Identification of sequence-dependent DNA features correlating to activity of DNA sites interacting with proteins

Motivation: The commonly, accepted statistical mechanical theory is now mul tiply, confirmed by using the weight matrix methods successfully recognizin g DNA sites binding regulatory, proteins in prokaryotes. Nevertheless, the recent evaluation of weight matrix methods application for transcription fa ctor binding site recognition in eukaryotes has unexpectedly revealed their the matrix scores correlate better ro each other than to the activity of D NA sites interacting with proteins. This observation points out that molecu lar mechanisms of DNA/protein recognition ave more complicated in eukaryote s than in prokaryotes. As the extra events in eukaryotes, the following pro cesses may be considered: (i) competition between the proteins and nucleoso me core particle for DNA sites binding these proteins and (ii) interaction between two synergetic/antagonist proteins recognizing a composed element c ompiled from two DNA sites binding these proteins. That is why identificati on of the sequence-dependent DNA features correlating with affinity magnitu des of DNA sites interacting with a protein can pinpoint the molecular even s limiting this protein/DNA recognition machinery. Results: An approach for predicting site activity based on its primary nucl eotide sequence has been developed. The approach is realized in the compute r system ACTIVITY, containing the databases on sire activity, and on confor mational and physicochemical DNA/RNA parameters. By using the system ACTIVI TY, an analysis of some sites was provided and the methods for predicting s ite activity were constructed. The methods developed are in good agreement with the experimental data.