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Professor Zhang Ge’s team develops a new strategy for virtual screening of natural products targeting non-coding nucleic acid miRNA


A research team led by Professor Zhang Ge, Director of the Technology Development Division and Associate Director of Law Sau Fai Institute for Advancing Translational Medicine in Bone and Joint Diseases; Professor Lyu Aiping, Dean of Chinese Medicine and Dr. Kennedy Y.H. Wong Endowed Chair of Chinese Medicine; and Professor Zhang Baoting, Assistant Director of the School of Chinese Medicine at The Chinese University of Hong Kong, has developed a novel drug discovery strategy for the virtual screening of natural products for microRNAs (miRNAs).  The findings of their research were recently published in the world-renowned journal Advanced Science (


The miRNA is a ribonucleic acid (RNA) molecule with a length of 21 to 23 nucleotides that is widely present in eukaryotes and can regulate gene expression.  A large number of studies have confirmed that miRNA plays an important role in many pathophysiological processes.  Through the analysis of miRNA databases of different species, the team found that miRNA and messenger RNA (mRNA) can form a unique loop structure during the interaction process.  This loop structure is very close to the spatial position of the Argonuate (AGO) protein it guides.  The complex composed of miRNA, mRNA and AGO protein has a high degree of structure-based drug target.  Therefore, the teamproposed to combine the structure-based and knowledge-based approaches to perform virtual drug screening for miRNA targets.  After clarifying the virtual screening strategy, it is necessary to consider the source of small molecule compounds for screening.  It is very promising to select lead compounds that can target a complex composed of miRNA and mRNA and AGO protein from a vast array of traditional Chinese medicine and natural products.


Mr. Wan Youyang, a senior researcher at the Institute of Integrated Bioinformedicine and Translational Science and also a key member of the team, developed a knowledge-based model with the application of machine learning algorithms to provide the loop (miRNA and mRNA non-complementary regions) and AGO-acting small molecules.  The corresponding binding sites were then predicted according to the size of the binding free energy with structure-based model.  The MS results of the combination of small molecules with loops and the pull-down experiments based on AGO proteins confirmed the reliability of the novel virtual screening strategy.  The team found two sets of compounds from the vast database of traditional Chinese medicine and natural products, which can target the miRNA214-ATF4-AGO complex and the miRNA214-TRAF3-AGO complex, respectively, and then through a series of in vitro cell activity verification experiments, two natural products, namely small molecules OB-4 (from locust tree) and OC-3 (from rut) were selected.


Dr. Ni Shuaijian and Ph.D. student Wang Luyao from the team of Professor Zhang Ge; Dr. Guan Daogang from the team of Professor Lyu Aiping; and Dr. Zhuo Zhenjian from the team of Professor Zhang Baoting were also involved in the project.