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Erschienen in:
2014 | OriginalPaper | Buchkapitel
A Novel Particle Swarm-Based Approach for 3D Motif Matching and Protein Structure Classification
verfasst von : Hazem Radwan Ahmed, Janice Glasgow
Erschienen in: Advances in Artificial Intelligence
Verlag: Springer International Publishing
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This paper investigates the applicability of Particle Swarm Optimization (PSO) to motif matching in protein structures, which can help in protein structure classification and function annotation. A 3D motif is a spatial, local pattern in a protein structure important for its function. In this study, the problem of 3D motif matching is formulated as an optimization task with an objective function of minimizing the least Root Mean Square Deviation (
l
RMSD) between the query motif and target structures. Evaluation results on two protein datasets demonstrate the ability of the proposed approach on locating the true query motif of
all
66 target proteins almost always (9 and 8 times, respectively, on average, out of 10 trials per target). A large-scale application of motif matching is protein classification, where the proposed approach distinguished between the positive and negative examples by consistently ranking
all
positive examples at the very top of the search results.