Central infusion of the hexapeptide angiotensin IV (Ang IV) and its analogs have been demonstrated to markedly enhance memory retention and retrieval in rats using a range of learning and memory paradigms. This effect is mediated by the binding of the peptide to the specific binding site previously described as the AT4 receptor. The AT4 receptor has been isolated and identified as insulin-regulated aminopeptidase (IRAP), a type II transmembrane protein belonging to the M1 family of zinc-dependent aminopeptidases. Subsequently, AT4 receptor ligands, including Ang IV and its analogues and the unrelated peptide LVV-hemorphin-7, were demonstrated to be peptide inhibitors of IRAP. These findings suggest that AT4 ligands may exert their cognitive effects by inhibiting the catalytic activity of IRAP in the brain. Therefore, IRAP is an important target for the development of a new class of therapeutic agents for the treatment of memory loss. / To characterize IRAP at the molecular level and identify non-peptide inhibitors of IRAP for drug development, the aims of this study were to: 1) determine whether IRAP exists as a homodimer; 2) identify cysteine residue(s) involved in IRAP dimerization; 3) investigate the roles of the conserved residues of the HEXXH(X)18E Zn2+-binding motif and the GAMEN motif in substrate/inhibitor binding using site-directed mutagenesis; 4) use a molecular model of the catalytic domain of IRAP based on the crystal structure of a related M1 family metallopeptidase to: (i) identify key residues required for substrate/inhibitor binding; (ii) identify and characterize non-peptide IRAP inhibitors from a compound database by in silico virtual screening based on the homology model of IRAP. / Co-immunoprecipitation followed by Western blotting of IRAP under reducing and non-reducing conditions showed IRAP exists both as covalently- and non-covalently-bound homodimers. Serine scanning of cysteine residues potentially involved in forming inter-molecule disulfide-bonds was performed. Mutational analyses indicated that covalent homodimerization of IRAP is due to more than one cysteine residue. Limited trypsin digestion followed by co-immunoprecipitation suggests that non-covalent homodimerization of IRAP involves residues/regions within the last 130 amino acids of the protein. / The catalytic site of IRAP contains two consensus motifs, the H464EXXH468(X)18E487 Zn2+-binding motif and the G428AMEN432 motif. The role of conserved residues with these motifs was investigated using site-directed mutagenesis and pharmacological analyses. The conserved His and Glu residues of the Zn2+-binding motif were shown to be essential for IRAP catalytic activity. This was also observed for the Met and Glu residues of the GAMEN motif, while Asn mutant retained some catalytic activity. Residues important for substrate or inhibitor binding were identified as Gly, Ala and Asn. / A molecular model of the catalytic domain of IRAP based on the crystal structure of a homologous M1 metallopeptidase, leukotriene A4 hydrolase (LTA4H) was used to compare the catalytic sites of IRAP and LTA4H, and identified two amino acids at the putative substrate-binding pocket: Ala427 and Leu483 in IRAP, and the corresponding residues Tyr267 and Phe314 in LTA4H. A mutational analysis involving substitution of Ala427 and Leu483 with the corresponding residues revealed Ala427 and Leu483 characterize the enzyme S1 subsite, influencing the affinity and placement of substrates and peptide inhibitors in the catalytic site. / The molecular model of IRAP was also used for virtual screening of compound databases to identify novel non-peptide inhibitors. After two rounds of in silico screening, a family of compounds was identified and shown to be specific and competitive inhibitors of IRAP. Preliminary results suggest that one of these inhibitors, referred to as HFI 142, may possess memory-enhancing properties. The identification of non-peptide IRAP inhibitors will assist in pharmacological studies aimed at understanding the molecular mechanisms of IRAP aminopeptidase activity and physiological role of IRAP. In addition, the new inhibitors have the potential to form the basis for the development of a novel class of drugs useful for treating memory disorders.

Locating a ligand-binding site is an important first step in structure-guided drug discovery, but current methods typically assess the pocket as a whole, doing little to suggest which regions and interactions are the most important for binding. This thesis introduces Fragment Hotspot Maps, a grid-based method that samples atomic propensities derived from interactions in the Cambridge Structural Database (CSD) with simple molecular probes. These maps specifically highlight fragment-binding sites and their corresponding pharmacophores, offering more precision over other binding site prediction methods. The method is validated by scoring the positions of 21 fragment and lead pairs. Fragment atoms are found in the highest scoring parts of the map corresponding to their atom type, with a median percentage rank of 98%. This is reduced to 72% for lead atoms, showing that the method can differentiate between the hotspots, and the warm spots later used during fragment elaboration. For ligand-bound structures, they provide an intuitive visual guide within the binding site, directing medicinal chemists where to grow the molecule and alerting them to suboptimal interactions within the original hit. These calculations are easily accessible through a simple to use web application, which only requires an input PDB structure or code. High scoring specific interactions predicted by the Fragment Hotspot Maps can be used to guide existing computer aided drug discovery methods. The Hotspots Python API has been created to allow these work flows to be executed programmatically through a single Python script. Two of the functions use scores from the Fragment Hotspot Maps to guide virtual screening methods, docking and field-based ligand screening. Docking virtual screening performance is improved by using a constraint selected from the highest scoring polar interaction. The field-based ligand screener uses modified versions of the Fragment Hotspot Maps directly to predict and score the binding pose. This workflow gave comparable results to docking, and for one target, Glucocorticoid receptor (GCR), showed much better results, highlighting its potential as an orthogonal approach. Fragment Hotspot Maps can be used at multiple stages of the drug discovery process, and research into these applications is ongoing. Their utility in the following areas are currently being explored: to assess ligandability for both individual structures and across proteomes, to aid in library design, to assess pockets throughout a molecular dynamics trajectory, to prioritise crystallographic fragment hits and to guide hit-to-lead development.

Malaria is prevalent in over 100 countries which is populated by half of the world’s population and culminates in approximately one million deaths per annum, 85% of which occurs in sub-Saharan Africa. The combined resistance of the mosquitoes and parasites to the currently available pesticides and antimalarial chemotherapeutic agents requires the concerted effort of scientists in the malaria field to identify and develop novel mechanisms to curb this deadly disease. In this study, a thorough understanding of the role players in the polyamine pathway of the parasite was obtained, which could aid future studies in the development of novel inhibitory compounds against these validated drug targets. The uniquely bifunctional S-adenosylmethionine decarboxylase/ornithine decarboxylase (AdoMetDC/ODC) of Plasmodium falciparum forms an important controlling node between the polyamine and methionine metabolic pathways. It has been speculated that the unique bifunctional association of the rate-limiting enzymes allows for the concerted regulation of the respective enzyme activities resulting in polyamine synthesis as per requirement for the rapidly proliferating parasite while the methionine levels are strictly controlled for their role in the methylation status. The results of this study showed that the enzyme activities of the bifunctional complex are indeed coordinated and subtle conformational changes induced by complex formation is suggested to result in these altered kinetics of the individual AdoMetDC and ODC domains. Studies also showed that the identification of the interaction sites between the domains, which allows for communication across the complex, may be targeted for specific interference with the enzyme activities. Furthermore, these studies showed that the current knowledge on the different subclasses of the AdoMetDC family should be re-evaluated since P. falciparum AdoMetDC shows diverse properties from orthologues and therefore points towards a novel grouping of the plasmodial protein. The extensive biochemical and biophysical studies on AdoMetDC has also provided important avenues for the crystallisation and solving of this protein’s 3D structure for subsequent structure-based identification of drug-like lead compounds against AdoMetDC activity. The application of structure-based drug design on malarial proteins was additionally investigated and consequently proved that the rational design of lead inhibitory compounds can provide important scaffold structures for the identification of the key aspects that are required for the successful inhibition of a specific drug target. Spermidine synthase, with its intricate catalytic mechanism involving two substrate binding sites for the products of the reactions catalysed by AdoMetDC/ODC, was used to computationally identify compounds that could bind within its active site. Subsequent testing of the compounds identified with a dynamic receptor-based pharmacophore model showed promising inhibitory results on both recombinant protein and in vitro parasite levels. The confirmation of the predicted interaction sites and identification of aspects to improve inhibitor interaction was subsequently investigated at atomic resolution with X-ray protein crystallography. The outcome of this doctoral study shows the benefit in applying a multidisciplinary and multinational approach for studying drug targets within the malaria parasite, which has led to a thorough understanding of the targets on both biochemical and structural levels for future drug design studies. / Thesis (PhD)--University of Pretoria, 2011. / Biochemistry / unrestricted

No description available.

O Projeto Genoma Humano do Câncer (PGHC), financiado pela FAPESP e pelo Instituto Ludwig de Pesquisa sobre o câncer, buscou identificar os genes expressos nos tipos mais comuns de câncer no Brasil. Tal projeto conseguiu identificar aproximadamente um milhão de seqüências de genes de tumores freqüentes no Brasil. A contribuição brasileira foi maior para tumores de cabeça e pescoço, mama e cólon. Uma das iniciativas mais recentes e estimuladas pelo PGHC é o projeto Genoma Clínico, o qual visa desenvolver novas formas de diagnóstico e tratamento do câncer através do estudo de genes expressos. A partir da análise molecular de tecidos saudáveis e neoplásicos em diferentes estágios, é possível identificar marcadores de prognóstico, permitindo escolhas de terapias mais adequadas e eficientes. A proteína hnRNP K foi identificada como um desses marcadores, em neoplasias da região da cabeça e pescoço, sendo objetivo deste estudo a aplicação de técnicas de bioinformática e modelagem molecular no planejamento baseado em estrutura de candidatos a fármacos antineoplásicos que bloqueiem a atividade da proteína. A proteína hnRNP K apresenta diversas funções e é encontrada nos mais diversos compartimentos celulares, interferindo, basicamente, no sistema de expressão gênica. Essa proteína apresenta 3 domínios KH, os quais são responsáveis por sua ligação à moléculas de DNA e RNA. Modelos de boa qualidade dos domínios KH foram construídos através da estratégia de modelagem molecular por homologia estrutural. Após screening virtual em bases de dados de compostos (330.000 aproximadamente) com propriedades drug-like, 15 compostos com potencial de interação com o domínio KH3 foram selecionados. Os modos de ligação para cada um dos mesmos no sítio ligante do domínio KH3 foram sugeridos por simulações de docking e apresentaram um bom encaixe espacial com os sítios receptores virtuais calculados pelos campos de interação molecular. Simulações de dinâmica molecular foram realizadas com o intuito de avaliar a estabilidade dos compostos selecionados, que também foram avaliados quanto à presença de grupamentos toxicofóricos em sua estrutura. / The Brazilian Project Genoma Câncer (PGHC) supported by FAPESP and the Ludwig Institute for Cancer Research, intended to identify the genes involved in the most common cases of cancer in Brazil. In this project about a million of gene sequences were identified. The major contribution was made in breast, colorectal and head and neck cancers. The results obtained stimulated the creation of another project, called Genoma Clínico, which intend to develop new trends in treatments and diagnosis of cancer based on the study of expressed genes. Analyzing healthy and neoplasic tissues in different stages, it is possible to identify molecular markers related to the prognosis of cancer, allowing the use of more efficient therapies. The hnRNP K protein was identified as a molecular marker in head and neck cancer, where the objective of this work lies in the application of bioinformatics and molecular modeling strategies by structure-based drug design to identify potential antineoplasic drug candicates that could act against hnRNP K protein. The hnRNP K protein is encountered in all cellular compartments and act, basically, in the gene expression pathways. Its structure is composed by three KH domains that mediate interactions with DNA and RNA molecules. High quality models of KH domains were built by homology modeling. After the virtual screening simulations performed with drug-like compound databases, containing approximately 330.000 compounds, 15 were selected as potential ligands of KH3 domain of hnRNP K. The binding modes suggested for these compounds, by docking simulations, presented a good spatial fit when compared with the virtual receptor sites calculated by molecular interaction fields. Molecular dynamics simulations were performed in order to evaluate de stability of the binding modes suggested. The potential ligands were also evaluated to identify toxicophoric features in its chemical structures.

O Projeto Genoma Humano do Câncer (PGHC), financiado pela FAPESP e pelo Instituto Ludwig de Pesquisa sobre o câncer, buscou identificar os genes expressos nos tipos mais comuns de câncer no Brasil. Tal projeto conseguiu identificar aproximadamente um milhão de seqüências de genes de tumores freqüentes no Brasil. A contribuição brasileira foi maior para tumores de cabeça e pescoço, mama e cólon. Uma das iniciativas mais recentes e estimuladas pelo PGHC é o projeto Genoma Clínico, o qual visa desenvolver novas formas de diagnóstico e tratamento do câncer através do estudo de genes expressos. A partir da análise molecular de tecidos saudáveis e neoplásicos em diferentes estágios, é possível identificar marcadores de prognóstico, permitindo escolhas de terapias mais adequadas e eficientes. A proteína hnRNP K foi identificada como um desses marcadores, em neoplasias da região da cabeça e pescoço, sendo objetivo deste estudo a aplicação de técnicas de bioinformática e modelagem molecular no planejamento baseado em estrutura de candidatos a fármacos antineoplásicos que bloqueiem a atividade da proteína. A proteína hnRNP K apresenta diversas funções e é encontrada nos mais diversos compartimentos celulares, interferindo, basicamente, no sistema de expressão gênica. Essa proteína apresenta 3 domínios KH, os quais são responsáveis por sua ligação à moléculas de DNA e RNA. Modelos de boa qualidade dos domínios KH foram construídos através da estratégia de modelagem molecular por homologia estrutural. Após screening virtual em bases de dados de compostos (330.000 aproximadamente) com propriedades drug-like, 15 compostos com potencial de interação com o domínio KH3 foram selecionados. Os modos de ligação para cada um dos mesmos no sítio ligante do domínio KH3 foram sugeridos por simulações de docking e apresentaram um bom encaixe espacial com os sítios receptores virtuais calculados pelos campos de interação molecular. Simulações de dinâmica molecular foram realizadas com o intuito de avaliar a estabilidade dos compostos selecionados, que também foram avaliados quanto à presença de grupamentos toxicofóricos em sua estrutura. / The Brazilian Project Genoma Câncer (PGHC) supported by FAPESP and the Ludwig Institute for Cancer Research, intended to identify the genes involved in the most common cases of cancer in Brazil. In this project about a million of gene sequences were identified. The major contribution was made in breast, colorectal and head and neck cancers. The results obtained stimulated the creation of another project, called Genoma Clínico, which intend to develop new trends in treatments and diagnosis of cancer based on the study of expressed genes. Analyzing healthy and neoplasic tissues in different stages, it is possible to identify molecular markers related to the prognosis of cancer, allowing the use of more efficient therapies. The hnRNP K protein was identified as a molecular marker in head and neck cancer, where the objective of this work lies in the application of bioinformatics and molecular modeling strategies by structure-based drug design to identify potential antineoplasic drug candicates that could act against hnRNP K protein. The hnRNP K protein is encountered in all cellular compartments and act, basically, in the gene expression pathways. Its structure is composed by three KH domains that mediate interactions with DNA and RNA molecules. High quality models of KH domains were built by homology modeling. After the virtual screening simulations performed with drug-like compound databases, containing approximately 330.000 compounds, 15 were selected as potential ligands of KH3 domain of hnRNP K. The binding modes suggested for these compounds, by docking simulations, presented a good spatial fit when compared with the virtual receptor sites calculated by molecular interaction fields. Molecular dynamics simulations were performed in order to evaluate de stability of the binding modes suggested. The potential ligands were also evaluated to identify toxicophoric features in its chemical structures.

Drug resistance is a global health threat costing society billions of dollars and impacting millions of lives each year. Current drug design strategies are inadequate because they focus on disrupting target activity and not restricting the evolutionary pathways to resistance. Improved strategies would exploit the structural and dynamic changes in the enzyme–inhibitor system integrating data from many inhibitors and variants. Using HIV-1 protease as a model system, I aimed to elucidate the underlying resistance mechanisms, characterize conserved protease-inhibitor interactions, and generate more robust inhibitors by applying these insights. For primary mechanisms of resistance, comparing interactions at the protease–inhibitor interface showed how specific modifications affected potency. For mutations distal to the active site, molecular dynamics simulations were necessary to elucidate how changes propagated to reduce inhibitor binding. These insights informed inhibitor design to improve potency against highly resistant variants by optimizing hydrogen bonding. A series of hybrid inhibitors was also designed that showed excellent potency by combining key moieties of multiple FDA-approved inhibitors. I characterized the structural basis for alterations in binding affinity in HIV-1 protease both from mutations and inhibitors. I applied these strategies to HTLV-1 protease, a potential drug target. I identified the HIV-1 inhibitor darunavir as a viable scaffold and evaluated analogues, leading to a low-nanomolar compound with potential for optimization. Hopefully, insights from this thesis will lead to the development of potent HTLV-1 protease inhibitors. More broadly, these inhibitor design strategies are applicable to other rapidly evolving targets, thereby reducing drug resistance rates in the future.

Philosophiae Doctor - PhD / Given the significant disease burden caused by human coronaviruses, the discovery of an effective antiviral strategy is paramount, however there is still no effective therapy to combat infection. This thesis details the in silica exploration of ligand libraries to identify candidate lead compounds that, based on multiple criteria, have a high probability of inhibiting the 3 chymotrypsin-like protease (3CUro) of human coronaviruses. Atomistic models of the 3CUro were obtained from the Protein Data Bank or theoretical models were successfully generated by homology modelling. These structures served the basis of both structure- and ligand-based drug design studies. Consensus molecular docking and pharmacophore modelling protocols were adapted to explore the ZINC Drugs-Now dataset in a high throughput virtual screening strategy to identify ligands which computationally bound to the active site of the 3CUro . Molecular dynamics was further utilized to confirm the binding mode and interactions observed in the static structure- and ligand-based techniques were correct via analysis of various parameters in a IOns simulation. Molecular docking and pharmacophore models identified a total of 19 ligands which displayed the potential to computationally bind to all 3CUro included in the study. Strategies employed to identify these lead compounds also indicated that a known inhibitor of the SARS-Co V 3CUro also has potential as a broad spectrum lead compound. Further analysis by molecular dynamic simulations largely confirmed the binding mode and ligand orientations identified by the former techniques. The comprehensive approach used in this study improves the probability of identifying experimental actives and represents a cost effective pipeline for the often expensive and time consuming process of lead discovery. These identified lead compounds represent an ideal starting point for assays to confirm in vitro activity, where experimentally confirmed actives will be proceeded to subsequent studies on lead optimization.

Les interactions protéine-protéine (IPPs) contrôlent de nombreux processus physiologiques importantsdans les cellules humaines. Une caractéristique des cancers est l'échappement des cellules àl'apoptose, qui est souvent associé à la surexpression de protéines anti-apoptotiques, membres de lafamille de protéines Bcl-2. Cette famille comprend des membres anti-apoptotiques (Bcl-2, Bcl-xL,Mcl-1) et pro-apoptotiques. Dans de nombreux cancers dont les cancers de l’ovaire chimiorésistants,l'équilibre entre les membres pro- et anti-apoptotiques de la famille de protéines Bcl-2 est altéré etconduit à la survie des cellules cancéreuses. Une des stratégies envisagées pour surmonter cettechimiorésistance est rétablir l’apoptose par l’inhibition concomitante des protéines Mcl-1 et Bcl-xL.L’objectif est de concevoir des inhibiteurs à dualité d’action visant les protéines Mcl-1 et Bcl-xL.Les travaux antérieurs du laboratoire ont permis la découverte d’un inhibiteur sélectif de la protéineMcl-1, appelé Pyridoclax. Par une approche combinant les méthodes de Fragment-Based Drug Designet Structure-Based Drug Design, à partir de la structure du Pyridoclax, la conception de dual inhibiteurs,leur synthèse et leur évaluation biologique, sont rapportées dans cette thèse. L’exploration de nouveauxespaces chimiques et biologiques est ainsi rendue possible par la mise en oeuvre de cette approche ausein de laquelle le développement de nouvelles méthodologies de synthèse dans le but de concevoirdes fragments tridimensionnels originaux sera présenté.Ces travaux de thèse ont permis de concevoir, synthétiser et caractériser plus de 90 molécules.Certaines ont montré une activité pro-apoptotique intéressante en inhibant les protéines Mcl-1 et Bcl-xLnotamment. / Protein-protein interactions (PPIs) control many important physiological processes within human cells.A hallmark of cancers is the escape of cells from apoptosis, which is often associated with theoverexpression of the anti-apoptotic proteins of the Bcl-2 family. This family comprises pro-survival(Bcl-2, Bcl-xL, Mcl-1) and pro-apoptotic members. In many cancers and, in particular, chemoresistantovarian cancers, the balance between the pro- and anti-apoptotic Bcl-2 family members is alteredleading to the survival of cancerous cells. One of the strategies used to overcome chemoresistance isto re-establish apoptosis by the concomitant inhibition of Mcl-1 and Bcl-xL proteins. Therefore, theobjective is to design dual Mcl-1/Bcl-xL inhibitors.Our groups previous work allowed the discovery of a selective Mcl-1 inhibitor, named Pyridoclax. UsingFragment-Based Drug Design and Structure-Based Drug Design approaches, from the structure ofPyridoclax, the design, synthesis and biological evaluation of dual inhibitors are reported in this thesis.The exploration of novel chemical and biological space is possible by the implementation of thisapproach. The development of synthetic methodologies for the design of new 3-dimensional fragmentswill be presented.In this work, around 90 molecules were synthesized using an approach which combined Fragment-Based Drug Design and Structure-Based Drug Design methods. Some showed a pro-apoptotic activityby inhibiting Mcl-1 and Bcl-xL proteins.

A esquistossomose é uma das principais causas de morbidade em países Tropicais e Subtropicais, gerando graves consequências socioeconômicas. Atualmente, os fármacos disponíveis para o tratamento da desta doença são praziquantel e oxamniquina, porém relatos de baixa susceptibilidade do parasita a esses medicamentos sugerem a necessidade de novas estratégias terapêuticas para o tratamento da doença. Todavia, existe pouco interesse da indústria farmacêutica no desenvolvimento de fármacos contra doenças tropicais e negligenciadas, entre as quais se encontra a esquistossomose. Devido a estes fatores, o presente trabalho teve por objetivo geral utilizar ferramentas computacionais para identificar inibidores da SmDHFR candidatos a novos fármacos. Avaliou-se as características exclusivas para a proteína de S. mansoni por meio de uma análise das sequências FASTA em comparação com a DHFR de outros organismos. A fim de garantir a ação seletiva dessas moléculas frente a enzima do parasita, os campos moleculares de interação seletivos para SmDHFR foram calculados e empregados na construção do modelo farmacofórico, o qual foi utilizado na triagem virtual de inibidores de SmDHFR. Os estudos computacionais realizados nos permitiram a seleção de 20 moléculas com uma boa complementariedade com o modelo farmacofórico gerado e com potencial para serem inibidores de SmDHFR. / Schistosomiasis is one of morbidity\'s main causes in tropical and subtropical countries, which leads to serious socioeconomic consequences. Praziquantel and oxamniquina are the drugs currently available for treating this disease, but reports points that the parasite has been resistant to both drugs, which suggests the need for new therapeutic strategies for the treatment of this disease. However, there is little interest in the pharmaceutical industry in developing drugs against neglected tropical diseases, including schistosomiasis. Due to these factors, the present work has the general objective to use computational tools to identify SmDHFR inhibitors which could be good candidates for developing new drugs. Evaluation of the exclusive characteristics of the S. mansoni protein were performed by FASTA sequence analyses in comparison to DHFR from other organisms. In order to guarantee the selective action of these molecules against the parasite enzyme, the molecular interaction fields selective for SmDHFR were calculated and used in the construction of the pharmacophoric model, which was further used in the virtual screening of SmDHFR inhibitors. Computational studies were performed and those led us to 20 molecules with a good complementarity with the pharmacophoric model that was previously generated and with potential to be SmDHFR inhibitors.