Development of in silico methodology for siRNA lipid nanoparticle formulations
Small interfering RNA (siRNA) gene silencing therapy has great potential for treating multiple diseases. The lipid nanoparticle (LNP) technology for siRNA delivery succussed in clinical treatment. However, the formulation design of siRNA-LNP still faces enormous challenges. Current research aims to develop an integrated computer methodology for the rational design of siRNA-LNP formulations.
Highlights
• Novel in silico formulation development methodology was applied in siRNA-LNP design.
• LightGBM was built to predict the knockdown efficiency of siRNA-LNP delivery.
• The experiment validated the accuracy of the ML model.
• MD simulation explained the interaction between siRNA and excipients.
The machine learning (ML) algorithm lightGBM was built to predict the knockdown efficiency of siRNA-LNP in vitro and in vivo delivery and reached good accuracy with 80% and 78.89% in the validation set. Further siRNA experiments well validated the ML model. Moreover, molecular dynamic (MD) simulation was utilized to investigate the molecular structure of siRNA-LNP. In conclusion, a novel integrated computer methodology based on ML, experimental, and MD simulation was successfully developed for siRNA-LNP formulation design.
Haoshi Gao, Stanislav Kan, Zhuyifan Ye, Yuchen Feng, Lei Jin, Xudong Zhang, Jiayin Deng, Ging Chan, Yuanjia Hu, Yongjun Wang, Dongsheng Cao, Yuanhui Ji, Mingtao Liang, Haifeng Li, Defang Ouyang,
Development of in silico methodology for siRNA lipid nanoparticle formulations,
Chemical Engineering Journal,
Volume 442, Part 1, 2022, 136310, ISSN 1385-8947,
https://doi.org/10.1016/j.cej.2022.136310.