|
※ INTRODUCTION:
As a special class
of post-translational modifications (PTMs), numerous proteins
could be covalently modified by a variety of lipids, including
myristate (C14), palmitate (C16), farnesyl (C15), geranylgeranyl
(C20) and glycosylphosphatidylinositol (GPI), etc (Casey,
1995; Nadolski
and Linder, 2007; Resh,
2006). Although most of lipid modifications are irreversible,
protein S-palmitoylation,
also called as thioacylation or S-acylation, could reversibly
attach 16-carbon saturated fatty acids to specific cysteine
residues in protein substrates through thioester linkages (Bijlmakers
and Marsh, 2003; Dietrich
and Ungermann, 2004; el-Husseini
Ael and Bredt, 2002; Greaves
and Chamberlain, 2007; Linder
and Deschenes, 2007; Nadolski
and Linder, 2007; Resh,
2006; Resh,
2006; Roth,
et al., 2006; Smotrys
and Linder, 2004; Wan,
et al., 2007). Palmitoylation will enhance the surface
hydrophobicity and membrane affinity of protein substrates,
and play important roles in modulating proteins' trafficking
(Draper,
et al., 2007; Linder
and Deschenes, 2007), stability (Linder
and Deschenes, 2007), and sorting (Greaves
and Chamberlain, 2007), etc. Also, protein palmitoylation
has been involved in numerous cellular processes, including
signaling (Casey,
1995; Kurayoshi,
et al., 2007; Resh,
2006), apoptosis (Chakrabandhu,
et al., 2007; Feig,
et al., 2007), and neuronal transmission (Roth,
et al., 2006; Stowers
and Isacoff, 2007), etc. Although many efforts have
been made in this field, the molecular mechanism underlying
protein palmitoylation still remain to be inexplicit.
In this work, we updated
our previous CSS-Palm 1.0 (Zhou,
et al., 2006) into version 2.0.
We manually collected the experimentally verified palmitoylation
sites from scientific literature. The non-redundant training
data contained 263 palmitoylation sites from 109 distinct proteins.
Then an improved version of CSS algorithm was deployed. The
leave-one-out validation and 4-, 6-, 8-, 10-fold cross-validations
were calculated to evaluate the prediction performance and system
robustness of CSS-Palm 2.0.
Again, the prediction performance was also tested on an additional
data set not included in the training data set, with 53 palmitoylation
sites in 26 proteins. By comparison with our previous CSS-Palm1.0
and NBA-Palm 1.0 (Xue,
et al., 2006; Zhou,
et al., 2006), the performance of CSS-Palm 2.0 was
greatly improved. Finally, the
CSS-Palm 2.0 was implemented in JAVA 1.4.2 with high speed.
The CSS-Palm 2.0 could predict out potential palmitoylation
sites for ~1,000 proteins (with an average length of ~1000aa)
within five minutes. Taken together, we proposed that the CSS-Palm
2.0 will be a great help for experimentalists. The CSS-Palm
2.0 is freely available at: http://bioinformatics.lcd-ustc.org/css_palm.
This website is free and open to all
users and there is no login requirement.
|
 |
