NDLI: B-Cell Conformational Epitope Prediction based on Structural Relationship and Antigenic Characteristics

Content Provider	IEEE Xplore Digital Library
Author	Wei-Kuo Wu Wei-Chun Chung Hao-Teng Chang Ron-shan Cheng Tun-Wen Pai
Copyright Year	2009
Abstract	Conformational Epitopes (CEs) are composed of discontinuous segments folding with polypeptide chains, which play an important role in vaccine designs and immuno-biological experiments. It has been estimated that more than 90% of B-cell epitopes are in a conformational structure, and therefore predic-tion of CEs becomes an important task for practical applications. The proposed system is the first tool that adopts three-dimensional mathematical morphology to define protein structural surface regions. Based on the surface information, spatial distance relationship and antigenic characteristics of amino acids are considered as key features for CEs candidate identification. In this paper, thirty three antigen-antibody complexes with verified CEs were adopted to evaluate prediction accuracy, and the performance was compared with PEPOP. To observe the influence of chemical property scales and surface ratios, a complete evaluation by various parameter settings were performed as well. It was discovered that the sensitivity was improved by selecting hydrophilicity rather than hydrophobicity features, while the specificity favored using hydrophobicity instead of hydrophilicity feature in general. The prediction results of the proposed systemachieves an overall accuracy of 75% and its performance is comparable to existing tools.
Starting Page	830
Ending Page	835
File Size	262907
Page Count	6
File Format	PDF
ISBN	9781424435692
DOI	10.1109/CISIS.2009.187
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-16
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sea surface Oceans Data acquisition Surface morphology surface region Amino acids Data mining Intelligent structures Chemicals Proteins conformational epitopes mathematical morphology Competitive intelligence
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Epitope and Paratope Region Analysis

Stepwise prediction of conformational discontinuous B-cell epitopes using the Mapitope algorithm.

Predicting Protective Linear B-Cell Epitopes Using Evolutionary Information

Comparison of HA, NA amino acid sequences of novel influenza virus A/H1N1 and prediction of related B cell epitopes

Prediction of conformational epitopes by geometrical affinity and chemical propensity approaches.

Conformational Changes of the Receptor Binding Domain of SARS-CoV-2 Spike Protein and Prediction of a B-Cell Antigenic Epitope Using Structural Data

A meta-learning approach for B-cell conformational epitope prediction

Comprehending B-Cell Epitope Prediction to Develop Vaccines and Immunodiagnostics

Prediction of conformational B-cell epitopes from 3D structures by random forests with a distance-based feature

B-Cell Conformational Epitope Prediction based on Structural Relationship and Antigenic Characteristics

Similar Documents

Epitope and Paratope Region Analysis

Stepwise prediction of conformational discontinuous B-cell epitopes using the Mapitope algorithm.

Predicting Protective Linear B-Cell Epitopes Using Evolutionary Information

Comparison of HA, NA amino acid sequences of novel influenza virus A/H1N1 and prediction of related B cell epitopes

Prediction of conformational epitopes by geometrical affinity and chemical propensity approaches.

Conformational Changes of the Receptor Binding Domain of SARS-CoV-2 Spike Protein and Prediction of a B-Cell Antigenic Epitope Using Structural Data

A meta-learning approach for B-cell conformational epitope prediction

Comprehending B-Cell Epitope Prediction to Develop Vaccines and Immunodiagnostics

Prediction of conformational B-cell epitopes from 3D structures by random forests with a distance-based feature

B-Cell Conformational Epitope Prediction based on Structural Relationship and Antigenic Characteristics