Next Article in Journal
Cobalt-Catalyzed (Hetero)arylation of Saturated Cyclic Amines with Grignard Reagents
Previous Article in Journal
Organic Fluorescent Compounds that Display Efficient Aggregation-Induced Emission Enhancement and Intramolecular Charge Transfer
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Molecules 2018, 23(6), 1448; https://doi.org/10.3390/molecules23061448

High-Throughput Identification of Mammalian Secreted Proteins Using Species-Specific Scheme and Application to Human Proteome

1
School of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, China
2
College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 13 April 2018 / Revised: 29 May 2018 / Accepted: 30 May 2018 / Published: 14 June 2018
Full-Text   |   PDF [2172 KB, uploaded 14 June 2018]   |  

Abstract

Secreted proteins are widely spread in living organisms and cells. Since secreted proteins are easy to be detected in body fluids, urine, and saliva in clinical diagnosis, they play important roles in biomarkers for disease diagnosis and vaccine production. In this study, we propose a novel predictor for accurate high-throughput identification of mammalian secreted proteins that is based on sequence-derived features. We combine the features of amino acid composition, sequence motifs, and physicochemical properties to encode collected proteins. Detailed feature analyses prove the effectiveness of the considered features. Based on the differences across various species of secreted proteins, we introduce the species-specific scheme, which is expected to further explore the intrinsic attributes of specific secreted proteins. Experiments on benchmark datasets prove the effectiveness of our proposed method. The test on independent testing dataset also promises a good generalization capability. When compared with the traditional universal model, we experimentally demonstrate that the species-specific scheme is capable of significantly improving the prediction performance. We use our method to make predictions on unreviewed human proteome, and find 272 potential secreted proteins with probabilities that are higher than 99%. A user-friendly web server, named iMSPs (identification of Mammalian Secreted Proteins), which implements our proposed method, is designed and is available for free for academic use at: http://www.inforstation.com/webservers/iMSP/. View Full-Text
Keywords: secreted proteins; species-specific; high-throughput; human proteome secreted proteins; species-specific; high-throughput; human proteome
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

Zhang, J.; Chai, H.; Guo, S.; Guo, H.; Li, Y. High-Throughput Identification of Mammalian Secreted Proteins Using Species-Specific Scheme and Application to Human Proteome. Molecules 2018, 23, 1448.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Molecules EISSN 1420-3049 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top