Prediction of Drug-Target Protein Interaction Based on the Minimization of Weighted Nuclear Norm and Similarity Graph between Drugs and Target Proteins

سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 330

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شناسه ملی سند علمی:

JR_IJE-34-7_018

تاریخ نمایه سازی: 12 مرداد 1400

چکیده مقاله:

Identification of drug-target protein interaction plays an important role in the drug discovery process. Given the fact that prediction experiments are time-consuming, tedious, and very costly, the computational prediction could be a proper solution for decreasing search space for evaluation of the interaction between drug and target. In this paper, a novel approach based on the known drug-target interactions based on similarity graphs is proposed. It was shown that use of this method was a low-ranking issue and WNNM (weighted nuclear norm minimization) method was applied to detect the drug-target interactions. In the proposed method, the interaction between the drug and the target is encoded by graphs. Also known drug-target interaction, drug-drug similarity, target-target and combination of similarities were used as input. The proposed method was performed on four benchmark datasets, including enzymes (Es), ion channels (IC), G protein-coupled receptors (GPCRs), and nuclear receptors (NRs) based on the AUC and AUPR criteria. Finally, the results showed the improved performance of the proposed method.

کلیدواژه ها:

Drug-target Interactionsو Drug discovery processو Computational Predictionو Weighted Nuclear Norm Minimization ، Similarity Graph ، Low-rank matrix

نویسندگان

A. Ghanbari Sorkhi

Faculty of Electrical and Computer Engineering, University of Science and Technology of Mazandaran, Behshahr, Iran

S.M.R. Hashemi

Young Researchers and Elite Clu, Qazvin Branch, Islamic Azad University, Qazvin, Iran

H. Yarmohammadi

Faculty of Computer Engineering, Shahrood university of technology, Shahrood, Iran

M. Iranpour Mobarakeh

Computer engineering and It department, Payam Noor University, Tehran, Iran

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