Immune thrombocytopenia (ITP) is an autoimmune condition characterized by platelet loss, with autophagy-related proteins such as Beclin-1 significantly contributing to pathogenesis. This research employed a computational structure-based virtual screening (SBVS) approach to identify novel inhibitors that target Beclin-1 as prospective therapies for ITP. A comprehensive virtual screening of an Enamine-AI-Enabled-TF library, succeeded by molecular docking to evaluate binding affinities. ADMET profiling was performed to assess the pharmacokinetic properties (molecular weight (MW), lipophilicity (LogP), total polar surface area (TPSA), solubility (LogS), and potential toxicity risks, including mutagenicity, carcinogenicity, and reproductive toxicity), resulting in the identification of two promising candidates: Z9255356311 and Z9255355469. These candidates were selected based on their advantageous characteristics in absorption, distribution, metabolism, excretion, and toxicity. Molecular dynamics (MD) simulations confirmed the structural stability and binding persistence of these compounds within the Beclin-1 binding pocket. The results establish a robust foundation for subsequent
in vitro
and
in vivo
validation, facilitating the advancement of Beclin-1-targeted therapies for ITP.