Petr Šulc, assistant professor in the Department of Molecular Sciences at Arizona State University and assistant professor in the Biodesign Center for Molecular Design and Biomimetics, was recently awarded the Faculty Early Career Development (CAREER) Award from the National Science Foundation.
Schulk’s laboratory is highly interdisciplinary, applying methods of statistical physics and computational modeling extensively to problems in chemistry, biology, and nanotechnology. This group is developing new multiscale models for studying interactions between biomolecules. It is particularly relevant to the design and simulation of DNA and RNA nanostructures and devices.
Petr Šulc is an assistant professor in the Department of Molecular Sciences and the Biodesign Center for Molecular Design and Biomimetics at Arizona State University. Photo courtesy of ASU
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“This research award will enable our lab to expand the range of systems under study and design new classes of nanodevices and nanomaterials that incorporate DNA, RNA, proteins, and other molecules. ‘ explained Shulk. “Just as the complex machines we use every day, such as airplanes, cars, and electronic chips, require sophisticated computer-aided design tools to reliably perform their intended function. There is an urgent need in molecular science to have access to such methods.”
Professor Tijana Rajh, Dean of the Department of Molecular Sciences, said: Young faculty members of the Faculty of Molecular Sciences are doing extraordinary work, and Professor Schulk is a role model in this respect. ”
The prestigious CAREER program supports early career development activities for teacher-scholars who most effectively integrate research and teaching within the organization’s mission. Provides each recipient with her five-year research grant.
bionano technology
DNA and RNA are the basic molecules of life. They serve many functions, such as storing and transmitting information within living cells. It also has promising applications in the field of nanotechnology, where engineered DNA and RNA strands are used to assemble nanoscale structures and devices. Shulk explains: Place them in a box and shake them randomly until only the structures you want come out.
This process is called self-assembly, and Šulc and his colleagues use computational modeling and design software to come up with building blocks that reliably assemble into desired shapes at nanoscale resolution.
“Promising applications in this area include diagnostics, therapeutics, and the construction of new materials,” Schulk says. “My lab is developing software to design these blocks and is working closely with experimental groups at ASU and other universities in the US and Europe.”
They are also interested in applying machine learning techniques to biological sequence ensembles, using neural networks to identify DNA or I am designing an RNA sequence.
SMS Junior Faculty Spotlight Video – Petr Šulc
Task
Computer-aided design software is often used in the macroscale world to design computer chips, cars, and airplanes. This allows device behavior to be tested first and optimized in simulation. However, construction at the nanoscale presents multiple challenges. In contrast to our macro world, nanostructures are usually obtained by self-assembly. Self-assembly involves the random diffusion of individual building blocks until they meet and organize into the desired structure.
To obtain more complex structures that self-assemble with high yields, new simulation frameworks that can efficiently and simultaneously accurately represent the assembly and function of nanostructures are needed.
Schulk’s lab develops a new modeling framework that can simulate self-assembled DNA nanostructures.
The research team will use this new framework to optimize nanostructure assembly with high yield and to computationally design new types of reconfigurable nanostructures. The team will then extend the modeling platform to allow the incorporation of other organic/inorganic molecules and materials.
Overall, the award encourages the creation of new nanodevices capable of performing complex tasks that are difficult to achieve experimentally without advanced modeling platforms. This brings the field closer to large-scale industrial use.
To realize the educational component of the project, Schultz’s lab develops new learning opportunities for college students and the general public. Major efforts include developing an online citizen science platform. The platform allows users to design and optimize structures themselves using a simulation platform and crowdsource nanotechnology designs.
