Carol K. Hall - US grants

Interest in new protein isolation techniques has been stimulated in recent years by recent advances in genetic engineering and by increased demand from the medical sector for high purity proteins and enzymes. Most needed are recovery processes which are gentle enough for recombinant proteins and constitutive intracellular proteins, and yet are easily adapted to large-scale production. A technique which fulfills both requirements is extraction with aqueous polymer two-phase systems containing either polyethylene glycol and dextran, or polyethylene glycol and salt. The aim of the proposed research is the development of a general, comprehensive theory, based in statistical mechanics of protein solubility in two-phase aqueous polymer solutions with or without salt. The theory is expected to provide insight into the molecular mechanisms responsible for protein partitioning. The objective is to predict free energies, aqueous phase separations and protein partition coefficients as a function of protein and polymer concentrations, protein and polymer molecular weights, protein charge, pH, protein type, polymer type, salt type, ionic strength, temperature, and the binding energy of affinity ligands. The theory should also allow the prediction of salt union and cation partition coefficients. The single protein partitioning results will be test against experimental data on the partitioning of lysozyme, fumarase, malate-dehydrogenase, human serum albumin, and catalase. The multiple protein partitioning results will be tested against experimental data on polyethylene glycol/dextran aqueous solutions containing CO-hemoglobin and human serum albumin. The proposed research is intended to provide a useful framework for the organization of existing data aqueous two-phase extraction and for the optimal design of new biorecovery processes based on this method.

The aim of this project is the development of a general, comprehensive theory, based on statistical mechanics, of protein solubility in two- phase aqueous polymer solutions containing either polyethylene glycol and dextran or polyethylene glycol and salt. The objective is to predict free energies, aqueous phase separations and protein partition coefficients for a model aqueous polymer two-phase system as a function of a number of important parameters: protein and polymer concentrations, protein and polymer molecular weights, protein charge, pH, protein type, polymer type, salt type, ionic strength, temperature and the binding energy of affinity ligands. The theory will be supported by a series of experiments conducted in international collaboration with a world-renown expert in aqueous two phase extraction, Prof. Dr. M. R. Kula of the Institute for Enzyme Technology in Dusseldorf, Germany. The experiments will be performed both in Dr. Kula's laboratory and in the North Carolina State University laboratory. Despite the projected importance of aqueous two-phase extractive techniques for future separations technology, no comprehensive theoretical framework exists for predicting protein partitioning in these systems. This approach, which is based in statistical mechanics, will allow one to investigate the relative importance of excluded volume effects and electronic interactions and to predict values for both protein partition coefficients and ion partition coefficients. The research should provide insight into the molecular basis of protein partitioning and yield a useful correlation of protein partition coefficients.

The problems of human resource development are of high priority at this time for Engineering. Efforts to encourage women, minorities and the handicapped to choose careers in engineering are needed. This grant is to provide funds for a reception for women in chemical engineering to be held at the 1989 annual American Institute of Chemical Engineers meeting in San Francisco, CA. The purpose is to give women a chance to meet and discuss issues of common concern. The reception is open to all who are attending the meeting. A product of the meeting is a list of all female faculty members in the US, a list that is circulated and should help open lines of communication.

When two aqueous solutions of water soluble polymer such as PEG and dextran are mixed together, above critical concentrations, a liquid-liquid phase separation occurs. A similar situation occurs when PEG and salt are mixed together. Proteins or enzymes added to either of the resulting two phase mixtures will tend to partition unequally between the two phases, thus allowing for the extraction of a particular protein. Over the past three years, in collaboration with Professor Kula of the Institute for Enzymetechnology in Julich, West Germany, and under the auspices of an NSF grant (CBT-872084), the PI has been developing a statistical mechanical theory for aqueous two phase partitioning, and has been undertaking complementary experiments on the phase behavior of the PEG/Dx system. The experimentation involved the careful assemblage of phase equilibria diagrams, and the identification of the interfacial tension between the two phases as a sensitive indicator of composition. Theoretically, simple models of polymer-polymer, polymer-protein, ion-ion, protein-protein, protein-ion and polymer-ion interactions have been developed which can be used to calculate potentials of mean force in water. The proposed research suggests additional theoretical work along the same lines. The mean force potentials which have been developed are to be used to obtain the radial distribution function via the closure postulation of the integral equation technique. From the radial distribution function, thermodynamic properties can be obtained, and phase separations behavior identified. These calculations will be supplemented by Gibbs Monte-Carlo computer simulations of the phase equilibria. These simulations will allow verification of the equilibria obtained by the integral equation route, and will provide a method for obtaining phase equilibria for which the integral equation approach proves inadequate. Simulations and integral phase equilibria calculations will be carried out to develop theories capable of predicting phase equilibria in polymer/polymer and polymer/salt mixtures, and the segregation g of proteins including multiple protein partitioning and possibly the effect of affinity ligands attached to the polymer molecule.. Complementary experiments on protein partitioning will also be undertaken.

ABSTRACT CTS-9704044 Carol Hall/N.C. State This proposal describes a program of theoretical research aimed at understanding the mechanisms by which solutes such as polyethylene glycol (PEG) enhance the refolding of proteins and prevent aggregation. The goal is to develop molecular-level models that capture the essential features that govern the competition protein refolding and aggregation in both the presence and absence of solutes. By simulating the properties of model proteins and solutes on the computer, we will be able to explore how protein folding and kinetics are influenced by: protein type and concentration; denaturant type and concentration; solute type; concentration, and size; and temperature. The investigators will work on three parallel tracks whose objectives are: (1) to extend the two dimensional lattice Monte Carlo studies of protein folding and aggregation previously performed under NSF sponsorship to include the presence of model solutes that mimic the effect of PEG, (2) to develop simple off-lattice models based on the heteronuclear square-well chain model and then to use discontinuous molecular dynamic (DMD) to simulate protein folding and aggregation in the presence and absence of model PEG molecules. ***

Protein aggregation is a serious problem. For example, protein aggregation can interfere with the recovery of recombinant proteins from inclusion bodies, is a cause or associated symptom in diseases such as Alzheimer's disease or Downs syndrome, and can limit the stability of protein-based drugs during their packaging, shipping, storage and administration. An intriguing way to circumvent this problem is to add solutes that have the ability to suppress aggregation, e.g. polyethylene glycol (in vitro) and chaperones (in vivo). This proposal describes a program of theoretical research aimed at understanding the basic principles that underlie protein aggregation, and the mechanisms by which solutes prevent aggregation and enhance refolding. The goal is to develop molecular-level models that capture the essential features that govern the competition between protein refolding and aggregation in both the absence and presence of solutes. By simulating the properties of model proteins and solutes on the computer, we will be able to explore how protein folding and kinetics are influenced by: protein sequence and concentration; denaturant type and concentration; solute type, concentration, and size; and temperature. The proposal has two specific aims: (1) to develop simple, very general, off-lattice protein models based an the heteronuclear square-well chain model and then to use discontinuous molecular dynamics (DMD) to simulate protein folding and aggregation in both the absence and presence of model PEG molecules, and (2) to modify a more realistic protein model, such as one of the more successful intermediate resolution protein folding models, for use with our DMD techniques, thereby enabling efforts to simulate the folding and aggregation of specific small proteins and peptides. These simulations are expected to serve as a future basis for modelling the aggregation of medically important proteins such as beta amyloid, the protein whose aggregation is associated with Alzheimer's disease. Our theoretical work should assist scientists in: (1) choosing and/or designing solutes to suppress unwanted aggregation, (2) optimizing the in vitro refolding of recombinant proteins by manipulation of process variables such as protein concentration, denaturant concentration, etc., and (3) understanding if and how "solutes" contribute to medically- relevant aggregation such as beta amyloid plaque formation in Alzheimer's disease.

DESCRIPTION (provided by applicant): The aberrant assembly of normally soluble proteins into ordered aggregates, called amyloid fibrils, is a cause or associated symptom of many different human disorders including Alzheimer's, Parkinson's and Huntington's diseases, the prion diseases and adult-onset diabetes. Known collectively as the amyloidoses, these diseases are characterized by the slow deposition of a specific protein into amyloid fibrils, which then accumulate into plaques, destroying the function of the affected tissue, usually with degenerative and ultimately fatal consequences. An understanding of the molecular-level mechanisms that result in the aggregation of proteins into amyloid is essential for the discovery of potential therapeutic strategies and diagnostics. As-part of our NIH-sponsored effort to uncover the general physical principles that govern protein aggregation, we developed an intermediate-resolution protein model that allowed the simulation using discontinuous molecular dynamics (DMD) of multi-protein systems within days on a fast workstation. A recent breakthrough enabled us to simulate assembly of 48 16-residue alanine peptides into a fibrillar structure starting from the random coil state. This suggests that the intermediate-resolution model could be used as a computational tool to explore fibril formation in short peptides. The project has three specific aims: (1) to learn the basic physical principles governing protein fibril formation by using DMD to simulate multi-protein systems containing polyalanine chains modeled using our intermediate-resolution model, (2) to shed light on the molecular-level mechanisms responsible for the aggregation of polyglutamine, the protein whose fibrillization is linked to Huntington's disease, by extending the intermediate-resolution model to the treatment of polyglutamine side chains and then performing DMD simulations, and (3) to investigate the aggregation and possible fibrillization of multi-protein systems containing specific amyloidogenic peptides, particularly the Alzheimer's peptides Abeta(1-40) and Abeta(1-42), by extending the intermediate-resolution model to a coarse-grained representation of all 20 residues, performing DMD simulations, and comparing our results with experiment. This work should culminate in a detailed molecular-level picture of the fibrillization process, thereby providing insights to guide medical research workers directly involved in developing therapeutic strategies or inhibitors to circumvent those steps in the fibrillization process that are most responsible for cell damage.

This proposal requests funds for the acquisition of a 64-node Linux cluster for bio- and nano-materials simulations. The cluster will be a shared facility to be used by four interdisciplinary research groups in Physics, Materials Science and Engineering, and Chemical Engineering. It will be maintained in partnership with NC State's High Performance Computing group, and used primarily by graduate and postdoctoral students in fullfillment of their research requirements. Current research of the group cuts across computational physics, materials science, and structural biology, with an emphasis on nanotechnology and biophysics applications. Research projects for which the cluster will be used include simulations of biomolecules such as solvated DNA and proteins, dynamics of protein aggregation and molecular recognition phenomena, investigation of quantum transport through molecular electronic systems, studies of nanoindentation, nanofluidics, smart materials, and many more. The research cuts across many length and time scales, and therefore typically requires a multiscale approach. Simulation technology in use ranges from state-of-the art quantum chemistry methods at its most accurate, to finite-element and phase-field approaches at the continuum length scale.


This is an Instrumentation for Materials Research (IMR) proposal aimed at acquiring a computer cluster to be used as a research tool for bio- and nano-materials modeling and student training. The cluster is to be shared by four research groups at NC State, and will maintain and enhance the research competitiveness of the groups. While expecting to use all of the computational cycles that this cluster would bring, any excess cycles will be donated free of charge to the larger NC State research community, thereby ensuring maximum impact and utilization of this important computational resource. The research that will take advantage of this facility will have a broad impact on the development of new materials and simulation technology for bio- and nanotechnology. The latter include topics such as materials with optimized microstructures, probes for the sub-micron scale, mechanical properties of materials relevant for the microelectronics industry, and molecular systems for nanoelectronic applications. Biological research applications include new understanding of protein aggregation, microarrays, the chemical and mechanical properties of DNA and solvated proteins, and understanding of molecular recognition phenomena.

ABSTRACT


Molecular Recognition in Microarrays: A Computer Simulation Study

Project Summary:

DNA microarrays have revolutionized the way that biological research is done, enabling
the analysis of thousands of genes in a single experiment. Microarrays are being used in gene profiling, toxicogenomics, drug discovery, pathway biochemistry, and legal identification. Even though this powerful technique has been enthusiastically adopted by the scientific community, it is far from mature. Considerable uncertainty exists about how to design microarrays for maximum sensitivity and specificity. A fundamental understanding of the interplay between the various factors that affect microarray performance is needed.

The proposed research has two basic objectives. The first objective is to develop guidelines for designing microarrays with maximum sensitivity and specificity. This will be accomplished by performing Monte Carlo simulations of the adsorption and molecular recognition of lattice model DNA target molecules by lattice model probe molecules tethered to a microarray surface. DNA is basically at the nano-scale. The factors that affect the sensitivity and specificity of microarrays will be systematically explored including: the probe sequence, length and concentration; the target sequence, length and concentration; the nucleotide compositions of the probe and target, the spacer length, and the temperature. Results from this study will be compared to those of our experimental collaborator, Professor Stefan Franzen and to data in the literature. The second objective is to develop a new computational tool that can be used to improve accuracy in interpreting microarray data. This will be accomplished by building a new intermediate resolution model of DNA molecules and then performing implicit-solvent discontinuous molecular dynamics simulations of the adsorption of target model DNA molecules (both perfect match and mismatch) on microarray surfaces containing probe model DNA molecules. A multiscale modeling approach will be used to extract the energetic and geometrical parameters in the model from potentials of mean force calculated during explicit-solvent CHARMM simulations. A sub-objective here is to quantify the difference between hybridization on surfaces and hybridization in bulk, and then to use this information to modify and improve the bulk-based theoretical models currently used
to correlate microarray data on perfect matches and mismatches. Results from this part of
the project will be compared to experimental results of our collaborator Professor Erdogan Gulari. Taken together these two projects should give us a good






physical picture of molecular recognition in DNA microarrays. The broader impacts of
the proposed research are the following. The proposed research could have an impact on the world of medical research. DNA microarrays are heavily used in cancer research today as researchers struggle to identify genes that are expressed in tumors, or to
identify genetic markers (oncogenes) that could serve as potential targets for
chemotherapy. In addition to training two graduate students, research and education will be fostered by the following two activities. (1) Hybridization of DNA on microarrays will be used as the basis for a number of examples that will be developed for the PI's undergraduate chemical engineering thermodynamics course, and inserted into an undergraduate chemical engineering thermodynamics textbook that she is writing. (2) A power point presentation describing the basics of genomics and culminating in a description of DNA microarrays will be prepared for dissemination via the web.
The PI will continue her considerable but informal activities to broaden the opportunities
for women. Since she was one of the first women to be appointed to a chemical engineering faculty in the US, the PI is now viewed as a role model by younger members of the academic community, and hence serves as an informal mentor to many women students (undergraduate and graduate) at NCSU, as well as to women faculty and prospective women faculty across the US. The PI attracts a disproportionate number of women graduate students to her research group; of the 16 graduate students that she has advised over the past five years, 9 have been women.

CBET-0835794
Hall

DNA can be possibly used to construct tiny scaffolds with many potential applications including molecular medicine, electronics, sensors, computing and communications equipment, and consumer electronics. Two-dimensional nanostructures have already been devised, but further design and development has so far been limited to making incremental improvements using empirically derived guidelines.

This project intends to break these barriers using advanced modeling techniques, a multidisciplinary team of modelers and experimentalists, and a cyber-driven strategy to design complex, three-dimensional objects at nanometer size scales. First, modified natural and non-natural nucleosides (the components RNA) will be devised to increase the number of molecular tools available to create these structures and to provide accessible sites for attachment of functional components. Structures will be computed for these two- and three-dimensional DNA-based building blocks, with and without modified nucleosides. Stability will then be determined for the building blocks in solution, on planar surfaces, and/or with metallic nanoparticles. Ultimately, new, hybrid extended three-dimensional architectures will be designed and built using these findings. A key to success is testing and refining the modeling approaches by comparing computed results to the team's experimental results.


The education and outreach agenda includes a team mentoring program for a small group of women graduate and undergraduate students, individual outreach efforts to underrepresented groups, and training of four graduate students and four undergraduates. Cyber-enabled education is an especially interesting aspect of the project, where a website containing freely-available cyber-structure software and visuals will allow researchers to design their own DNA superstructures and will also allow community members, including grades 7-12, to learn more about DNA self-assembly.

This program will provide a strong international experience for doctoral students at North Carolina State University and University of North Carolina at Chapel Hill, through collaborative research projects and teaching with institutions in and near Berlin, Germany. The research project will focus on interdisciplinary studies of self-assembly of molecules on solid surfaces to form nanostructures. The German institutions involved will be the Technical University of Berlin (the lead institution on the German side), Humboldt University and the Max Planck Institute of Colloid and Interface Science (Golm, Potsdam). The collaborative program will involve 13 faculty members in Germany, and 15 doctoral students there. On the U.S. side the project will involve 12 faculty at NCSU and UNC-Chapel Hill, and will support visits by 15 U.S. doctoral students to Berlin, where they will spend a part of their doctoral study period (a minimum of 11 weeks) working in the overseas partner institution. U.S IRES Fellows will have a U.S. advisor and a co-advisor in the partner institution in Germany, and will continue working on their research project after return to the U.S. The German doctoral students will spend a similar or longer amount of time working in the U.S. host institutions; funding for the visits by German students to the U.S. is available from a grant from the Graduate College program of the German Science Foundation (DFG). The educational program will include course modules in theory, experiment and technology of nanoscience taught by faculty on both sides and made available by video transmission. Regular IRES seminars, in which faculty, students and postdocs give short accounts of their latest results, will be broadcast synchronously as video conferences. There will be an annual meeting of the participants, including German colleagues (students and faculty), to discuss results and to assess the program. The plan described here is the result of workshops & discussions held by the participants in Berlin and Raleigh.
Intellectual Merit. The self-assembly of surface-active molecules to form various nano-scale structures on solid surfaces (micellar structures on surfaces and in pores, thin films, patterned films, nanoclusters, etc.) lies at the heart of many biological and physical processes, but the fundamental principles of how molecules self-assemble to form these structures are poorly understood, making it difficult to predict and design nano-structured devices. This graduate program will bring together many experts from diverse fields and institutions to develop a fundamental understanding of such processes.
Broader Impact. Improved understanding of directed self-assembly will impact many important technologies, including microelectronics, chemical and biological sensors, photonics, catalysis, drug delivery and medicine. The strong international aspects of the program address an important need in U.S. graduate education at a time of increasing globalization. We believe the international experience gained will have an important and lasting impact on the outlook and careers of the students. Recruitment of students from under-represented groups will be facilitated by our close contacts with North Carolina Central University (NCCU), a nearby (20 miles) HBCU, through coordination with NCSU?s AGEP/Opt-Ed program, and NCSU?s Women in Science & Engineering (WISE) program which is aimed at encouraging women to enter this field. Prior to departure the U.S. students will network with the visiting German students and will be encouraged to take the German for Graduate Students course offered at NCSU. Students whose research is in appropriate areas will have access in Berlin to the North German supercomputer network (at Konrad-Zuse-Institut, Berlin), and to the national synchrotron source BESSY, located at the Helmholtz-Zentrum in Berlin.

This project is supported by NSF's Office of International Science and Engineering (OISE) and the NSF Directorate of Engineering (ENG), Division of Chemical, Bioengineering, Environmental, and Transport Systems (CBET).

The Triangle Center of Excellence for Materials Research and Innovation (CEMRI)* will be a national resource for materials science and engineering research and education in the Raleigh-Durham-Chapel Hill (Triangle) area of North Carolina, a thriving technological and economic hub with a high concentration of materials innovation activity in both academia and industry. The Triangle CEMRI will focus on the study and development of soft matter components to be used in programmable assembly and functional and hybrid materials that result from the assembly of these components. It will synergistically leverage existing and complementary strengths of Duke, NC State, UNC-Chapel Hill and North Carolina Central University, a top-ranked public HBCU. The Triangle CEMRI will have a significant impact in soft matter materials science through generation of (i) new fundamental insights and theoretical understanding, (ii) new design principles, (iii) new applications and uses for colloidal and macromolecular materials and their higher order assemblies, and (iv) an integrated education and outreach program. Understanding, harnessing and exploiting the dynamic processes related to the aggregation of multicomponent particulate and macromolecular assemblies represent significant current frontiers in materials research. Two interdisciplinary research groups (IRGs) comprised of leading researchers in materials theory, simulation, synthesis, processing and applications will surmount these frontiers. A Seed-funding program will also be instituted to allow the extension of the Triangle CEMRI's scope to new areas of soft matter research.

IRG1: Multicomponent Colloidal Assembly by Comprehensive Interaction Design. The goal of IRG1 is to develop a fundamental understanding of self-assembly of bulk materials from multi-component suspensions of very small particles (colloids). The team will focus on elucidating the fundamental rules that govern programmed colloidal assembly for materials fabrication by design. Ultimately, this work will have ramifications for the production of hybrid photonic and phononic crystals, anisotropic conducting films, self-healing materials, "smart" gels, metamaterials, and other advanced engineering materials.

IRG2: Genetically Encoded Polymer Syntax for Programmable Self-Assembly. The overall goal of IRG2 is to establish the rules for the design of "syntactomers" whose phase behaviors facilitate programming of their self-assembly into supramolecular structures. Syntactomers are macromolecules that consist of a collection of "letters" (monomers that can either be amino acids, nucleotides or synthetic components) are arranged within "words" (repeat units), which are in turn arranged by following a syntax - defined as the arrangement of words - into "phrases" (macromolecules). A new paradigm for macromolecular design will lead to new materials to be used as drug delivery vehicles, actuators, nanofibers, switchable membranes, functional connectors, and scaffolds for mineralization, tissue implants or 3-D cell culture.

The Triangle CEMRI will coordinate establishment and access to specialized materials research facilities across the Research Triangle. Its researchers will have access to a global network of research resources, including several national laboratories and laboratories in Europe and Asia. Innovation and technology transfer will be enhanced by the Triangle CEMRI activities aimed at facilitating and catalyzing interactions with both large and small industrial and non-profit commercialization and innovation partners. A comprehensive integration of training, educational and outreach activities will take advantage of the high level of scholarship in materials research and related areas in the Research Triangle area. The overarching goal of the Triangle CEMRI in education, training, and outreach is to infuse materials science, engineering and technology education with a new relevance, excitement and value to audiences ranging from G5-12 students, undergraduate students, graduate students, postdoctoral researchers, to the public sector.

* an NSF Materials Research Science and Engineering Center (MRSEC)

Abstract

#1236053
Hall, Carol K.

Excitement about the potential of nanotechnology to revolutionize the fields of electronics, materials, medicine, and energy is tempered by concerns about the impact of engineered nanomaterials on the environment and on human health. The small sizes that make nanomaterials so attractive for the creation of new molecular-scale engineering devices render them highly susceptible to adsorption by the human body through inhalation, ingestion and skin penetration. Previous studies suggest that toxicity is related to the physicochemical properties of nanoparticles such as size, shape, surface area, charge, agglomeration status, and hydrophobicity but no general trends have been established. Our research is based on the current thinking that a key step in the body's response to nanoparticle intrusion is the formation of the protein corona, an envelope surrounding the nanoparticle containing proteins adsorbed from the biological fluid following initial exposure. The long term goal of the proposed research is to develop a correlation tool capable of predicting the nature and composition of the protein corona on engineered nanomaterials. This research is intended to be the first step in the development of risk assessment models for nanoparticles. Subsequent steps will be done with collaborators who plan to use the correlation to help predict the in vivo disposition (ADME) of nanomaterials, develop physiologically- based pharmacokinetic (PBPK) models and ultimately create risk assessment model.

Intellectual Merit: The objectives are: (1) to predict which proteins in biological fluids adhere to specific engineered nanomaterials, (2) to provide a set of descriptors that characterize the composition and physico-chemical properties of the corona of a given engineered nanomaterial, and (3) to use these tools to rank order the affinities of proteins for specific nanoparticles. Multiscale modeling will be used to determine geometric and energetic parameters for a new intermediate-resolution model, "PRIME/NP" for protein/nanoparticle systems. Energy calculations based on PRIME/NP will be used to predict nanoparticle/protein affinities, and discontinuous molecular dynamics (DMD) simulations will be used to model competitive adsorption of proteins on nanoparticles.

Broader Impacts: The proposed research could impact research in the area of biomaterials where the biocompatibility of medical implants is an issue. In addition to training a (female) Ph.D student, research and education will be fostered by: (1) using nanoparticle-protein corona formation, its relation to the potential toxicity of engineered nanomaterials, and the response to this issue by government and society as the basis for examples developed for the PI's undergraduate chemical engineering thermodynamics course, (2) creating a power-point presentation describing the basics of nanotechnology and measurement of toxicity for dissemination via the web, and (3) making a video presentation targeted for general audiences that shows how molecular-level computer simulation can be used to understand nanoparticle toxicity The PI will continue her considerable but informal activities to broaden the opportunities for women and will introduce a brown bag lunch series for women graduate students and postdocs in her department at NCSU.

ID: MPS/DMR/BMAT(7623) 1207022 PI: Sofou, Stavroula ORG: Rutgers University
ID: MPS/DMR/BMAT(7623) 1206943 PI: Hall, Carol ORG: NC State University

INTELLECTUAL MERIT: The most promising strategy at present to provide effective control of advanced solid cancer is a combination of therapies. A potential component of this combination is antivascular therapy. The goal of this work is to design iv-administered theranostic liposome nanocarriers that can be programmed to target tumor vasculature while sparing healthy sites and to release a chemotherapeutic agent, deliver a radioactive imaging agent or both. This will be accomplished through a combined experimental and theoretical approach to develop highly selective lipid vesicles composed of a new class of bi-lipid membranes that rapidly and extensively release doxorubicin intracellularly or deliver positron emitters. The high killing efficacy of the liposomes is based on a dual fusion mechanism that is activated only upon cellular internalization. The project's innovation lies in the choice of individual base components and the synergistic way that they work together to optimize delivery of the drug to the proper site. An additional innovation is the use of molecular level computer simulation to explore the consequences of various choices of liposome parameters "in silico" before trying them out in the lab, thus reducing the number of trial-and-error steps that would normally characterize this type of work . The base components are the following: PSMA (Prostate Specific Membrane Antigen), which is present on tumor vasculature but not in normal tissue, is the target. An anti-PSMA antibody is the ligand. The liposomes are comprised of two functionalized lipids: PEGylated lipids tethered to anti-PSMA antibodies and lipids functionalized with a fusion peptide that promotes fusion with the endosomal membrane. The mechanisms of delivery are the following. During circulation in the blood, the exposed anti-PSMA antibodies result in selective neovasculature targeting while uniformly distributed PEGylated lipids on the liposome surface mask the fusion peptides. Upon endocytosis of liposomes by tumor endothelial cells, pH-induced lipid phase-separation, and domain formation on liposome membranes activates two fusion mechanisms: (1) The fusion peptides become unmasked and bind to the endosome membrane, and (2) The liposomal domain boundaries serve as sites to nucleate fusion with the endosomal membrane. The net result is that the liposome releases its cargo directly into the cytoplasm of tumor endothelial cells, as opposed to the endosome, avoiding entrapment in the endosomal pathway and subsequent degradation by the lysosome. There are three aims: (1) Develop an experimentally informed general computational tool to facilitate the design of liposomes and to test hypotheses about the role of the different components in the proposed hierarchical assembly. (2) Engineer liposomes containing anti-PSMA ligands and small fusion peptides, and investigate the conditions in which the corresponding functionalities exhibit optimal behavior. (3) Demonstrate that dual-fusion liposomes loaded with doxorubicin and Y-86 exhibit: (a) selective targeting of tumor endothelium analogues, (b) effective release of chemotherapeutics and killing of targeted cells, and (c) delivery of sufficient amounts of Y-86 for diagnostic applications.

BROADER IMPACTS: Since advanced solid cancer has no cure, many patients could benefit from the proposed research that aims to develop diagnostic and treatment protocols that significantly extend the life expectancy and improve patients? quality of life. The research pursued here will be supplemented by a strong educational component that includes training of two female graduate students and several undergraduate students assigned to this project, integration of several topics of this research in a newly launched open-ended senior design project, general outreach and mentoring activities for high school students and their teachers, and mentoring activities for women graduate students and faculty across the nation. In particular, the 6-week outreach summer program, which will be conducted at Rutgers University, aims to encourage underrepresented and minority high school students to follow a career in sciences and engineering. The program includes hands-on research training, a series of lectures given by speakers from academia and industry on contemporary issues related to biomaterials, and visits to neighboring pharmaceutical industries. Educational materials will be developed that highlight this research including a power point presentation introducing the basics of nanotechnology and drug delivery via soft materials for dissemination over the web.

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Hall, Carol K.


Generic adhesives capable of sticking to surfaces in water or in high moisture conditions are in demand for applications ranging from marine coatings to medical devices to underwater sensors. One way to develop such adhesives is to learn from nature. Analysis of the adhesive substances employed by mussels, barnacles, algae and yeasts reveals two common factors that seem to contribute to their ability to attach to a wide range of surfaces in water: 3, 4-dihydroxyphenylalanine (DOPA) and amyloid-forming peptides. A new class of generic underwater adhesives will be developed by combining synthetic DOPA-containing polymers and amyloid-forming peptides. Synthetic materials will be deployed, instead of the naturally-occurring proteins favored by other investigators, because they should be easier to tailor and to produce in large scale. A computationally-driven program of research will be conducted to better the understanding of how the peptide sequences and DOPA-containing polymers in a peptide-polymer conjugate can be engineered to function synergistically, thereby providing superior adhesion to surfaces in water.

Atomistic and coarse-grained molecular simulations will be used to develop a set of molecular-level principles that can guide the design of DOPA-peptide conjugates. Such materials, which are inspired by naturally-occurring materials including mussels and barnacles, are expected to form the basis of a new generation of underwater adhesives capable of binding to a wide range of surfaces. Five short peptide sequences taken from the amyloid forming regions of the glues employed by yeast cells have been identified as good starting sequences. Four surfaces will be considered: graphite, graphite coated with OH groups, gold, and titanium oxide. The specific aims of this project are to: 1) identify the roles played by each amino-acid residue on naturally-derived peptides in forming amyloid structure; 2) develop a set of principles for designing polymer-peptide conjugates such that the peptides can form amyloid structures without associating with the polymers; and 3) investigate the behavior of conjugates near four model surfaces to assess their ability to attach nonspecifically in water. The DOPA-peptide conjugates that show the most promise will be synthesized by an experimentalist collaborator, and tested to see if they form amyloid structures and if they adhere strongly to the four surfaces.

The proposed project could impact research in the areas of interfacial phenomena, sensing, coating, surface modification and drug delivery where material adherence to surfaces in water is critical. The computational design strategy, which draws initial inspiration from natural products and then iterates back and forth between atomistic and coarse-grained simulations to home in on promising molecular architectures, could point the way to the systematic design and discovery of other new materials that are tailored for specific applications. In addition to training a Ph.D. student, research and education will be fostered by: (1) using the computational design of the new materials as the basis for examples developed for the PI's undergraduate chemical engineering thermodynamics course, (2) creating a power-point presentation describing the basics of computational materials design and distributing via the web, and (3) making a video presentation targeted for general audiences that shows how molecular-level computer simulation can be used to design materials with special functionality. The PI will continue her considerable, but informal, nationwide activities to broaden the opportunities for women in STEM fields and will introduce a brown bag lunch series for women graduate students and postdocs in her department at NCSU to discuss topics of common interest.

This RAISE project is jointly funded by the Biological and Environmental Interactions of Nanoscale Materials program in CBET Division in the Engineering Directorate, the Molecular Biophysics Program in the Division of Molecular and Cellular Biosciences in the Biological Sciences Directorate, and the Office of Integrative Activities.

In this multi-disciplinary project, nanomaterial scaffolds, or hydrogels, with immobilized enzymes will be produced using proteins as a design template. The proposed method provides a novel alternative to conventional immobilization techniques which are more difficult and time consuming. This novel assembly technique is designed so that it selectively self-assembles into nano fiber structures. This targeted design and assembly of proteins into nanofibers is an exciting new research frontier that is largely unexplored with regard to both fundamental protein assembly and design of functional nanomaterials. A multi-disciplinary team of investigators will combine their expertise in modeling, imaging and characterization methods in order to demonstrate novel protein assembly and to advance fundamental understanding of protein assembly. The proposed technique will be an extraordinary improvement over the current state-of-the-art in protein assembly methods. Successful implementation of the proposed technique is anticipated to have a long-term broad impact on the engineering of novel functional materials for various biomedical and biotechnological applications. A variety of educational activities will be developed, including an iPad app on protein folding, and a video describing how computational methods can be used to design new biomaterials.

The proposed method bypasses conventional immobilization techniques in which the nanostructured scaffold is functionalized post-assembly via reactions at its surface. Instead, enzymes are expressed by bacteria from recombinant DNA with peptide fusion tags that mediate their assembly into nanostructured materials. The key to the method is the use of fusion tags that co-assemble into fibrillar structures when mixed with a complementary peptide, but remain unassembled when pure. Co-assembling peptides are an exciting research frontier that is virtually unexplored in both protein biophysics and functional nanomaterials. The goals of the project are to demonstrate novel enzyme-functionalized supramolecular hydrogels, and to advance fundamental biophysical understanding necessary to predict peptide co-assembly. Three specific aims are proposed: (1) characterize the assembly process and resultant structure for known â-sheet nanofiber-forming co-assembling peptide pairs, (2) design and test new pairs of selectively co-assembling peptides and, (3) test co-assembling peptides as tags to immobilize proteins in nanostructured biomaterials. Each aim will leverage the computational modeling expertise of PI Hall, with expertise in spectroscopic and microscopic characterization of peptide nanofibers provided by Co-PI Hudalla and solid-state nuclear magnetic resonance expertise provide by Co-PI Paravastu. The proposed enzyme immobilization method will be an extraordinary improvement over the current state-of-the-art in protein immobilization methods and hence opens the door to addressing long-standing challenges in installing biologically-active, folded proteins into biomaterials. A variety of educational activities will be developed, including an iPad app on protein folding, and a video describing how computational methods can be used to design new biomaterials.

Computer simulation methods based on Molecular Dynamics (MD) have been used for decades to understand chemical and biochemical phenomena at the molecular level. MD is a very powerful tool that has enabled scientists to understand the behavior of molecules crucial for life such as proteins and nucleic acids. MD has also been used to understand diseases and develop new drugs. However, MD is limited in both the size of the systems that can be studied and the amount of time that can be simulated. Many complex phenomena relevant to life involve systems too large to study with MD, or require following the system for much longer times. An alternative to traditional MD called discontinuous molecular dynamics (DMD) has been shown to be much more efficient to study biomolecular processes. To date, however, the use of DMD has been limited due to its inability to take advantage of modern parallel computers. This project will develop a next-generation parallel DMD software that will enable the study of complex molecular phenomena involving larger systems and longer time scales. Detailed knowledge of such processes will considerably advance the development of new materials and drugs, and human health. The project team combines the computational and experimental expertise to successfully develop and validate a robust parallel DMD software framework. The software and results will be actively shared both with the computational simulation community and with the scientific and engineering community at large, contributing to the capability, capacity, and cohesiveness of the national cyber-infrastructure ecosystem. Furthermore, the results of this project will be used in outreach efforts geared toward the education and inclusion of minorities traditionally underrepresented in higher STEM education.


This project aims to develop an open software framework that enables multi-millisecond dynamic simulations of peptides and peptide-mimetics by implementing a parallel discontinuous molecular dynamics (DMD) package. Unlike current molecular dynamics (MD), which features limited simulation timescales, discontinuous molecular dynamics (DMD) assumes ballistic motion of the particles between interaction events and enables the study of phenomena across much longer time scales. To demonstrate the approach, the project will (1) develop a parallel version of existing serial DMD codes to enable extending simulation times from hundreds of microseconds to several milliseconds; (2) extend and improve the available DMD peptide force field, adding parameters for non-natural peptides and peptoids; and (3) develop software for translating interaction potentials from traditional MD to DMD. The project team possesses the complementary expertise necessary for this project, including coarse-grained models and force fields for complex polymers and peptoids, MD simulation of protein self-assembly and peptide-protein binding processes, synthesis of protein-binding peptides and peptoids, and measurement of thermodynamic and kinetic binding parameters. The tools resulting from this research will allow the scientific and engineering community to model and study very long time-scale phenomena, such as biopolymer folding, aggregation and inhibition of aggregation, fibril formation, and protein-binding. This toolbox shows great promise to not only accelerate innovation in the computational design of biomaterials, but also to impact the molecular simulation community focusing on highly complex systems, up to cell-level dynamics. Notably, this project is ideal for the National Science Foundation's Cyber-infrastructure for Sustained Scientific Innovation (CSSI), as it (i) contributes to the capability, capacity, and cohesiveness of the national cyberinfrastructure ecosystem by providing user-friendly open-source computational tools, (ii) actively engages CI experts and testers of our toolbox, who would potentially be its ultimate users, (iii) advances our current capabilities in developing bioactive peptides and peptoids, (iv) establishes plans and metrics that encourage measurement of progress and certify the quality of shared tools and results, and (iv) devise strategies to combine wide-access with long-term community-driven development and progress.

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.

Developing a drug that will cure cancer is the holy grail of the pharmaceutical industry. One strategy is to produce antibodies that mimic, yet enhance, the body's natural ability to bind to, and eliminate, foreign agents (antigens) that lead to chronic and fatal diseases, including cancer. Improving upon the body's natural ability to self-heal requires producing high quantities of highly purified antibodies that are designed to seek out specific antigens while leaving healthy cells unharmed. Producing high purity, targeted synthetic antibodies requires isolation and growth of a culture of cells that produces that antibody, followed by recovery of the antibody from the cell culture. This process leads to monoclonal antibodies, reflecting that one (mono) immune cell able to produce the antibody of interest was "cloned" (reproduced and grown) in large quantity. Recovery and purification of monoclonal antibodies from the complex media that comprises the cell culture is difficult, and thus expensive. Furthermore, monoclonal antibodies are large and complex biological molecules, features that lead to sluggish penetration of the monoclonal antibody into biological tissues. Identifying the particular fragment of the antibody that binds to the targeted antigen and producing only that fragment of the antibody (Fab), thus increases tissue penetration and the potency of the treatment. Fragmentation addresses penetration concerns, but recovery of Fabs from isolated cell cultures remains a challenge. Current methods for Fab recovery are expensive and use potentially-immunogenic proteins. The goal of this project is thus to computationally design and synthesize new peptide ligands (short protein-derived molecules) that will selectively recover targeted Fabs, and can easily be produced in a laboratory rather than derived from cell cultures.

This computational project will screen short novel peptides for affinity, selectivity, and reversible binding to FAbs. The screening will use a previously developed search algorithm that identifies short peptide sequences (less than 25 amino acids) that have high affinity for a target Fab at neutral pH, but release the Fab at mildly acidic conditions (4.0 < pH < 5.0). Moreover, the computations will identify short peptide sequences that distinguish between Fabs with kappa and lambda light chains, and allow fractionation of kappa-lambda mixtures. The project is 'high risk' and exploratory because a good initial guess for the sequence of the peptide binder is currently unavailable. The computational predictions will be validated with laboratory synthesis and testing. The project will train a post doctoral researcher, and enable further efforts to broaden participation of women and under-represented minorities in STEM via mentoring, seminars, and outreach efforts. If successful, this project will lead to the development of short chain (<15 amino acids) synthetic peptides for Fab recovery and selective differentiation of kappa and lambda Fabs. These two outcomes represent a new paradigm for antibody purification, with foreseeable extension to fractionation of other antibodies, assay development, investigation of the individual therapeutic powers of antibody subclasses for immune protection, disease diagnosis, and design of novel antibody therapeutics.

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.

Peptides are short chains (sequences) of naturally-occurring amino acids. They are found in all living cells and tissues, where they perform vital biological functions. Peptides are now being considered for use in nanotechnology as they are able to assemble to form a variety of nanostructures - nanofibers, nanosheets, and nanoparticles. Such structures have potential applications in a wide variety of fields including medicine, electronics, enzyme catalysis and drug release. The goal of this project is to develop an open software toolkit that enables the identification of peptide sequences that are capable of assembling into user-selected fiber-like structures. Users will be able to screen potentially thousands of peptide sequences that assemble into the nanostructure of their choosing, and rank order them according to their stability. An algorithm, PepAD (Peptide Assembly Design) will be developed that searches for sequences that assemble into structures specified by the user. An accompanying software package will allow further analysis of the relative speed at which a large number of these peptide sequences form the desired structure. To establish efficacy and a basis for future improvement of computational tools, selected designs will be validated experimentally using advanced biophysical characterization techniques and solid-state nuclear magnetic resonance spectroscopy. PepAD will be open source and easy to run. Its use by the developers and by members of the scientific and engineering communities should lead to the ability to design the next generation of complex nanostructures. The toolkit, which will be the first of its kind for these types of assemblies, will be available on GitHub and on the NSF-sponsored Molecular Simulation and Design Framework (MoSDeF).

Many peptides are known to adopt beta strand conformations and assemble spontaneously into a variety of nanostructures--- nanofibers, nanosheets, nanoparticles, etc. - with applications in a wide variety of fields including nanomedicine, electronics, drug release, and hydrogels. The goal of this project is to develop an open software toolkit that enables the identification of peptide sequences that are capable of assembling into user-selected beta-sheet-based structures. An algorithm, PepAD (Peptide Assembly Design) will be developed that searches for sequences that assemble into structurers specified by the user. PepAD will allow users to screen potentially thousands of peptide sequences that assemble spontaneously into the structure of their choosing, and rank order them according to their stability. Discontinuous molecular dynamics (DMD) simulation software along with the PRIME20 force field will also be made available to enable analysis of the designed structures? assembly kinetics. To establish efficacy and a basis for future improvement of computational tools, selected designs will be validated experimentally using biophysical characterization techniques and solid-state nuclear magnetic resonance (ssNMR) spectroscopy. There are four objectives: (1) develop an algorithm, PepAD, that identifies short peptide sequences that are capable of self-assembling into user-determined amyloid structures; (2) perform DMD/PRIME20 simulations to examine assembly kinetics, (3) synthesize and test the peptide designs using biophysical characterization experiments and ssNMR, and (4) community test and refine the PepAD software and then install it on GitHub and on MoSDeF as a plugin. The toolkit, which will be the first of its kind for beta-sheet assemblies, will be open source and easy to use. Successful implementation of this software will pave the way for the computational design of nanostructures that self-assemble: (a) in response to a trigger such as a change in temperature, pH, or specific ions, and (b) when the peptides are conjugated to functionalities like small molecules, recognition elements, fluorophores or enzymes. Outreach activities include the creation of a video for general audiences that describes how molecular-level computer simulations can be used in the design of new materials and an iPad app that allows users to computationally design model proteins and then watch movies of them as they fold. The project will use the concept of harnessing self-assembly and related ideas to design educational activities for undergraduate STEM students. The project will work to broaden opportunities for women and minorities, and to increase science awareness in K-12 students.

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.

Many biological processes such as cancer cell proliferation, inflammation, and infection occur in the human gut. Biologic therapies, or treatments using substances made from living organisms, are particularly useful in treating these diseases and infections. The biological molecules used in biologic therapy tightly bind to specific molecules or organisms within the gut to modulate their behavior. Unfortunately, production and distribution of biologic therapies is incredibly complex and expensive, limiting availability to the public. A possible alternative approach is to make the biologic drugs directly in the patient's gut using unused dietary material and engineered microbes. Since the human gut is much more complex than an industrial bioreactor used to produce conventional biologics, there is still much to learn about how to accomplish this feat. This project will investigate strategies for biomanufacturing short chains of amino acids (peptides) directly in the large intestine using engineered probiotic yeast. The peptides will be optimized to bind with the toxins produced by Clostridioides difficile, the hospital-acquired gastrointestinal infection commonly referred to as C. diff. A yeast strain related to baker's yeast, Saccharomyces boulardii, will be engineered to produce the peptides under the harsh conditions of the human gut. The effectiveness of this approach will be examined in model organs, or 'miniguts.' This process of delivering drug molecules directly to the gut using engineered microbes promises to substantially reduce the cost of biologic therapeutics and, subsequently, improve human health. The investigators will also engage in research-related education and outreach, including developing a weekend symposium for high school teachers on microbiome engineering. Activities toward broadening the participation of underrepresented groups in STEM will include mentoring and active recruitment efforts.

In situ biomanufacturing, wherein therapeutic molecules are synthesized directly in the human gut by engineered microbes, is an attractive alternative to the complex manufacturing and oral delivery of biologic therapies. However, the human gut is unlike any industrial bioreactor, and many outstanding questions remain before in situ biomanufacturing becomes reality. The investigators posit that manufacturing peptide-based drugs in the probiotic yeast Saccharomyces boulardii to target Clostridioides difficile infection will serve as an ideal platform and model system by which to develop design strategies enabling efficient production of biologic molecules directly in the gut. Two complementary objectives will be pursued toward testing the engineering strains and peptides. First, peptides that specifically bind to C. difficile toxin A and to its surface layer protein (SlpA) will be designed. The peptides will be designed by combining solid phase library screening and computational peptide design/optimization approaches. The efficiency of thousands of peptides will be tested using in vitro gut models. Second, the physiological state of S. boulardii in gut models will be characterized by determining which genes are expressed and which proteins are secreted while residing in the gut. This knowledge will be applied to develop engineered S. boulardii strains that can effectively secrete and display the peptides designed in the first objective. The ability of the engineered strains to counteract C. difficile pathogenesis in 3D organoids will also be determined. The project will advance understanding of in situ biomanufacturing and reveal best practices for ensuring peptide efficacy.

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.

The removal of the polymeric microparticles (microplastics) that pervade the Earth?s oceans and waterways, and their conversion to value-added products, is an unresolved societal challenge. The scale of the problem prevents use of conventional chemical process technologies. To address this challenge, this Emerging Frontiers in Research and Innovation (EFRI) team will establish the intellectual foundations of a new technology platform aimed at addressing microplastics pollution. The platform includes efficient collection of microplastics from water bodies using self-propelled microcleaners that navigate complex environments and selectively capture/remove dispersed microplastic particles. The scavenged microplastics are then processed, using engineered microorganisms, into simple and versatile chemical building blocks that can be recycled into value-added products. A key goal of the project is to implement artificial intelligence methods to achieve the level of scalability and circularity necessary to enable the deconstructed microplastics products to be used for further microplastics capture. The team assembled to address these goals will create an outstanding interdisciplinary environment for training the next generation of scientists and engineers versed in the challenges of developing a circular economy. New educational opportunities centered on sustainability for K-16 and graduate students from diverse and underrepresented backgrounds will be offered. Public outreach efforts, which include development of research-inspired portable experimental kits, interactive games, and online maps, are to be disseminated by partnering with educational programs at museums.

This project will advance the frontiers of fundamental knowledge related to active colloidal and soft matter systems, computational design of molecular recognition processes, directed evolution of biocatalysts, and process intensification using artificial intelligence, all in the context of developing innovative technological solutions to the massive problem of microplastics pollution in marine and freshwaters. EFRI team members will integrate these advances to provide the intellectual foundations of a circular and scalable technology platform in which captured microplastics are processed into deconstructed products that can be used for the capture of additional microplastics or converted into other value-added products. Specific intellectual challenges to be addressed include (i) the design of next-generation "active" particle microcleaners that have fibrillar coronas and/or move autonomously in aqueous environments thus providing efficient capture of microplastics, (ii) the discovery of genetic pathways enabling efficient depolymerization of microplastics and their implementation in rapidly-growing marine bacteria, (iii) the computational design of peptides that recognize specific polymeric surfaces for capture and sensing of microplastics and (iv) the development of liquid crystal-based sensors for microplastics and deep-learning algorithms that will be used to intensify the overall capture and deconstruction processes. This project will also provide an outstanding interdisciplinary environment for training the next generation of engineers. The team?s broadening participation plan is committed to providing interdisciplinary education and research opportunities centered on sustainability to K-16 and graduate students from diverse and underrepresented backgrounds. Research-inspired portable experimental kits, interactive games, and online maps will be developed and disseminated through partnerships with public educational programs. Thus, this project will not only introduce technologies for remediation of microplastics but will also train a diverse engineering cohort to solve grand engineering challenges, such as the "circular plastics economy." This project is supported by the Directorate for Engineering and the Directorate for Biological Sciences.

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.