Biology – Quantitative Biology – Biomolecules
Scientific paper
2007-11-07
BIOPHYSICS Vol. 3, pp. 75-84 (2007)
Biology
Quantitative Biology
Biomolecules
29 pages, 8 figures, 3 tables
Scientific paper
10.2142/biophysics.3.75
A method to search for local structural similarities in proteins at atomic resolution is presented. It is demonstrated that a huge amount of structural data can be handled within a reasonable CPU time by using a conventional relational database management system with appropriate indexing of geometric data. This method, which we call geometric indexing, can enumerate ligand binding sites that are structurally similar to sub-structures of a query protein among more than 160,000 possible candidates within a few hours of CPU time on an ordinary desktop computer. After detecting a set of high scoring ligand binding sites by the geometric indexing search, structural alignments at atomic resolution are constructed by iteratively applying the Hungarian algorithm, and the statistical significance of the final score is estimated from an empirical model based on a gamma distribution. Applications of this method to several protein structures clearly shows that significant similarities can be detected between local structures of non-homologous as well as homologous proteins.
Kinjo Akira R.
Nakamura Haruki
No associations
LandOfFree
Similarity search for local protein structures at atomic resolution by exploiting a database management system does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Similarity search for local protein structures at atomic resolution by exploiting a database management system, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Similarity search for local protein structures at atomic resolution by exploiting a database management system will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-502015