Generic placeholder image

Current Molecular Medicine

Author(s): Chaokun Yan, Luping Feng, Wenxiu Wang, Jianlin Wang, Ge Zhang and Junwei Luo*

DOI: 10.2174/1566524019666191115103307

DownloadDownload PDF Flyer Cite As
A Novel Drug Repositioning Approach Based on Integrative Multiple Similarity Measures

Page: [442 - 451] Pages: 10

  • * (Excluding Mailing and Handling)

Explore Articles
About Journal
For Authors
For Editors
For Reviewers

Abstract

Background: Drug repositioning refers to discovering new indications for the existing drugs, which can improve the efficiency of drug research and development.

Methods: In this work, a novel drug repositioning approach based on integrative multiple similarity measure, called DR_IMSM, is proposed. The process of integrative similarity measure contains three steps. First, a heterogeneous network can be constructed based on known drug-disease association, shared entities information for drug pairwise and diseases pairwise. Second, a deep learning method, DeepWalk, is used to capture the topology similarity for drug and disease. Third, a similarity integration and adjusting process is further conducted to obtain more comprehensive drug and disease similarity measure, respectively.

Results: On this basis, a Bi-random walk algorithm is implemented in the constructed heterogeneous network to rank diseases for each drug. Compared with other approaches, the proposed DR_IMSM can achieve superior performance in terms of AUC on the gold standard datasets. Case studies further confirm the practical significance of DR_IMSM.

Keywords: Drug repositioning, heterogeneous network, similarity measure, logistic function, deepwalk, bi-random walk.

[1]
Li J, Zheng S, Chen B, Butte AJ, Swamidass SJ, Lu Z. A survey of current trends in computational drug repositioning. Brief Bioinform 2016; 17(1): 2-12.
[http://dx.doi.org/10.1093/bib/bbv020] [PMID: 25832646]
[2]
Grabowski H. Are the economics of pharmaceutical research and development changing?: productivity, patents and political pressures. Pharmacoeconomics 2004; 22(2)(Suppl. 2): 15-24.
[http://dx.doi.org/10.2165/00019053-200422002-00003] [PMID: 15660474]
[3]
Hurle MR, Yang L, Xie Q, Rajpal DK, Sanseau P, Agarwal P. Computational drug repositioning: from data to therapeutics. Clin Pharmacol Ther 2013; 93(4): 335-41.
[http://dx.doi.org/10.1038/clpt.2013.1] [PMID: 23443757]
[4]
Ashburn TT, Thor KB. Drug repositioning: identifying and developing new uses for existing drugs. Nat Rev Drug Discov 2004; 3(8): 673-83.
[http://dx.doi.org/10.1038/nrd1468] [PMID: 15286734]
[5]
Andronis C, Sharma A, Virvilis V, Deftereos S, Persidis A. Literature mining, ontologies and information visualization for drug repurposing. Brief Bioinform 2011; 12(4): 357-68.
[http://dx.doi.org/10.1093/bib/bbr005] [PMID: 21712342]
[6]
Napolitano F, Zhao Y, Moreira VM, et al. Drug repositioning: a machine-learning approach through data integration. J Cheminform 2013; 5(1): 30.
[http://dx.doi.org/10.1186/1758-2946-5-30] [PMID: 23800010]
[7]
Martínez V, Navarro C, Cano C, Fajardo W, Blanco A. DrugNet: network-based drug-disease prioritization by integrating heterogeneous data. Artif Intell Med 2015; 63(1): 41-9.
[http://dx.doi.org/10.1016/j.artmed.2014.11.003] [PMID: 25704113]
[8]
Chen H, Zhang H, Zhang Z, Cao Y, Tang W. Network-based inference methods for drug repositioning. Comput Math Methods Med 2015; 2015130620
[http://dx.doi.org/10.1155/2015/130620] [PMID: 25969690]
[9]
Luo H, Wang J, Li M, et al. Drug repositioning based on comprehensive similarity measures and Bi-Random walk algorithm. Bioinformatics 2016; 32(17): 2664-71.
[http://dx.doi.org/10.1093/bioinformatics/btw228] [PMID: 27153662]
[10]
Zhang J, Li C, Lin Y, et al. Computational drug repositioning using collaborative filtering via multi-source fusion. Expert Syst Appl 2017; 84: 281-9.
[http://dx.doi.org/10.1016/j.eswa.2017.05.004]
[11]
Luo H, Wang J, Li M, et al. Computational drug repositioning with random walk on a heterogeneous network. IEEE/ACM Trans Comput Biol Bioinformatics 2018; 16(6): 1890-900.
[http://dx.doi.org/10.1109/TCBB.2018.2832078] [PMID: 29994051]
[12]
Gottlieb A, Stein GY, Ruppin E, Sharan R. PREDICT: a method for inferring novel drug indications with application to personalized medicine. Mol Syst Biol 2011; 7(1): 496.
[http://dx.doi.org/10.1038/msb.2011.26] [PMID: 21654673]
[13]
Wishart DS, Knox C, Guo AC, et al. A comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res 2006; 34(1): D668-72.
[14]
Hamosh A, Scott AF, Amberger J, Bocchini C, Valle D, McKusick VA. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res 2002; 30(1): 52-5.
[http://dx.doi.org/10.1093/nar/30.1.52] [PMID: 11752252]
[15]
Luo H, Li M, Wang S, Liu Q, Li Y, Wang J. Computational drug repositioning using low-rank matrix approximation and randomized algorithms. Bioinformatics 2018; 34(11): 1904-12.
[http://dx.doi.org/10.1093/bioinformatics/bty013] [PMID: 29365057]
[16]
Yang C, Liu Z. Comprehend deepwalk as matrix factorization. arXiv preprint arXiv: 1501.00358.
[17]
Steinbeck C, Han Y, Kuhn S, Horlacher O, Luttmann E, Willighagen E. The chemistry development Kit (CDK): An open-source Java library for chemo-and bioinformatics. J Chem Inf Comput Sci 2003; 43(2): 493-500.
[http://dx.doi.org/10.1021/ci025584y] [PMID: 12653513]
[18]
Tanimoto T. An Elementary mathematical theory of classification and prediction Internal IBM Technical Report 1957.
[19]
Weininger D. SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. J Chem Inf Comput Sci 1988; 28(1): 31-6.
[http://dx.doi.org/10.1021/ci00057a005]
[20]
Liu H, Song Y, Guan J, Luo L, Zhuang Z. Inferring new indications for approved drugs via random walk on drug-disease heterogenous networks. BMC Bioinformatics 2016; 17(17)(Suppl. 17): 539.
[http://dx.doi.org/10.1186/s12859-016-1336-7] [PMID: 28155639]
[21]
Vanunu O, Magger O, Ruppin E, Shlomi T, Sharan R. Associating genes and protein complexes with disease via network propagation. PLOS Comput Biol 2010; 6(1)e1000641
[http://dx.doi.org/10.1371/journal.pcbi.1000641] [PMID: 20090828]
[22]
van Driel MA, Bruggeman J, Vriend G, Brunner HG, Leunissen JA. A text-mining analysis of the human phenome. Eur J Hum Genet 2006; 14(5): 535-42.
[http://dx.doi.org/10.1038/sj.ejhg.5201585] [PMID: 16493445]
[23]
Lipscomb CE. Medical subject headings (MeSH). Bull Med Libr Assoc 2000; 88(3): 265-6.
[PMID: 10928714]
[24]
Xie M, Hwang T, Kuang R. Prioritizing disease genes by bi-random walk. InPacific-Asia Conference on Knowledge Discovery and Data Mining 2012 292-303.
[http://dx.doi.org/10.1007/978-3-642-30220-6_25]
[25]
Davis J, Goadrich M. The relationship between Precision-Recall and ROC curves. Proceedings of the 23rd international conference on Machine learning 2006. 233-40.
[http://dx.doi.org/10.1145/1143844.1143874]
[26]
Wang W, Yang S, Li J. Drug target predictions based on heterogeneous graph inference. Pac Symp Biocomput 2013; 2013: 53-64.
[PMID: 23424111]
[27]
Cheng F, Liu C, Jiang J, et al. Prediction of drug-target interactions and drug repositioning via network-based inference. PLOS Comput Biol 2012; 8(5)e1002503
[http://dx.doi.org/10.1371/journal.pcbi.1002503] [PMID: 22589709]
[28]
Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M. Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res 2014; 42(Database issue): D199-205.
[http://dx.doi.org/10.1093/nar/gkt1076] [PMID: 24214961]
[29]
Study of pralatrexate and gemcitabine with b12 and folic acid to treat relapsed/refractory lymphoproliferative malignancies. Clinical Trials gov. 2007.
[30]
Phase II study of the effect of leuprolide acetate and spironolactone on insulin resistance in hyperandrogenic women with polycystic ovarian disease or hyperandrogenism insulin resistance acanthosis nigricans syndrome. Clinical Trials gov 2006.
[31]
Docetaxel, doxorubicin, and prednisone in treating patients with advanced prostate cancer that has not responded to hormone therapy. Clinical Trials gov. 2006.
[32]
Desmopressin melt: impact on sleep and daytime functioning (sleep). Clinical Trials gov . 2014.