PSS-SQL: Protein Secondary Structure - Structured Query Language

Protein secondary structure describe protein construction in terms of regular spatial shapes, including alpha-helices, beta-strands, and loops, which protein amino acid chain can adopt in some of its regions. This information is supportive for protein classification, functional annotation, and 3D structure prediction. The relevance of this information and the scope of its practical applications cause the requirement for its effective storage and processing. Relational databases, widely-used in commercial systems in recent years, are one of the serious alternatives honed by years of experience, enriched with developed technologies, equipped with the declarative SQL query language, and accepted by the large community of programmers. Unfortunately, relational database management systems are not designed for efficient storage and processing of biological data, such as protein secondary structures. In this paper, we present a new search method implemented in the search engine of the PSS-SQL language. The PSS-SQL allows formulation of queries against a relational database in order to find proteins having secondary structures similar to the structural pattern specified by a user. In the paper, we will show how the search process can be accelerated by multiple scanning of the Segment Index and parallel implementation of the alignment procedure using multiple threads working on multiple-core CPUs.

In this paper, we present a novel indexing method called ProtDex to facilitate fast searching in 3-dimensional protein structure database. In ProtDex, we first build an index on the representative properties of all proteins in the database. When evaluating a query, with the help of the index, we filter out a small candidate list of proteins. Then, we can either directly report them, with their respective rankings, to the user, or do the expensive actual alignments on them upon user's request. Preliminary experimental results show that our solution is up to 16 times faster than the popular DALI method for database searching task (without actual alignments), while its overall accuracy is only slightly inferior to that of DALI. The software is available upon request by sending emails to the authors.

Drug Discovery Today, 2007

Motivation: One common task in structural biology is to assess the similarities and differences among protein structures. A variety of structure alignment algorithms and programs have been designed and implemented for this purpose. A major drawback with existing structure alignment programs is that they require a large amount of computational time, rendering them infeasible for pairwise alignments on large collections of structures. To overcome this drawback, a fragment alphabet learned from known structures has been introduced. The method, however, considers local similarity only, and therefore occasionally assigns high scores to structures that are similar only in local fragments. Method: We propose a novel approach that eliminates false positives, through the comparison of both local and remote similarity, with little compromise in speed. Two kinds of contact libraries (ContactLib) are introduced to fingerprint protein structures effectively and efficiently. Each contact group of the contact library consists of one local or two remote fragments and is represented by a concise vector. These vectors are then indexed and used to calculate a new combined hit-rate score to identify similar protein structures effectively and efficiently. Results: We tested our method on the high-quality protein structure subset of SCOP30 containing 3, 297 protein structures. For each protein structure of the subset, we retrieved its neighbor protein structures from the rest of the subset. The best area under the ROC curve, archived by ContactLib, is as high as 0.960. This is a significant improvement compared to 0.747, the best result achieved by FragBag. We also demonstrated that incorporating remote contact information is critical to consistently retrieve accurate neighbor protein structures for all-β query protein structures. Availability: 1 https

Searching for structural similarities of proteins has a central role in bioinformatics. Most tasks of bioinformatics depends on investigating the homologous protein's sequence or structure these tasks vary from predicting the protein structure to determine sites in protein structure where drug can be attached. Protein structure comparison problem is extremely important in many tasks. It can be used for determining function of protein, for clustering a given set of proteins by their structure, for assessment in protein fold prediction. Protein Structure Indexing using Suffix Array and Wavelet (PSISAW) is a hybrid approach that provides the ability to retrieve similarities of proteins based on their structures. Indexing the protein structure is one approach of searching for protein similarities. The suffix arrays are used to index protein structure and the wavelet is used to compress the indexed database. Compressing the indexed database is supposed to make the searching time fast...

Citeseer

Nucleic Acids Research, 2010

ProteinDBS v2.0 is a web server designed for efficient and accurate comparisons and searches of structurally similar proteins from a large-scale database. It provides two comparison methods, global-to-global and local-to-local, to facilitate the searches of protein structures or substructures. ProteinDBS v2.0 applies advanced feature extraction algorithms and scalable indexing techniques to achieve a high-running speed while preserving reasonably high precision of structural comparison. The experimental results show that our system is able to return results of global comparisons in seconds from a complete Protein Data Bank (PDB) database of 152 959 protein chains and that it takes much less time to complete local comparisons from a non-redundant database of 3276 proteins than other accurate comparison methods. ProteinDBS v2.0 supports query by PDB protein ID and by new structures uploaded by users. To our knowledge, this is the only search engine that can simultaneously support global and local comparisons. ProteinDBS v2.0 is a useful tool to investigate functional or evolutional relationships among proteins. Moreover, the common substructures identified by local comparison can be potentially used to assist the human curation process in discovering new domains or folds from the ever-growing protein structure databases. The system is hosted at

Nucleic Acids Research, 2004

SA-Search is a web tool that can be used to mine for protein structures and extract structural similarities. It is based on a hidden Markov model derived Structural Alphabet (SA) that allows the compression of threedimensional (3D) protein conformations into a one-dimensional (1D) representation using a limited number of prototype conformations. Using such a representation, classical methods developed for amino acid sequences can be employed. Currently, SA-Search permits the performance of fast 3D similarity searches such as the extraction of exact words using a suffix tree approach, and the search for fuzzy words viewed as a simple 1D sequence alignment problem. SA-Search is available at http://bioserv.rpbs. jussieu.fr/cgi-bin/SA-Search.

Bioinformatics, 2003

The expanding protein sequence and structure databases await methods allowing rapid similarity search. Geometric parameters-dihedral angle between two sequential peptide bond planes (V ) and radius of curvature (R) as they appear in pentapeptide fragments in polypeptide chains-are proposed for use in evaluating structural similarity in proteins (VeaR). The parabolic (empirical) function expressing the radius of curvature's dependence on the V -angle in model polypeptides is altered in real proteins in a form characteristic for a particular protein. This can be used as a criterion for judging similarity. Results: A structural comparison of proteins representing a wide spectrum of structures was assessed versus sequence similarity analysis based on the genetic semihomology algorithm. The term 'consensus structure', analogous to 'consensus sequence', was introduced for the serpine family.

We consider the problem of similarity searches on protein databases based on both sequence and structure information simultaneously. Our program extracts feature vectors from both the sequence and structure components of the proteins. These feature vectors are then combined and indexed using a novel multi-dimensional index structure. For a given query, we employ this index structure to find candidate matches from the database. We develop a new method for computing the statistical significance of these candidates. The candidates with high significance are then aligned to the query protein using the Smith-Waterman technique to find the optimal alignment. The experimental results show that our method can classify up to 97 % of the superfamilies and up to 100 % of the classes correctly according to the SCOP classification. Our method is up to 37 times faster than CTSS, a recent structure search technique, combined with Smith-Waterman technique for sequences.

International Journal of Biological Macromolecules, 2005

We have implemented a relational database comprising a representative dataset of amino acid sequences and their associated secondary structure. The representative amino acid sequences were selected according to the PDB_SELECT program by choosing proteins corresponding to protein crystal structure data deposited in the protein data bank that share less than 25% overall pair-wise sequence identity. The secondary structure was extracted from the protein data bank website. The information content in the database includes the protein description, PDB code, crystal structure resolution, total number of amino acid residues in the protein chain, amino acid sequence, secondary structure conformation and its summary. The database is freely accessible from the website mentioned below and is useful to query on any of the above fields. The database is particularly useful to quickly retrieve amino acid sequences that are compatible to any super-secondary structure conformation from several proteins simultaneously.