Niles A. Pierce - US grants

The Pierce Lab at Caltech proposes a research program that combines theoretical, computational
and experimental components to advance the field of structural nucleic acid nanotechnology in developing rigorous and robust methods for encoding arbitrary mechanical function in nucleic acid sequences. Modeling and algorithm development projects will address key analysis and design challenges. The investigation of pseudoknot biophysics will help to create a physically based potential for partition function algorithms and illuminate the role of topology in the behavior of the "kissing hairpin" mechanism under experimental study for catalytic fuel delivery to autonomous devices as well as:
-on implementing an efficient hierarchical mutation algorithm for optimizing affinity and specificity for target secondary structures using partition function information
-on methods for identifying and designing multiple features of an energy landscape including networks of metastable states relevant to autonomous device design
-and on formulating and optimizing the multi-objective design problem that characterizes device engineering, in which multiple strands must conditionally adopt different structures depending on the subsets of strand species that are present.

Intellectual Merit
The proposed research program seeks to develop analysis and design tools that will dramatically increase the level of rigor, accuracy, and automation with which nucleic acid devices are engineered. The work encompasses physical modeling, algorithm development, mechanism design, and experimental validation, with the unifying goal of enabling the manipulation of subtle features in the multiple energy landscapes that underlie the design of devices with many conditionally stable states. The development of a practical catalytic fuel delivery method and subsequent construction of a robust autonomous walker that can take hundreds of unassisted steps would represent a breakthrough in the field. Likewise, HCR provides a new functional paradigm for nucleic acid nanotechnology, creating many attractive avenues for investigation.

Broader Impact
The ability to engineer autonomous devices at the nanometer length scale may someday have importantmedical applications including the targeted delivery of toxic drugs. In the nearer term, HCR has the potential to facilitate the construction of versatile and inexpensive biosensors. Undergraduates have the opportunity to participate fully in this interdisciplinary research through the Caltech Summer Undergraduate Research Fellowship program. Researchers at other universities can freely download source code for the analysis and design software developed in the Pierce Lab. At Pasadena public schools, 62% of students participate in free or reduced-price meal programs and more than 80% of students are underrepresented minorities. For many students, the Jr. Teacher program will provide a rare opportunity to consider the attractions of pursuing a career in science or engineering.

DNA is best known as the genetic storage medium for life. However, its unique structural properties make it attractive for engineering nanoscale structures and devices. Remarkably, synthetic DNA systems can be programmed to self-assemble into complex objects implementing dynamic mechanical tasks by appropriately designing the sequence of bases (A,C,G and T) comprising the constituent DNA strands. When mixed, the strands "hybridize" in prescribed ways by forming "base-pairs" between complementary bases (A with T, C with G). DNA nanotechnology explores and develops these capabilities for applications in nanorobotics, nanofabrication, biomolecular computation, biosensing, nanoelectronics and nanomedicine.
In principle, equilibrium and kinetic properties of a DNA strand can be characterized by the features of its "free energy landscape". Likely equilibrium structures correspond to deep valleys in the landscape, and the rate of conversion between two structures depends on the nature of the valleys and ridges separating them. The dynamics of a folding DNA strand define a path somewhat analogous to a ball rolling over the landscape. To analyze functional DNA systems with moving parts, it is important to identify large-scale landscape features that dominate experiments. Unfortunately, in practical problems, existing physical models define landscapes with fine-grained detail that obscures the large-scale features. For example, DNA systems commonly have theoretical landscapes containing more states than there are atoms in the universe, though experiments suggest that a small number of features dominate the landscape.
The project will develop algorithms for efficiently exploring large landscapes that cannot be enumerated explicitly, including coarse-graining approaches to simulate the temporal evolution of physically meaningful "macrostates" without having to simulate full "microstate" landscapes. These macrostate predictions will guide and interpret experimental studies of DNA systems of fundamental interest to current nanorobotics and biosensing efforts. Custom-built fluorescence instruments will probe free energy landscapes at the level of single molecules. While our expertise in DNA nanotechnology motivates our experiments on synthetic DNA, the new coarse-graining theory, computational algorithms, and experimental methods will be equally applicable to analysis of natural RNA molecules (such as the mutant of human telomerase RNA that is thought to cause dyskeratosis congenita by altering the free energy landscape of a conformational switch).
Our research objectives are integral with an education program dedicated to training undergraduates, graduate students, and postdocs in distinctly interdisciplinary research groups that currently involve Applied & Computational Mathematics, Applied Physics, Biochemistry, Bioengineering, Biology, Chemistry, Chemical Engineering, Computer Science, Computation & Neural Systems, and Physics. This is coupled with an outreach program that brings local high school science students to Caltech to discover DNA nanotechnology, meet with lab members in small informal groups, and generate enthusiasm for pursuing careers in science and engineering. We will also continue our policy of freely distributing the source code for our analysis and design software.

With this Chemical Bonding Center (CBC) Phase I, Step II award, the Division of Chemistry and the Office of Multidisciplinary Activities of the Mathematical and Physical Sciences Directorate jointly support the research of Milan N. Stojanovic, of Columbia University, who will lead a collaborative effort involving eight PIs from a variety of institutions to create a Center for Molecular Cybernetics. The unified goal of this center is to produce synthetic molecular machines that are powered by molecular bond formation. Chemical structures that will have two or more protruding appendages of DNA will be synthesized. These appendages, or arms of molecular "spiders", will have the ability to attach to or detach from a position on a surface in response to external stimulus. When a spider arm reattaches to a different position, the spider will move across the surface. The successful construction and description of these autonomously moving molecules will generate both scientific and public interest, and these studies have the potential to lead to applications in areas such as drug delivery and nanopatterning.

Chemical Bonding Centers are designed to focus innovative collaborative efforts that address a "big problem" which will lead to a major advance in chemistry or at the interface of chemistry and other sciences and will have the potential to attract broad scientific and public interest.

DESCRIPTION (provided by applicant): The recent explosion of genomic data has offered an unprecedented opportunity to study the molecular basis for developmental and disease processes. Although microarray techniques for profiling the genes expressed in a given tissue have become commonplace, methods for determining the exact spatial and temporal extent of gene expression are still in need of improvement. In situ hybridization techniques for gene expression studies often have limited sensitivity and significant background signal even in locations where no target genes are present. Furthermore, existing technologies do not fully exploit the potential for imaging many genes simultaneously. The goal of the proposed research is to adapt a newly developed nanosensor technology for multiplexed in situ amplification of gene expression. This amplification tool, termed hybridization chain reaction (HCR), reduces background by activating only when a probe molecule binds specifically to its target. This event triggers the self-assembly of a tethered 'polymer' from fluorescently-labeled DMA hairpins. Parallel multiplexing can be achieved simply by using independent HCR amplifiers for each unique target species. The research plan involves the design, validation and application of in situ HCR amplifiers. Specific aims are: 1: Design triggered, multiplexed, nonlinear HCR amplifiers, and refine the computational tools for the design of HCR amplifiers. 2: Validate the spatial localization, sensitivity, specificity and multiplexing of the amplifiers in situ using nanolithography techniques to precisely pattern target molecules on surfaces. 3: Apply HCR to in situ hybridization of patterning genes in avian embryos, testing for the co- expression of genetic markers predicted by previous studies. The objective is to develop in situ HCR amplifiers that will enable the sensitive and simultaneous detection of numerous targets in biological specimens. If successful, this nanotechnology will serve as an important adjunct to modern genomic and proteomic tools in settings ranging from biological experiments to tissue biopsies.

Project Summary Hybridization Chain Reaction: In Situ Ampli?cation for Biological Imaging Life is orchestrated by programmable biomolecules ? DNA, RNA, and proteins ? interacting within complex biolog- ical circuits. RNA in situ hybridization (RNA-ISH) methods provide biologists with a crucial window into the spatial organization of this circuitry, enabling imaging of mRNA expression in an anatomical context from subcellular to organismal length scales. Due to variability between specimens, examination of detailed spatial relationships requires multiplexed experiments in which multiple target mRNAs are imaged with high resolution within a single biological sample. Using traditional RNA-ISH methods in thick auto?uorescent samples including whole-mount vertebrate embryos, multiplexing is cumbersome or impractical, spatial resolution is frequently compromised by diffusion of reporter molecules, and staining is non-quantitative. The same drawbacks apply using traditional immunohistochemistry (IHC) methods to image protein expression in these challenging samples, while with tradi- tional DNA in situ hybridization (DNA-ISH) methods, it is not currently routine to image single-copy small genomic loci in any sample, much less in vertebrate embryos. These longstanding shortcomings of traditional ISH and IHC methods are a signi?cant impediment to the study of genetic regulatory networks in systems most relevant to human development and disease. In situ ampli?cation based on the mechanism of hybridization chain reaction (HCR) draws on concepts from the emerging discipline of dynamic nucleic acid nanotechnology to achieve three mRNA imaging breakthroughs in whole-mount vertebrate embryos and thick tissue sections: straightforward 5-channel multiplexing, subcellular relative quantitation, and single-molecule resolution and sensitivity. The proposed research will build on these unique capabilities to dramatically advance the robustness, multiplexing, and quantitation capabilities of HCR for RNA-ISH and to extend the bene?ts of multiplexed, quantitative, enzyme-free HCR signal ampli?cation to IHC and DNA-ISH in thick auto?uorescent samples. Major goals are: In situ HCR v3.0: automatic background suppression using cooperative probes for next-generation robust- ness and signal-to-background imaging mRNAs and short RNA targets (miRNAs, mRNA splice junctions, and closely related RNA sequences) in diverse organisms. Next-generation multiplexing (15-plex with simultaneous HCR signal ampli?cation for all targets) and quan- titation (high-?delity mRNA absolute quantitation with subcellular resolution and whole-embryo scale). Next-generation versatility: extend the bene?ts of HCR imaging to protein targets, single-copy small ge- nomic loci, and molecular complexes, enabling compatible multiplexed imaging of all target classes. Realization of these goals would have a broad impact on research in the biological sciences, providing an un- precedented combination of multiplexing, quantitation, resolution, sensitivity, and versatility for the study of genetic regulatory networks in an anatomical context.

Background. One of the greatest contrasts between the biological organisms and human technology lies in how they are constructed. Plants and animals grow from the inside out, often from a single cell to an organism containing billions of cells, each of which is built from molecular components that are manufactured with atomic precision within the cell. In contrast, mankind's greatest engineering marvels, such as airplanes and skyscrapers and computers, are put together from the outside in, with components being manufactured in factories and assembled piece by piece. This distinction is often referred to as "bottom-up" vs "top-down" assembly in the biological "bottom-up" approach, the assembly process is guided by the components themselves, while in the engineering "top-down" approach, there is an entity conceptually above the object being built that supervises and guides the manufacturing process. Human engineering has mastered top-down methods to create systems of great complexity (but has not extended them to the atomic and molecular scale) and has exploited bottom-up methods for the synthesis of diverse molecular, polymeric and crystalline structures (but has not created information-rich structures of great complexity).
Project Goals. Our goal is to demonstrate how bottom-up techniques can create complex atomically-defined structures, as biology does, by embedding information and computational processes within the molecules themselves. In biological development, a program (the genome) uses biochemistry to guide the growth process and determine the ultimate form of the organism. In the parlance of computer science, a system that can be programmed to accomplish any task that can be accomplished is called a "universal" system. A universal computer can be programmed to perform any computation, while a universal constructor can be programmed to carry out any construction task. Recent work has theoretically shown that universal molecular self-assembly is possible and has experimentally demonstrated that the approach shows promise, using DNA as a construction material to create functional molecular devices so-called "DNA nanotechnology". In this proposal, we aim to bring DNA nanotechnology to the point where universal bottom-up self-assembly can be achieved well enough that immediate technological applications can be demonstrated.
Specific Aims. We aim to make major advances both in our ability to program complex self-assembly logic and in our ability to interface the DNA structures to chemically-, optically-, and electronically-relevant materials. We will focus on four main goals, which span the range from long-term fundamental work to near-term development: (1) self-assembly of a template for a complex molecular-scale electronic circuit; (2) programming the behavior of molecular walking motors to transport components in nanofabrication tasks; (3) attaching carbon nanotube wires to create small nanoscale electronic circuits; and (4) integrating bottom-up and top-down fabrication by placing and orienting self-assembled components at target locations on silicon wafers with functional electrical contacts.
Uniquely, the aims of this research require simultaneously development of two novel computing systems: the first, inspired by biological self-assembly and development, operates at the level of molecular machines and biochemistry, and will be programmed to construct the second, composed of carbon nanotubes assembled into nanoscale circuits, which operates at the electrical level like conventional computing devices.
Broader Impact. An important aspect of this project will be the training of young scientists (undergraduates, graduate students, and postdocs) capable of spanning the interdisciplinary subjects involved in this work.

There is great potential for adapting biopolymer molecules such as RNA and DNA to meaningful computational tasks and purposes. Having the ability to program molecules at many orders of magnitude larger scale than at present using new algorithms and software analogues has the potential to change the way we analyze, understand and manipulate molecular systems. It can lead to practical applications of significant benefit to society across a wide range of national initiatives in materials, nano-biotechnology, tissue engineering, regenerative medicine, and many other emerging areas. This ambitious Expedition addresses the exciting challenge of developing initial foundational steps toward creating large-scale molecular programs. This experimental technology Expedition aims to develop a functional abstraction hierarchy to create molecular programming languages, compilers, tools and models; a theoretical framework for the analysis and design of molecular programs; validation of the above utilizing molecular programs with orders of magnitude higher scale of components than at present; and testing of the developed molecular programming technologies on real-world applications. This high-risk/high-payoff research will increase our understanding of the relationship between computation and the physical world, how information can be stored and processed by molecules, and the possibilities and limits of what can be computed and fabricated. Outreach includes summer undergraduate and minority student research fellowships, K-12 visiting days, boot camps, workshops and many other efforts to create a broader molecular programming research community.

Project Summary: Engineering Triggered Nanomechanical Therapeutics The goal of this program of research is to develop the molecular foundations for a new therapeutic paradigm based on triggered nanomechanical transduction using synthetic nucleic acid devices. Traditional drugs may be viewed as 'structural therapeutics' that bind specifically to a target molecule that serves as both the marker for the disease and the means of treating the disease. This dual role is undesirable if the target is not specific to diseased cells (exemplified by toxicity side effects with cancer chemotherapies), or limiting if the target does not facilitate potent treatment. Here, we propose to develop 'mechanical' therapeutics in which the activity of the treatment domain is under the mechanical control of an independent diagnosis domain: if and only if the diagnosis domain binds to its target (selected for its specificity as a disease marker), the initially inactive treatment domain switches to an activated conformation capable of binding to a second unrelated target (selected for its potent activation of a therapeutic pathway). The use of distinct diagnosis and treatment domains allows independent optimization of specificity and potency; the introduction of triggered mechanical transduction between these domains provides active suppres- sion of the drug's activity until a positive diagnosis is achieved at the molecular level (minimizing side effects). Mechanical transduction also provides the flexibility to implement elementary molecular logic, permitting triggered activation following diagnosis based on multiple disease markers. This dynamic functionality will be encoded in the sequences of therapeutic RNA molecules that interact and change conformation to implement two conceptually powerful therapeutic strategies: If gene A is detected, silence gene B via triggered RNA interference. If gene A is detected, kill the cell via triggered immune response. In both cases, the key point is that the activity of the drug (i.e., gene silencing or cell death) is triggered by the detection of an unrelated disease marker. The concept of triggered nanomechanical transduction suggests potentially transformative therapeutic strate- gies for treating broad classes of disease, including cancers, autoimmune diseases such as multiple sclerosis, and mosquite-borne viral infections such as dengue fever. Our current objective is to demonstrate the promise of nanomechanical transduction by robustly triggering gene silencing and cell death in mammalian cells, providing a proof-of-principle to motivate further exploration of this new therapeutic concept. 1

With this award from the Major Research Instrumentation (MRI) program and the Chemistry Division, Professor Thomas F. Miller and colleagues John F. Brady, William A. Goddard, Zhen-Gang Wang and Niles A. Pierce from the California Institute of Technology will acquire a computer cluster with graphical processing units. The proposal will enhance research in a variety of areas characterized as soft matter behavior/simulations. The projects include investigations aimed at the rational design of nucleic acid, protein and enzyme systems, conformational dynamics of proteins and molecular motors, enzyme-catalyzed electron-transfer and hydrogen-transfer dynamics, trans-membrane signaling and transport processes, the nucleation of membrane adhesion, protein secretion across a cellular membrane, the formation of gels, the dynamics of ring-polymer mixtures, and polymer-based tissue engineering.

A computer cluster is a group of linked processors that work in concert to achieve vastly more computational power that individual computers. These are employed to investigate complex problems using computational methods based on theoretical models and programs. Such calculations, often used in conjunction with experimental data, allow chemists and biochemists to better understand many types of complex chemical and biological phenomenon. This resource will be used by students and faculty to develop the use of computer clusters based on graphical processing units (GPUs) rather than CPUs. This approach can speed up calculations and simulations enabling larger, more complex systems to be investigated.

This project will explore the future of molecular programming area via a Special Session at the 17th
International Conference on DNA Computing & Molecular Programming (DNA17). The conference will take
at California Institute of Technology, Pasadena, California, USA on September 19, 2011. The conference website is http://dna17.caltech.edu. The goals of the event are to elucidate future directions and specific challenges for the field of DNA computation and molecular programming, and to facilitate discussion on how these visions are to be met. The DNA17 conference is the flagship conference in this emerging area.

A report will be provided to NSF after the event, consisting of a short statement from each invited panelist and a summary of each panel discussion by the organizers. The panel discussions will provide a timely assessment of the field and the challenges and opportunities for the future, which will be useful to conference attendees and other researchers working in this area as they formulate their next research directions.

Requested funds will primarily go to support registration and travel expenses for the invited panelists,
as well as incidental costs associated with the impromptu parallel sessions.

Student travel support for DNA17
Conference title: 17th International Conference on DNA Computing and
Molecular Programming (DNA17)
Location: California Institute of Technology, Pasadena, California, USA
Dates: September 19?23, 2011
Website: http://dna17.caltech.edu



Summary
This is an unsolicited proposal for 12,000 USD for student travel support for the 17th International Conference on DNA Computing and Molecular Programming (DNA17). The primary purpose of the proposal is to give travel assistance to students who are giving oral or poster presentations at the conference. The selection procedure for travel awards is described in detail below and is designed to give priority to women and underrepresented minorities, and to research quality. Approximately 20 successful student applicants, from US institutions (excluding Caltech), will be funded for travel and accommodation, with an expected average award of 600 USD per student.


Intellectual Merit
The annual International Conference on DNA Computing and Molecular Programming (DNAx) is the premier forum where scientists with diverse backgrounds come together with the common purpose of advancing the engineering and science of biology and chemistry from the point of view of computer science, physics, and mathematics. Continuing this tradition, the 17th International Conference on DNA Computing and Molecular Programming (DNA17), under the auspices of the International Society for Nanoscale Science, Computation and Engineering (ISNSCE), will focus on the most recent experimental and theoretical results that promise the greatest impact. A steady stream of papers in the field appear in Nature and Science, as well as other top journals such as Nature Nanotechnology, Nature Chemistry, Nature Biotechnology, Angewandte Chemie, JACS, Physical Review Letters, Physical Review Letters, SIAM Journal on Computing ? and the authors of these papers regularly attend DNAx conferences to present their work in a preliminary form.


Broader Impact
By funding travel to students we are actively encouraging and incentivizing a new generation of researchers to attend the conference. We are giving special priority to women and minority applicants whose papers or posters were accepted at the conference. Students who attend DNA17 will get exposure to early versions of work that will go on to be published in top venues and, furthermore, they will have the opportunity to interact with, and potentially collaborate with, researchers who are producing work of the highest quality.

The computing revolution began over two thousand years ago with the advent of mechanical devices for calculating the motions of celestial bodies. Sophisticated clockwork automata were developed centuries later to control the machinery that drove the industrial revolution, culminating in Babbage's remarkable design for a programmable mechanical computer. With the electronic revolution of the last century, the speed and complexity of computers increased dramatically. Using embedded computers we now program the behavior of a vast array of electro-mechanical devices, from cell phones and satellites to industrial manufacturing robots and self-driving cars. The history of computing has taught researchers two things: first, that the principles of computing can be embodied in a wide variety of physical substrates from gears to transistors, and second, that the mastery of a new physical substrate for computing has the potential to transform technology. Another revolution is just beginning, one whose inspiration is the incredible chemistry and molecular machinery of life, one whose physical computing substrate consists of synthetic biomolecules and designed chemical reactions. Like the previous revolutions, this "molecular programming revolution" will have the principles of computer science at its core. By systematically programming the behaviors of a wide array of complex information-based molecular systems, from decision-making circuitry and molecular-scale manufacturing to biomedical diagnosis and smart therapeutics, it has the potential to radically transform material, chemical, biological, and medical industries. With molecular programming, chemistry will become a major new information technology of the 21st century.

This Expeditions-in-Computing project aims to establish solid foundations for molecular programming. Building on advances in DNA nanotechnology, DNA computing, and synthetic biology, the project will develop methods for programmable self-assembly of DNA strands to create sophisticated 2D and 3D structures, dynamic biochemical circuitry based on programmable interactions between DNA, RNA, and proteins, and integrated behaviors within spatially organized molecular systems and living cells. These architectures will provide systematic building blocks for creating programmable molecular systems able to sense molecular input, compute decisions about those inputs, and act on their environment. To manage system complexity and to provide modularity, the project will establish abstraction hierarchies with associated high-level languages for programming structure and behavior, compilers that turn high-level code into lists of synthesizable DNA sequences, and analysis software that can predict the performance of the sequences. This will allow molecular programmers to specify, design, and verify the correctness of their systems before they are ever synthesized in the laboratory. In addition to these software tools, the project will study the theory of molecular algorithms in order to understand the potential and limitations of information-based molecular systems, what makes them efficient at the tasks they can perform, and how they can be effectively designed and analyzed. Putting the products of this fundamental research to the test, the project will pursue real-world applications such as molecular instruments for probing biological systems and programmable fabrication of nanoscale devices.

This project will expand the network of scientists and engineers working in molecular programming by building a diverse community of students, teachers, researchers, scientists, and engineers. This community will be fostered through the creation of publicly accessible software tools, courses, textbooks, workshops, tutorials, undergraduate research competitions, and popular science videos to teach the principles and methods of molecular programming and to engage young researchers and the public in this exciting new field. Industrial partnerships with relevant biotechnology and other high-tech companies will ensure fast transfer of knowledge generated into real-world products. Perhaps most importantly, as molecular programming becomes a widespread technology, it has the potential to transform industry with new complex nanostructured materials, to transform chemistry with integrated and autonomous control of reactions, to transform biology with advanced molecular instruments, and to transform health care with more sophisticated diagnostics and therapeutics.

This INSPIRE project is jointly funded by the Chemical Theory, Models, and Computational Methods program in the Division of Chemistry in the Directorate for Math and Physical Science, the Algorithmic Foundations program in the Division of Computing and Communication Foundations in the Directorate for Computer & Information Science, and the INSPIRE program in the Office of Integrative Activities. This project advances the objectives of the National Strategic Computing Initiative (NSCI), an effort aimed at sustaining and enhancing the U.S. scientific, technological, and economic leadership position in High-Performance Computing (HPC) research, development, and deployment.

DNA and RNA base-pairing (A pairs with T, C pairs with G for DNA; A pairs with U, C pairs with G for RNA) play central roles in the biological circuits that operate within living organisms. This base-pairing also offers a rich design space for the new engineering disciplines of molecular programming and synthetic biology. These engineering efforts are greatly assisted by the use of computational algorithms to design and analyze the base-pairing (secondary structure) properties of DNA or RNA strands before beginning more costly and time-consuming laboratory studies. Historically, the secondary structure models underlying these calculations have been parameterized based on experiments performed piecemeal over a period of decades, making it difficult to improve the models (still incomplete after 45 years of effort) or to extend the models (to new materials and experimental conditions critical to modern applications). Departing dramatically from this experimental parameterization approach, the proposed work will establish a computational parameterization framework, in which state-of-the-art computational chemistry methods with be used - for the first time - to perform atomistic simulations on a carefully chosen suite of small model problems, enabling automated parameterization of new secondary structure models from scratch. This strategy requires a high level of inter-disciplinarity beyond the capabilities of any individual research group, demanding computational and algorithmic expertise to perform modeling at both the atomistic level and the secondary structure level, and experimental expertise to test key ensemble properties predicted from new parameter sets. This effort draws together three laboratories (Miller, Pierce, Winfree) spanning three Caltech Divisions (Biology & Biological Engineering, Chemistry & Chemical Engineering, and Engineering & Applied Science) to achieve major impact on the molecular programming, synthetic biology, and life sciences research communities by dramatically improving current secondary structure models and by creating a repeatable, improvable, extensible computational framework for generating new models long into the future. Over the coming decades, the fields empowered by these advances are poised to generate transformative molecular and cellular technologies addressing challenges to science and society ranging from neuroscience and development, to diagnosis and treatment, and from renewable energy to sustainable manufacturing.

The programmable chemistry of nucleic acid base pairing is central to the circuits that orchestrate life and to the emerging engineering disciplines of molecular programming and synthetic biology. Existing secondary structure models have great utility for analyzing and designing functional DNA and RNA systems, but current equilibrium parameter sets are incomplete, apply to a limited set of experimental conditions, and are difficult to extend or improve as they are based on empirical parameters measured over the course of 45 years. Furthermore, essentially no kinetic parameters have been measured to date. Departing from this piecemeal experimental approach, the proposed work will parameterize equilibrium and kinetic secondary structure models - for the first time - using atomistic molecular simulations. State-of-the-art computational chemistry methods will be used to set up a forward compatible framework for parameter generation that is automated and repeatable, enabling researchers to rerun the parameterization suite from scratch to generate an entire parameter set for a new set of experimental conditions (salt, temperature, denaturant), for new synthetic analogs (LNA, 2?OMe-RNA), or for mixed-material interactions (DNA/RNA, RNA/2'OMe-RNA, RNA/LNA) that are crucial for modern in situ and in vivo applications. The computational framework will initially be validated via comparison to the subset of DNA and RNA parameters that have been most carefully measured in existing empirical models, followed by validation with respect to key equilibrium and kinetic results extracted from the experimental literature, or measured in the laboratory.

Life is orchestrated by programmable biomolecules (DNA, RNA, and proteins) that interact within complex molecular machines and biological circuits to grow, regulate, and repair organisms. These biological proofs-of-principle inspire diverse engineering efforts within the new fields of molecular programming, nucleic acid nanotechnology, and synthetic biology. Over the coming decades, these fields are poised to generate transformative programmable molecular and cellular technologies addressing challenges to science and society ranging from neuroscience and development, to diagnosis and treatment, and from renewable energy to sustainable manufacturing. To support these engineering efforts, the PI is engaged in a multi-decade effort to develop NUPACK (Nucleic Acid Package), a growing software suite for analyzing and designing nucleic acid structures, devices, and systems. Launched in 2007, NUPACK usage has grown to the point where the NUPACK compute resource is frequently overwhelmed by the research community. With the proposed work, the NUPACK web application will be re-architected from the ground up to run in the cloud, enabling the resource to scale dynamically in response to spikes in researcher demand and to growth year-over-year. The NUPACK user interface will be substantially expanded to allow users to harness next-generation analysis and design tools. Additionally, the re-architected web application will benefit from a complete re-write of the NUPACK scientific code base (moving from NUPACK 3.2 to 4.0) to achieve dramatic computational speed-ups and exploit enhanced physical models. With NUPACK in the cloud, users will be able to perform calculations far beyond current capabilities both in terms of scale and scientific scope, enabling exploration of a growing frontier of programmable molecular technologies.

NUPACK is a growing software suite for the analysis and design of nucleic acid structures, devices, and systems serving the needs of researchers in the emerging disciplines of molecular programming, nucleic acid nanotechnology, and synthetic biology. NUPACK algorithms are unique in treating complex and test tube ensembles containing arbitrary numbers of interacting strand species, providing crucial tools for capturing concentration effects essential to analyzing and designing the intermolecular interactions that are a hallmark of these new fields. Usage has increased to the point where the NUPACK compute cluster is frequently overwhelmed. With the proposed work, the NUPACK web application will be re-architected to enable deployment on the cloud, containerizing the dozens to thousands of jobs that are launched by a single click, and enabling the scale of the resource to vary dynamically minute-to-minute and year-over-year. To move to a sustainable model for NUPACK compute hardware and engineering support, NUPACK user accounts will be created that enable users to view and retrieve old jobs, to seamlessly pay for the cloud compute cycles that are used for their jobs, and to provide incremental support for the NUPACK Software Engineer proportional to their usage of this non-profit academic resource. The user interface will be substantially expanded to allow users to harness the new capabilities of the enhanced NUPACK backend, including kinetic analysis for complex and test tube ensembles, kinetic design for test tube ensembles, equilibrium design for large-scale pseudo-knotted structures in test tube ensembles, and use of new computationally parameterized physical models generated for custom experimental conditions. The re-architected web application will also benefit from a complete re-write of the NUPACK scientific code base, featuring improved implementations, reduced-complexity algorithms, overflow-safe evaluation algebras, and expanded physical models.

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.