Discovering sequence-structure patterns in proteins with variable secondary structure

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Abstract

Proteins that share a similar function often exhibit conserved sequence patterns. Sequence patterns help to classify proteins into families where the exact function may or may not be known. Research has shown that these domain signatures often exhibit specific three-dimensional structures. We have previously shown that sequence patterns combined with structural information, in general, have superior discrimination ability than those derived without structural information. However in some cases, divergent backbone configurations and/or variable secondary structure in otherwise well-aligned proteins make identification of conserved regions of sequence and structure problematic. In this paper, we describe improvements in our method of designing biologically meaningful sequence-structure patterns (SSPs) starting from a seed sequence pattern from any of the existing sequence pattern databases. Improved pattern precision is achieved by including conserved residues from coil regions that are not readily apparent from examination of multiple sequence alignments alone. Pattern recall is improved by systematically comparing the structure of all known true family members and to include all the allowable variations in the pattern residues. © Springer-Verlag Berlin Heidelberg 2006.

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APA

Milledge, T., Zheng, G., & Narasimhan, G. (2006). Discovering sequence-structure patterns in proteins with variable secondary structure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3992 LNCS-II, pp. 702–709). Springer Verlag. https://doi.org/10.1007/11758525_95

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