A Novel Drug Repositioning Approach Based on Integrative Multiple Similarity Measures

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

Journal Name: Current Molecular Medicine

Volume 20 , Issue 6 , 2020

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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.

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Article Details

Year: 2020
Published on: 21 June, 2020
Page: [442 - 451]
Pages: 10
DOI: 10.2174/1566524019666191115103307
Price: $65

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