Author:
Bagherian Maryam,Kim Renaid B,Jiang Cheng,Sartor Maureen A,Derksen Harm,Najarian Kayvan
Abstract
Abstract
Predicting the interactions between drugs and targets plays an important role in the process of new drug discovery, drug repurposing (also known as drug repositioning). There is a need to develop novel and efficient prediction approaches in order to avoid the costly and laborious process of determining drug–target interactions (DTIs) based on experiments alone. These computational prediction approaches should be capable of identifying the potential DTIs in a timely manner. Matrix factorization methods have been proven to be the most reliable group of methods. Here, we first propose a matrix factorization-based method termed ‘Coupled Matrix–Matrix Completion’ (CMMC). Next, in order to utilize more comprehensive information provided in different databases and incorporate multiple types of scores for drug–drug similarities and target–target relationship, we then extend CMMC to ‘Coupled Tensor–Matrix Completion’ (CTMC) by considering drug–drug and target–target similarity/interaction tensors. Results: Evaluation on two benchmark datasets, DrugBank and TTD, shows that CTMC outperforms the matrix-factorization-based methods: GRMF, $L_{2,1}$-GRMF, NRLMF and NRLMF$\beta $. Based on the evaluation, CMMC and CTMC outperform the above three methods in term of area under the curve, F1 score, sensitivity and specificity in a considerably shorter run time.
Publisher
Oxford University Press (OUP)
Subject
Molecular Biology,Information Systems
Reference33 articles.
1. Machine learning approaches and databases for prediction of drug–target interaction: a survey paper;Bagherian;Brief Bioinform,2020
2. Nrlmf$\beta $: beta-distribution-rescored neighborhood regularized logistic matrix factorization for improving the performance of drug–target interaction prediction;Ban;Biochem Biophys Rep,2019
3. Virtual screen for ligands of orphan g protein-coupled receptors;Bock;J Chem Inf Model,2005
4. A singular value thresholding algorithm for matrix completion;Cai;SIAM J Optim,2010
5. Exact matrix completion via convex optimization;Candes;Found Comput Math
Cited by
16 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献