(4p) De Novo Protein Design for Programmable Biomaterials and Delivery

My expertise and passion lie in addressing complex self-assembly challenges through de novo protein design and biomolecular engineering with DNA. My current research focuses on the computational design of both symmetric and quasi-symmetric protein assemblies with tailorable structures, assembly dynamics, and biological functions. This work has recently been recognized with the 2024 Burroughs Wellcome Career Award at the Scientific Interface, supporting my transition to a junior faculty position. In my future lab, I will implement an 'understanding-by-design' approach to create functional supramolecular structures with emergent biological properties via programmed self-assembly. Initial efforts will focus on de novo virus-like particles engineered for modular delivery systems and well-defined microcompartments that act as intracellular nanoreactors. This endeavor aims to synergistically combine computational design with experimental validation, to address pressing challenges in human health and sustainable development.

Research proposal

Throughout my academic career, I have developed a unique combination of expertise in computational protein design, nucleic acid chemistry, and colloidal crystal engineering. During my independent career, I aim to combine computational design with experimental validation to develop genetically encodable macromolecular assemblies that exhibit emergent biological functions at both organelle and cellular levels. My vision is that addressing the challenges in complex living systems requires innovative and systematic solutions, potentially extending beyond the molecular level and our empirical knowledge. These supramolecular solutions will benefit from the precise integration of de novo functional modules, fully genetically encodable, and guided by computational design. My immediate objectives are: 1) Computational design of delivery systems based on de novo protein capsids, followed by lipid bilayer envelopment, for therapeutic and gene-editing applications. They will offer enhanced structural tailorability and safety as compared to conventional viral vectors and may achieve cell-type targeting specificity and delivery of ribonucleoproteins, which are known current limitations of lipid nanoparticles. My study will advance fundamental knowledge of protein design for overcoming delivery barriers and enable programmable cargo packaging and sorting as engineered extracellular vesicles. 2) Building customizable nanoreactors in living cells based on de novo designed 3D protein crystals. As compared to liquid phase condensates, crystalline protein frameworks offer well-defined local environments and structural addressability for studying host-guest interactions involving substrate diffusion, and could serve as potential nucleation sites for interfacing cells with polymeric or inorganic synthetic materials. Knowledge learned from this project will translate into design rules to create customizable microcompartments for programming cellular activities and biosynthesis. Importantly, these emergent functionalities, achievable only through precisely designed macromolecular assemblies, are genetically encodable and not inherent in their individual building blocks at the molecular level. Together, my lab is committed to combining advanced AI-driven computational protein design, programmable assembly, and experimental validation, to create biomaterials capable of being produced by, interfacing with, and integrated into living systems in the context of precision medicine and sustainable development.

Research accomplishments

My previous research has primarily focused on programmable self-assemblies through biomolecular engineering. During my PhD, I discovered particle analogs of electrons in colloidal crystals (Science 2019), where the dynamic nature of DNA bonds allows smaller particles to move freely across unit cells in a superlattice of larger complementary particles. The delocalized spatial distribution of small particles suggests a metallic phase behavior, which challenges the conventional understanding of colloidal crystals that assumes colloidal particles are stationary and occupy specific lattice positions. Furthermore, I established the concept of colloidal valency based upon these small roaming particles to create unprecedented intermetallic phase crystals (JACS 2019, Nat. Mater. 2022). As a synthetic chemist, I created a class of phosphate-based surface ligands for surface functionalizing metal-organic framework nanoparticles (MOF NPs) with biomolecules, including lipids and DNA (Angew. Chemie. 2015, JACS 2017). DNA modified MOF NPs were developed as effective intracellular protein delivery vehicles and modular building blocks for hierarchical colloidal crystal engineering (JACS 2019, Nat. Commun. 2020). Currently I’m a postdoc in the Baker lab working on computational protein design. I co-developed the first general strategy to design de novo 3D protein crystals (Nat. Mater. 2023). X-ray crystallography confirmed the experimental structures match with in silico near-angstrom-level accuracy. These genetically encodable protein crystals exhibit attractive material properties, including robust assemblies, high thermal stability and porosity, and excellent potential for crystal engineering, which opens up new opportunities in synthetic biology. In a subsequent project, I created the first “top-down” approach to design protein architectures with reinforcement learning (Science 2023). Inspired by AlphaGo’s success in mastering the game of Go, I led a team to convert protein design tasks into puzzles defined by custom rules and rewards, which are solved by AI agent with an iterative learning process, employing a RL algorithm termed Monte Carlo tree search (MCTS). I successfully designed the most compact icosahedral protein capsid to date (54 amino acids) and used it to create potent influenza vaccines. The introduction of RL to protein design enables generative molecular engineering to be explored in complex environments and under dynamic control. Through these past research experiences, I have built a comprehensive skill set including computational design, synthetic chemistry, and structural biology. Currently, I'm actively working on developing cellular assays, large-scale screening methods, and screening experiments. Equipped with these tools, I'm poised to fulfill my future research objectives.

Teaching interests

Throughout my academic career, I've been fortunate to benefit from the guidance of exceptional teachers and mentors. Their influence not only shaped my academic identity but also instilled in me the profound importance of education and mentorship as cornerstones to academic success. I firmly believe that promoting diversity is a core value in all facets of a faculty member’s work. I plan to foster an inclusive environment and ensure equal opportunities within my research group and classroom. As a member of the broader science community, I will continue to impact the general public through my service work. During my PhD, I taught 4 quarters of organic and advanced chemistry lab as a teaching assistant at Northwestern University. Beyond classroom teaching, I actively involved in designing assessment criteria, setting up a communication platform for vibrant discussion, and coordinating with the administrative branch. I’ve also developed my role as a scientific mentor. During my Ph.D. and postdoc, I’ve mentored a total of six Ph.D. students, including one who is now a postdoctoral researcher at MIT with academic aspirations. Looking ahead, I am committed to dedicating my efforts towards educating future generations of chemical engineers. Throughout my academic career, I have developed a unique combination of expertise in computational protein design, nucleic acid chemistry, and colloidal crystal engineering, which allows me to teach both experimental and computational courses. Given my background, I am passionate about providing instruction across a broad spectrum of courses at both undergraduate- and graduate-level, such as thermodynamics, kinetics, soft matter and colloidal systems, protein engineering, biotechnology, and crystallization.