The Human Kinome Targeted by FDA Approved Multi-Target Drugs and Combination Products: A Comparative Study from the Drug-Target Interaction Network Perspective

Abstract

The human kinome is one of the most productive classes of drug target, and there is emerging necessity for treating complex diseases by means of polypharmacology (multi-target drugs and combination products). However, the advantages of the multi-target drugs and the combination products are still under debate. A comparative analysis between FDA approved multi-target drugs and combination products, targeting the human kinome, was conducted by mapping targets onto the phylogenetic tree of the human kinome. The approach of network medicine illustrating the drug-target interactions was applied to identify popular targets of multi-target drugs and combination products. As identified, the multi-target drugs tended to inhibit target pairs in the human kinome, especially the receptor tyrosine kinase family, while the combination products were able to against targets of distant homology relationship. This finding asked for choosing the combination products as a better solution for designing drugs aiming at targets of distant homology relationship. Moreover, sub-networks of drug-target interactions in specific disease were generated, and mechanisms shared by multi-target drugs and combination products were identified. In conclusion, this study performed an analysis between approved multi-target drugs and combination products against the human kinome, which could assist the discovery of next generation polypharmacology.

Coral: Clear and Customizable Visualization of Human Kinome Data

“…These proteins have been implicated in a variety of diseases including pathological hypertrophy (Heineke and Molkentin, 2006; Vlahos et al, 2003), rheumatoid arthritis (Gaestel et al, 2009; Patterson et al, 2014), and cancer (Fleuren et al, 2016; Ventura and Nebreda, 2006). As a result, protein kinases are common candidates for drug targets and are increasingly the focus of large-scale studies (Cohen, 2002; Cohen and Alessi, 2013; Duong-Ly and Peterson, 2013; Hu et al, 2017; Li et al, 2016; Wu et al, 2016). High-throughput approaches to study kinase abundance and activity–including proteomics, genomics, and kinase profiling screens–have created a need to visualize and interpret results in the greater context of the human kinome.…”

“…This dendrogram was then modified in reference to other trees and manually refined into an aesthetically pleasing image in which branches are colored by kinase group and kinase names are HTML links to websites with information specific to each kinase (www.cellsignal.com). Several groups have manually modified this image, encoding qualitative or quantitative kinase information in either branch color (Fleuren et al, 2016; Phanstiel et al, 2011) or in the color and size of circular nodes placed at the end of each branch (Hu et al, 2017; Li et al, 2016; Wu et al, 2016). These figures are powerful tools for data interpretation and communication but are labor intensive to create and often infeasible for large or more complex experimental data sets.…”

Identification of novel immune‐relevant drug target genes for Alzheimer's Disease by combining ontology inference with network analysis

“…Due to the time‐consuming and extremely high cost of modern drug discovery, computational methods have emerged as one of the most effective approaches for the discovery of new targets . However, these computational methods focused mainly on single biologic perspective, such as pathway profile‐based, gene expression‐based, and similarity‐based methods.…”

A Definition of “Multitargeticity”: Identifying Potential Multitarget and Selective Ligands Through a Vector Analysis

“…We selected 10 known FDA-approved drugs labeled multikinasedirected drugs as models of multitarget drugs (Li et al, 2016). The full list of the drugs we considered can be found in the Supplementary Information.…”