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    The past decades of research have demonstrated the potentials of nanomaterials in treating diseases or delivering drugs. These potentials of nanomaterials are rooted in their specific behaviors in biosystems and have provided an opportunity to solve the serious diseases and health problems faced by the human race. Developing theoretical models to predict the behaviors of nanomaterial in biosystems will accelerate the development of biomedical applications, which, however, is still a huge challenge. We are interested in theoretical and computational study of the fundamental interactions between nanomaterials and molecules in biosystems, aiming at developing theories to systematically predict nanomaterials’ behaviors in living biosystems and to computationally design nanomedicine.

We are particularly interested in theory and modeling of the following two topics.

    1) Nano-catalysis for cell signaling. In this topic, we focus on the in vivo catalytic role of nanomaterials that contribute to regulate cell signaling pathways relevant to tumor therapy. Considerable progress has been made by our group. A set of theories describing the rule how nanocatalysis drives the chemical reactions of reactive oxygen species in living cells have been proposed and a system of theories describing the modulation of apoptosis, ferroptosis, and hypoxia signaling pathways by nanocatalysis has been initially established. The results have been verified by experimental studies of catalytic nanomaterials in tumor chemodynamic therapy, alleviating tumor hypoxia, and bio-antioxidant, and achieved the breakthrough from trial and error to computational design for the experiments. We will upgrade our research from single-reaction design to reaction-network design on the basis of the previous work, and develop an efficient design schemeindependent of high performance computing by using machine learning to achieve the large-scale and accurate design of biomedical functions of nanomaterials.

    2) Nano-adsorption for brain drug delivery. This on-going project is joint with Prof. Tomasz Puzyn (University of Gdańsk, Gdańsk, Poland). Penetrating the blood-brain-barrier (BBB) is one of the biggest challenges in developing new drugs for treating neurodegenerative diseases. Nanoparticles have attracted great attention as potential brain drug delivery carriers to penetrate the BBB. Computer-aided design of nanoparticle-based drug delivery carriers has been employed to support in vitro and in vivo experiments. While classical molecular simulations are limited by computational resources and time required, machine learning techniques have brought new solutions, but their applications in nanomedicine are still uncommon. In view of this background, the proposed project aims to develop an integrated “molecular modelling-machine learning (MM-ML)” approach for the design of brain-targeted drug delivery systems. This project will focus on developing new methods to investigate the properties of nanomaterials. The expected progress involves the relationship between the structures of nanoparticles, microenvironment and their performances, which will have a significant impact on materials science and open up new ideas for the design of nanoparticle-based brain drug delivery carriers.