Predição de estrutura terciária de proteínas com técnicas multiobjetivo no algoritmo de monte carlo

• Autor(a) principal: Almeida, Alexandre Barbosa de
• Data de Publicação: 2016
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• dARK ID: ark:/38995/00130000073tj
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/5872
• topic: Predição da estrutura terciária de proteínas; Otimização multiobjetivo; Monte carlo metropolis; Monte carlo com dominância; Protein tertiary structure prediction; Multi-objective optimization; Monte carlo metropolis; Monte carlo with dominance; CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO

Proteins are vital for the biological functions of all living beings on Earth. However, they only have an active biological function in their native structure, which is a state of minimum energy. Therefore, protein functionality depends almost exclusively on the size and shape of its native conformation. However, less than 1% of all known proteins in the world has its structure solved. In this way, various methods for determining protein structures have been proposed, either in vitro or in silico experiments. This work proposes a new in silico method called Monte Carlo with Dominance, which addresses the problem of protein structure prediction from the point of view of ab initio and multi-objective optimization, considering both protein energetic and structural aspects. The software GROMACS was used for the ab initio treatment to perform Molecular Dynamics simulations, while the framework ProtPred-GROMACS (2PG) was used for the multi-objective optimization problem, employing genetic algorithms techniques as heuristic solutions. Monte Carlo with Dominance, in this sense, is like a variant of the traditional Monte Carlo Metropolis method. The aim is to check if protein tertiary structure prediction is improved when structural aspects are taken into account. The energy criterion of Metropolis and energy and structural criteria of Dominance were compared using RMSD calculation between the predicted and native structures. It was found that Monte Carlo with Dominance obtained better solutions for two of three proteins analyzed, reaching a difference about 53% in relation to the prediction by Metropolis.