://apps.sanbi.ac.za/DESHCV/ or http://cbrc.kaust.edu.sa/deshcv/ and (ii) Hepatitis C Virus Protein Interaction Database (HCVpro) accessible via http://apps.sanbi.ac.za/hcvpro/ or http://cbrc.kaust.edu.sa/hcvpro/. DESHCV is a text mining system implemented using named concept recognition and cooccurrence based approaches to computationally analyze about 32, 000 HCV related abstracts obtained from PubMed. As part of DESHCV development, the pre-constructed dictionaries of the Dragon Exploratory System (DES) were enriched with HCV biomedical concepts, including HCV proteins, name variants and symbols to enable HCV knowledge specific exploration. The DESHCV query inputs consist of user-defined keywords, phrases and concepts. DESHCV is therefore an information extraction tool that enables users to computationally generate association between concepts and support the prediction of potential hypothesis with diagnostic and therapeutic relevance. Additionally, users can retrieve a list of abstracts containing tagged concepts that can be used to overcome the herculean task of manual biocuration. DESHCV has been used to simulate previously reported thalidomide-chronic hepatitis C hypothesis and also to model a potentially novel thalidomide-amantadine hypothesis. HCVpro is a relational knowledgebase dedicated to housing experimentally detected HCV-HCV and HCV-human protein interaction information obtained from other databases and curated from biomedical journal articles. Additionally, the database contains consolidated biological information consisting of hepatocellular carcinoma (HCC) related genes, comprehensive reviews on HCV biology and drug development, functional genomics and molecular biology data, and cross-referenced links to canonical pathways and other essential biomedical databases. Users can retrieve enriched information including interaction metadata from HCVpro by using protein identifiers, gene chromosomal locations, experiment types used in detecting the interactions, PubMed IDs of journal articles reporting the interactions, annotated protein interaction IDs from external databases, and via “string searches”. The utility of HCVpro has been demonstrated by harnessing integrated data to suggest putative baseline clues that seem to support current diagnostic exploratory efforts directed towards vimentin. Furthermore, eight genes comprising of ACLY, AZGP1, DDX3X, FGG, H19, SIAH1, SERPING1 and THBS1 have been recommended for possible investigation to evaluate their diagnostic potential. The data archived in HCVpro can be utilized to support protein-protein interaction network-based candidate HCC gene prioritization for possible validation by experimental biologists. / South Africa

Magister Scientiae - MSc / Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb). TB mainly affects lungs of patients but other parts of the body can also be affected. It kills approximately 2 million people annually. HIV/AIDS and drug resistance make TB difficult to control. Mtb CarD protein forms a physiological complex with Ribonucleic Acid Polymerase (RNAP). This complex causes Mtb to undergo dormancy rendering it difficult to control using current antibiotics. CarD and a size-reduced subunit β1 (denoted β1m for “minimized”) of Thermus thermophilus RNAP, in which the central domain has been replaced by a Gly-Gly linker, were produced and purified using affinity nickel nitrilotriaceticacid and glutathione-Stransferase (GST) affinity chromatography techniques respectively. CarD N terminal domain (CarDN) was generated from CarD by inserting a stop codon by site directed mutagenesis. CarD was stabilised by adding 5 % (v/v) glycerol to PBS pH 7.4 ensuring protein stability of up to 67 days rather than 2 days without glycerol. CarDN was stable in PBS pH 7.4 without addition of glycerol. This suggests that the CarD C terminal domain may be responsible for CarD instability. To further purify the proteins both anion exchange and gel permeation chromatography techniques were used. CarD and CarDN degrade immediately after anion exchange potentially because of the high ion concentration which partially unfolds the protein making it prone to proteolytic cleavage. GST-pull down assays were used to demonstrate complex formation between RNAP β1m and both CarD and CarDN confirming that complex formation is dependent on the N-terminal domain of CarD.

The 90-KDa heat shock protein (Hsp90) is part of the molecular chaperone family, and as such it is involved in the regulation of protein homeostasis within cells. Specifically, Hsp90 aids in the folding of nascent proteins and re-folding of denatured proteins. It also plays an important role in the prevention of protein aggregation. Hsp90’s functionality is attributed to its several staged, multi-conformational ATPase cycle, in which associated client proteins are bound and released. Hsp90 is known to be associated with a wide array of client proteins, some of which are thought to be involved in multiple oncogenic processes. Indeed Hsp90 is known to be directly involved in perpetuating the stability and function of multiple mutated, chimeric and over-expressed signalling proteins that are known to promote the growth and survival of cancer cells. Hsp90 inhibitors are thus thought to be promising therapeutic agents for cancer treatment. A lack of a 3D structure of human Hsp90 however has restricted Hsp90 inhibitor development in large to in vivo investigations. This study, aims to investigate and calculate hypothetical homology models of the full human Hsp90 protein, and to probe these structural models for novel drug target sites using several in silico techniques. A multi-template homology modelling methodology was developed and in conjunction with protein-protein docking techniques, two functionally important human Hsp90 structural models were calculated; the nucleotide free “v-like” open and nucleotide bound closed conformations. Based on the conservation of ligand binding, virtual screening experiments conducted on both models using 316 natural compounds indigenous to South Africa, revealed three novel putative target sites. Two binding pockets in close association with important Hsp90-Hop interaction residues and a single binding pocket on the dimerization interface in the C-terminal domain. Targeted molecular docking experiments at these sites revealed two compounds (721395-11-5 and 264624-39-7) as putative inhibitors, both showing strong binding affinities for at least one of the three investigated target sites. Furthermore both compounds were found to only violate one Lipinski’s rules, suggesting their potential as candidates for further drug development. The combined work described here provides a putative platform for the development of next generation inhibitors of human Hsp90.

The papain-like cysteine protease family (C1 proteases) is highly important because of its involvement in research and industrial applications and its role in various human diseases. Protein inhibitors are an important aspect of C1 protease biology and are relevant to its clinical, industrial and research importance. To study the interaction between the proteases and the inhibitors it is very useful to have accurate structural models of the protease-inhibitor complexes. To this end, a high-throughput pipeline for modelling complexes of papain-like cysteine proteases and protein inhibitors was implemented and tested (Tastan Bishop & Kroon, 2011). The pipeline utilizes a novel technique for obtaining modelling templates by using superpositioning to combine coordinates from separate experimental structures. To test the pipeline, models of complexes with known structures (test set) were modelled using many different templates and the resultant models evaluated to compare the quality of the different templates. It was found that use of the new technique to obtain templates did not introduce significant errors, while allowing closer homologs to be used for modelling - leading to more accurate models. The test set models were also used to evaluate certain steps of the modelling protocol. The effect of Rosetta energy minimization on model accuracy and the use of Rosetta energy and DOPE Z-score values to identify accurate models were investigated. Several complexes were then modelled using the best available templates according to criteria informed by the previous results. A website was built that allows a user to download any of the metrics or models produced in the study. This website is accessible at http://rubi.ru.ac.za/cpmdb