ILBE for Computational Identification of Linear B-cell Epitopes by Integrating Sequence and Evolutionary Features

Overview

Journal Genomics Proteomics Bioinformatics

Specialty Biology

Date 2020 Oct 25

PMID 33099033

Citations 18

Authors

Md Mehedi Hasan

Mst Shamima Khatun

Hiroyuki Kurata

Affiliations

Soon will be listed here.

Abstract

Linear B-cell epitopes are critically important for immunological applications, such as vaccine design, immunodiagnostic test, and antibody production, as well as disease diagnosis and therapy. The accurate identification of linear B-cell epitopes remains challenging despite several decades of research. In this work, we have developed a novel predictor, Identification of Linear B-cell Epitope (iLBE), by integrating evolutionary and sequence-based features. The successive feature vectors were optimized by a Wilcoxon-rank sum test. Then the random forest (RF) algorithm using the optimal consecutive feature vectors was applied to predict linear B-cell epitopes. We combined the RF scores by the logistic regression to enhance the prediction accuracy. iLBE yielded an area under curve score of 0.809 on the training dataset and outperformed other prediction models on a comprehensive independent dataset. iLBE is a powerful computational tool to identify the linear B-cell epitopes and would help to develop penetrating diagnostic tests. A web application with curated datasets for iLBE is freely accessible at http://kurata14.bio.kyutech.ac.jp/iLBE/.

Citing Articles

Prediction of linear B-cell epitopes based on protein sequence features and BERT embeddings.

Liu F, Yuan C, Chen H, Yang F Sci Rep. 2024; 14(1):2464.

PMID: 38291341 PMC: 10828400. DOI: 10.1038/s41598-024-53028-w.

DeepLBCEPred: A Bi-LSTM and multi-scale CNN-based deep learning method for predicting linear B-cell epitopes.

Qi Y, Zheng P, Huang G Front Microbiol. 2023; 14:1117027.

PMID: 36910218 PMC: 9992402. DOI: 10.3389/fmicb.2023.1117027.

NetBCE: An Interpretable Deep Neural Network for Accurate Prediction of Linear B-cell Epitopes.

Xu H, Zhao Z Genomics Proteomics Bioinformatics. 2022; 20(5):1002-1012.

PMID: 36526218 PMC: 10025766. DOI: 10.1016/j.gpb.2022.11.009.

Advances in antibody discovery from human BCR repertoires.

Xu Z, Ismanto H, Zhou H, Saputri D, Sugihara F, Standley D Front Bioinform. 2022; 2:1044975.

PMID: 36338807 PMC: 9631452. DOI: 10.3389/fbinf.2022.1044975.

Antibody Class(es) Predictor for Epitopes (AbCPE): A Multi-Label Classification Algorithm.

Kadam K, Peerzada N, Karbhal R, Sawant S, Valadi J, Kulkarni-Kale U Front Bioinform. 2022; 1:709951.

PMID: 36303781 PMC: 9581038. DOI: 10.3389/fbinf.2021.709951.

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