Computational Insights into Pharmacokinetic Profiling of Amygdalin: An In-Silico Study

Abstract

Amygdalin is a naturally occurring cyanogenic glycoside which has been used as an alternative anti-cancer agent despite controversies surrounding its efficacy and safety. This study utilized computational approaches to investigate the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of amygdalin based on its molecular structure. Amygdalin was modeled in ChemBio3D and submitted to SwissADME and admetSAR servers for ADMET parameter prediction. The in-silico simulations indicated suboptimal pharmacological properties for amygdalin, including low lipophilicity, poor bioavailability, minimal blood-brain barrier permeability and non-compliance with drug-likeness criteria. Additional pharmacokinetic modeling through Simcyp suggested rapid clearance and short half-life after intravenous administration.While toxicity was predicted to be low at regular dosages, the overall pharmacological limitations may pose challenges for amygdalin’s efficacy as an anti-cancer therapy. The computational findings provide comprehensive insights into amygdalin’s drug-like behavior and can inform future in vitro/in vivo investigations on this naturally derived compound.