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Doctoral Thesis
DOI
https://doi.org/10.11606/T.46.2017.tde-28112017-141755
Document
Author
Full name
Erika Piccirillo
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2017
Supervisor
Committee
Amaral, Antonia Tavares do (President)
Baader, Josef Wilhelm
Farah, Chuck Shaker
Ferreira, Elizabeth Igne
Guido, Rafael Victório Carvalho
Title in Portuguese
Busca virtual de inibidores de proteases dos vírus da dengue e da febre aftosa: construção de bancos de dados, simulações de dinâmica molecular e validação experimental
Keywords in Portuguese
Bancos de dados
Busca virtual
Dengue
Dinâmica molecular
Febre aftosa
Inibidores de proteases
Abstract in Portuguese
A Dengue e a Febre Aftosa são infecções virais que ocorrem tanto no Brasil como no mundo, apresentando enorme impacto socioeconômico. As proteases virais são reconhecidas como alvos de grande interesse para o planejamento de antivirais, devido ao seu papel fundamental no ciclo de vida de muitos vírus, incluindo-se os flavivirus (vírus da Dengue DENV) e os picornavirus (vírus da Febre Aftosa FA). Com o objetivo de buscar e identificar novos inibidores de proteases virais (da NS2B/NS3pro do DENV ou da Lbpro do vírus da FA) propusemos modelos de busca virtual, incluindo diferentes filtros de seleção (ex. farmacofórico, drug-like, similaridade e ancoramento) aplicados, sequencialmente, a bancos de dados de compostos comerciais (280x103 a 23x106 compostos). A seleção final dos compostos foi sempre feita por inspeção visual. Para NS2B/NS3pro do DENV, construíram-se quatro modelos de busca virtual (Modelo I-DENV a Modelo IV-DENV). O primeiro foi construído, baseando-se na estrutura cristalográfica ligada a um inibidor peptidomimético, e aplicado ao banco ZINC. Ao final, dez compostos foram comprados e submetidos a testes de inibição enzimática, frente à NS2B/NS3pro, para validação experimental deste modelo. Dois compostos mostraram alguma atividade inibitória (IC50 150 - 300 µM). Visando-se melhorar estes resultados, a flexibilidade da NS2B/NS3pro foi incluída, usando simulações de dinâmica molecular (DM), e um novo banco de dados construído (ZINC-Curated). Através de uma análise extensiva do banco ZINC-Curated, usando ferramentas estatísticas/quimiométricas, confirmou-se que este foi enriquecido com compostos com características de fármacos. Outros três modelos de busca virtual foram construídos incluindo-se diferentes informações obtidas nas simulações de DM. O modelo II-DENV foi feito usando ancoramento e aplicado ao banco ZINC-Curated, selecionando dezesseis compostos. Nenhum deles apresentou atividade inibitória significativa frente à NS2B/NS3pro do DENV. Os modelos III-DENV e IV-DENV utilizaram modelos farmacofóricos, que tiveram seus desempenhos previamente avaliados usando dados de literatura, e foram aplicados aos bancos NCI e ZINC-Curated, respectivamente. O modelo III-DENV selecionou quinze compostos, tendo quatro deles apresentado atividade inibitória (IC50 30 - 100 µM). O modelo IV-DENV selecionou dezoito compostos, sendo quatro ativos frente a esta protease (IC50 4 - 90 µM), representando uma taxa de acerto de ~22 %. Ainda, uma série de treze análogos estruturais do composto mais ativo foi construída, sendo três deles também ativos. Portanto, as modificações incluídas na busca virtual permitiram melhorar, significativamente, os resultados obtidos. Para Lbpro do vírus da FA, construíram-se dois modelos de busca virtual (Modelos I-FA e II-FA). O primeiro foi construído usando sua estrutura cristalográfica, sem ligantes, e uma série in house de potenciais inibidores covalentes. Seis compostos foram selecionados e testados frente à Lbpro, tendo dois deles baixa atividade inibitória (IC50 300 - 600 µM). A partir da disponibilidade da estrutura da Lbpro com ligante, o modelo IIFA foi construído e aplicado ao banco ZINC-Curated, selecionando quinze compostos. Estes foram adquiridos e testados frente à Lbpro, não apresentando atividade inibitória significativa. Assim, as modificações incluídas ainda não foram suficientes para selecionar inibidores mais potentes. No entanto, estes modelos/resultados contribuíram para o entendimento da(s) interação(ões) no sítio ativo da Lbpro.
Title in English
Virtual screening for protease inhibitors of dengue and foot-and-mouth disease virus: database building, molecular dynamics simulations and experimental validation
Keywords in English
Database
Dengue
Foot-and-mouth disease
Molecular dynamics
Protease inhibitors
Virtual screening
Abstract in English
Dengue and Food-and-mouth disease are viral infections that occur in Brazil and in the world, causing a huge socioeconomic impact. Viral proteases are recognized as targets for antiviral design, because they are crucial for the life cycle of many viruses, such as flavivirus (Dengue virus DENV) and picornavirus (Food-and-mouth disease virus FMDV). In order to discovery novel inhibitors of viral proteases (of NS2B/NS3pro of DENV or of Lbpro of FMDV) virtual screening models were proposed comprising a sequence of different filters (e.g. pharmacophore, drug-like, similarity and docking) applied to databases of commercial compounds (280x103 to 23x106 compounds). In all models, the final selection of compounds was always done by visual inspection. For DENV NS2B/NS3pro, four virtual screening models were proposed (Model I-DENV to Model IV-DENV). Model I-DENV was built, based on the crystal structure bound to a peptidemimetic inhibitor, and applied to ZINC database. Finally, ten compounds were purchased and submitted to enzymatic assays against this protease to the experimental validation of this model. Two compounds showed some inhibitory activity (IC50 150 - 300 µM). In order to improve these results, NS2B/NS3pro flexibility was included, using molecular dynamics (MD) simulations, and a novel database was built (ZINC-Curated). Throughout an exhaustively analysis of ZINC-Curated, using statistical/chemometrics tools, we confirmed that this new database was enriched with drug like compounds. Other three virtual screening models were built including different information from MD simulations. Model II-DENV was built using docking and applied to the ZINC-Curated database, selecting sixteen compounds. None of them showed a significant inhibitory activity against DENV NS2B/NS3pro. Models III-DENV and IV-DENV were built using pharmacophore models, which have their performance previously evaluated using literature data, and applied to NCI and ZINC-Curated databases, respectively. Model III-DENV selected fifteen compounds, showing four of them inhibitory activity (IC50 30 - 100 µM). Model IV-DENV selected eighteen compounds. Four of them were active against this protease (IC50 4 - 90 µM), representing a hit rate of ~22 %. Moreover, a set of thirteen structural analogues of the most active compound were built, being three of them also active. Thus, the modifications done in the virtual screening procedure really improved our results. For FMDV Lbpro, two virtual screening models were built (Models I-FMDV and II-FMDV). The first one was based on the crystal structure, without ligands, and used a set of in house potential covalent inhibitors. Six of the in house compounds were selected and tested against this protease. Two of them showed a weak inhibitory activity (IC50 300 - 600 µM). Later on, the Lbpro bound with ligands was available being therefore used to build another model. Model II FMDV was applied to the ZINC-Curated database, selecting fifteen compounds that were purchased and also tested against the target protease. But none of them showed a significant inhibition. Thus, the incorporated changes were not enough to retrieve active compounds. However, these models/results contributed to better understand Lbpro binding site interactions
 
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Publishing Date
2017-12-20
 
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