Date post: | 18-Jul-2015 |
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Upload: | malla-reddy-college-of-pharmacy |
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To find the putative protein family if querying a new sequence has failed using alignment methods
By neglecting the order of amino acid residues in a sequence, it uses the amino acid composition
144 properties like mol.wt, hydrophobicity, average charge etc., are weighted individually and are used as query vector
PROPSEARCH
PepMAPPER: Takes peptide mass as the input
Mascot: Can take the following as input, 1) Peptide mass fingerprint 2) Sequence query 3) MS/MS ion search
Peptide mass fingerprinting tools
To identify peptides that from unspecific cleavage of proteins from their experimental masses
Takes chemical modifications, post-translational modifications(PTM) and protease autolytic cleavage in account
Findpept
Compute pI/Mw: Calculates pI and mol.wt
ProtParam: • Computation of physical and chemical parameters for a protein sequence• Computed parameters include, Mol.Wt, Theoretical pI, amino acid composition, atomic composition, estimated half-life etc.,
Primary structure analysis and prediction
PHDacc: Simple hydrophobicity analysis
ProtScale: • Computation of physical and chemical parameters for a protein sequence• Computed parameters include, Mol.Wt, Theoretical pI, amino acid composition, atomic composition, estimated half-life etc.,
Hydrophobicity prediction
Chou-Fasman methodGOR (Garnier, Osguthorpe and Robson) MethodNearest Neighbour MthodHidden Markov ModelsNeural networksSOPMA (self-Optimized Prediction method based on MSA)
Secondary structure prediction
Relative frequencies of each Amino acid in different secondary structures
Less accurate than GOR method
Amino acid propensities is the basis
Chou-Fasman method
Four out of six amino acids have high probability >1.03 α helix
Three out of five amino acids with a probability of >1.00 β Sheet
Predictive values