@article {3,
	title = {A novel method to compare protein structures using local descriptors.},
	journal = {BMC bioinformatics},
	volume = {12},
	year = {2011},
	month = {08/2011},
	pages = {344},
	abstract = {BACKGROUND: Protein structure comparison is one of the most widely performed tasks in bioinformatics. However, currently used methods have problems with the so-called "difficult similarities", including considerable shifts and distortions of structure, sequential swaps and circular permutations. There is a demand for efficient and automated systems capable of overcoming these difficulties, which may lead to the discovery of previously unknown structural relationships.

RESULTS: We present a novel method for protein structure comparison based on the formalism of local descriptors of protein structure - DEscriptor Defined Alignment (DEDAL). Local similarities identified by pairs of similar descriptors are extended into global structural alignments. We demonstrate the method{\textquoteright}s capability by aligning structures in difficult benchmark sets: curated alignments in the SISYPHUS database, as well as SISY and RIPC sets, including non-sequential and non-rigid-body alignments. On the most difficult RIPC set of sequence alignment pairs the method achieves an accuracy of 77\% (the second best method tested achieves 60\% accuracy).

CONCLUSIONS: DEDAL is fast enough to be used in whole proteome applications, and by lowering the threshold of detectable structure similarity it may shed additional light on molecular evolution processes. It is well suited to improving automatic classification of structure domains, helping analyze protein fold space, or to improving protein classification schemes. DEDAL is available online at http://bioexploratorium.pl/EP/DEDAL.},
	keywords = {Algorithms, Animals, Bacterial Proteins, Carrier Proteins, Computational Biology, GTP Phosphohydrolases, Humans, Models, Molecular, Proteins, Saposins, Structural Homology, Protein},
	issn = {1471-2105},
	doi = {10.1186/1471-2105-12-344},
	author = {Daniluk, Pawe{\l} and Lesyng, Bogdan}
}
@article {44,
	title = {CASP6 data processing and automatic evaluation at the protein structure prediction center.},
	journal = {Proteins},
	volume = {61 Suppl 7},
	year = {2005},
	month = {2005},
	pages = {19-23},
	abstract = {We present a short overview of the system governing data processing and automatic evaluation of predictions in CASP6, implemented at the Livermore Protein Structure Prediction Center. The system incorporates interrelated facilities for registering participants, collecting prediction targets from crystallographers and NMR spectroscopists and making them available to the CASP6 participants, accepting predictions and providing their preliminary evaluation, and finally, storing and visualizing results. We have automatically evaluated predictions submitted to CASP6 using criteria and methods developed over the successive CASP experiments. Also, we have tested a new evaluation technique based on non-rigid-body type superpositions. Approximately the same number of predictions has been submitted to CASP6 as to all previous CASPs combined, making navigation through and understanding of the data particularly challenging. To facilitate this, we have substantially modernized all data handling procedures, including implementation of a dedicated relational database. An overview of our redesigned website is also presented (http://predictioncenter.org/casp6/).},
	keywords = {Algorithms, Automation, Computational Biology, Crystallography, X-Ray, Internet, Magnetic Resonance Spectroscopy, Models, Molecular, Protein Conformation, Protein Folding, Protein Structure, Secondary, Protein Structure, Tertiary, Proteins, Proteomics, Software},
	issn = {1097-0134},
	doi = {10.1002/prot.20718},
	author = {Kryshtafovych, Andriy and Milostan, Maciej and Szajkowski, Lukasz and Daniluk, Pawe{\l} and Fidelis, Krzysztof}
}
