Using estimative reaction free energy to predict splice sites and their flanking competitors.
A crucial part in the gene structure prediction is to identify the accurate splice sites, not only constitutive but also alternative ones. Here, we use the maximum information principle (MIP) to analyze the conservative segments around splice sites. According to the MIP, a reaction free energy (RFE) expression is deduced, which can be employed to estimate the free energy change during splicing reaction involving a donor or acceptor site. The expression contains not only the background probability factors, but also all kinds of dependencies among both adjacent and non-adjacent bases. We apply the RFE expression to recognize splice sites and their flanking competitors in human genes, the results show high sensitivity and specificity, so the RFE expression accords well with the splicing reaction process. Moreover, the RFE expression is better than previous methods for predicting competitors of splice sites, and it outperforms the reaction free energy subtraction (RFES), that implies RFE competition between a given splice site and its flanking competitor may not be an only primary factor for alternative splice site selection. The work is helpful to not only the understanding of splicing reaction from its relation to MIP, but also the research on computational recognition of splicing sites and alternative splice events.
Jin
Hong-Ying
HY
Laboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot 010021, China.
Luo
Liao-Fu
LF
Zhang
Li-Rong
LR