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Master's Dissertation
DOI
https://doi.org/10.11606/D.76.2017.tde-15092017-084415
Document
Author
Full name
Mariana Lopes Garcia
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2017
Supervisor
Committee
Guido, Rafael Victório Carvalho (President)
Cordeiro, Artur Torres
Trossini, Gustavo Henrique Goulart
Title in Portuguese
Estudos computacionais da enzima N-miristoiltransferase de Plasmodium falciparum e seus inibidores como candidatos a agentes antimaláricos
Keywords in Portuguese
Malária
N-Miristoiltransferase
QSAR
Abstract in Portuguese
A malária é uma doença infecciosa causada pelos parasitas do gênero Plasmodium e transmitida pelo mosquito Anopheles spp. Devido ao surgimento de casos de resistência aos fármacos disponíveis novos alvos e candidatos a fármacos são necessários. Recentemente, a enzima N-miristoiltransferase (NMT) foi confirmada como essencial para o parasita e validada como alvo terapêutico para o desenvolvimento de candidatos a fármacos antimaláricos. O objetivo desse trabalho foi identificar os determinantes moleculares responsáveis pela atividade inibitória de uma série de derivados benzotiofênicos frente à NMT. Nesse sentido, estudos de relação quantitativa estrutura-atividade (QSAR) 2D e 3D foram desenvolvidos para dois conjuntos de dados de derivados benzotiofênicos como inibidores da enzima do parasita (PfNMT) e a homóloga humana (HsNMT). Além disso, estudos de modelagem por homologia da PfNMT foram conduzidos. Os estudos de QSAR 2D foram desenvolvidos pelo método de Holograma QSAR (HQSAR). O modelo estrutural de PfNMT foi aplicado na construção dos modelos QSAR 3D CoMFA (Comparative Molecular Field Analysis) e CoMSIA (Comparative Molecular Similarity Index Analysis). Os estudos de QSAR 3D foram conduzidos com diferentes métodos de cálculo de carga parcial atômica (Gasteiger-Hückel, MMFF94 e AM1-BCC, CHELPG e Mulliken) e de alinhamento molecular (Máxima Subestrutura Comum, alinhamento flexível e baseada no alvo molecular). Os melhores modelos construídos pelos métodos de QSAR 2D e 3D foram robustos, internamente consistentes e com elevada capacidade de predição da atividade de novos compostos contra a PfNMT. Os mapas de contribuição e de contorno geraram informações importantes sobre a relação estrutura-atividade dos compostos. Os resultados permitiram a identificação das bases moleculares responsáveis pela atividade dos inibidores benzotiofênicos e são úteis para o planejamento de novos inibidores mais potentes e seletivos para a enzima do parasita.
Title in English
Computational studies on Plasmodium falciparum N-myristoyltransferase enzyme and its inhibitors as antimalarial drug candidates
Keywords in English
Malaria
N-Myristoyltransferase
QSAR
Abstract in English
Malaria is an infectious disease caused by protozoan parasites of the genus Plasmodium and transmitted by Anopheles spp. mosquitos. Due to the emerging resistance to current available drugs, great efforts for new molecular target and drugs are required. Recently, N-myristoyltransferase (NMT) was confirmed as an essential enzyme to malaria parasites and validated as a chemically tractable target for the development of new drug candidates against malaria. This work aimed to shed light on the molecular requirements underlying the inhibitory activity of benzothiophene derivatives against NMT. Therefore, 2D and 3D quantitative structure-activity relationship (QSAR) studies were developed for two datasets of benzothiophene derivatives as P. falciparum NMT (PfNMT) and the human homologue (HsNMT) inhibitors. Also, homology modeling studies for PfNMT were developed. The 2D QSAR studies were developed by the Hologram QSAR (HQSAR) method. The PfNMT structural model was applied in the construction of 3D QSAR models CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Index Analysis). Different molecular alignment (maximum common substructure, flexible alignment and structure based) and atomic partial charge calculation (Gasteiger-Hückel, MMFF94, AM1-BCC, CHELPG and Mulliken) methods were used to build the 3D QSAR models. The best models showed internal consistency and high predictive ability of biological activity against PfNMT. The contribution and contour maps gave important information about compounds structure-activity relationship. The results allowed the identification of the molecular requirements underlying the inhibitory activity and should be useful for the design of novel potent and selective PfNMT inhibitors as antimalarial drug candidates.
 
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Publishing Date
2017-09-22
 
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