Research Foundation CUNY - Advanced Science Research Center

NSF Awards · FY 2026 · 2026-06

Natural proteins perform critical functions in our bodies. Proteins can be designed to perform new functions that help society. For example, designed proteins could detect diseases, transport drugs, generate clean fuels, and defuse toxins. However, designed proteins perform worse than natural ones. This project aims to use lessons from natural proteins to produce better designed proteins. This will be done by testing whether existing designed proteins move differently than natural ones. The work will also use artificial intelligence (AI) to design new proteins with different types of motions. Overall, this research will leverage AI to help design powerful new proteins. This will pave the way for the use of designed proteins in biotechnology, medicine, and chemical manufacturing. To connect with the public, AI-powered protein design competitions will be held in classrooms nationwide, along with science comedy events. This project advances NSF’s priorities in AI, biotechnology, and advanced manufacturing. Protein design has vast potential to generate new proteins that address unmet societal needs. For example, designed proteins could detect disease biomarkers, catalyze the creation of clean fuel sources, and defuse toxic chemicals in our environment. However, the functions of designed proteins to date pale in comparison to those of natural proteins, preventing us from achieving these goals. Notably, most protein design efforts to date have focused on stabilizing a single rigid target structure. By contrast, natural proteins must move to function, including induced fit upon ligand binding, catalytic motions in enzymes, and allosteric conformational changes. The hypothesis underlying this project is that existing designed proteins populate unnatural conformational landscapes that are too rigid, too dynamic, or otherwise different from those of highly functional natural proteins – and that explicitly designing for desired conformational landscapes will improve the functions of designed proteins. The recent revolution in fast, highly accurate AI-based protein design and structure prediction algorithms presents a prime opportunity to test these ideas. First, patterns of “hidden” conformational landscapes will be contrasted in crystal structures of traditional physics-based designed proteins, new AI-based designed proteins, and fold-matched natural proteins. Second, sequence space and conformational landscapes will be iteratively explored with AI-based methods for rigid vs. dynamic proteins. Third, the set of conformational inputs needed for efficient enzymatic function will be defined using crystallographic ensembles and AI-based multistate design, coupled to biochemical and biophysical experiments. This project will illuminate new paths forward for rational design of functional proteins to address myriad challenges in biotechnology, medicine, and other industries, and will help prepare the next generation of AI-aware protein scientists. 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.

NSF Awards · FY 2025 · 2025-05

Non-technical summary. Plastics are indispensable materials in modern society because they are lightweight, cheap, flexible, and durable. These properties make plastics useful in daily consumer applications (such as in packaging materials) as well as in high performance applications (such as adhesives, electronics, or even body armor). However, we currently rely on a small set of chemical building blocks to create most plastics, which makes it difficult to repurpose one type of plastic for other applications and to safely and easily degrade plastics at their end of life. A new set of chemical building blocks will be used—based on naturally occurring biological molecules—to create degradable plastics with custom properties. A new method is being developed to link together short biomolecules into long polymer chains (which are the general building blocks of plastics). By using a small set of biomolecules but arranging them along the chain in different sequences, it is expected that plastics with a wide range of properties (and thus, applications) can be created. It is also hypothesized that the biomolecule arrangement will control how rapidly the plastics break down in water or soil conditions, thereby leading to plastics that can be safely degraded in the environment. Success of this proposed research may lead to a new class of plastics that are created from renewable resources, degraded safely in the environment, having tailored properties to suit a wide range of applications. Technical summary. Sequence-specific polymers are ubiquitous in biology, and synthetic analogues have shown promise as building blocks for materials with highly tunable properties. However, current approaches to synthesize sequence-specific polymers generally suffer from some combination of low efficiencies and yields, high cost, and an inability to generate polymer chains with high enough molecular weights to create free-standing materials. Here it is proposed to use modular short peptides as “macromonomers,” allowing one to synthesize sequence-specific polymers with high molecular weights in a scalable manner via traditional chemical polymerization approaches. Specifically, native di- or tri-peptide molecules will first be coupled together to create a macromonomer that terminates at both ends in the same functional group and thus can be subsequently polymerized into high molecular weight chains using step growth polymerizations. This approach should lead to polymer chains with sufficiently high molecular weights to create free-standing materials and whose sequence and composition are programmed via the initial di- or tri-peptide selection. Based on this sequence specificity and chemical diversity, it is hypothesized that peptide-based plastics can be fabricated with a wide range of tunable structures and bulk properties, analogous to how a biopolymer’s sequence dictates the structure and function of biological molecules and materials. Further, it is hypothesized that the plastics can be degraded in eco-friendly conditions (by enzymes or microbes) in a manner that also depends on the polymers’ sequence. Success of the proposed work may lead to a new class of peptide-based plastics with customizable properties that can be synthesized in a scalable manner. 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.

NSF Awards · FY 2025 · 2025-05

Nontechnical Description This collaborative project will explore how polymers can be designed to leverage electron spin properties using light. This quantum phenomenon offers potential to transform emerging applications in information science and imaging. One promising but unproven way of generating useful spins involves a special class of organic molecules that, when properly designed, can efficiently use light to generate desirable quantum states. In this project the research team will develop a new approach to assemble light harvesting polymers that contain stable radicals to study the flow of energy to the spin center. The discoveries that ensue from these studies will lead to transformative technologies for spintronics, magnetic imaging, and quantum information science. The collaborative approach also focuses on mentorship, collaboration, and inclusion to foster a sense of belonging while expanding access to science. The researchers will promote recruitment and long-term success through initiatives that create pipelines from K-12 to professional careers. Technical Description This project will explore the unique spin characteristics of triplet pairs generated through singlet fission (SF) in macromolecular systems. The research team will develop macromolecular architectures that enable control over exciton dynamics and spin interactions in radical-containing polymers. The research will focus on designing novel multifunctional systems that can harness high spin polarization of the triplet pair multiexciton state to achieve enhanced energy conversion, spin polarization transfer, and optoelectronic applications. The project is structured around two primary objectives: (1) designing and characterizing multiexciton dynamics in radical-containing polymers, and (2) determining the spin and population dynamics to demonstrate the efficacy of spin polarization transfer in these systems. These activities will address significant hurdles hindering substantial progress in applications of SF that span from the lack of fundamental guidelines of multichromophore design in macromolecules to the orchestration of spin polarization transfer pathways to stable radicals. Traditional studies have focused on generating multiple excitons from a single photon, but this project differentiates itself by emphasizing the control and utilization of spin dynamics for energy conversion and quantum information processes. The project’s success will lead to a deeper understanding of the fundamental interactions between triplet pairs and radical spin centers, establishing new paradigms in multiexciton chemistry and molecular spintronics. This will significantly impact emerging technologies such as spintronics, magnetic imaging, and quantum information science by providing foundational knowledge for designing systems with enhanced spin polarization and stability at non-cryogenic temperatures. 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.