Prediction of Drug Pathway-based Disease Classes using Multiple Properties of Drugs

Title:Prediction of Drug Pathway-based Disease Classes using Multiple Properties of Drugs

Volume: 19 Issue: 9

Author(s): Lei Chen*Linyang Li

Affiliation:

• College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, China

Abstract:

Background: Drug repositioning now is an important research area in drug discovery as it can accelerate the procedures of discovering novel effects of existing drugs. However, it is challenging to screen out possible effects for given drugs. Designing computational methods are a quick and cheap way to complete this task. Most existing computational methods infer the relationships between drugs and diseases. The pathway-based disease classification reported in KEGG provides us a new way to investigate drug repositioning as such classification can be applied to drugs. A predicted class of a given drug suggests latent diseases it can treat.

Objective: The purpose of this study is to set up efficient multi-label classifiers to predict the classes of drugs.

Method: We adopt three types of drug information to generate drug features, including drug pathway information, label information and drug network. For the first two types, drugs are first encoded into binary vectors, which are further processed by singular value decomposition. For the third type, the network embedding algorithm, Mashup, is employed to yield drug features. Above features are combined and fed into RAndom k-labELsets (RAKEL) to construct multi-label classifiers, where support vector machine is selected as the base classification algorithm.

Results: The ten-fold cross-validation results show that the classifiers provide high performance with accuracy higher than 0.95 and absolute true higher than 0.92. The case study indicates the novel effects of three drugs, i.e., they may treat new diseases.

Conclusion: The proposed classifiers have high performance and are superiority to the classifiers with other classic algorithms and drug information. Furthermore, they have the ability to discover new effects of drugs.

Cite this article as:

Chen Lei*, Li Linyang, Prediction of Drug Pathway-based Disease Classes using Multiple Properties of Drugs, Current Bioinformatics 2024; 19 (9) . https://dx.doi.org/10.2174/0115748936284973240105115444