General Information & Help
Antigen Processing and Presentation:-

Antigen processing and presentation are processes that occur within a cell that result in fragmentation (proteolysis) of proteins, association of the fragments with MHC molecules, and expression of the peptide-MHC molecules at the cell surface where they can be recognized by the T cell receptor on a T cell. This lead to the stimulation of CTL cells to clear the infection.The three major step where we can devise rules

  • Degradation of antigens by proteasomes.
  • Transport of peptides fragments through TAP transporter
  • Binding of transported peptides MHC molecules.

20S Proteasome:-

The 20S proteaosme is the key enzyme for degradation of most of cytosolic and nuclear protein found in all living cell from the eukaryotes to prokaryotes. The proteasome mostly degrade the ubiqtinated and non-ubiqtinated proteins. The cleavage specificity of proteasome is believed to be an important factor in antigen processing because the MHC class I epitopes must conform to stringent structural requirement of both length and composition for efficient presentation.

The 20S proteasome is consist of 28 subunits into four heptameric rings (alpha7-beta7--beta7-alpha7 ). The two inner beta subunits have three active sites for making cleavage whereas a subunits create environment for making cleavage. These active sites have distinct but overlapping cleavage specificity. The different active sites of the proteasome are associated with chymotrypysin like (i.e. cleavage after basic residues), Trypsin like (i.e. cleavage after large hydrophobic residues) and peptidyl-glutamyl-peptide-hydrolyzing activity (i.e. cleavage after acidic amino acids). The experimentally identified proteasome cleavages patterns are therefore represent a mixture of cleavages carried out by different active sites or subunits. This makes the modeling of proteasomal cleavage a complex task.

In the past, digestion of synthetic peptides or proteins and through analysis of degraded products provided more insight into cleavage specificity. The analysis of fragment generated by constitutive proteasome provide better understanding into P1 (the position that lies at N terminal of cleavage site. and P1' (position that lies at C terminal of cleavage site). More amount of data about the cleavage products of proteasome are generated by the invitro digestion of complete proteins like enolase and b-casein. The increase amount of data made it possible to derive rules for devising computational methods for modeling the proteasomal cleavage specificity.

At the moment, three methods (PAProc MAPPP and NetChop) are available on the worldwide web for prediction of proteasomal cleavage sites from the proteins.

PAProC: is a method for predicting human and yeast (wild and mutated type) cleavage sites based on the in vitro digestion data of enolase I. The quantitative effect of different residues on cleave specificity is considered using hill climbing algorithm.

MAPPP: is a linear method for the prediction of 20S proteasomal cleavage sites. The method is based on the "cleavage determining amino acid motifs". The method was further improved by developing kinetic model of 20S proteasome, which took in consideration the time dependent degradation of peptides.

NetChop: is recently published best method for predicting the constitutive or immunoproteasome cleavage sites on the basis of multilayered artificial neural network. The method is based on the invitro digestion data and sequence signal from the boundaries of naturally processed MHC class I ligands. The latter was included on the basis of assumption that proteasome cleavage sites mostly lies at the C terminal of MHC class I ligands.

In this study a, systematic attempt have been made to improve these predictions for constitutive proteasome (20S proteasome) by using various machine learning tools. In order to develop a highly accurate method for proteasome cleavage prediction, we have applied commonly used techniques i.e. Support Vector Machines, Parallel Exemplar Based Learning (PEBLS) and weka (Waikato Environment for Knowledge analysis) on in vitro digestion data. The SVM based method outperformed the machine learning techniques used in this study as well all the exiting prediction methods. The MCC of SVM based prediction method is 0.43. The performance of the method was evaluated through five set cross-validation as well on an independent dataset.

Detailed Stepwise Help

Sample of Sequence Submission Form-:
Submission Form

Name of Protein-: The name of sequence may have letters and number with the "-" or "_". All other character are non-permissible. If the name of the sequence is submitted with illegal characters then warning will appear ( sorry,sequence have some illegal characters). The field is assigned a default name "Protein". The sequence name is just used for only your information. It may be a problem with , , for example or an empty space within the name of the sequence, which is not allowed for reasons of security.

Sequence submission: This server allows the submission of sequence in any of the standard formats. The user can paste plain sequence in the provided text area.The server also has the facility for uploading the local sequence files. Amino acid sequences must be entered in the one-letter code.All the non standard characters like [*&^%$@#!()_+~=;'",<>?.\|} are ignored from the sequence.The minimum length of the submitted sequence should be 10 otherwise server will show prediction have which may be wrong interpetaion.The warning is also displayed if the user submitted sequences from both sources.

Format of Antigenic sequence-: The server can accept both the formatted or unformatted raw antigenic sequences.The server uses ReadSeq routine to parse the input.The user should choose wether the sequence uploaded or pasted is plain or formatted before running prediction.The results of the prediction will be wrong if the format choosen is wrong.

Prediction Approaches-:In Vitro Digestion Data This SVM classifier can predict the proteasomal cleavage sites with constitutive proteasome cleavage specificity.The classifiers for prediction of constitutive proteasome cleavag e sites were trained and tested on yeast enolase I and b-casein digestion data obtained from the work of Toes et al., 2001 and Emmerich et al., 2000, respectively.

Prediction Approaches-:MHC Ligand Data This SVM classifier can predict the cleavage sites with constitutive and immuno- proteasome cleavage sites with cleavage specificity.The natural MHC class I ligands or T cell epitopes were con sidered to have cleavage site at their C terminal rest of the positions between N- and C- terminal have minor or no cleavage sites.

Threshold-: The threshold is used to discriminate the cleavage and non-cleavage sites.The user can vary the threshold score between the -1.5 to 1.5. The residues achieving score more then the cutoff score are predicted as P1 cleavage site otherwise they are predicted as non-cleavage site.if the user did not select threshold then the default threshold of prediction methods will be used.The default threshold is that at which the maximum MCC of prediction method is achieved. The default threshold for in vitro digested data based and MHC ligands based classifiers is "-0.1" and "0.3" respectively. The higher the threshold (= high stringency), the lower the false positive rate and the hi gher the false negative rate. in contrast the low the threshold (= low stringency), the higher the false positive rate and the lower the false negative rate. In short, from the same protein sequence input, a threshold setting of 1.0 will predict a lower number of cleavage sites (cleavage sites with high score), compared to 0.0 or lesser thresholds.

Prediction Results-: The results of the prediction displayed in user-friendly text formats.Each of result display format firstly provides a comprehensive account of length of input sequence, prediction approach, selected classifier and cutoff threshold as shown below. The result of prediction will be displayed in these two formats.

  • Outlines Display
  • Complete Display

Outlines Display : The display format will provide the comprehensive information about the occurrence of the cleavage sites in the uploaded protein sequence. The P1 cleavage site or residue is shown with large and bold red color font. The cleavage site occurs between P1 and following C terminal residue.An example of output is shown below. The cleavage site is marked by arrow and P1 site is shown by large red color font.

Complete Display:- This display from at will show the overall distribution of the cleavage sites in the sequence by using "outlines display format". This format also display the P1 cleavage sites, their position,predicted state and achieved score for each residue of sequence.

Position:-This column specify the position of the residues in the primary amino acid sequence. The positions are shown in ascending order starting with "1".

Amino Acid:-This column specify the amino acid of the sequence corresponding to the position shown in column 1.

State:- The N and S states specify the cleavage & non-cleavage sites respectively. The predicted state is decided on the basis of score achieved. A residue is assigned cleavage state (S) if the achieved score is greater then selected threshold. It means that in the primary amino acids sequence a cleavage site occurs at C terminal of that residue. On the other hand a residue is assigned non-cleavage state (N) if the achieved score is lesser then selected threshold.

Score:-This column specify the score obtained by the residues on prediction.The higher the score achieved by a residue it is having more accessible proteasomal cleavage site.

An example of the complete display format is shown below.

Complete Display

Finally click on "Submit" button.