Open AccessThe VHSE-Based Prediction of Proteasomal Cleavage Sites
Author(s) -
Jiehong Xie,
Zhuwen Xu,
Shan Zhou,
Xianchao Pan,
Shaoxi Cai,
Yang Li,
Hu Mei
Publication year - 2013
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0074506
Subject(s) - cleavage (geology) , steric effects , principal component analysis , chemistry , in vitro , in vivo , support vector machine , upstream (networking) , computational biology , biological system , computer science , stereochemistry , biochemistry , biology , artificial intelligence , microbiology and biotechnology , paleontology , computer network , fracture (geology)
Prediction of proteasomal cleavage sites has been a focus of computational biology. Up to date, the predictive methods are mostly based on nonlinear classifiers and variables with little physicochemical meanings. In this paper, the physicochemical properties of 14 residues both upstream and downstream of a cleavage site are characterized by VHSE (principal component score vector of hydrophobic, steric, and electronic properties) descriptors. Then, the resulting VHSE descriptors are employed to construct prediction models by support vector machine (SVM). For both in vivo and in vitro datasets, the performance of VHSE -based method is comparatively better than that of the well-known PAProC, MAPPP, and NetChop methods. The results reveal that the hydrophobic property of 10 residues both upstream and downstream of the cleavage site is a dominant factor affecting in vivo and in vitro cleavage specificities, followed by residue’s electronic and steric properties. Furthermore, the difference in hydrophobic potential between residues flanking the cleavage site is proposed to favor substrate cleavages. Overall, the interpretable VHSE -based method provides a preferable way to predict proteasomal cleavage sites.