Predição de estrutura terciária de proteínas com técnicas multiobjetivo no algoritmo de monte carlo
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2016-06-17
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Universidade Federal de Goiás
Resumo
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.
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ALMEIDA, A. B. Predição de estrutura terciária de proteínas com técnicas multiobjetivo no algoritmo de monte carlo. 2016. 129 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2016.