In silico Target Fishing for Rationalized Ligand Discovery Exemplified on Constituents of Ruta graveolens

The identification of targets whose interaction is likely to result in the successful treatment of a disease is of growing interest for natural product scientists. In the Current Study we performed an exemplary application of a virtual parallel screening approach to identify potential targets for 16 secondary metabolites isolated and identified from the aerial parts of the medicinal plant Ruta graveolens L. Low energy conformers of the isolated constituents were simultaneously screened against a set of 2208 pharmacophore models generated in-house for the in silico prediction of putative biological targets, i.e., target fishing, Based on the predicted ligand-target interactions, we focused on three biological targets, namely acetylcholinesterase (AChE), the human rhinovirus (HRV) coat protein and the cannabinoid receptor type-2 (CB2). For a critical evaluation of the applied parallel screening approach, virtual hits and non-hits were assayed on the respective targets. For AChE the highest scoring virtual hit, arborinine, showed the best inhibitory in vitro activity on AChE (IC50 34.7 mu M). Determination of the anti-HRV-2 effect revealed 6,7,8-trimethoxycoumarin and arborinine to be the most active antiviral constituents with IC50 values of 11.98 mu M and 3.19 mu M, respectively. Of these, arborinine was predicted virtually. Of all the molecules subjected to parallel screening, one virtual CB2 ligand was obtained, i.e., rutamarin. Interestingly, in experimental Studies only this compound showed a selective activity to the CB2 receptor (Ki of 7.4 mu M) by using a radioligand displacement assay. The applied parallel screening paradigm with constituents of R. graveolens on three different proteins has shown promise as an in silico tool for rational target fishing and pharmacological profiling of extracts and single chemical entities in natural product research.