This problem under the assumption that the structures under comparison are
This problem under the assumption that the structures under comparison are considered as rigid bodies. However, proteins are flexible entities often undergoing movements that alter the positions of domains or subdomains with respect to each other. Such movements can PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/25609842 impede the identification of structural equivalences when rigid aligners are used. Results: We introduce a new method called purchase Mangafodipir (trisodium) RAPIDO (Rapid Alignment of Proteins in terms of Domains) for the three-dimensional alignment of protein structures in the presence of conformational changes. The flexible aligner is coupled to a genetic algorithm for the identification of structurally conserved regions. RAPIDO is capable of aligning protein structures in the presence of large conformational changes. Structurally conserved regions are reliably detected even if they are discontinuous in sequence but continuous in space and can be used for superpositions revealing subtle differences. Conclusion: RAPIDO is more sensitive than other flexible aligners when applied to cases of closely homologues proteins undergoing large conformational changes. When applied to a set of kinase structures it is able to detect similarities that are missed by other alignment algorithms. The algorithm is sufficiently fast to be applied to the comparison of large sets of protein structures.BackgroundWhen comparing structures of related proteins with different amino-acid sequences it is necessary to first perform a structural alignment, i.e. to define an equivalence map between the residues in the different structures based on their relative position in space. Once structures have been successfully aligned in three dimensions, similarities and differences can be studied in order to understand function and behaviour of the molecules under consideration.It has been demonstrated that the problem of defining an equivalence map for residues in protein structures has no unique optimal solution [1] and that it remains computationally hard [2-4] even when it is described by a well defined optimization function. Nevertheless, many tools have been created for the pairwise and the multiple alignment of protein structures using different heuristics to produce results on acceptable time-scales (for comprehensive reviews see [5-7]).Page 1 of(page number not for citation purposes)BMC Bioinformatics 2008, 9:http://www.biomedcentral.com/1471-2105/9/Alignment methods can be classified based on whether the two structures to be aligned are considered as rigid bodies or whether internal flexibility between domains or subdomains is accommodated in the alignment. Methods belonging to the group of ‘rigid aligners’ are SSAP [8], CE [9], ProSup [10], KENOBI [11], MAMMOTH [12], TOPOFIT [13], TM-align [14], SABERTOOTH [15] and TetraDA [16]. DALI [17] allows for limited molecular flexibility through the use of an elasticity term in its similarity function, but nevertheless is considered to be a rigid aligner [18]. The group of rigid aligners also includes algorithms like VAST [19] and SSM [20] that, in order to produce alignments rapidly, first identify correspondences between secondary structure elements (SSE) and then extend the alignment to the residue level. Several rigid aligners have been extended for addressing the multiple alignment problem (CE-MC [21] and MAMMOTH-Mult [22]). As it is well known, protein molecules are flexible entities with internal movements ranging from the displacement of individual atoms to movements of entire domai.
