The advent of protein design in recent years has brought us within reach of developing a ?nanoscale programing language,? in which molecules serve as operands with their conformational states functioning as logical gates. Combining these operands into larger molecules and molecular complexes through protein engineering will allow us to write and execute ?code? using nanoscale computing agents (NCAs). These agents would respond to any given input and return a desired output signal. While the speed of the ?computation? will be significantly slower than that of inorganic silicon-based computers, one cell can contain more NCAs than the number of CPUs in any supercomputer currently in existence. The ability to utilize natural evolutionary processes would allow code to ?evolve? in the course of computation, thus enabling radically new algorithmic developments. NCAs will revolutionize the studies of biological systems, enable a deeper understanding of human biology and disease, and facilitate development of in situ precision therapeutics. Since NCAs can be extended to novel reactions and processes not seen in biological systems, growth of this field will spark the growth of biotechnological applications with wide-ranging impact, including to fields not typically considered relevant to biology. Unlike traditional approaches in synthetic biology that are based on rewiring of signaling pathways in cells, NCAs are autonomous vehicles based on single chain proteins. NCAs offer an orthogonal and complementary means for controlling cellular phenotypes. In the past 12 years, our group has developed technology toward this end, by engineering proteins that can be controlled by light and small molecules. We designed functional prototypes that have already offered valuable insights in the cellular motility field. Here, we plan to (i) further expand the repertoire of NCA inputs, (ii) include other biological molecules, such as RNA, in our library of NCAs, and (iii) expand the portfolio of methods for ?writing? algorithms at the nanoscale level. The main objectives of this proposal are: (1) Extend the repertoire of inputs for regulation of proteins. We plan to utilize/design proteins that respond to pH and temperature via conformational change in order to modulate the activities of target proteins. (2) Extend our approaches to model and regulate RNA molecules. No tools currently exist for computational evaluation of small molecule binding to RNA (the docking problem). Modeling the structure and dynamics of RNA is challenging due to backbone flexibility. We plan to develop a platform to address both the RNA structure and small molecule docking problems. (3) Develop tools to rationally design allosteric networks in proteins. The technology to ?rewire? allosteric networks in proteins does not exist yet. Capitalizing on our method for mapping allostery, we plan to build a search algorithm that will iteratively rewire communication pathways between distal protein sites. Addressing these challenges will provide a significant leap in technology for programming living cells. While the research directions outlined in this proposal are ambitious, we and others have created the basis for this technology to be feasible and within reach.

Public Health Relevance

We plan to develop a radically new technology for molecular computation, whereby molecules themselves respond to external stimuli and produce output at the level of cellular phenotype, serving as nanocomputing agents (NCAs). Advent of such NCAs would revolutionize the interrogation of biological systems, enable a deeper understanding of human biology and disease, and facilitate development of in situ precision therapeutics.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Unknown (R35)
Project #
5R35GM134864-02
Application #
10071173
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Lyster, Peter
Project Start
2020-01-01
Project End
2024-12-31
Budget Start
2021-01-01
Budget End
2021-12-31
Support Year
2
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Pennsylvania State University
Department
Pharmacology
Type
Schools of Medicine
DUNS #
129348186
City
Hershey
State
PA
Country
United States
Zip Code
17033