Background: Prediction of drug-target interactions is an essential step in drug discovery. Given drug-target interactions network, the objective of this task is to predict probable missing edges from known interactions. Computationally predicting drug-target interactions is an appropriate alternative for the time-consuming and costly experimental process of drug-target interaction prediction. A large number of computational methods for solving this problem have been proposed in recent years.
Objective: In recent years, several review articles have been published in the field of drug-target interactions prediction. Compared to other review articles, this paper includes a qualitative analysis in the form of a framework, a drug-target interactions prediction (DTIP) framework.
Methods: The framework consists of three sections. Initially, a classification has been presented for drug-target interactions prediction methods based on the link prediction approaches used in these methods. Secondly, general evaluation criteria have been introduced for analyzing approaches. Finally, a qualitative comparison is made between each approach in terms of their advantages and disadvantages.
Results: By providing a new classification of the drug-target interactions prediction approaches and comparing them with the proposed evaluation criteria, this framework provides a convenient and efficient way to select and compare the methods. Moreover, using the framework, we can improve these techniques further.
Conclusion: This paper provides a study to select, compare, and improve chemogenomic drugtarget interactions prediction methods. To this aim, an analytical framework is presented.
[http://dx.doi.org/10.2174/1381612822666160418121534] [PMID: 27087598]
[http://dx.doi.org/10.2174/1389203720666190123164310] [PMID: 30674253]
[http://dx.doi.org/10.1093/nar/gkt1223] [PMID: 24288371]
[http://dx.doi.org/10.1038/s41467-017-00680-8] [PMID: 28924171]
[http://dx.doi.org/10.2174/1573409915666190613113822] [PMID: 31198115]
[http://dx.doi.org/10.1016/j.compbiolchem.2011.10.003] [PMID: 22099632]