MULTI-OBJECTIVE EVOLUTIONARY APPROACH TO <i>AB INITIO</i> PROTEIN TERTIARY STRUCTURE PREDICTION

Lima, Telma Woerle de; Gabriel, Paulo Henrique Ribeiro; Delbem, Alexandre C. B.; Faccioli, Rodrigo Antonio; Silva, Ivan

doi:10.1142/9789812708779_0018

Cited by 4 publications

(14 citation statements)

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“…Neste trabalho, foram usados os parâmetros de campos de força do CHARMM e as funções de energia baseadas no TINKER [72,122]. Para o cálculo da área SASA, adaptou-se o código do STRIDE em nossa implementação.…”

Section: áRea De Acessibilidadeunclassified

“…Primeiramente, a Seção 5.1.1 descreve o algoritmo ProtPred [120,122,72,18], uma abordagem puramente ab initio. A Seção 5.2 propõe AEMTs para o problema PSP apresentando as etapas de desenvolvimento do método.…”

Section: Considerações Iniciaisunclassified

“…No contexto de PSP puramente ab initio, um conjunto de trabalhos tem mostrado que Algoritmos Evolutivos Multiobjetivos (AEMOs) podem contribuir significativamente [79,81,80,120,122,123,121,72,71,29,28,25,27,7,18,26]. A otimização multiobjetivo mostra que, além do espaço de busca (todas as combinações de valores possíveis das variáveis de um problema), há o espaço das funções objetivo.…”

Section: Introductionunclassified

“…Este trabalho busca avançar em relação ao projeto de um AEMO que gerou o método ProtPred [120,122,123,121,72,71,29,28,25,27,7,18,26]. O ProtPred, inclui uma abordagem mono-objetivo (mono-ProPred) e outra multi-objetiva (NSGA-ProtPred) baseada no AEMO denominado NSGA-II [122] (do inglês, Non-dominated Sorting Genetic Algorithm).…”

Section: Introductionunclassified

“…O ProtPred, inclui uma abordagem mono-objetivo (mono-ProPred) e outra multi-objetiva (NSGA-ProtPred) baseada no AEMO denominado NSGA-II [122] (do inglês, Non-dominated Sorting Genetic Algorithm). Em [152] foi proposto um novo AEMO, chamado Algoritmo Evolutivos Multiobjetivo por Tabelas (AEMT) que foi capaz de gerar soluções mais interessantes que o NSGA-II para o problema combinatório de projeto de redes de distribuição de energia elétrica [152].…”

Section: Introductionunclassified

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Algoritmo evolutivo de muitos objetivos para predição ab initio de estrutura de proteínas

Brasil¹

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Section: áRea De Acessibilidadeunclassified

Section: Considerações Iniciaisunclassified

Section: Introductionunclassified

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Algoritmo evolutivo de muitos objetivos para predição ab initio de estrutura de proteínas

Brasil¹

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Multiobjective evolutionary algorithm with many tables for purely ab initio protein structure prediction

2013

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This article focuses on the development of an approach for ab initio protein structure prediction (PSP) without using any earlier knowledge from similar protein structures, as fragment-based statistics or inference of secondary structures. Such an approach is called purely ab initio prediction. The article shows that well-designed multiobjective evolutionary algorithms can predict relevant protein structures in a purely ab initio way. One challenge for purely ab initio PSP is the prediction of structures with β-sheets. To work with such proteins, this research has also developed procedures to efficiently estimate hydrogen bond and solvation contribution energies. Considering van der Waals, electrostatic, hydrogen bond, and solvation contribution energies, the PSP is a problem with four energetic terms to be minimized. Each interaction energy term can be considered an objective of an optimization method. Combinatorial problems with four objectives have been considered too complex for the available multiobjective optimization (MOO) methods. The proposed approach, called "Multiobjective evolutionary algorithms with many tables" (MEAMT), can efficiently deal with four objectives through the combination thereof, performing a more adequate sampling of the objective space. Therefore, this method can better map the promising regions in this space, predicting structures in a purely ab initio way. In other words, MEAMT is an efficient optimization method for MOO, which explores simultaneously the search space as well as the objective space. MEAMT can predict structures with one or two domains with RMSDs comparable to values obtained by recently developed ab initio methods (GAPFCG , I-PAES, and Quark) that use different levels of earlier knowledge.

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A mono-objective evolutionary algorithm for Protein Structure Prediction in structural and energetic contexts

Faccioli

Silva

Bortot

et al. 2012

2012 IEEE Congress on Evolutionary Computation

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The Protein Structure Prediction (PSP) problem is concerned about the prediction of the native structure of a protein from its amino acid sequence. PSP is a challenging and computationally open problem. Therefore, several researches and methodologies have been developed for it. This paper presents the application of protpred-GROMACS, an evolutionary framework for PSP, in structural and energetic contexts. The performance of mono-objective algorithm was compared with other methodologies, such as multi-objective evolutionary algorithm, coarse grained monte carlo and replica exchange molecular dynamics.

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MULTI-OBJECTIVE EVOLUTIONARY APPROACH TO AB INITIO PROTEIN TERTIARY STRUCTURE PREDICTION

Cited by 4 publications

References 11 publications

Algoritmo evolutivo de muitos objetivos para predição ab initio de estrutura de proteínas

Algoritmo evolutivo de muitos objetivos para predição ab initio de estrutura de proteínas

Multiobjective evolutionary algorithm with many tables for purely ab initio protein structure prediction

A mono-objective evolutionary algorithm for Protein Structure Prediction in structural and energetic contexts

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