Michael Hagan - US grants

DESCRIPTION (provided by applicant): Viral proteins assemble into capsids rapidly and reproducibly in many different organisms and environments. This project is designed to determine what features of protein-protein interactions are required for such robust assembly. Identifying the requirements for robust assembly could play a critical role in antiviral strategies as well as in the development of viral vectors for gene therapy. More significantly, organization of basic units into well defined, large scale structures is integral to many biological systems. Hence, understanding assembly at a fundamental level for a relatively simple system, such as a virus capsid, could have broad applications throughout biology. In order to capture essential details of individual proteins while describing large scale assembly processes, a hierarchy of simulations and theoretical methods is proposed. The theoretical efforts at each level are coupled to experiments that probe the same phenomena. This endeavor is viewed as a springboard for the development of a general algorithm for systematically coarse-graining in assembly processes.

DESCRIPTION (provided by applicant): During the replication of many viruses, hundreds to thousands of protein subunits assemble around the viral nucleic acid to form a protein shell called a capsid. Within their host organism, most viruses form one particular structure with astonishing fidelity; yet, recent experiments demonstrate that capsids can assemble with different sizes and morphologies to accommodate nucleic acids, inorganic nanoparticles, and polyanions with different sizes. This project will use computational models to determine the features of viral proteins and their cargoes that enable assembly to be so precise and yet so adaptable. We develop simplified representations of viral proteins and cargoes that range from rigid spheres to fluctuating polymers to model nucleic acids. With these models we will develop experimentally testable predictions for the mechanisms by which viral proteins dynamically encapsidate these objects, and which factors direct the assembly process towards a particular size and morphology. These coarse-grained models of the overall assembly process will be validated and guided by atomic-resolution simulations that examine the dynamic conformations of viral proteins.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This proposal requests CPU time on TeraGrid resources for research aimed at understanding the assembly of viral proteins to form capsids. The projects will examine the mechanisms of conformational transitions required for capsid formation in the proteins of two icosahedral viruses, and will study the association/dissociation of HIV capsid proteins. The simulations will use NAMD to simulate proteins in explicit water. Because conformational transitions and association events are not accessible to straightforward molecular dynamics simulations, the simulations will use recently developed path sampling methodologies to focus simulation time on the transitions. The proposed work is funded by the NIH NIAID (Award No. R01AI080791).

The objective of this award is to assemble self-limited structures and material that undergo large-scale structural changes in response to changing environmental conditions such as temperature, solution properties, or imposed force. As a basic building block the project will utilize bacterial flagella, a helical polymer which acts as a nanoscale spring and exhibits non-monotonic force-extension relationship that is not commonly found in synthetic materials. To achieve the goal the project will utilize a combination of experimental, computational and theoretical tools to elucidate the behavior of flagella based materials at three levels of hierarchy. First, the project will characterize and model the mechanics of individual flagella, as well as chimeric flagella engineered to achieve new polymorphic switching responses. Second, will be to generate, characterize, and control attractive interactions between a pair of flagella. Finally, these same attractive interactions will be used to assemble flagellar bundles or ropes consisting of thousands of flagella.

This study holds the promise to generate nano-structured, responsive fibrous materials with well-controlled mechanical and structural properties, in which conformational changes of individual monomeric units at Angstrom scales cooperatively cascade across multiple lengthscales to produce macroscopic mechanical changes in millimeter-sized materials. The educational and research component of this project will be integrated by expanding an REU program to hold an annual "Theory Meets Experiment" symposium for undergraduates participating in summer research at Brandeis and University of Massachusetts, to expose novice researchers to the distinct and complementary methods of theoretical and experimental research in soft materials. In addition, a partnership will be explored with Jennifer Sabin, architect, designer, and lecturer at the University of Pennsylvania School of Design in order to explore the relationship between complex biopolymer assembly motifs and a state-of-the-art textile design and fabrication process.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. We propose to use the multi-microsecond capabilities of ANTON to harvest one or more spontaneous transitions between the active and inactive conformations of the signaling protein NtrC using unbiased molecular dynamics. The resulting trajectory will be analyzed to identify intramolecular interactions that stabilize the transition. These findings will be directly tested by experiments performed in the lab of one the PI's (D. Kern). Specifically, site directed mutagenesis will be used to create mutant NtrC proteins for which the computationally identified interactions are disabled;transition rates for these mutant proteins will be compared to those for wild type. Significant differences in transition rates will confirm the computational predictions. By taking advantage of this close integration between computation and experiment, the proposed simulations on ANTON will significantly advance the understanding of conformational transitions in NtrC, and the mechanisms that underlie transitions among folded protein states in general.

ID: MPS/DMR/BMAT(7623) 1256701 PI: Hagan, Michael ORG: Brandeis University

Title: Proposal for Conference/Workshop Support for CECAM workshop: Self-assembly: from fundamental principles to design rules for experiment

INTELLECTUAL MERIT: The proposal asks for funds to support the travel and subsistence costs for seven early-career US scientists to attend a workshop to be held at the Centre Europeen de Calcul Atomique et Moleculaire (CECAM) in Lausanne, Switzerland. This workshop aims to bring together computer simulators and experimentalists whose work bears upon the fundamental rules that govern soft matter self-assembly. Participants will be united not by their study of a particular physical system, but by their focus on the forces that control assembly. The proposed speaker list is highly multidisciplinary, and includes theoretical physicists, virologists, synthetic biologists, and materials scientists. Despite their common interests, researchers who study biological assemblages and those who study crystallization rarely overlap. The format of a CECAM workshop provides an ideal environment to bring members of these fields together to benefit from commonalities in subject and complementary techniques used in each of these fields.

BROADER IMPACTS: It is anticipated that the workshop will have a much broader impact than that realized from a typical conference. Speakers and attendees from a wide range of disciplines, geographical locations, and career stages will engage in intensive small-group discussions. Thus, participants with different areas of expertise, experience levels, genders, and ethnic backgrounds will interact closely. NSF funding support will be given to both emerging scientists (students, postdocs, and junior faculty) and under-represented groups in order to increase their participation. Such support will help fulfill the urgent, national need to train the future scientific community in the areas of nanotechnology and biological research. Furthermore, by encouraging US scientists to attend through NSF support, the workshop will serve to increase the engagement of the US with the European soft matter community.

Molecular motors are nanoscale machines that convert chemical energy from ATP hydrolysis into mechanical movement along a filamentous track. Over the past two decades experimental advances have yielded remarkable images of single molecular motors taking nanometer-sized steps. Furthermore, state-of-the-art technology also makes it possible to pull on such nanomachines with optical traps thus determining the maximal force they can exert. Taken together these efforts have provided essential insight into biochemical mechanisms driving the motility of isolated molecular motors. However in many instances, ranging from contraction of a skeletal muscle to spontaneous beating of a biological cilium, motors do not act in isolation. Instead, thousands of motors coordinate their activity to produce large scale molecular motion. Despite its importance, little is known about the emergent collective properties of molecular motor ensembles. The first goal of this project is to develop an experimental assay that will quantify contractile sliding forces between a pair of aligned microtubules, exerted by molecular motor clusters that simultaneously bind and move along both filaments. Such structural motifs drive numerous complex processes in a biological cell. Using this information, the project will build microtubule bundles that are clamped at their base and driven by molecular motors. Theoretical models predict that such structures will spontaneous beat, thus mimicking the dynamical behavior of biological cilia. Experimental efforts will directly verify this prediction and provide insight into the mechanisms that control beating patterns of biological cilia. In parallel with experimental efforts, this project will also pursue development of computer simulation models for collective behavior of molecular motors; these will bridge the gap between existing theoretical models and experimental data.

Broader Impacts: The research and outreach efforts will be seamlessly integrated through a mutual emphasis on visualization and microscopy. Movies of dynamical biological structures obtained via microscopy capture the imagination and interest of scientists and non-scientists alike. The PIs will organize outreach activities at The Discovery Museum in Acton, MA, in which optical microscopes and specimens will be available at the museum, allowing visitors to peer into the microscopic world and directly visualize biological motion. The PIs will also disseminate practical knowledge of optical microscopy by teaching an intensive hands-on one-week summer course. Investigator involvement with the highly successful science Posse program will further enhance undergraduate and graduate student involvement from historically underrepresented groups.

DESCRIPTION (provided by applicant): Protein conformational transitions are fundamental to signaling, enzyme catalysis, and assembly of cellular structures. Developing a quantitative understanding of how proteins interconvert between different folded structures is a grand challenge in biology; meeting this challenge would have an impact in treating a large number of diseases that are linked to signaling cascades or enzymes. This proposal aims to understand the physical principles that control protein conformational transitions by characterizing transitio pathways in proteins. Since these pathways are very complex, homologous proteins will be compared to make this aim feasible. We focus on a signaling proteins from the two-component system family (NtrC) and homologs of the enzyme adenylate kinase (Adk) from E. coli and extremophiles. These Adk homologs have optimal enzymatic activity at extreme temperature or pressure. An iterative approach between NMR dynamics experiments, advanced computational methods and functional assays is proposed. (1) Structures of stable conformational states and rates of interconversion between them are measured experimentally, (2) transition pathways are computationally characterized in atomistic detail, (3) crucial interactions that facilitate pathway are identified, (4) mutations are designed that disable these interactions, (5) the resulting changes in interconversion rates are measured experimentally, and (6) new computations are performed based on experimental observations. By comparing transition pathways among homologous proteins and mutants key residues are identified that lead to mechanistic differences, and confer their respective temperature or pressure behaviors. Furthermore, determining interconversion entropy and entropy changes for these enzymes adapted to extreme environments may shed light on the evolutionary selection mechanisms that shaped primitive enzymes. In a broader context, knowledge gained from the molecular pathways may elucidate general principles of conformational transitions in proteins, thereby expanding our understanding of protein energy landscapes from the ground states to transition landscapes.

DESCRIPTION (provided by applicant): In many virus families, replication requires that hundreds to thousands of proteins assemble around the viral nucleic acid (NA) to form a protein shell called a capsid. Furthermore, many animal viruses use protein assembly to drive budding of the capsid from a cell membrane. Understanding the mechanisms that control assembly around NAs and on membranes would identify targets for novel antivirus therapies that inhibit NA packaging or budding, and would guide efforts to exploit viruses as targeted transport vehicles. Assembly mechanisms inferred from experiments alone are incomplete because intermediates are transient. Therefore, this project develops and applies computational models for capsid proteins, NAs, and lipids that reveal details of assembly and membrane budding not accessible to experiments. To understand how the properties of viral NAs facilitate assembly, models are developed for capsid proteins and NAs that begin with a linear polyelectrolyte (without base-pairing) and then systematically add the geometric and electrostatic features of NAs that arise due to base-pairing. Comparison of predicted assembly kinetics and thermodynamics for each model identifies the contributions of base-pairing to assembly. Predictions for each model are tested against experiments performed by collaborating labs on capsid assembly around corresponding molecules (e.g., synthetic polyelectrolytes, heterologous NAs, and viral genomic NAs). The mechanism by which capsids form different icosahedral morphologies to accommodate NAs with different sizes is also studied. Employed simulation techniques include Brownian dynamics and equilibrium calculations. For some enveloped viruses (e.g., HIV) capsid assembly drives budding from a cell membrane, while for others (e.g., alphaviruses) assembly of membrane proteins drives budding of a pre-assembled capsid. Simulations are used to investigate how these two classes of assembly-driven budding processes depend on properties such as protein interactions and membrane rigidity, and why many viruses preferentially bud from particular membrane microdomains. Predictions will be compared to experiments on alphavirus budding. In addition to identifying factors that can be manipulated to prevent or exploit viral assembly, the proposed simulations will elucidate how biology employs membranes and filamentous scaffolds to assemble multi- macromolecular complexes. The research combines coarse-grained models that are informed by atomistic simulations and experiments with recent advances in GPUs and distributed computing to simulate relevant time and length scales. A new method to apply Markov state models to assembly reactions is developed.

NON-TECHNICAL SUMMARY
This project draws inspiration from the sinuous motion of a lamprey, in which neurons running down the spinal column are excited in sequence causing the musculature to contract, thereby propelling the lamprey. The fundamental principles underlying this behavior are understood, and this team seeks to engineer nonliving materials that possess these properties of living matter. They will develop purely synthetic materials that will operate autonomously, driven solely by chemistry without electricity, computers, or motors. These materials will execute multiple functions and be externally triggered to modify their behavior. Thus, this work will establish a new paradigm of precise and programmable chemical control for the fledgling field of soft robotics, in which soft, tissue-like materials replace the rigid, hard materials now found in robots on factory floors.

TECHNICAL SUMMARY
The objective of the project is to develop purely synthetic, chemomechanical materials that emulate biological processes, such as the beating of a heart, at programmable rates and rhythms. The long-term goal is to elucidate the fundamental physical principles of active soft matter based on reaction-diffusion chemistry, enabling engineering of materials capable of chemical control and chemomechanical transduction. This research will address two fundamental challenges in the design of chemomechanical materials. The first is to understand and develop mechanisms of volume transitions in redox-sensitive gels, by which forces can be actuated. Materials engineered from a selection of promising building blocks will be probed over length scales ranging from nanometers to millimeters in order to fully elucidate gel structure and dynamics. These findings will be fed into atomistic and mesoscopic computer models, which will in turn inform the chemical synthesis of next-generation materials with desirable properties. The second challenge is to engineer a control mechanism comprised of an array of micron-scale compartmentalized reactors that contain an oscillating chemical reaction, and are physically networked via diffusion. Coupling the control and actuation sub-systems will yield chemically responsive gels that can change volume in concert with predictable and tunable chemical activity. Such materials will have attributes heretofore found only in living matter, such as flexibility in mammalian tongues, pulsatile contractions in human intestines, and heliotropism in plants. Thus, this work will establish a new paradigm of precise and programmable chemomechanical control for the fledgling field of soft robotics.

The mechanism of memory is one the major mysteries of biology. Recent work suggests that as a result of learning synapses grow and that the size of the synapse is what stores the components of memories. The aim of the proposed work is to visualize directly this growth process in brain tissue using a newly developed super-resolution microscope, and to understand why such structures have stable size once learning has occurred. Instability would result is loss of memory, so evolution is thought to have favored ways of maximizing stability. To gain insight into the mechanism of stability, physical and computational model systems will be used. If the principles that underlie stability in the face of variable size can be understood, the outcome of this work could open the door to a new era in nanotechnology in which these principles could be utilized, leading potentially to novel solutions to problems in self-assembly. Additional contributions of this project include the organization and instruction of a course in the scientific programming language, MATLAB, in an enrichment course for students from groups under-represented in science and technology, and the opportunity for US trainees to participate in an international collaboration.

This proposal focuses on supramolecular structures that do not have fixed size but can exist in multiple different sizes, all of which are stable. Thus, if a stimulus causes the transition from one stable state to another, the structure has information storage capability (memory). The investigators termed this type of structure variable-size stable structures (VSSS). Interest in VSSS arises from two seemingly unrelated fields: neuroscience and the physics of nanostructures. The molecular basis of memory is one the most fundamental unsolved problems in neuroscience. Evidence strongly suggests that synapses grow to encode memory. Thus, memory storage in the brain appears to be a structural problem, and efforts need to be made to understand the structural principles that make memory storage possible. The project integrates cutting-edge optical microscopy with theoretical modeling. Utilizing a newly-available super-resolution microscope, the investigators will make the first effort to observe synaptic growth during synaptic plasticity in real time. The goal of the theoretical efforts is to develop a physical theory of VSSS and evaluate different models, including ones that have emerged from the study of synapses. Questions to be addressed include: (i) The importance of cooperative interactions among multiple components to generating stable yet kinetically accessible and reconfigurable assemblages. (ii) Design principles that lead to self-terminating assembly, such as growth by finite-size modules. (iii) Mechanisms by which nonequilibrium energy consumption changes the limits of VSSS. An ultimate goal is a generalized theory for nonequilibrium self-assembly capable of describing VSSS.

This project is jointly funded by the Neural Systems Cluster in the Division of Integrative Organismal Systems and by the Physics of Living Systems Program in the Physics Division.

In many virus families, replication requires that hundreds to thousands of proteins assemble around the viral nucleic acid to form a protein shell called a capsid. Understanding the assembly pathways for capsid formation and learning how antiviral drugs can block or alter these pathways would provide information to develop new antiviral strategies and improve existing ones. Similarly, at least 20% of bacterial species have protein-based organelles called bacterial microcompartments, which are protein shells that assemble around a group of enzymes. Since microcompartments are essential for bacterial growth and pathogenesis, understanding the mechanisms that control their assembly would provide information for developing novel antibiotics that work by inhibiting microcompartment formation. Assembly mechanisms inferred from experiments alone are incomplete because intermediates are transient and thus not readily observed. Therefore, this project develops and applies computational models for capsid proteins, nucleic acids (NAs), putative antiviral agents, and microcompartment components that reveal details of assembly not accessible to experiments. The first aim will study how NAs guide assembly pathways toward particular capsid structures. Goals will include understanding experiments in which capsid proteins form different icosahedral morphologies to accommodate NAs with different physical properties (e.g. sequence length and base-pairing interactions), and testing simulated pathways against experiments from collaborators. The latter effort will include developing a computational tool to predict small angle x-ray scattering profiles from simulation trajectories as well as developing models that interpret novel light scattering experiments that monitor assembly of individual capsids. The second aim will examine how small molecules that perturb protein-protein or protein- NA interactions redirect assembly pathways. The goal is to learn how to design optimal antiviral agents. We will develop coarse-grained computational models that are informed by atomistic simulations and predict assembly pathways and products as a function of the amount and type of putative antiviral agent. Predictions will be compared against extensive data from our experimental collaborator on assembly of hepatitis B virus (HBV) proteins in the presence of potential antiviral agents. Finally, the third aim will study how bacterial microcompartments assemble around their enzyme cargos. The simulations will identify assembly pathways and critical control parameters for microcompartment assembly, while learning how protein shell assembly can promote and regulate liquid-liquid phase separation within cells. To enable simulating the length and time scales of assembly, our simulations employ advanced GPU computing and an approach to apply Markov state modeling to assembly reactions developed by our group. Furthermore, we use coarse-grained models that are informed by experiments and atomistic simulations.

Large scale data analysis capability has become the key factor that is driving rapid progress in all fields of science. This project will significantly expand the high-performance computing resources at Brandeis University, by acquiring state of the art GPU computing machines that enable big data driven research. The new capability will support integrated research projects across a variety of disciplines, including the areas of Biology, Biochemistry, Chemistry, Computer Science, Math, Physics, and Psychology. It will also provide a platform at Brandeis University for training the next generation workforce to develop and apply deep learning techniques, thus accelerating discoveries in basic research and technological innovations. The project will enable Brandeis researchers and instructors to utilize modern computing techniques to broaden participation in science, technology, engineering, and mathematics (STEM) fields.

Specifically, the new resources will include 16 GPU nodes and 1 storage node on a 10Gbit network fabric to allow rapid internode communications. This project will enable Brandeis researchers to conduct big data driven convergence research that enhances our understanding of the Rules of Life in areas ranging from neuroscience to virus assembly, and addresses the fundamental problems underlying societal needs (e.g., green energy). The emerging interdisciplinary research activities will also create an inclusive environment for developing novel and more powerful big data driven techniques. The project will enable courses and workshops that train faculty, postdocs, graduate students, and undergraduate students to effectively use state of the art GPU computing and deep learning techniques. It will allow Brandeis to further integrate its education and research via a current NSF funded REU site at Brandeis Materials Research Science and Engineering Research Center. In addition, it will enhance Brandeis' ability to broaden participation in STEM, especially by women and underrepresented minorities, through several existing programs, including the NSF funded REU site, the Transitional Year Program for economically disadvantaged students, the local Society for Advancement of Chicanos/Hispanics and Native Americans in Science chapter at Brandeis, the Brandeis Science Posse Program, and the Brandeis Scientists in the Classroom Workshop.

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.

This award provides support for a combined Gordon Research Conference (GRC) on Physical Virology: Viruses at multiple levels of complexity and Gordon Research Seminar (GRS), to be held Jan 22-27, 2023 in Lucca (Barga), Italy. The biennial GRC aims to transform the study of these processes by establishing Physical Virology as a paradigm for the intersection of fundamental physical laws and emergent biological function. The meeting brings together researchers with scientific expertise in virology, chemistry, materials science, mathematics, physics, and engineering who share a common desire to (1) understand the physical mechanisms that enable and regulate viral lifecycles, (2) use this knowledge to develop and engineer novel nanotechnology platforms based on viral particles or other self -assembling structures, with applications including biomimetic materials and optoelectronics, and (3) broaden physical virology to leverage recent advances in cell biology and protein design. The associated GRS workshop is a school that takes place immediately prior to the main (GRC) conference. The GRS is organized by a graduate student and a postdoc. The school will feature 11 talks by students and postdocs; a career and mentorship panel discussion comprised of individuals invited from industry, academia, and science communication. The COVID-19 pandemic highlights the need for these cross-disciplinary approaches to understand viral biology, predict global spread and impact, and generate the fundamental knowledge that provides the foundation for developing new treatments.<br/><br/>Broader impacts of this award include fostering interdisciplinary science, increasing the diversity, equity, and inclusivity (DEI) of the Physical Virology community, and the training and career development for early career researchers.<br/><br/>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.