557 research outputs found
Quantitative prediction of 3D solution shape and flexibility of nucleic acid nanostructures
No full textDNA nanotechnology enables the programmed synthesis of intricate nanometer-scale structures for diverse applications in materials and biological science. Precise control over the 3D solution shape and mechanical flexibility of target designs is important to achieve desired functionality. Because experimental validation of designed nanostructures is time-consuming and cost-intensive, predictive physical models of nanostructure shape and flexibility have the capacity to enhance dramatically the design process. Here, we significantly extend and experimentally validate a computational modeling framework for DNA origami previously presented as CanDo [Castro,C.E., Kilchherr,F., Kim,D.-N., Shiao,E.L., Wauer,T., Wortmann,P., Bathe,M., Dietz,H. (2011) A primer to scaffolded DNA origami. Nat. Meth., 8, 221–229.]. 3D solution shape and flexibility are predicted from basepair connectivity maps now accounting for nicks in the DNA double helix, entropic elasticity of single-stranded DNA, and distant crossovers required to model wireframe structures, in addition to previous modeling (Castro,C.E., et al.) that accounted only for the canonical twist, bend and stretch stiffness of double-helical DNA domains. Systematic experimental validation of nanostructure flexibility mediated by internal crossover density probed using a 32-helix DNA bundle demonstrates for the first time that our model not only predicts the 3D solution shape of complex DNA nanostructures but also their mechanical flexibility. Thus, our model represents an important advance in the quantitative understanding of DNA-based nanostructure shape and flexibility, and we anticipate that this model will increase significantly the number and variety of synthetic nanostructures designed using nucleic acids.MIT Faculty Start-up Fun
Cytokinesis and the contractile ring in fission yeast: towards a systems-level understanding
No full textCytokinesis, the final stage of the cell division cycle, requires the proper placement, assembly and contraction of an actomyosin-based contractile ring. Conserved sets of cytokinesis proteins and pathways have now been identified and characterized functionally. Additionally, fluorescent protein fusion technology enables quantitative high-resolution imaging of protein dynamics in living cells. For these reasons, the study of cytokinesis is now ripe for quantitative, systems-level approaches. Here, we review our current understanding of the molecular mechanisms of contractile ring dynamics in the model organism Schizosaccharomyces pombe (fission yeast), focusing on recent examples that illustrate a synergistic integration of quantitative experimental data with computational modeling. A picture of a highly dynamic and integrated system consisting of overlapping networks is beginning to emerge, the detailed nature of which remains to be elucidated.National Institutes of Health (U.S.) (NIH grant GM05683)Massachusetts Institute of Technology (Samuel A. Goldblith Career Development Professorship)Massachusetts Institute of Technology (Faculty startup funds
DNA Nanotechnology: A foundation for Programmable Nanoscale Materials
No full textDNA nanotechnology is a materials design paradigm in which synthetic nucleic acids are used to program the structure and dynamics of nanometer-scale devices and materials. Driven by the convergence of decreasing DNA synthesis costs, advanced yet easy-to-use computational design and analysis tools, and, most importantly, a myriad of innovative studies demonstrating DNA’s extraordinary power to organize functional materials, DNA nanotechnology is spreading into diverse areas of traditional materials science. To further promote the integration of DNA nanotechnology into materials science, this issue of MRS Bulletin provides an overview of the unique capabilities offered by DNA nanotechnology, a set of practical techniques that make it accessible to a broad audience, and a vision for its future applications, described by international leaders in the field.United States. Office of Naval Research (Award N00014-16-1-2181)United States. Office of Naval Research (Award N00014-13-1-0664)United States. Office of Naval Research (Award N00014-15-1-2830)United States. Office of Naval Research (Award N00014-16-1-2506)United States. Office of Naval Research (Award N00014-16-1-2953)United States. Office of Naval Research (Award N00014-17-1-2609)National Science Foundation (U.S.) (Grant CMMI-1334109)National Science Foundation (U.S.) (Grant CCF-1547999)National Science Foundation (U.S.) (Grant CCF-1564025
Conformational dynamics of supramolecular protein assemblies
No full textSupramolecular protein assemblies including molecular motors, cytoskeletal filaments, chaperones, and ribosomes play a central role in a broad array of cellular functions ranging from cell division and motility to RNA and protein synthesis and folding. Single-particle reconstructions of such assemblies have been growing rapidly in recent years, providing increasingly high resolution structural information under native conditions. While the static structure of these assemblies provides essential insight into their mechanism of biological function, their dynamical motions provide additional important information that cannot be inferred from structure alone. Here we present an unsupervised computational framework for the analysis of high molecular weight protein assemblies and use it to analyze the conformational dynamics of structures deposited in the Electron Microscopy Data Bank. Protein assemblies are modeled using a recently introduced coarse-grained modeling framework based on the finite element method, which is used to compute equilibrium thermal fluctuations, elastic strain energy distributions associated with specific conformational transitions, and dynamical correlations in distant molecular domains. Results are presented in detail for the ribosome-bound termination factor RF2 from Escherichia coli, the nuclear pore complex from Dictyostelium discoideum, and the chaperonin GroEL from E. coli. Elastic strain energy distributions reveal hinge-regions associated with specific conformational change pathways, and correlations in collective molecular motions reveal dynamical coupling between distant molecular domains that suggest new, as well as confirm existing, allosteric mechanisms. Results are publically available for use in further investigation and interpretation of biological function including cooperative transitions, allosteric communication, and molecular mechanics, as well as in further classification and refinement of electron microscopy based structures.Massachusetts Institute of Technology (MIT Faculty Start-up Funds)Massachusetts Institute of Technology (Samuel A. Goldblith Career Development Professorship
A Regulatory Switch Alters Chromosome Motions at the Metaphase-to-Anaphase Transition
No full textSummaryTo achieve chromosome segregation during mitosis, sister chromatids must undergo a dramatic change in their behavior to switch from balanced oscillations at the metaphase plate to directed poleward motion during anaphase. However, the factors that alter chromosome behavior at the metaphase-to-anaphase transition remain incompletely understood. Here, we perform time-lapse imaging to analyze anaphase chromosome dynamics in human cells. Using multiple directed biochemical, genetic, and physical perturbations, our results demonstrate that differences in the global phosphorylation states between metaphase and anaphase are the major determinant of chromosome motion dynamics. Indeed, causing a mitotic phosphorylation state to persist into anaphase produces dramatic metaphase-like oscillations. These induced oscillations depend on both kinetochore-derived and polar ejection forces that oppose poleward motion. Thus, our analysis of anaphase chromosome motion reveals that dephosphorylation of multiple mitotic substrates is required to suppress metaphase chromosome oscillatory motions and achieve directed poleward motion for successful chromosome segregation
Perancangan Bisnis untuk Produk Natural Personal Care "Bathe"
No full textNowadays, there are so many soap and lotion brand with various price and variations in the market. But, people do not know that the products they used containing bad chemicals either for their skin or enviroment. In this research, author wants to develop for Bathe products in order to know more about people’s awareness about natural products and best business strategic for Bathe. This journal is supported by using field data (primary) and literature (secondary). The products development process has done through several stages starting from observation, interview, and online survey. The results are people still did not know about the ingredients of the product they used everyday, why people have to change to natural products, and people’s visual preferences and variations.
Structure-based model for light-harvesting properties of nucleic acid nanostructures
No full textProgrammed self-assembly of DNA enables the rational design of megadalton-scale macromolecular assemblies with sub-nanometer scale precision. These assemblies can be programmed to serve as structural scaffolds for secondary chromophore molecules with light-harvesting properties. Like in natural systems, the local and global spatial organization of these synthetic scaffolded chromophore systems plays a crucial role in their emergent excitonic and optical properties. Previously, we introduced a computational model to predict the large-scale 3D solution structure and flexibility of nucleic acid nanostructures programmed using the principle of scaffolded DNA origami. Here, we use Förster resonance energy transfer theory to simulate the temporal dynamics of dye excitation and energy transfer accounting both for overall DNA nanostructure architecture as well as atomic-level DNA and dye chemical structure and composition. Results are used to calculate emergent optical properties including effective absorption cross-section, absorption and emission spectra and total power transferred to a biomimetic reaction center in an existing seven-helix double stranded DNA-based antenna. This structure-based computational framework enables the efficient in silico evaluation of nucleic acid nanostructures for diverse light-harvesting and photonic applications.United States. Office of Naval Research (ONR N000141210621)United States. Army Research Office (ARO MURI W911NF1210420
Bayesian Model Selection Applied to the Analysis of Fluorescence Correlation Spectroscopy Data of Fluorescent Proteins in Vitro and in Vivo
No full textFluorescence correlation spectroscopy (FCS) is a powerful technique to investigate molecular dynamics with single molecule sensitivity. In particular, in the life sciences it has found widespread application using fluorescent proteins as molecularly specific labels. However, FCS data analysis and interpretation using fluorescent proteins remains challenging due to typically low signal-to-noise ratio of FCS data and correlated noise in autocorrelated data sets. As a result, naive fitting procedures that ignore these important issues typically provide similarly good fits for multiple competing models without clear distinction of which model is preferred given the signal-to-noise ratio present in the data. Recently, we introduced a Bayesian model selection procedure to overcome this issue with FCS data analysis. The method accounts for the highly correlated noise that is present in FCS data sets and additionally penalizes model complexity to prevent over interpretation of FCS data. Here, we apply this procedure to evaluate FCS data from fluorescent proteins assayed in vitro and in vivo. Consistent with previous work, we demonstrate that model selection is strongly dependent on the signal-to-noise ratio of the measurement, namely, excitation intensity and measurement time, and is sensitive to saturation artifacts. Under fixed, low intensity excitation conditions, physical transport models can unambiguously be identified. However, at excitation intensities that are considered moderate in many studies, unwanted artifacts are introduced that result in nonphysical models to be preferred. We also determined the appropriate fitting models of a GFP tagged secreted signaling protein, Wnt3, in live zebrafish embryos, which is necessary for the investigation of Wnt3 expression and secretion in development. Bayes model selection therefore provides a robust procedure to determine appropriate transport and photophysical models for fluorescent proteins when appropriate models are provided, to help detect and eliminate experimental artifacts in solution, cells, and in living organisms.National Science Foundation (U.S.). Physics of Living Systems ProgramNational Institute of Mental Health (U.S.) (Award U01MH106011
Conformational dynamics data bank: a database for conformational proteins and supramolecular protein assemblies
No full textThe conformational dynamics data bank (CDDB, http://www.cdyn.org) is a database that aims to provide comprehensive results on the conformational dynamics of high molecular weight proteins and protein assemblies. Analysis is performed using a recently introduced coarse-grained computational approach that is applied to the majority of structures present in the electron microscopy data bank (EMDB). Results include equilibrium thermal fluctuations and elastic strain energy distributions that identify rigid versus flexible protein domains generally, as well as those associated with specific functional transitions, and correlations in molecular motions that identify molecular regions that are highly coupled dynamically, with implications for allosteric mechanisms. A practical web-based search interface enables users to easily collect conformational dynamics data in various formats. The data bank is maintained and updated automatically to include conformational dynamics results for new structural entries as they become available in the EMDB. The CDDB complements static structural information to facilitate the investigation and interpretation of the biological function of proteins and protein assemblies essential to cell function
On the predictive capability and stability of rubber material models
No full textThesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 99-101).Due to the high non-linearity and incompressibility constraint of rubber materials, the predictive capability and stability of rubber material models require specific attention for practical engineering analysis. In this thesis, the predictive capability of various rubber material models, namely the Mooney-Rivlin model, Arruda-Boyce model, Ogden model and the newly proposed Sussman-Bathe model, is investigated theoretically with continuum mechanics methods and tested numerically in various deformation situations using the finite element analysis software ADINA. In addition, a recently made available stability criterion of rubber material models is re-derived and verified through numerical experiments for the above four models with ADINA. Thereafter, the predictive capability and stability of material models are studied jointly for non-homogenous deformations. The Mooney-Rivlin model, Arruda-Boyce model, Ogden model have difficulties in describing the uniaxial compression data while the Sussman-Bathe model can fit both compression and extension data well. Thus, the Sussman-Bathe model has the best predictive capability for pure shear deformations. Furthermore, with respect to more complex non-homogenous deformations, a conclusion is drawn that all three major deformations, namely uniaxial deformation, biaxial deformation and pure shear deformation, must satisfy the stability criterion to obtain physically correct non-homogenous simulation results.by Haining Zheng.S.M
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