1991
DOI: 10.1111/j.1399-3011.1991.tb00756.x
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Minimum analogue peptide sets (MAPS) for quantitative structure‐activity relationships

Abstract: The information contents in previously published peptide sets was compared with smaller sets of peptides selected according to statistical designs. It was found that minimum analogue peptide sets (MAPS) constructed by factorial or fractional factorial designs in physicochemical properties contained substantial structure‐activity information. Although five to six times smaller than the originally published peptide sets the MAPS resulted in QSAR models able to predict biological activity. The QSARs derived from … Show more

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Cited by 137 publications
(79 citation statements)
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“…The peptide descriptors used to construct the QSAR models were either based on physicochemical characteristics 32,45 or scalar amino acid descriptors. [30][31][32]46 Most of the QSAR studies have successfully proposed the structural requirements linked with the ACE inhibitory properties of peptides. These consisted of specic amino acids located at different positions in the peptide sequence (Table 3).…”
Section: Ace Inhibitory Peptidesmentioning
confidence: 99%
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“…The peptide descriptors used to construct the QSAR models were either based on physicochemical characteristics 32,45 or scalar amino acid descriptors. [30][31][32]46 Most of the QSAR studies have successfully proposed the structural requirements linked with the ACE inhibitory properties of peptides. These consisted of specic amino acids located at different positions in the peptide sequence (Table 3).…”
Section: Ace Inhibitory Peptidesmentioning
confidence: 99%
“…24,26,30,31 For comparative purposes, it is recommended that the bioactivity output should be obtained under similar experimental conditions. 18,27,32 The peptide database may be restricted to sequences which originate from a single protein 26 or a group of proteins found within certain species (e.g., Homo sapiens, Bos taurus, etc.).…”
mentioning
confidence: 99%
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“…[6][7][8] The parameters are hydrophobicity, STERIMOL minimum width of the side chain, loss of side chain hydropathy by helix formation, optical rotation, side chain molecular volume, frequency of the 4th residue in turn, AA composition of EXT of multi-spanning proteins and net charge index, and they were encoded as G1~G8 (Table 1). For a set of peptide analogues, the chemical structures would be now characterized by describing each varied amino acid position with 8 G-scale values.…”
Section: Molecular Descriptorsmentioning
confidence: 99%
“…Since Kidera et al (1985) first coded 10 orthogonal factors from 188 reported physicochemical properties through factor analysis, a series of inductive descriptors have been constructed and applied in peptide computational study. Some examples are Z-scales (Hellberg et al 1991;Sandberg et al 1998), ISA-ECI (Collantes and Dunn 1995), SZOTT (Liang et al 2006), T-scales (Tian et al 2007), ATS-QTMS (Yousefinejad et al 2012), etc. However, these inductive descriptors are the linear combinations of the multiple physicochemical property parameters selected for the amino acids and hence, the QSAR models established using these descriptors could not clearly elucidate the correlation between the initial physicochemical properties and the bioactivity of peptides.…”
Section: Introductionmentioning
confidence: 99%