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Drug-Target Interaction Prediction Based on Gaussian Interaction Profile and Information Entropy

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Bioinformatics Research and Applications (ISBRA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 13064))

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Abstract

Identifying drug-target interaction (DTI) is an important component of drug discovery and development. However, identifying DTI is a complex process that is time-consuming, costly, long, and often inefficient, with a low success rate, especially with wet-experimental methods. In contrast, numerous computational methods show great vitality and advantages. Among them, the precisely calculation of the drug-drug, target-target similarities are their basic requirements for accurate prediction of the DTI. In this paper, the improved Gaussian interaction profile similarity and the similarity fusion coefficient based on information entropy are proposed, which are fused with other similarities to enhance the performance of the DTI prediction methods. Experimental results on NR, GPCR, IC, Enzyme, all 4 benchmark datasets show that the improved similarity enhances the prediction performance of all six comparison methods.

Supported by the National Natural Science Foundation of China (No. 62002227,62031003) and Zhejiang Provincial Natural Science Foundation of China (Grant No. LY20F020011).

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Author information

Authors and Affiliations

  1. Soochow University, Suzhou, China

    Lina Liu

  2. China Jiliang University, Hangzhou, China

    Shuang Yao

  3. National University of Defense Technology, Changsha, China

    Zhaoyun Ding

  4. Beijing University of Civil Engineering and Architecture, Beijing, China

    Maozu Guo

  5. Shaoxing University, Shaoxing, China

    Donghua Yu & Keli Hu

  6. Information Technology R&D Innovation Center of Peking University, Shaoxing, China

    Keli Hu

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  1. Lina Liu
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  2. Shuang Yao
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  3. Zhaoyun Ding
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  4. Maozu Guo
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  5. Donghua Yu
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  6. Keli Hu
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Editor information

Editors and Affiliations

  1. Shenzhen Institutes of Advanced Technology, Shenzhen, China

    Yanjie Wei

  2. Central South University, Changsha, China

    Min Li

  3. Georgia State University, Atlanta, GA, USA

    Pavel Skums

  4. Georgia State University, Atlanta, GA, USA

    Zhipeng Cai

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Liu, L., Yao, S., Ding, Z., Guo, M., Yu, D., Hu, K. (2021). Drug-Target Interaction Prediction Based on Gaussian Interaction Profile and Information Entropy. In: Wei, Y., Li, M., Skums, P., Cai, Z. (eds) Bioinformatics Research and Applications. ISBRA 2021. Lecture Notes in Computer Science(), vol 13064. Springer, Cham. https://doi.org/10.1007/978-3-030-91415-8_33

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  • DOI: https://doi.org/10.1007/978-3-030-91415-8_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-91414-1

  • Online ISBN: 978-3-030-91415-8

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