6. 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
9. 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
13. 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
15. 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
16. 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
18. Chou-Fasman method
GOR (Garnier, Osguthorpe and Robson) Method
Nearest Neighbour Mthod
Hidden Markov Models
Neural networks
SOPMA (self-Optimized Prediction method based on
MSA)
Secondary structure prediction
19. Relative frequencies of each Amino acid in different
secondary structures
Less accurate than GOR method
Amino acid propensities is the basis
Chou-Fasman method
20. Ala, Glu, Leu, Met Helix formers
Pro, Gly Helix breakers
Amino acid propensities
21. 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