| Summary: | 碩士 === 國立交通大學 === 生物資訊及系統生物研究所 === 105 === Epigenetics is a popular research topic in recent years, which explores gene expression without modifying DNA sequences. There are two research fields: DNA methylation and histone modifications. The SET domain of the histone lysine methyltransferases (HKMT) modifies lysines of the histone. A lot of studies have verified the important role of motifs in the SET domain. If we can develop an efficient algorithm to discover novel motifs or functional peptides, we can further understand the mechanism of histone lysine methylation.
The classical methods that identify functional peptides utilized the sequence alignment methods first and further verified those peptides using biological experiments. In this thesis, we propose a new method, SCMHKMT, based on a scoring card method (SCM) developed in our laboratory to discover novel functional peptides. We collected datasets and calculated the difference between HKMT and non-HKMT sequences in terms of the dipeptide score of SCM. Consequently, we used the SCMHKMT method to screen potential motifs of tripeptides which have high appearance probability and high propensity score. As a result, there were 17 functional tripeptides discovered in which GEE, PNN, WPN, and SCS have been reported in published papers. Using other motif prediction tools, DEE and KGE have also been identified, suggesting that these two peptides are highly potential functional peptides.
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