Unravelling the multifaceted actions of neurosteroids: Machine learning and in vitro screening for novel target discovery.

background and purposeNeurosteroids (NS) modulate neuronal function and are promising therapeutic agents for neuropsychiatric disorders. NS analogues are approved for treating postpartum depression and are of interest in other disorders. Gamma-aminobutyric acid type A (GABA EXPERIMENTAL APPROACH: We performed hypothesis-generating in silico analyses using machine learning and broad in vitro biological screens to assess the range of actions of NS analogues of varying structural attributes. We employed machine learning for molecular similarity analysis and network pharmacology to elucidate likely targets. KEY

resultsThis analysis confirmed likely targets beyond GABA CONCLUSIONS AND IMPLICATIONS: NS compounds are ascendant treatments in neuropsychiatry, but their full spectrum of actions remains unclear. This virtual and biological screening discovery approach opens new vistas for exploring the mechanism of NS analogues. The multifaceted approach provides an unbiased, holistic exploration of the potential effects of NS compounds across various molecular targets and provides a platform for future validation studies to aid drug discovery.