Constraint-based evolutionary local search for protein structures with secondary motifs
Author(s)
Shatabda, Swakkhar
Newton, MA Hakim
Sattar, Abdul
Griffith University Author(s)
Year published
2014
Metadata
Show full item recordAbstract
On-lattice protein structure prediction with empirical energy minimisation has drawn significant research effort. However, energy minimisation with free-modelling not necessarily leads to structures that are similar to the native structure of the given protein. In this paper, we show that energy minimisation has a positive correlation with structural similarity measures if we consider secondary motifs. We then present a constraint-based evolutionary local search framework for on-lattice protein structure prediction using secondary structural information. We approximate secondary motifs such as a-helix and ߭strands on the ...
View more >On-lattice protein structure prediction with empirical energy minimisation has drawn significant research effort. However, energy minimisation with free-modelling not necessarily leads to structures that are similar to the native structure of the given protein. In this paper, we show that energy minimisation has a positive correlation with structural similarity measures if we consider secondary motifs. We then present a constraint-based evolutionary local search framework for on-lattice protein structure prediction using secondary structural information. We approximate secondary motifs such as a-helix and ߭strands on the lattice and propose a set of neighbourhood generation operators that respect those motifs. Our experimental results show significant improvement over the state-of-the-art methods in terms of similarity with the native structures determined by laboratory methods.
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View more >On-lattice protein structure prediction with empirical energy minimisation has drawn significant research effort. However, energy minimisation with free-modelling not necessarily leads to structures that are similar to the native structure of the given protein. In this paper, we show that energy minimisation has a positive correlation with structural similarity measures if we consider secondary motifs. We then present a constraint-based evolutionary local search framework for on-lattice protein structure prediction using secondary structural information. We approximate secondary motifs such as a-helix and ߭strands on the lattice and propose a set of neighbourhood generation operators that respect those motifs. Our experimental results show significant improvement over the state-of-the-art methods in terms of similarity with the native structures determined by laboratory methods.
View less >
Conference Title
PRICAI 2014: TRENDS IN ARTIFICIAL INTELLIGENCE
Volume
8862
Publisher URI
Subject
Artificial intelligence not elsewhere classified