Real-Time Protein Tertiary Structure (3D) Retrievals and Classifications
http://ProteinDBS.rnet.missouri.edu

Protein fold is known to be an important clue of detecting possible biological functions. The study of the structure-to-function relationships usually relies on an effective protein structure retrieval and classification method. The task of protein structure retrieval compares a query structure and each known proteins from a database and returns the ones with high similarities. The classification of protein structures categorizes and annotates a newly-discovered protein to possible folds, which could be relevant to the functional properties. With efforts of Structural Genomics (SG) projects, a large amount of protein structures has been identified in recent years via the high-throughput structural determination techniques such as X-ray crystallography and nuclear magnetic resonance (NMR). In the future, more new structures could be solved. To meet the needs of retrieving and classifying these high-throughput protein data, the research activities of this project are designed to face four central challenges.

1) To compare globally similar 3D tertiary structures using content-based information retrieval (CBIR) and high-dimensional indexing techniques in real time.

2) To efficiently classify newly-discovered proteins into the fold hiereachy of the Structural Classification of Protein (SCOP) database based on the structural similarity.

3) To fast retrieve locally similar protein substructures with the non-contiguous structural core identifications in a large-scale protein database.

4) To fuse the retrieval and classification results from different structure cores and provide suggestions to assist the functional predictions.

The proposed system will be the first in the research community that allows a life science researcher or an educator to submit an unknown protein tertiary structure and ask, "What proteins in Protein Data Bank (PDB) have similar non-contiguous structure cores to the query protein?" or “Which fold of SCOP database maintains similar 3D structures to the query protein?”

• Status: Active
• Funding: University of Missouri-Columbia Research Council
• Members: Pin-Hao Chi Heather Nelson Bin Pang Grant Scott Chi-Ren Shyu

• Publications:
  Chi-Ren Shyu, Pin-Hao Chi, Grant Scott, and D. Xu. ProteinDBS - A content-based retrieval system for protein structure database, in Nucleic Acids Research, Vol. 32, July 2004; W572-W575
  
  Pin-Hao Chi, Grant Scott, and Chi-Ren Shyu. A fast protein structure retrieval system using image-based distance matrices and multidimensional index, in International Journal of Software Engineering and Knowledge Engineering, Vol. 15, No. 3 , Special Issue on Software and Knowledge Engineering Support in Bioinformatics 2005; 527-545
  
  Pin-Hao Chi, Grant Scott, and Chi-Ren Shyu. A fast protein structure retrieval system using image-based distance matrices and multidimensional index, in Proc. of IEEE Fourth Symposium on Bioinformatics and Bioengineering, Taichung, Taiwan 2004
  
  Pin-Hao Chi, Chi-Ren Shyu, and D. Xu. A fast SCOP fold classification system using content-based E-Predict algorithm, in BMC Bioinformatics, Vol. 7:362 2006
  
  Pin-Hao Chi, and Chi-Ren Shyu. Predicting Ranked SCOP Domains by Mining Associations of Visual Contents in Distance Matrices, in Proc. of The Fourth Asia Pacific Bioinformatics Conference, Taipei, Taiwan 2006; 49-58
  
  Pin-Hao Chi, Bin Pang, Dmitry Korkin, and Chi-Ren Shyu. Efficient SCOP fold classification and retrieval using index-based protein substructure alignments (IPSA), in Bioinformatics 2009; (to appear)
  
  

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