PMID- 18496789
OWN - NLM
STAT- MEDLINE
DCOM- 20081219
LR  - 20081127
IS  - 1096-987X (Electronic)
IS  - 0192-8651 (Linking)
VI  - 30
IP  - 1
DP  - 2009 Jan 15
TI  - HIV-1 protease cleavage site prediction based on amino acid property.
PG  - 33-9
LID - 10.1002/jcc.21024 [doi]
AB  - Knowledge of the polyprotein cleavage sites by HIV protease will refine our 
      understanding of its specificity, and the information thus acquired is useful for 
      designing specific and efficient HIV protease inhibitors. Recently, several works 
      have approached the HIV-1 protease specificity problem by applying a number of 
      classifier creation and combination methods. The pace in searching for the proper 
      inhibitors of HIV protease will be greatly expedited if one can find an accurate, 
      robust, and rapid method for predicting the cleavage sites in proteins by HIV 
      protease. In this article, we selected HIV-1 protease as the subject of the 
      study. 299 oligopeptides were chosen for the training set, while the other 63 
      oligopeptides were taken as a test set. The peptides are represented by features 
      constructed by AAIndex (Kawashima et al., Nucleic Acids Res 1999, 27, 368; 
      Kawashima and Kanehisa, Nucleic Acids Res 2000, 28, 374). The mRMR method 
      (Maximum Relevance, Minimum Redundancy; Ding and Peng, Proc Second IEEE Comput 
      Syst Bioinformatics Conf 2003, 523; Peng et al., IEEE Trans Pattern Anal Mach 
      Intell 2005, 27, 1226) combining with incremental feature selection (IFS) and 
      feature forward search (FFS) are applied to find the two important cleavage sites 
      and to select 364 important biochemistry features by jackknife test. Using KNN 
      (K-nearest neighbors) to combine the selected features, the prediction model 
      obtains high accuracy rate of 91.3% for Jackknife cross-validation test and 87.3% 
      for independent-set test. It is expected that our feature selection scheme can be 
      referred to as a useful assistant technique for finding effective inhibitors of 
      HIV protease, especially for the scientists in this field.
CI  - Copyright 2008 Wiley Periodicals, Inc.
FAU - Niu, Bing
AU  - Niu B
AD  - School of Materials Science and Engineering, Shanghai University, 149 Yan-Chang 
      Road, Shanghai 200072, People's Republic of China.
FAU - Lu, Lin
AU  - Lu L
FAU - Liu, Liang
AU  - Liu L
FAU - Gu, Tian Hong
AU  - Gu TH
FAU - Feng, Kai-Yan
AU  - Feng KY
FAU - Lu, Wen-Cong
AU  - Lu WC
FAU - Cai, Yu-Dong
AU  - Cai YD
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - United States
TA  - J Comput Chem
JT  - Journal of computational chemistry
JID - 9878362
RN  - 0 (Amino Acids)
RN  - 0 (Oligopeptides)
RN  - EC 3.4.23.- (HIV Protease)
RN  - EC 3.4.23.- (p16 protease, Human immunodeficiency virus 1)
SB  - IM
MH  - Algorithms
MH  - Amino Acids/*chemistry
MH  - Binding Sites
MH  - Computational Biology
MH  - HIV Protease/*chemistry/metabolism
MH  - HIV-1/*enzymology
MH  - Models, Chemical
MH  - Oligopeptides/*chemistry/metabolism
MH  - Structure-Activity Relationship
MH  - Substrate Specificity
EDAT- 2008/05/23 09:00
MHDA- 2008/12/20 09:00
CRDT- 2008/05/23 09:00
PHST- 2008/05/23 09:00 [pubmed]
PHST- 2008/12/20 09:00 [medline]
PHST- 2008/05/23 09:00 [entrez]
AID - 10.1002/jcc.21024 [doi]
PST - ppublish
SO  - J Comput Chem. 2009 Jan 15;30(1):33-9. doi: 10.1002/jcc.21024.