The Division of Materials Research in the Mathematical and Physical Sciences Directorate and the Division of Chemical, Bioengineering, Environmental and Transport Systems in the Engineering Directorate contribute funds to this CAREER award. It supports research, educational, and outreach activities to advance the fundamental understanding and design of nanomaterials. Spherical metal nanoparticles less than 10 nanometers in diameter are promising materials for biomedical applications because they can circulate in the bloodstream for long periods of time and interact with target cells. Some applications, such as the delivery of nucleic acids, require nanoparticles to enter the cell interior by crossing the cell membrane - the barrier that separates the cell interior from the environment - without damaging the cell. A small number of nanoparticles have exhibited this desirable cell entry behavior, but the mechanisms underlying this behavior are not understood. Consequently, general rules for designing nanoparticles that can efficiently cross the cell membrane do not exist.
The PI will utilize a combination of computational methods to address this knowledge gap and test hypotheses to understand how the properties of nanoparticles affect their interaction with cell membranes. Such methods permit the analysis of nanoparticle properties and interactions that are difficult to discern experimentally and to gain insight into the fundamental mechanisms by which nanoparticles enter cells. New machine learning methods will be further developed to predict how nanoparticle properties can be synthetically tuned to facilitate cell entry. This computational approach will permit the creation of new types of nanoparticles more rapidly than would be possible through experiments alone, enabling the rational design of next-generation nanomaterials with various biomedical applications.
This award also supports integrated education and outreach activities. The PI will create visually appealing, interactive, and easily accessible computer simulations that illustrate molecular-scale phenomena. These simulations will be used as a “computational microscope†to demonstrate nanoscale phenomena to the public and grade 6-12 students during events hosted on the University of Wisconsin-Madison campus. They will also be integrated into a range of undergraduate chemical engineering courses and disseminated broadly through online resources. The project will further help train the next generation of scientists in computational science by providing research opportunities for undergraduate students from underrepresented groups and local high school teachers.
This CAREER award supports research, and integrated educational, and outreach activities to advance the fundamental understanding and design of functionalized nanomaterials. Designing materials to efficiently deliver cargo to intracellular targets without adverse side effects would have a transformative impact on biomedical applications including protein and drug delivery, gene editing, and bioimaging. Surface-functionalized gold nanoparticles have the potential to achieve this goal, but a longstanding challenge is designing nanoparticles that can enter cells without being trapped in endosomes and without disrupting the cell membrane. Surprisingly, some nanoparticles can non-disruptively penetrate into cells by translocating across the cell membrane, potentially enabling exciting new avenues for intracellular delivery. However, cell penetration mechanisms remain largely unknown, inhibiting the optimization and design of cell-penetrating nanoparticles.
To address this knowledge gap, this project will use molecular dynamics simulations at multiple length scales to understand the thermodynamic and kinetic factors that influence the insertion of nanoparticles into lipid bilayers and test the hypothesis that bilayer insertion predicts cell penetration. The objectives of this project are to: (1) characterize mechanisms of bilayer insertion for different nanoparticle compositions using all-atom simulations with enhanced sampling techniques, (2) determine the impact of bilayer composition on nanoparticle insertion and penetration with coarse-grained simulations, and (3) train machine learning models to discover new classes of synthetically accessible cell-penetrating nanoparticles. Computational predictions of new cell-penetrating nanoparticles will be experimentally verified by collaborators at the University of Wisconsin-Madison. These studies will provide new insight into nano-bio interactions that will impact understanding of diverse classes of nanomaterials and demonstrate how the combination of machine learning and molecular simulation can inform nanomaterial design.
This award also supports integrated education and outreach activities. The PI will design simulation modules that utilize molecular dynamics simulations to illustrate nanoscale phenomena. Modules will be: (1) visually appealing, to engage students and illustrate concepts; (2) interactive, to increase student engagement and improve learning outcomes; (3) accessible, to ensure simulations can be performed without computational expertise; and (4) distributable, to maximize impact without requiring substantial computational resources. Modules will be designed in collaboration with educational experts then integrated into outreach events to impact grade 6-12 students, integrated into classes within the University of Wisconsin-Madison chemical engineering curriculum to engage undergraduate students, and will be disseminated online to the broader nanomaterials education community. Module development will also broaden participation by providing opportunities for undergraduates from underrepresented groups to contribute to the project’s research activities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
