In Silico Rational Design and Virtual Screening of Bioactive Peptides Based on QSAR Modeling.

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Abstract

Predicting the bioactivity of peptides is an important challenge in drug development and peptide research. In this study, numerical descriptive vectors (NDVs) for peptide sequences were calculated based on the physicochemical properties of amino acids (AAs) and principal component analysis (PCA). The resulted NDV had the same length as the peptide sequence, so that each entry of NDV corresponded to one AA in the sequence. They were then applied to quantitative structure-activity relationship (QSAR) analysis of angiotensin-converting enzyme (ACE) inhibitor dipeptides, bitter-tasting dipeptides, and nonameric binding peptides of the human leukocyte antigens (HLA-A*0201). Multiple linear regression was used to construct the QSAR models. For each peptide set, a proper subset of physicochemical properties was chosen by the ant colony optimization algorithm. The leave-one-out cross-validation (q loo 2) values were 0.855, 0.936, and 0.642 and the root-mean-square errors (RMSEs) were 0.450, 0.149, and 0.461. Our results revealed that the new numerical descriptive vector can afford extensive characterization of peptide sequence so that it can be easily employed in peptide QSAR studies. Moreover, the proposed numerical descriptive vectors were able to determine hot spot residues in the peptides under study.

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AAindex: amino acid index database.

S Kawashima (2000)

AAindex is a database of amino acid indices and amino acid mutation matrices. An amino acid index is a set of 20 numerical values representing various physico--chemical and biochemical properties of amino acids. An amino acid mutation matrix is generally 20 x 20 numerical values representing similarity of amino acids. AAindex consists of two sections: AAindex1 for the collection of published amino acid indices and AAindex2 for the collection of published amino acid mutation matrices. Each entry of either AAindex1 or AAindex2 consists of the definition, the reference information, a list of related entries in terms of the correlation coefficient and the actual data. The database may be accessed through the DBGET/LinkDB system at GenomeNet (http://www. genome.ad.jp/aaindex/ ) or may be downloaded by anonymous FTP (ftp://ftp.genome.ad.jp/db/genomenet/aaindex/ ).

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Predicting the secondary structure of globular proteins using neural network models.

Ning Qian, Terrence Sejnowski (1988)

We present a new method for predicting the secondary structure of globular proteins based on non-linear neural network models. Network models learn from existing protein structures how to predict the secondary structure of local sequences of amino acids. The average success rate of our method on a testing set of proteins non-homologous with the corresponding training set was 64.3% on three types of secondary structure (alpha-helix, beta-sheet, and coil), with correlation coefficients of C alpha = 0.41, C beta = 0.31 and Ccoil = 0.41. These quality indices are all higher than those of previous methods. The prediction accuracy for the first 25 residues of the N-terminal sequence was significantly better. We conclude from computational experiments on real and artificial structures that no method based solely on local information in the protein sequence is likely to produce significantly better results for non-homologous proteins. The performance of our method of homologous proteins is much better than for non-homologous proteins, but is not as good as simply assuming that homologous sequences have identical structures.

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AAindex: Amino Acid Index Database.

M Kanehisa, S Kawashima, Yukio Ogata (1999)

AAindex is a database of numerical indices representing various physicochemical and biochemical properties of amino acids and pairs of amino acids. It consists of two sections: AAindex1 for the amino acid index of 20 numerical values and AAindex2 for the amino acid mutation matrix of 210 numerical values. Each entry of either AAindex1 or AAindex2 consists of the definition, the reference information, a list of related entries in terms of the correlation coefficient, and the actual data. The database may be accessed through the DBGET/LinkDB system at GenomeNet (http://www.genome.ad. jp/dbget/) or may be downloaded by anonymous FTP (ftp://ftp.genome. ad.jp/db/genomenet/aaindex/).