We show that in silico target prediction appears to have potential in assessing new psychoactive compounds where experimental data are scarce.
This abstract is provided here as a convenience only. Check the publisher's website (if available) for the definitive version.
OBJECTIVE: This study exemplifies computer-aided (in silico) approaches in assessing the risks of new psychoactive substances emerging in the European Union. In this work, we (i) consider the potential of Ostarine exhibiting psychoactivity and (ii) anticipate potential activities and toxicities of 4-methylamphetamine.
METHOD: The approach, termed in silico target prediction, suggests potential protein targets modulated by compounds given their chemical structure. This is achieved by first establishing the associations between chemical structure and protein targets using data from the bioactivity database, ChEMBL, via the use of two different computational algorithms. On the basis of the associations, protein targets and consequently the mode of action of novel compounds were predicted.
RESULTS: For Ostarine, none of the targets anticipated are currently known to elicit psychoactivity. Furthermore, Ostarine is unlikely to cross the blood-brain barrier to reach relevant target sites on the basis of its physicochemical properties. For 4-methylamphetamine, toxicities were anticipated, that is, serotonin syndrome (based on the prediction of SERT) and other effects similar to related substances, that is, methamphetamine.
CONCLUSION: From the two case studies, we showed that in silico target prediction appears to have potential in assessing new psychoactive compounds where experimental data are scarce. The applicability domain of target predictions when applied to psychoactive compounds needs to be established in future work.