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L’évolution des protéines est un domaine important de la recherche en bioinformatique et catalyse l'intérêt de trouver des outils d'alignement qui peuvent être utilisés de manière fiable et modéliser avec précision l'évolution d'une famille de protéines. TM-Align (Zhang and Skolnick, 2005) est considéré comme l'outil idéal pour une telle tâche, en termes de rapidité et de précision. Par conséquent, dans cette étude, TM-Align a été utilisé comme point de référence pour faciliter la détection des autres outils d'alignement qui sont en mesure de préciser l'évolution des protéines. En parallèle, nous avons élargi l'actuel outil d'exploration de structures secondaires de protéines, Helix Explorer (Marrakchi, 2006), afin qu'il puisse également être utilisé comme un outil pour la modélisation de l'évolution des protéines. / Protein evolution is an important field of research in bioinformatics and catalyzes the requirement of finding alignment tools that can be used to reliably and accurately model the evolution of a protein family. TM-Align (Zhang and Skolnick, 2005) is considered to be the ideal tool for such a task, in terms of both speed and accuracy. Therefore in this study, TM-Align has been used as a point of reference to facilitate the detection of other alignment tools that are able to accurately model protein evolution. In parallel, we expand the existing protein secondary structure explorer tool, Helix Explorer (Marrakchi, 2006), so that it can also be used as a tool to model protein evolution.

A acne é uma condição da pele multifatorial com implicações socioeconômicas importantes. Um dos principais fatores que contribuem com a sua etiologia é a superprodução de sebo. Até o momento, há poucos tratamentos seguros e eficazes disponíveis. O receptor de melanocortina-5 (MC5R), um receptor acoplado à proteína G da família das rodopsinas, é uma das proteínas responsáveis pela diferenciação de sebócitos e consequente produção de sebo, mas não há opções de tratamento através do antagonismo deste receptor. Neste trabalho, investigamos a melanocortina-5 como alvo molecular para a descoberta de ligantes como moduladores da sebogênese. Para tanto, empregamos estudos de modelagem por homologia e triagem virtual baseada em estrutura do alvo para construir um modelo 3D da MC5R e identificar de candidatos a ligantes da proteína, respectivamente. Em seguida, avaliamos o potencial de inibição da sebogênese em sebócitos SEBO662AR em meio lipogênico. Os resultados obtidos indicaram a descoberta de peptídeos e flavonoides com características inibidoras e estimuladoras da produção de sebo. Novos esqueletos moleculares foram identificados como promissores para a modulação da sebogênese. Os estudos realizados permitirão o desenvolvimento de novos ativos dermatológicos e cosméticos com potencial de modular a oleosidade da pele, de modo a contribuir com a mitigação dos efeitos da acne, psoríase, alopecia e seborreia, entre outras doenças. / Acne is a multifactorial skin condition with important socioeconomic implications. One of the main factors that contribute with its etiology is sebum overproduction. Until now, there are few safe, effective treatments available. Melanocortin-5 receptor (MC5R), a G protein-coupled receptor of the rhodopsin family, is one of the proteins responsible for sebocyte differentiation and consequent sebum production, but there are no options for treatment by antagonism of this receptor. In this work, we investigated MC5R as molecular target for the discovery of ligands as sebogenesis modulators. For that, we used homology modeling studies, and structure-based virtual screening in order to, respectively, build a MC5R 3D model and identify ligand candidates for this protein. Then, we evaluated their sebogenesis inhibition potential on SEBO662AR sebocytes in lipogenic conditions. The obtained results indicated the discovery of peptides and flavonoids with inhibitory and stimulatory sebum production characteristics. New scaffolds were identified as promising for sebogenesis modulation. The performed studies will allow the development of novel dermatologic and cosmetic actives with the potential to modulate skin oiliness in order to contribute to the mitigation of the effects of acne, psoriasis, alopecia and seborrhea, among other diseases.

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.

This thesis describes studies directed towards development of novel antiadhesive agents, with particular emphasis on compounds that prevent attachment of bacteria to a host-cell. Three different proteins involved in the assembly or function of adhesive pili in uropathogenic Escherichia coli have been targeted either by rational structure based design or statistical molecular methods. A library of substituted galabiose (Galα1-4Gal) derivatives was screened for binding to the E. coli adhesin PapG in an assay based on surface plasmon resonance, and for inhibition of Streptococcus suis adhesins PN and PO in a hemagglutination assay. The results were used to generate QSAR models which had good predictive powers and provided further insight in the structural requirements needed for high affinity binding. 2-pyridones and amino acid derivatives were modelled into the binding site of chaperones involved in pilus assembly in E. coli and a heuristic method, VALIDATE, was used for affinity prediction. The affinity of the compounds for the chaperones PapD and FimC were assessed in assays based on surface plasmon resonance and relaxation-edited NMR spectroscopy. Their ability to disrupt chaperone/subunit complexes was investigated in vitro through a FPLC assay and their capacity to inhibit pilus formation in vivo was determined via hemagglutination and confirmed with atomic force microscopy. Statistical molecular design was used to design a diverse peptide library targeting pili subunits, and an ELISA was developed to investigate the ability of the peptides to inhibit chaperone/subunit complexation. The resulting QSAR model provided extensive information regarding binding of the peptides to the subunits. Because the peptides were suggested to bind in an extended β-strand formation, β-strand mimetics consisting of oligomeric enaminones were designed. Finally, new methods to synthesize enaminone building blocks were developed using microwave assisted chemistry. The projects described have generated compounds that besides their value as leads for developing novel antibacterial agents, also constitute new chemical tools to study the mechanisms underlying bacterial virulence.

L’évolution des protéines est un domaine important de la recherche en bioinformatique et catalyse l'intérêt de trouver des outils d'alignement qui peuvent être utilisés de manière fiable et modéliser avec précision l'évolution d'une famille de protéines. TM-Align (Zhang and Skolnick, 2005) est considéré comme l'outil idéal pour une telle tâche, en termes de rapidité et de précision. Par conséquent, dans cette étude, TM-Align a été utilisé comme point de référence pour faciliter la détection des autres outils d'alignement qui sont en mesure de préciser l'évolution des protéines. En parallèle, nous avons élargi l'actuel outil d'exploration de structures secondaires de protéines, Helix Explorer (Marrakchi, 2006), afin qu'il puisse également être utilisé comme un outil pour la modélisation de l'évolution des protéines. / Protein evolution is an important field of research in bioinformatics and catalyzes the requirement of finding alignment tools that can be used to reliably and accurately model the evolution of a protein family. TM-Align (Zhang and Skolnick, 2005) is considered to be the ideal tool for such a task, in terms of both speed and accuracy. Therefore in this study, TM-Align has been used as a point of reference to facilitate the detection of other alignment tools that are able to accurately model protein evolution. In parallel, we expand the existing protein secondary structure explorer tool, Helix Explorer (Marrakchi, 2006), so that it can also be used as a tool to model protein evolution.

Until recently, the standard therapy for hepatitis C treatment has been interferon and ribavirin. Such treatment has only 50% efficacy and is not well tolerated. The emergence of new drugs has increased the treatment efficacy to 90%. Despite such an achievement, the success is limited since the virus mutates rapidly, causing the emergence of drug resistant forms. In addition, most new drugs were developed to treat genotype 1 infections. Thus, development of new potent antivirals is needed and drug discovery against hepatitis C is continued. In this thesis, a FRET-based protease assay was used to evaluate new pyrazinone based NS3 protease inhibitors that are structurally different to the newly approved and currently developing drugs. Several compounds in this series showed good potencies in the nanomolar range against NS3 proteases from genotype 1, 3, and the drug resistance variant R155K. We assume that these compounds can be further developed into drug candidates that possess activity against above mentioned enzyme variants. By using SPR technology, we analyzed interaction mechanisms and characteristics of allosteric inhibitors targeting NS5B polymerases from genotypes 1 and 3. The compounds exhibited different binding mechanisms and displayed a low affinity against NS5B from genotype 3. In order to evaluate the activity and inhibitors of the NS5B polymerase, we established an SPR based assay, which enables the monitoring of polymerization and its inhibition in real time. This assay can readily be implemented for the discovery of inhibitors targeting HCV. An SPR based fragment screening approach has also been established. A screen of a fragment library has been performed in order to identify novel scaffolds that can be used as a starting point for development of new allosteric inhibitors against NS5B polymerase. Selected fragments will be further elaborated to generate a new potent allosteric drug candidate. Alternative approaches have successfully been developed and implemented to the discovery of potential lead compounds targeting two important HCV drug targets.

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.

Computational drug design methods have great potential in drug discovery particularly in lead identification and lead optimization. 3-Phosphoinositide dependent kinase-1 (PDK1) is a protein kinase and a well validated anti-cancer target. Inhibitors of PDK1 have the potential to be developed as anti-cancer drugs. In this work, we have applied various novel computational drug design strategies to design and identify new PDK1 inhibitors with potential anti-cancer activity. We have pursued novel structure-based drug design strategies and identified a new binding mode for celecoxib and its derivatives binding with PDK1. This new binding mode provides a valuable basis for rational design of potent PDK1 inhibitors. In order to understand the structure-activity relationship of indolinone-based PDK1 inhibitors, we have carried out a combined molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling study. The predictive ability of the developed 3D-QSAR models were validated using an external test set of compounds. An efficient strategy of the hierarchical virtual screening with increasing complexity was pursued to identify new hits against PDK1. Our approach uses a combination of ligand-based and structure-based virtual screening including shape-based filtering, rigid docking, and flexible docking. In addition, a more sophisticated molecular dynamics/molecular mechanics- Poisson-Boltzmann surface area (MD/MM-PBSA) analysis was used as the final filter in the virtual screening. Our screening strategy has led to the identification of a new PDK1 inhibitor. The anticancer activities of this compound have been confirmed by the anticancer activity assays of national cancer institute-developmental therapeutics program (NCI-DTP) using 60 cancer cell lines. The PDK1-inhibitor binding mode determined in this study may be valuable in future de novo drug design. The virtual screening approach tested and used in this study could also be applied to lead identification in other drug discovery efforts.

The majority of drugs are small organic molecules, so-called ligands, that influence biochemical processes by interacting with proteins. The understanding of how and why they interact and form complexes is therefore a key component for elucidating the mechanism of action of drugs. The research presented in this thesis is based on studies of acetylcholinesterase (AChE). AChE is an essential enzyme with the important function of terminating neurotransmission at cholinergic synapses. AChE is also the target of a range of biologically active molecules including drugs, pesticides, and poisons. Due to the molecular and the functional characteristics of the enzyme, it offers both challenges and possibilities for investigating protein-ligand interactions. In the thesis, complexes between AChE and drug-like ligands have been studied in detail by a combination of experimental techniques and theoretical methods. The studies provided insight into the non-covalent interactions formed between AChE and ligands, where non-classical CH∙∙∙Y hydrogen bonds (Y = O or arene) were found to be common and important. The non-classical hydrogen bonds were characterized by density functional theory calculations that revealed features that may provide unexplored possibilities in for example structure-based design. Moreover, the study of two enantiomeric inhibitors of AChE provided important insight into the structural basis of enthalpy-entropy compensation. As part of the research, available computational methods have been evaluated and new approaches have been developed. This resulted in a methodology that allowed detailed analysis of the AChE-ligand complexes. Moreover, the methodology also proved to be a useful tool in the refinement of X-ray crystallographic data. This was demonstrated by the determination of a prereaction conformation of the complex between the nerve-agent antidote HI-6 and AChE inhibited by the nerve agent sarin. The structure of the ternary complex constitutes an important contribution of relevance for the design of new and improved drugs for treatment of nerve-agent poisoning. The research presented in the thesis has contributed to the knowledge of AChE and also has implications for drug discovery and the understanding of biochemical processes in general.