Bioinformatics Advance Access originally published online on February 4, 2007
Bioinformatics 2007 23(7):832-841; doi:10.1093/bioinformatics/btm022
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Assessment of the probabilities for evolutionary structural changes in protein folds
ksna 1,*1Institute of Mathematics and Computer Science, University of Latvia, Rainis boulevard 29, Riga LV-1459, Latvia and 2Bioinformatics Research Centre, Glasgow University, A416 Davidson Building, Glasgow G12 8QQ, UK
*To whom correspondence should be addressed.
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Abstract |
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Motivation: The evolution of protein sequences can be described by a stepwise process, where each step involves changes of a few amino acids. In a similar manner, the evolution of protein folds can be at least partially described by an analogous process, where each step involves comparatively simple changes affecting few secondary structure elements. A number of such evolution steps, justified by biologically confirmed examples, have previously been proposed by other researchers. However, unlike the situation with sequences, as far as we know there have been no attempts to estimate the comparative probabilities for different kinds of such structural changes.
Results: We have tried to assess the comparative probabilities for a number of known structural changes, and to relate the probabilities of such changes with the distance between protein sequences. We have formalized these structural changes using a topological representation of structures (TOPS), and have developed an algorithm for measuring structural distances that involve few evolutionary steps. The probabilities of structural changes then were estimated on the basis of all-against-all comparisons of the sequence and structure of protein domains from the CATH-95 representative set.
The results obtained are reasonably consistent for a number of different data subsets and permit the identification of several ‘most popular’ types of evolutionary changes in protein structure. The results also suggest that alterations in protein structure are more likely to occur when the sequence similarity is >10% (the average similarity being 
6% for the data sets employed in this study), and that the distribution of probabilities of structural changes is fairly uniform within the interval of 15–50% sequence similarity.
Availability: The algorithms have been implemented on the Windows operating system in C++ and using the Borland Visual Component Library. The source code is available on request from the first author. The data sets used for this study (representative sets of protein domains, matrices of sequence similarities and structural distances) are available on http://bioinf.mii.lu.lv/epsrc_project/struct_ev.html.
Contact: juris.viksna{at}mii.lu.lv
Associate Editor: Anna Tramontano
Received on October 10, 2006; revised on January 18, 2007; accepted on January 21, 2007
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