Programa de Pós-graduação em Inovação Farmacêutica em Rede
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Navegando Programa de Pós-graduação em Inovação Farmacêutica em Rede por Por Orientador "Andrade, Carolina Horta"
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Item Estratégias computacionais como métodos alternativos para avaliação da sensibilização cutânea(Universidade Federal de Goiás, 2017-05-12) Alves, Vinícius de Medeiros; Tropsha, Alexander; Muratov, Eugene; http://lattes.cnpq.br/9372290911831306; Andrade, Carolina Horta; http://lattes.cnpq.br/2018317447324228; Andrade, Carolina Horta; Oliveira, Gisele Augusto Rodrigues de; Ferreira, Márcia Miguel Castro; Costa, Fernando Batista da; Nascimento, Paulo Gustavo Barboni DantasIntroduction: Skin sensitization is a major environmental and human health hazard. Although many chemicals have been evaluated in humans, there have been no efforts to model these data to date. Skin sensitization is commonly evaluated using structural alerts. However, there has been a growing concern that alerts disproportionally flag too many chemicals as toxic, which questions their reliability as toxicity markers. The main goal of this thesis was to develop and apply new cheminformatics methods to predict skin sensitization of chemical compounds that lack experimental data. Methodology: It has been compiled, curated, analyzed, and compared the available human data and the murine (performed in mice) animal model data, named LLNA (local lymph node assay). Using these data, it was developed reliable computational models and applied them for virtual screening of chemical libraries to identify putative skin sensitizers. It was developed a freely accessible web-based application for the identification of potential skin sensitizers. In addition, it was demonstrated that contrary to the common perception of QSAR models as “black boxes” they can be used to identify statistically significant chemical substructures (QSAR-based alerts) that influence toxicity. Results and discussion: The overall concordance between murine LLNA and human skin sensitization responses for a set of 135 unique chemicals was low (R = 28-43%), although several chemical classes had high concordance. We have succeeded to develop predictive QSAR models of all available human data with the external correct classification rate of 71%. A consensus model integrating concordant QSAR predictions and LLNA results afforded a higher correct classification rate of 82% but at the expense of the reduced external dataset coverage (52 %). We used the developed QSAR models for virtual screening of CosIng database and identified 1,061 putative skin sensitizers; for seventeen of these compounds, we found published evidence of their skin sensitization effects. The developed Pred-Skin web app (http://www.labmol.com.br/predskin/) is based on binary QSAR models of human (109 compounds) and LLNA (515 compounds) data with good external correct classification rate (70-81% and 72-84%, respectively). It is also included a multiclass potency model based on LLNA data (accuracy ranging between 73-76%). Conclusions: Models reported herein provide more accurate alternative to LLNA testing for human skin sensitization assessment across diverse chemical data. In addition, they can also be used to guide the structural optimization of toxic compounds to reduce their skin sensitization potential. The Pred-Skin web app is a fast, reliable, and user-friendly tool for early assessment of chemically-induced skin sensitization. A new approach that synergistically integrates structural alerts and rigorously validated QSAR models for a more transparent and accurate safety assessment of new chemicals was also proposed.Item Planejamento, síntese guiada por QSAR, avaliação biológica e modelagem molecular de chalconas com atividade antituberculose(Universidade Federal de Goiás, 2017-04-06) Gomes, Marcelo do Nascimento; Oliveira, Guilherme Roberto de; http://lattes.cnpq.br/8239498431579015; Andrade, Carolina Horta; http://lattes.cnpq.br/2018317447324228; Andrade, Carolina Horta; Emery, Flávio da Silva; Lião, Luciano Morais; Romeiro, Luiz Antônio Soares; Oliveira, Valéria deIn view of the current panorama of tuberculosis (TB) pandemic in the world, aggravated by co-infection with the HIV virus and the emergence of resistant strains of Mycobacterium tuberculosis (M. tb.), The research and discovery of new Anti-TB drugs. The present work aimed at the planning, synthesis and biological evaluation of new compounds with anti-TB activity, candidates for TB drugs. Structure and activity relationship (SAR) studies were developed using Matched Pair Molecular Analysis (MMPA) and binary models of quantitative relations between structure and activity (QSAR) using a combination of molecular fingerprints and machine learning methods. Bioisosteric replacement were proposed to plan new aryl and heteroaryl chalcones using the information obtained from SAR and QSAR analyses. Thirty-three compounds were selected by the consensus QSAR model for the synthesis. These compounds were synthesized and their structures confirmed by infrared (IR), hydrogen nuclear magnetic resonance (1H NMR) and carbon (13C NMR) spectroscopic methods and mass spectrometry (MS). Compounds which showed high purity (≥95% in HPLC) were tested against strains of M. tb. H37Rv (sensitive) and resistant to rifampicin (RMP) or isoniazid (INH). In addition, they were also tested in mammalian cell cytotoxicity assays and activity spectrum. We identified 22 hits with anti-TB activity, with minimum inhibitory concentration (MIC) in M. tb. H37Rv in aerobic conditions (MABA) <10 μM. Of these, 12 compounds exhibited potent M. tb. replication activity on nanomolar scale, with MIC values in MABA <1 μM and in micromolar under anaerobic conditions (LORA) with MIC <10 μM. In addition, these compounds also showed potent inhibitory activity against monoresistant strains at RMP or INH (MIC <1 μM and MIC <10 μM, respectively). Hits also demonstrated low cytotoxicity in mammalian cells (Vero cells) and selectivity index between 11 and 545 for M. tb. The same selectivity was verified in the activity spectrum assay against four commensal strains and six strains of non-tuberculosis mycobacteria (NTMs), in which the compounds presented broad spectrum against the NTMs strains. These results demonstrated that the combination of in silico strategies for the design of aryl and heteroaryl chalcones was efficient in identifying new compounds that proved to be potent, selective and promising candidates for prototypes of anti-TB drugs.