NDLI: Quantitative Prediction of Peptide Binding to HLA-DP1 Protein

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Quantitative Prediction of Peptide Binding to HLA-DP1 Protein

Content Provider	IEEE Xplore Digital Library
Author	Ivanov, S. Dimitrov, I. Doytchinova, I.
Copyright Year	2004
Abstract	The exogenous proteins are processed by the host antigen-processing cells. Peptidic fragments of them are presented on the cell surface bound to the major hystocompatibility complex (MHC) molecules class II and recognized by the CD4+ T lymphocytes. The MHC binding is considered as the crucial prerequisite for T-cell recognition. Only peptides able to form stable complexes with the MHC proteins are recognized by the T-cells. These peptides are known as T-cell epitopes. All T-cell epitopes are MHC binders, but not all MHC binders are T-cell epitopes. The T-cell epitope prediction is one of the main priorities of immunoinformatics. In the present study, three chemometric techniques are combined to derive a model for in silico prediction of peptide binding to the human MHC class II protein HLA-DP1. The structures of a set of known peptide binders are described by amino acid z-descriptors. Data are processed by an iterative self-consisted algorithm using the method of partial least squares, and a quantitative matrix (QM) for peptide binding prediction to HLA-DP1 is derived. The QM is validated by two sets of proteins and showed an average accuracy of 86 percent.
Sponsorship	IEEE Computer Society
Page Count	5
File Size	817111
Starting Page	811
Ending Page	815
File Format	PDF
ISSN	15455963
Volume Number	10
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Peptides Proteins Immune system Amino acids Diseases Training Predictive models partial least squares method proteins bonds (chemical) cellular biophysics least squares approximations molecular biophysics quantitative prediction peptide binding prediction quantitative matrix partial least squares iterative self-consisted algorithm amino acid z-descriptors in silico prediction chemometric techniques immunoinformatics MHC binders T-cell epitopes MHC proteins stable complexes T-cell recognition MHC binding CD4+ T lymphocytes MHC molecules class II major hystocompatibility complex cell surface peptidic fragments host antigen-processing cells exogenous proteins HLA-DP1 protein z-descriptors MHC binding prediction iterative self-consistent algorithm
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Genetics Biotechnology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Quantitative Prediction of Peptide Binding to HLA-DP1 Protein

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Towards the in silico identification of class II restricted T-cell epitopes: a partial least squares iterative self-consistent algorithm for affinity prediction

PREDIVAC: CD4+ T-cell epitope prediction for vaccine design that covers 95% of HLA class II DR protein diversity

NetMHCIIpan-3.0, a common pan-specific MHC class II prediction method including all three human MHC class II isotypes, HLA-DR, HLA-DP and HLA-DQ

Potential link between MHC–self-peptide presentation and hematopoiesis; the analysis of HLA-DR expression in CD34-positive cells and self-peptide presentation repertoires of MHC molecules associated with paroxysmal nocturnal hemoglobinuria

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