Integrated artificial neural network analysis and functional cell based affinity mass spectrometry for screening a bifunctional activator of Ca2+ and β2AR in aconite

Abstract

Arrhythmia, a common heart disease, is an abnormal frequency or rhythm of heartbeat caused by the origin or conduction obstacle of the heart. Aconite (Fuzi) has been regarded as an effective cardiotonic agent in traditional Chinese medicine (TCM), but it sometimes induces cardiac toxicity, such as arrhythmia, in the clinic. It is still a challenge to identify the active ingredients related to the therapeutic effect or toxicity in the application of aconite. To clarify which ingredient or derivative plays a key role of reducing toxicity and improving efficiency in the use of aconite, a serum pharmacology approach integrated with metabolomics and artificial neural network (ANN) analysis was used to in vivo screen Ca2+ and β2AR regulators from the extracts of Heishunpian (HSP), which a processed lateral root of aconite. In addition, β2AR transfected CHO and myocardium H9C2 functional cells-based affinity mass spectrometry (AMS) screening tests were carried out for evaluating the active ingredients in vitro. The results demonstrated that the monoester diterpenoid alkaloids (MDAs) represented by fuziline were the key bifunctional activators that could activate Ca2+ and β2AR simultaneously. The effective compatibility of the calcium antagonists could regulate the heart rhythm to alleviate arrhythmia while maintain their cardiotonic effect, which was induced by aconite. In this study, ANN analysis based on serum pharmacology combined with AMS screen, which utilized with functional cells presented a powerful analytical strategy to the discovery and evaluation of active ingredients from a complex system.