Abstract
Drug discovery is a constant struggle to overcome hurdles posed by the complexity of biological systems. One of these hurdles is to find and understand the molecular target and the biological mechanism of action. Although the molecular target has been determined, the true biological effect may be unforeseen also for well-established drugs. Hence, there is a need for novel ways to increase the knowledge of the biological effects of drugs in the developmental process. In this study, we have determined cytokine profiles for 26 non-biological immunomodulatory drugs or drug candidates and used these profiles to cluster the compounds according to their effect in a preclinical ex vivo culture model of arthritis. This allows for prediction of functions and drug target of a novel drug candidate based on profiles obtained in this study. Results from the study showed that the JAK inhibitors tofacitinib and ruxolitinib formed a robust cluster and were found to have a distinct cytokine profile compared to the other drugs. Another robust cluster included the calcineurin inhibitors cyclosporine A and tacrolimus and the protein kinase inhibitors fostamatinib disodium and sotrastaurin acetate, which caused a strong overall inhibition of the cytokine production. The results of this methodology indicate that cytokine profiles can be used to provide a fingerprint-like identification of a drug as a tool to benchmark novel drugs and to improve descriptions of mode of action.
Highlights
One of the most important steps in drug discovery is to identify and validate the target of a new compound
The induced disease state can be transferred by T cells through ex vivo stimulation with ConA [6], which provides a good model for studying drug effects on cytokine production in vitro
The effect on the cytokine production for each drug was analyzed by the fold change (FC) where the cytokine levels from cultures in the presence of drug were divided by the corresponding positive control
Summary
One of the most important steps in drug discovery is to identify and validate the target of a new compound. Identifying the target as well as description of possible alternative targets provide valuable information since the therapeutic effect and possible side effects of the drug candidate can be predicted in the early phase [1]. There is a need for tools to deal with the complex drug mechanism as well as identification of valuable biomarkers and clinical endpoint phenotypes for evaluation of drug effects. This is especially true for compounds developed through phenotypical assays, and for compounds where the molecular target is known. The importance of polypharmacology is increasingly acknowledged adding another level of complexity [2]
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