Designing combinational herbal drugs based on target space analysis

Abstract

In this study, by integrating traditional oriental medicine formulas and pharmaceutical drugs, we performed target space analysis between TOM formulas target space and small-molecule drug target space. We tried to provide scientific evidence about the effectiveness of the formulas to treat the main indication with side effects that could come from the use of small-molecule drugs. To do so, we manually curated 46 TOM formulas that are known to treat Anxiety, Diabetes mellitus, Epilepsy, Hypertension, Obesity, and Schizophrenia. Then, the target space analysis was performed between the TOM formula and drugs: (i) both are known to treat the same disease, and (ii) each is known to treat different diseases. Then, the statistical significance of the overlapped target space between the TOM formula and small-molecule drugs was measured using support. Support value distribution from randomly selected target space was calculated to validate the result. The analysis between the TOM formula and small-molecule drugs in which both are known to treat the same disease shows that many targets overlapped between the two medications with a support value of 0.84 and weighted average support of 0.72 for a TOM formula known to treat Epilepsy. Furthermore, support value distribution from randomly selected target spaces showed that the number of overlapped targets is much higher between TOM formula and small-molecule drugs that are known to treat the same disease than in randomly selected target spaces.