Epitope identification using
different Tools
Different roads often lead to the same destination, Like taking a consensus approach using different tools to arrive at the same final epitopes!
With the availability of different epitope determining servers/tools based on different algorithms, we have also attempted the consensus based approach to find out common epitopes and their functional domains for the protein targets shortlisted for vaccine candidate.
- For B cell, 3 different tools were employed BCEPRED (http://crdd.osdd.net/raghava/bcepred/), Bepipred (http://www.cbs.dtu.dk/services/BepiPred/), ABCPred (http://crdd.osdd.net/raghava/abcpred/ ).
- Similarly form HTL (MHC-1) epitopes: NetCTL (http://www.cbs.dtu.dk/services/NetCTL/), NetMHC (http://www.cbs.dtu.dk/services/NetMHC/), EpiJen (http://www.ddg-pharmfac.net/epijen/EpiJen/EpiJen.htm) & Propred-1 (http://crdd.osdd.net/raghava/propred1/) were used.
- IEDB MHC II (http://tools.iedb.org/mhcii/), MHC2Pred (http://crdd.osdd.net/raghava/mhc2pred/) & Propred(http://crdd.osdd.net/raghava/propred/) were used for determining the HTL epitopes (MHC-II). The above mentioned tools shows their output in different formats; Only high ranked/scored peptide were analysed and used in the image construction while others were used to reach out the common epitopes from this analysis.
To sum up, a unique image was drawn showing different epitopes on the protein sequences.
For B-cell epitope Identification:
ABCPred: This tool relies on an RNN algorithm and is used to predict B-Cell epitopes in an antigen sequence. This tool has a prediction accuracy of 65.93%.
https://drive.google.com/drive/folders/1XEQ59MvcARE2EqSRIDFnzWVckIz8GnSP?usp=sharing
BepiPred: This tool is based on the HMM algorithm, and helps in the prediction of B-Cell epitopes. The prediction accuracy of the tool varies with the threshold. At default threshold (0.5), the accuracy can be approximated at 58%, which goes up till 99.9% at a threshold exceeding 0.7.
docs.google.com/spreadsheets/d/1N4fqT0CazTmEcnqikAKP3LSuCzlEJMQY8Rk7gJk5IHs/edit?usp=sharing
BCEPRED: This server allows users to predict B-cell epitopes using any of the physico-chemical properties ( hydrophilicity, flexibility/mobility, accessibility, polarity, exposed surface and turns) or combination of properties and works with the accuracy of 58.70% at threshold 2.38
For CTL-epitope Identification:
- NetMHC: This tool relies on a SVM based method for prediction of promiscuous MHC class II binders. This tool is claimed to have a prediction accuracy approximating at 74%.
- EpiJen: This tool is based on an additive approach, and tries to model several important stage of the MHC degradation pathway: proteasome cleavage, TAP binding and MHC binding. This tool has a prediction accuracy of 62%. docs.google.com/spreadsheets/d/1eT3hXRK5QCaHIQTbOMggSnrV_y9P_JLy8HeP9qIpDAQ/edit?usp=sharing
NetCTL: This tool predicts CTL epitopes in protein sequences. The accuracy of the MHC class I peptide binding affinity is significantly improved compared to the earlier version.
For HTL-epitope Identification:
MHC2Pred: This tool relies on a SVM based method for prediction of promiscuous MHC class II binders. This tool is claimed to have a prediction accuracy
exceeding 78%.
docs.google.com/spreadsheets/d/1IRkEa2PMmyJZcCRzByfAcHNGenEGo9sCpkNg3E8Ie3A/edit?usp=sharing
Propred: This tool is used to predict MHC Class-II binding regions in an antigen sequence, using quantitative matrices derived from published literature by Sturniolo et. al., 1999.
IEDB MHC-2: This website provides access to predictions of peptide binding to MHC class II molecules.