At the University of Macau (UM), the State Key Laboratory of Quality Research in Chinese Medicine (SKL-QRCM) and the Institute of Chinese Medical Sciences (ICMS) are working closely with the Faculty of Health Sciences, Faculty of Science and Technology, Zhuhai UM Science & Technology Research Institute, and State Key Laboratory of Internet of Things for Smart City to conduct interdisciplinary studies. They focus on the application of advanced bioactive materials, synthetic biology, and artificial intelligence in Chinese medicine research.

 

Promoting skin tissue repair with natural polysaccharide drugs

 

Many active ingredients of Chinese medicine are difficult for the human body to absorb. To address this, experts at UM are developing innovative materials derived from Chinese medicine to enhance the efficacy of these active ingredients in the body, with a focus on bioactive materials that can induce cellular activity or tissue regeneration. A team led by Wang Chunming, professor in SKL-QRCM and ICMS, has made significant progress. They extracted a polysaccharide dressing called EUP3 from Eucommia, a traditional Chinese medicinal herb known for promoting wound healing, which has shown notable effects on chronic wounds on the feet of diabetic mice. The team completed basic research in 2019, achieved technological translation in 2022, and initiated preclinical testing in 2023. 

 

Prof Wang’s team is developing these active polysaccharide dressings into formulations and conducting clinical trials in Class A tertiary hospitals in mainland China. They are also developing other polysaccharide-based products derived from Chinese medicine. Notably, an alcohol-free, antibacterial hand sanitising gel containing glucomannans from Bletilla striata is already on the market.

 

On another front, Prof Wang’s team has recently discovered a distinctive oligosaccharide fraction and is collaborating with Sinopharm Group to develop it into a medical device. This substance can guide regulatory T cells (or Tregs, a type of immune cells) to gather around hair follicles, thereby accelerating hair growth in mice. ‘This research demonstrates the precise immune-modulating function of glycan materials,’ Prof Wang says. ‘It addresses the issue of traditional polysaccharide materials exhibiting varied activity with inconsistent therapeutic effects. This discovery unlocks the potential for safer, more targeted treatments based on Chinese medicine polysaccharides, with promising applications in the repair of skin and its appendages.’

 

Discovering chemical defence systems of plants

 

UM researchers are also investigating how active ingredients in Chinese medicinal plants inhibit pathogen invasion, with the aim of developing more stable and effective plant-based pesticides to reduce reliance on chemical pesticides. In recent years, a team led by Wan Jianbo, professor in SKL-QRCM and ICMS, in collaboration with experts from Beijing University of Chinese Medicine and Southwest Forestry University, made a breakthrough. They have discovered that Panax notoginseng (a type of ginseng and a key ingredient in Yunnan Baiyao) has a two-component chemical defence system mediated by specific enzymes, which helps protect the plant from pathogens.

 

Prof Wan explains that plants produce a series of secondary metabolites when exposed to various environmental stresses, and this chemical defence mechanism is essential for their survival. His research team found that the defence system in Panax notoginseng consists of a specific enzyme (β-glucosidase) and a class of protopanaxadiol-type saponins. When the plant is infected by pathogenic fungi, enzymes released by these fungi disrupt the integrity of chloroplasts (organelles in plant cells responsible for photosynthesis), thereby activating the plant’s defence system. The β-glucosidase enzyme then selectively hydrolyses the glycosides in the saponin molecules, producing a potent active substance to combat the pathogens.

 

‘We have also identified similar two-component defence systems in other medicinal Panax species, such as Asian ginseng and American ginseng,’ adds Prof Wan. ‘This discovery provides insights for developing plant-based pesticides, which can help reduce the excessive use of chemical pesticides in the cultivation of medicinal ginseng and support sustainable practices in Chinese herbal medicine production.’

 

Speeding up drug screening with artificial intelligence

 

Artificial intelligence enables scientists to analyse vast amounts of data, including combinations of traditional Chinese medicine formulas, pharmacological mechanisms, formulation development, and clinical trial results, accelerating the discovery of potential drugs. A team led by Lu Jiahong, deputy director of ICMS and associate professor in SKL-QRCM, has collaborated with partners such as the University of Oslo in Norway, Wenzhou Medical University, and MindRank (a drug discovery company). They have developed an advanced machine-learning algorithm for drug screening by combining the AI-assisted drug screening platform with cells, C. elegans, and mouse models of Alzheimer’s disease, and identified several small-molecule compounds from Chinese medicinal plants with potential for treating Alzheimer’s disease.

 

According to Prof Lu, his team pre-trained a representation model incorporating multi-dimensional molecular information from data on 19 million small molecules sourced from two databases. Following this, the team screened 3,724 natural small molecules and eventually identified 18 for further validation.

 

Their efforts led to the discovery of two promising compounds: the natural flavonoid kaempferol from sand ginger and the stilbenoid rhapontigenin from Gnetum cleistostachyum. ‘We found that these two compounds significantly improved neurodegenerative symptoms in mouse models of Alzheimer’s disease, reducing pathological markers such as the aggregation of amyloid plaques and tau protein, while also improving their learning and memory abilities,’ Prof Lu says. ‘This discovery lays a foundation for our future research into using mitochondrial activation strategies to treat Alzheimer’s disease.’

 

Supporting drug design through algorithm platform

 

Meanwhile, a team led by Ouyang Defang, associate professor in SKL-QRCM and ICMS, has developed a machine learning framework called DeepCSP to address the challenges of traditional crystal structure prediction. ‘The crystal structure of a drug directly affects its safety, efficacy, and production efficiency,’ says Prof Ouyang. ‘Different crystal structures also affect the absorption, stability, and efficacy of drugs in the human body. Given the complex and variable nature of Chinese medicine components, finding stable crystalline forms is often a challenge.’ According to Prof Ouyang, DeepCSP, which integrates generative adversarial networks with molecular graph convolutional networks, can rapidly generate potential crystal structures and predict their stability, and the whole process takes only a few minutes.

 

Prof Ouyang adds that formulation design is a crucial stage in drug development, which involves the testing of a drug’s physical and chemical properties as well as its release mechanisms. However, traditional formulation design is time-consuming and costly as it relies heavily on extensive experimentation and experience. To streamline this process, Prof Ouyang’s team has launched the Formulation AI platform. This platform integrates drug formulation databases with advanced AI algorithms to optimise drug design process, improving efficiency and accuracy while reducing reliance on experiments.

 

According to Prof Ouyang, Formulation AI can predict and evaluate 17 key characteristics of solubility-enhancing formulations for poorly soluble drugs in six delivery systems: cyclodextrin complexes, solid dispersions, phospholipid complexes, nanocrystals, self-emulsifying systems, and liposomes. ‘Formulation AI can provide rapid predictions without complex theoretical calculations or laboratory testing, transforming formulation development from an experience-driven process to a data-driven one,’ Prof Ouyang says. ‘Over 300 leading pharmaceutical companies and research institutes are using the platform.’

 

Advancing research in synthetic biology for Chinese medicine

 

Many medicinal plants are scarce and highly susceptible to factors such as cultivation environment and climate, leading to variability in both quality and active ingredient content. To address this, researchers at UM are exploring ways to simulate the biosynthesis of active ingredients in Chinese medicine. By constructing artificial biological systems and using synthetic methods, they aim to stabilise the extraction of active ingredients. Additionally, ICMS and the Tianjin Institute of Industrial Biotechnology of the Chinese Academy of Sciences have been jointly training doctoral students since 2023. The two parties are also working on the development of a joint laboratory for synthetic biology in Chinese medicine.

 

Driving innovation in Chinese medicine through interdisciplinary research

 

UM’s SKL-QRCM works closely with research institutes both within and outside the university. Their collaborative efforts promote interdisciplinary research in the field of Chinese medicine, open up new avenues for the sustainable development of the Chinese medicine industry, expand the global influence of Chinese medicine, and make greater contributions to the development of the ‘big health’ industry.

Chinese & English Text / Gloria Kuok, Davis Ip

Photo / Jack Ho, with some provided by the interviewees

Source: UMagazine ISSUE 30

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