Design and Synthesis of Magnolol Derivatives Using Integrated CNNs and Pharmacophore Approaches for Enhanced Parasiticidal Activity in Aquaculture

Aquaculture is a rapidly growing sector of global food production, playing a vital role in poverty alleviation, food security, and income generation. However, it faces substantial challenges, particularly due to infections caused by the protozoan <i>Ichthyophthirius multifiliis</i>, leading to reduced yields and economic losses. In this study, two classes of magnolol derivatives (M1-M26) were synthesized and evaluated for their parasiticidal activity against <i>I. multifiliis</i> theronts and tomonts. Based on the determined EC₅₀ values, two significant convolutional neural networks (CNNs) and pharmacophore models were developed, guiding the design and synthesis of three new compounds. Among these, compound new-1 exhibited superior parasiticidal efficacy both <i>in vitro</i> and <i>in vivo</i> compared to magnolol and the commercial parasiticide methylene blue, with EC₅₀ values of 0.197 and 0.252 mg/L, respectively. Toxicity assays demonstrated that compound new-1 showed no significant harmful effects on goldfish and zebrafish embryos at effective concentrations. Further, <i>in silico</i> and experimental analyses identified CDK2 as a molecular target for compound new-1, which disrupted the reproduction and exerts parasiticidal activity against <i>I. multifiliis</i>. Additionally, compound new-1 exhibited antifungal activity against <i>Aspergillus flavus</i> with a MIC of ∼0.8 mg/mL, suggesting its potential application in food preservation. This study provides valuable insights into the development of magnolol-based agents for aquaculture.