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Protein Identification & Characterization
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Page 1: Protein identication characterization

Protein Identification

&

Characterization

Page 2: Protein identication characterization

AACompIdent

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AACompIdent

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AACompIdent

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AACompIdent TagIdent

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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

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PROPSEARCH-DISTANCE

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Tool for identification by peptide mapping or peptideSequencing

PepSea

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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

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PepMAPPER

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MASCOT

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MASCOT

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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

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TMAP

TMHMM

TMPRED

TopPred2

PHDhtm

DAS

Transmembrane helices prediction

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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

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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

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Identifies possible PEST regions

PEST

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Chou-Fasman methodGOR (Garnier, Osguthorpe and Robson) MethodNearest Neighbour MthodHidden Markov ModelsNeural networksSOPMA (self-Optimized Prediction method based on MSA)

Secondary structure prediction

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Relative frequencies of each Amino acid in different secondary structures

Less accurate than GOR method

Amino acid propensities is the basis

Chou-Fasman method

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Ala, Glu, Leu, Met Helix formers

Pro, Gly Helix breakers

Amino acid propensities

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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

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Amino acid propensities & conditional probabilities are the basis

GOR Method