IRC-Fuse: Improved and Robust Prediction of Redox-sensitive Cysteine by Fusing of Multiple Feature Representations

Overview

Journal J Comput Aided Mol Des

Publisher Springer

Specialties Biomedical Engineering
Molecular Biology

Date 2021 Jan 4

PMID 33392948

Citations 4

Authors

Md Mehedi Hasan

Md Ashad Alam

Watshara Shoombuatong

Hiroyuki Kurata

Affiliations

Soon will be listed here.

Abstract

Redox-sensitive cysteine (RSC) thiol contributes to many biological processes. The identification of RSC plays an important role in clarifying some mechanisms of redox-sensitive factors; nonetheless, experimental investigation of RSCs is expensive and time-consuming. The computational approaches that quickly and accurately identify candidate RSCs using the sequence information are urgently needed. Herein, an improved and robust computational predictor named IRC-Fuse was developed to identify the RSC by fusing of multiple feature representations. To enhance the performance of our model, we integrated the probability scores evaluated by the random forest models implementing different encoding schemes. Cross-validation results exhibited that the IRC-Fuse achieved accuracy and AUC of 0.741 and 0.807, respectively. The IRC-Fuse outperformed exiting methods with improvement of 10% and 13% on accuracy and MCC, respectively, over independent test data. Comparative analysis suggested that the IRC-Fuse was more effective and promising than the existing predictors. For the convenience of experimental scientists, the IRC-Fuse online web server was implemented and publicly accessible at http://kurata14.bio.kyutech.ac.jp/IRC-Fuse/ .

Citing Articles

PMTPred: machine-learning-based prediction of protein methyltransferases using the composition of k-spaced amino acid pairs.

Yadav A, Gupta P, Singh T Mol Divers. 2024; 28(4):2301-2315.

PMID: 39033257 DOI: 10.1007/s11030-024-10937-2.

Meta-2OM: A multi-classifier meta-model for the accurate prediction of RNA 2'-O-methylation sites in human RNA.

Harun-Or-Roshid M, Pham N, Manavalan B, Kurata H PLoS One. 2024; 19(6):e0305406.

PMID: 38924058 PMC: 11207182. DOI: 10.1371/journal.pone.0305406.

PredNTS: Improved and Robust Prediction of Nitrotyrosine Sites by Integrating Multiple Sequence Features.

Nilamyani A, Auliah F, Moni M, Shoombuatong W, Hasan M, Kurata H Int J Mol Sci. 2021; 22(5).

PMID: 33800121 PMC: 7962192. DOI: 10.3390/ijms22052704.

PUP-Fuse: Prediction of Protein Pupylation Sites by Integrating Multiple Sequence Representations.

Auliah F, Nilamyani A, Shoombuatong W, Alam M, Hasan M, Kurata H Int J Mol Sci. 2021; 22(4).

PMID: 33672741 PMC: 7924619. DOI: 10.3390/ijms22042120.

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