Abstract
Computing alignments of proteins based on their structure is one of the fundamental tasks of bioinformatics. It is crucial in all kinds of comparative analysis as well as in performing evolutionary and functional classification. Whereas determination of sequence relationships is well founded in statistical models, there is still considerable uncertainty over how to describe geometric relationships between proteins. Continuous growth of structural databases calls for fast and reliable algorithmic methods, enabling one to effectively compute alignments of pairs and larger sets of protein molecules. Although such methodologies have been developed over the past two decades, there exist so-called “difficult similarities” which may include repeats, insertions or deletions, permutations, and conformational changes. A brief overview of existing methodologies with emphasis on different approaches to decomposition of structures into smaller fragments is followed by a presentation of a formalism of local descriptors of protein structures. A formal definition of the problem of computing optimal alignments accommodating aforementioned difficulties is presented along with an analysis of the computational complexity of its important variants. Examples of “difficult similarities” and practical aspects of protein structure comparison are discussed.
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Daniluk, P., Lesyng, B. (2014). Theoretical and Computational Aspects of Protein Structural Alignment. In: Liwo, A. (eds) Computational Methods to Study the Structure and Dynamics of Biomolecules and Biomolecular Processes. Springer Series in Bio-/Neuroinformatics, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28554-7_17
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