AASD-Tool

AASD-Tool(Amino acid structural descriptors)

AASD-Tool is to generate the peptide feature vectors in batches, which contains 20 structural characterization scales. By uploading txt text containing peptide sequences, you can quickly generate the feature vectors of bioactive peptides, which can be used for molecular modeling and bioinformatics prediction, etc.

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Descriptors	Explanation
FASGAI	Through factor analysis, the FASGAI descriptors cluster 334 physicochemical properties of each of 20 coded amino acids into 6 factors, which are related to hydrophobicity, alpha and turn propensities, bulky properties, compositional characteristics, local flexibility and electronic properties, respectively.
Z-scales	The 3 principal component scores are derived from PCA of a matrix of 29 physicochemical variables for 20 coded amino acid are related to hydrophilicity (z₁), bulk (z₂), and electronic properties (z₃).
NNAAIndex	The NNAAIndex scales characterize a total of 155 physiochemical properties of 22 natural and 593 non-natural amino acids, followed by clustering the structural matrix into 6 representative property patterns by factor analysis. The six factors are geometric characteristics, H-bond, connectivity, accessible surface area, integy moments index, and volume and shape, respectively.
ISA-ECI	The isotropic surface area (ISA) approximates the hydrophobic character of the side chain substituent; The electronic charge index (ECI) is a measure of the charge concentration of the amino acid. Each residue was described by a combination of ISA and ECI descriptors.
MS-WHIM	MS-WHIM indexes, which are three principal components derived from PCA, are a collection of 36 statistical indexes aimed at extracting and condensing steric and electrostatic 3D-properties of a molecule.
SZOTT	The SZOTT descriptors are derived from PCA of a matrix of 1369 structural variables including 0D, 1D, 2D and 3D information for 20 coded amino acids.
ST-scales	The 8 principal component scores of ST-scales are derived from 827 structural variables of 167 amino acids by PCA.
T-scales	The 5 principal component scores of T-scales are derived from PCA on the collected 67 kinds of structural and topological variables of 135 amino acids.
VHSE	The VHSE descriptors are derived from the PCA on independent families of 18 hydrophobic properties, 17 steric properties, and 15 electronic properties, respectively. Among them, VHSE₁ and VHSE₂ are related to hydrophobic properties, VHSE₃ and VHSE₄ to steric properties, and VHSE₅–VHSE₈ to electronic properties.
VSTV	The 3 principal component scores as VSTV descriptors are derived from PCA on a matrix of 25 structural and topological variables of 20 coded amino acids.
GRID	The 7 principal properties of the GRID scales are derived from PCA on interaction energies of 20 coded amino acids, with six different probes mimicking various functional groups which can be involved in peptide-peptide interactions.
DPPS	The DPPS descriptors for 20 amino acids are derived by PCA. The electronic properties of the amino acid are characterized by V₁-V₄, steric properties by V₅ and V₆, hydrophobic properties by V₇ and V₈, and hydrogen bond contributions by V₉ and V₁₀.
BLOSUM62	The BLOSUM matrix-derived descriptors (BLOSUM) including 10 indices, representing hydrophobicity, alpha-helix propensity, beta-sheet propensity, bulkiness, charge, and composition, are based on both physicochemical properties that have been subjected to a ARIMAX analyses and an alignment matrix of 20 coded amino acids, the BLOSUM62 matrix.
HESH	These 12 vectors of HESH for 20 amino acids were obtained by PCA. The V₁–V₄ were hydrophobic properties, V₅–V₆ were steric properties, V₇–V₁₀ were electronic properties, and V₁₁–V₁₂ were hydrogen bond contribution properties.
Lin’s scales	Three kinds of physicochemical parameters selected from properties of 20 coded amino acids, namely Van Der Waal’s volume, net charge index and hydrophobic parameter, construct the vectors to characterize the structures of peptides.
ProtFP	The 8 principal component scores based on a PCA analysis of 58 amino acids properties explain 92% of the variances. For these predominant components, the first one is related to hydrophobicity and the second one is related to the size of amino acids.
QTMS(ADFQ) indices	The amino acids indices of QTMS are obtained by application of PCA on the unfolded loadings of the a data matrix of QTMS of all bonds of amino acids.
SVRG	The 16 principal component scores are derived from PCA of 150 radial distribution function and 74 geometrical descriptors.
SVWG	The 10 principal component scores are obtained by PCA on 99 WHIM and 197 GETWAY descriptors.
VSW	The 9 principal component scores are obtained by PCA on 99 WHIM descriptors.