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

Abstract

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 Ichthyophthirius multifiliis, 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. multifiliis 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 in vitro and in vivo 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, in silico and experimental analyses identified CDK2 as a molecular target for compound new-1, which disrupted the reproduction and exerts parasiticidal activity against I. multifiliis. Additionally, compound new-1 exhibited antifungal activity against Aspergillus flavus 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.