Computational Prediction of Human Saliva-Secreted Proteins

Using proteins in saliva as biomarkers has great advantage in early diagnosis and prognosis evaluation of health conditions or diseases. In this article, we present a computational method for predicting secreted proteins in human saliva. Firstly, we collected currently known saliva-secreted proteins and the representatives that deem to be not extracellular secretion into saliva. Secondly, we pruned the negative data concerned the imbalance condition, and then extracted the relevant features from the physicochemical and sequence properties of all remained proteins. After that, a support vector machine classifier was built which got performance of average sensitivity, specificity, precision, accuracy and Matthews correlation coefficient value to 80.67%, 90.56%, 90.09%, 85.53% and 0.7168, respectively. These results indicated that the selected features and the model are effective. Finally, a screening test was implemented to all human proteins in UniProt and acquired 5811 proteins as predicted saliva-secreted proteins which may be used as biomarker candidates for further salivary diagnosis.

[1]  Ying Xu,et al.  Computational prediction of human proteins that can be secreted into the bloodstream , 2008, Bioinform..

[2]  Chiara Baldini,et al.  Proteome analysis of whole saliva: A new tool for rheumatic diseases – the example of Sjögren's syndrome , 2007, Proteomics.

[3]  Craig S. Miller,et al.  Rheumatoid arthritis and salivary biomarkers of periodontal disease. , 2010, Journal of clinical periodontology.

[4]  Juan Cui,et al.  Advances in Exploration of Machine Learning Methods for Predicting Functional Class and Interaction Profiles of Proteins and Peptides Irrespective of Sequence Homology , 2007 .

[5]  W. Dubinsky,et al.  Breast Cancer Related Proteins Are Present in Saliva and Are Modulated Secondary to Ductal Carcinoma In Situ of the Breast , 2008, Cancer investigation.

[6]  John C. Gunsolley,et al.  Macrophage Inflammatory Protein‐1α: A Salivary Biomarker of Bone Loss in a Longitudinal Cohort Study of Children at Risk for Aggressive Periodontal Disease? , 2009 .

[7]  L. Holm,et al.  The Pfam protein families database , 2005, Nucleic Acids Res..

[8]  Peter Beyerlein,et al.  Diagnostic potential of saliva: current state and future applications. , 2011, Clinical chemistry.

[9]  Celine S. Hong,et al.  A Computational Method for Prediction of Excretory Proteins and Application to Identification of Gastric Cancer Markers in Urine , 2011, PloS one.

[10]  Jason Weston,et al.  Gene Selection for Cancer Classification using Support Vector Machines , 2002, Machine Learning.

[11]  I. Lamster,et al.  The diagnostic applications of saliva--a review. , 2002, Critical reviews in oral biology and medicine : an official publication of the American Association of Oral Biologists.

[12]  Shen Hu,et al.  Human saliva proteome analysis and disease biomarker discovery , 2007, Expert review of proteomics.

[13]  Nicholas A. Hamilton,et al.  LOCATE: a mammalian protein subcellular localization database , 2007, Nucleic Acids Res..

[14]  Yong Zhang,et al.  SPD—a web-based secreted protein database , 2004, Nucleic Acids Res..

[15]  J. Molina,et al.  Saliva levels of Abeta1-42 as potential biomarker of Alzheimer's disease: a pilot study , 2010, BMC neurology.

[16]  S. Shintani,et al.  Identification of a truncated cystatin SA-I as a saliva biomarker for oral squamous cell carcinoma using the SELDI ProteinChip platform. , 2010, International journal of oral and maxillofacial surgery.

[17]  Surendra Dasari,et al.  Proteomic identification of salivary biomarkers of type-2 diabetes. , 2009, Journal of proteome research.

[18]  Yanchun Liang,et al.  Computational Prediction of Human Salivary Proteins from Blood Circulation and Application to Diagnostic Biomarker Identification , 2013, PloS one.

[19]  John R Yates,et al.  The proteomes of human parotid and submandibular/sublingual gland salivas collected as the ductal secretions. , 2008, Journal of proteome research.

[20]  D. Wong,et al.  Salivary diagnostics powered by nanotechnologies, proteomics and genomics. , 2006, Journal of the American Dental Association.

[21]  Yusuke Mori,et al.  Association between saliva PSA and serum PSA in conditions with prostate adenocarcinoma , 2011, Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals.

[22]  C. Dawes,et al.  The intra-oral distribution of unstimulated and chewing-gum-stimulated parotid saliva. , 1997, Archives of oral biology.

[23]  S. Wang,et al.  Differential gene expression profiles of normal human parotid and submandibular glands. , 2008, Oral diseases.

[24]  Rong Zeng,et al.  Sys-BodyFluid: a systematical database for human body fluid proteome research , 2008, Nucleic Acids Res..

[25]  Rachael P. Huntley,et al.  The UniProt-GO Annotation database in 2011 , 2011, Nucleic Acids Res..

[26]  D. Sidransky,et al.  Gene mutations in saliva as molecular markers for head and neck squamous cell carcinomas. , 1994, American journal of surgery.

[27]  D. Wong,et al.  Salivary diagnostics for oral cancer. , 2006, Journal of the California Dental Association.

[28]  M. Tempero,et al.  Relationship of carbohydrate antigen 19-9 and Lewis antigens in pancreatic cancer. , 1987, Cancer research.