NDLI: Prediction of functional sites by analysis of sequence and structure conservation.

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Prediction of functional sites by analysis of sequence and structure conservation.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Panchenko, Anna R. Kondrashov, Fyodor Bryant, Stephen
Description	Country affiliation: United States Author Affiliation: Panchenko AR ( Computational Biology Branch, NCBI, Bldg. 38A, Rm. 8N805, NIH, Bethesda, MD 20894, USA. panch@ncbi.nlm.nih.gov)
Abstract	We present a method for prediction of functional sites in a set of aligned protein sequences. The method selects sites which are both well conserved and clustered together in space, as inferred from the 3D structures of proteins included in the alignment. We tested the method using 86 alignments from the NCBI CDD database, where the sites of experimentally determined ligand and/or macromolecular interactions are annotated. In agreement with earlier investigations, we found that functional site predictions are most successful when overall background sequence conservation is low, such that sites under evolutionary constraint become apparent. In addition, we found that averaging of conservation values across spatially clustered sites improves predictions under certain conditions: that is, when overall conservation is relatively high and when the site in question involves a large macromolecular binding interface. Under these conditions it is better to look for clusters of conserved sites than to look for particular conserved sites.
ISSN	09618368
e-ISSN	1469896X
Journal	Protein Science
Issue Number	4
Volume Number	13
Language	English
Publisher	Wiley-Blackwell (on behalf of The Protein Society)
Publisher Date	2004-04-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Algorithms Proteins Chemistry Sequence Alignment Structural Homology, Protein Amino Acid Sequence Binding Sites Computational Biology Databases, Protein Protein Folding Protein Structure, Tertiary Research Support, U.s. Gov't, P.h.s. Discipline Biochemistry
Content Type	Text
Resource Type	Article
Subject	Medicine Molecular Biology Biochemistry

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