Modelagem molecular de quitosana e glifosato e análise de suas interações

• Autor(a) principal: Faria, Roberto Ribeiro
• Data de Publicação: 2019
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFU
• Texto Completo: https://repositorio.ufu.br/handle/123456789/26843; https://dx.doi.org/10.14393/ufu.te.2019.2271
• topic: Quitosana; Chitosan; Glifosato; Glyphosate; Campo de Força; Force Field; Simulação Computacional; Computational Simulation; CNPQ::CIENCIAS EXATAS E DA TERRA::QUIMICA::FISICO-QUIMICA::QUIMICA TEORICA

The glyphosate is the most consumed herbicide in the world and has threatening and harmful properties for living beings, because of its chronic toxicity and carcinogenicity. The proposal of remove glyphosate through chitosan in aqueous medium occurs due to the high biopolymer’s ability to chelate contaminants. This can be done computationally, simulating models representing real systems through the methodology of molecular dynamic (MD). However, for the MD simulations to describe the studied molecules with precision, a force field containing exact information about the atoms and their interactions is necessary. Taking this into consideration, the objectives of this thesis were to parameterize the OPLS-AA force field for the chitosan biopolymer and glyphosate herbicide, in order to test the performance of the parameterizations by simulating them in molecular systems by MD, compute the specific interaction groups between chitosan and glyphosate, and calculate the potential mean force (PMF) of their interactions. Here we present the final force field containing all the necessary parameters for the studied molecules and it can be designed for several simulations with GROMACS software. The simulations performed for chitosan produce equivalent results to another previously validated force field (Gromos53a6) and the analysis about the adsorption between chitosan and glyphosate are comparable to experimental results. The force field may therefore be used in several atomistic computational studies for chitosan and glyphosate.