AI-Designed Dual-Locked Prodrugs in M-cell–Targeted Oral Nanoliposomes for Multi-Target Malaria Killing

Bagratee et al. (2024) highlight the promise of hybrid antimalarials; Chai et al. (2025) demonstrate cRGD–PDA oral nanoliposomes that home to Peyer’s patches and release cargo in parasite-like pH/GSH environments while depleting GSH; Noviandy et al. (2024) show SHAP-interpretable ML can rationalize structure–activity rules. This project integrates all three: design “dual-locked” hybrids that remain inert until (1) falcipain (or plasmepsin) cleavage separates the molecule and (2) disulfide or boronate linkers react with high parasite GSH or ROS to release two complementary actives (e.g., a DHODH or PfNMT inhibitor plus an artemisinin analog). SHAP-guided QSAR prioritizes linker chemistries and substituents that maximize on-target activation and minimize off-target toxicity. Encapsulation in cRGD–PDA nanoliposomes (Chai et al.) enhances oral bioavailability, bypasses first-pass metabolism, and coordinates parasite-triggered release while also depleting GSH to tip the redox balance. Relative to current single-trigger prodrugs or simple hybrids, the novelty is mechanism orthogonality plus dual activation, which should lower resistance propensity (Cheuka et al., 2024) and improve therapeutic index. Head-to-heads against artemisinin-resistant k13 lines and calcium-disruptor combinations (Chia et al., 2021) would test whether multi-target, multi-trigger logic outperforms monotherapies and conventional combos.

References:

1. Exploring the Recent Pioneering Developments of Small Molecules in Antimalarial Drug Armamentarium: A Chemistry Prospective Appraisal. Tameika Bagratee, Ritika Prawlall, Thabani Ndlovu, Sinqobile Sibisi, Sisa Ndadane, B. Shaik, M. Palkar, Raghavachary Gampa, R. Karpoormath (2024). Chemistry and Biodiversity.
2. Oral nanoliposomes functionalized with cRGD and polydopamine for enhanced antimalarial efficacy of disulfide bond-modified dihydroartemisinin prodrug. Liqing Chai, Xiaomin Niu, Xiaoning Li, Jingjing Han, Fugui Guo, Rongrong Wang, Xiaohui Zhou, Xiaozhou Dong, Guoshun Zhang, Rui-li Wang, Guolian Ren (2025). Drug Delivery.
3. An Interpretable Machine Learning Strategy for Antimalarial Drug Discovery with LightGBM and SHAP. T. R. Noviandy, Ghalieb Mutig Idroes, Irsan Hardi (2024). Journal of Future Artificial Intelligence and Technologies.
4. Emerging Drug Targets for Antimalarial Drug Discovery: Validation and Insights into Molecular Mechanisms of Function.. P. Cheuka, Paul Njaria, G. Mayoka, Evelyn Funjika (2024). Journal of Medicinal Chemistry.
5. High-Content Phenotypic Screen of a Focused TCAMS Drug Library Identifies Novel Disruptors of the Malaria Parasite Calcium Dynamics.. W. Chia, Maria G. Gomez-Lorenzo, Isabel Castellote, J. Tong, Rajesh Chandramohanadas, Trang Thi Thu Chu, Wanxiang Shen, M. Go, Cristina de Cózar, Benigno Crespo, M. J. Almela, Fernando Neria-Serrano, Virginia Franco, F. Gamo, K. Tan (2021). ACS Chemical Biology.