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Barrels, magnets, and flying insects

February 23, 2012 By

Bunch of new reviews by Brandeis authors in press, check one out if you need to catch up on the state of the art.

  • Lisman J, Yasuda R, Raghavachari S. Mechanisms of CaMKII action in long-term potentiation. Nat Rev Neurosci. 2012.
  • Griffith LC. Identifying behavioral circuits in Drosophila melanogaster: moving targets in a flying insect. Curr Opin Neurobiol. 2012.
  • Hedstrom L. The dynamic determinants of reaction specificity in the IMPDH/GMPR family of (beta/alpha)(8) barrel enzymes. Crit Rev Biochem Mol Biol. 2012.
  • Pan Y, Du X, Zhao F, Xu B. Magnetic nanoparticles for the manipulation of proteins and cells. Chem Soc Rev. 2012.
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Jordan-Dreyer Summer Undergraduate Research Assistantships in the Department of Chemistry

February 14, 2012 By

The Department of Chemistry is pleased to announce the availability of the Jordan-Dreyer Summer Research Fellowships for the Summer of 2012 to work in a lab in the Department of Chemistry. The fellowships provide a total of $3000 for a ten week period. It may be possible to supplement the stipend with research funds from other sources. A commitment from a Chemistry faculty member to serve as your mentor in Summer 2012 is required.

The program will run from May 30 – Aug 3, 2012. Recipients are expected to be in residence during that period, and must commit to presenting a poster at the final poster session on Aug 2, 2012.

The application deadline is 01 March 2012. Applications from declared chemistry majors will receive a strong preference. Please send either paper or electronic materials to Anna Battista, Undergraduate Senior Coordinator, Department of Chemistry, MS015, battista@brandeis.edu.

Required Material:

  1. Current CV for the applicant;
  2. Unofficial Transcript;
  3. One page description of proposed research, with student and supervisor names clearly identified at the top of the page;
  4. Two letters of reference, one of which must be from the summer supervisor.

Please contact Prof. Foxman (foxman1@brandeis.edu) for questions/further information.

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Who is Selma?

December 25, 2011 By

A new paper in Angewandte Chemie International Edition from a Brandeis group led by postdoc Iain MacPherson, Professor of Biology Liz Hedstrom and Assistant Professor of Chemistry Isaac Krauss introduces a new technique they dub SELMA, short for “selection with modified aptamers”. Currently available selection methods can identify the few oligonucleotides in a library of 107 random DNAs or RNAs that bind specifically to a target protein (these specific binders are termed aptamers). However, nucleic acids have a very limited repertoire of chemical functionality — SELMA expands this functionality by introducing an alkyne-modified nucleotide that can be coupled to virtually any azide-containing compound using a copper catalyzed azide-alkyne cycloaddition reaction (“click chemistry“).

The Brandeis group used SELMA to create a library of sugar-modified oligonucleotides and selected for glycoclusters that mimic the epitope of 2G12, an antibody that protects against HIV infection by binding to a cluster of high-mannose glycans on the HIV envelope protein gp120. This is the first example of the application of directed evolution to protein-carbohydrate interactions, a particularly difficult class of interactions to mimic with traditional synthetic methods. Protein carbohydrate interactions are involved in wide array of biological processes, including cell-cell signaling, cell migration and developmental programming as well as immune recognition, so this method should prove very useful.

MacPherson, I. S., Temme, J. S., Habeshian, S., Felczak, K., Pankiewicz, K., Hedstrom, L. and Krauss, I. J. (2011), Multivalent Glycocluster Design through Directed Evolution. Angewandte Chemie International Edition, 50: 11238–11242. doi: 10.1002/anie.201105555

 

Filed Under: Biology, chemistry, labs Tagged With: , , , , , , , ,

An Amyloid Organelle

December 23, 2011 By

There is a common notion that “If Nature can find a use for something, She will.” and this story has been gradually playing out for the cross-beta protein fold. Known generally as “amyloid”, the cross-beta fold was first identified in pathologies including neurodegenerative disorders such as Alzheimer’s and systemic amyloidoses such as amyotrophic lateral sclerosis (often referred to as “Lou Gehrig’s Disease”). This happenstance initially pegged the fold as a feature unique to abnormal proteins. However, it subsequently became clear that normal proteins subjected to abnormal conditions would also assume the cross-beta fold. Still, it seemed that the fold was a sign of proteins gone awry. Then came discoveries of cross-beta folds in native, functional proteins. Some are primarily extracellular bacterial proteins involved in negotiating air-water interfaces at sporulation. But some involve the intracellular packaging of proteins in humans. Now Brandeis investigators Eugenio Daviso, Marina Belenky and Judith Herzfeld, with MIT collaborators Marvin Bayro and Robert Griffin, have found that an entire organelle is assembled with the cross-beta fold.1 Gas vesicles, the pressure-resistant floatation organelles of aquatic micro-organisms, comprise a protein-encased gas bubble. Assembly and disassembly of these bodies allows the cells to navigate up and down the water column and the cross-beta fold of the protein shell lends the vesicles the strength and interfacial stability that is critical for their function.

(Left) Schematic of the architecture of a gas vesicle. The gas vesicle is a bipolar cylinder with conical end caps. The ribs of the vesicle comprise GvpA monomers assembled in a low pitch helix. The horizontal lines shown within one of these ribs illustrate the orientation of the β-strands of GvpA as determined previously by x-ray diffraction.2 The expanded view of this rib shows the contacts between β-strands that have now been detected with solid-state NMR, thus establishing the presence of a continuous cross-beta sheet.1

1.      Bayro M, Daviso E, Belenky M, Griffin RG and Herzfeld J*. An Amyloid Organelle: Solid State NMR Evidence for Cross-Beta Assembly of Gas Vesicles.  J. Biol. Chem., DOI 10.1074/jbc.M111.313049.

2.      Blaurock AE and Walsby AE (1976) Crystalline structure of the gas vesicle wall from Anabaena flos-aquae, J. Mol. Biol. 105, 183-199.

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No Dice

December 16, 2011 By

Magnetic resonance is a powerful tool for interrogating materials at the atomic level, whether in determining protein structures or imaging the body. The procedure entails measuring the dynamics of the magnetism after it has been perturbed by radio waves. Usually the evolution is sampled at equal intervals, which is straightforward over one evolution period. However, experiments increasingly involve transfers of magnetization between different groups of atoms and require measurements after each transfer. In such experiments, it can become overwhelming to sample all the points in each evolution period, from the early ones needed because they have the strongest signal, to the late points needed because they provide the resolution of different contributions. Therefore, much recent attention has been given to finding ways to sample non-uniformly. This work led to a consensus that if one drops points it is necessary to do so randomly to minimize artifacts. The problem is that one can randomly get a very bad sampling schedule and waste a whole experiment (worse yet without necessarily knowing that the sampling schedule is the problem). Now, a MIT-Brandeis team1 has shown that non-uniform sampling need not be random and that adhering closely to a suitable distribution function produces high quality results.

1.      Eddy MT, Ruben D, Griffin RG and Herzfeld J*.  Deterministic schedules for robust and reproducible non-uniform sampling in multidimensional NMR, J. Magn. Reson. (2011), doi:10.1016/j.jmr.2011.12.002

An example of cumulative distribution functions (top) and results (bottom) for non-random sampling (right) compared with random sampling (left).

Filed Under: chemistry, labs Tagged With: , ,

Escaping the Lattice

December 5, 2011 By

The next best thing to seeing real atoms is to mimic them in silico: we assign interactions between the atoms and then — pouf –They’re alive!

The number of particles in a visible sample is on the order of Avogadro’s constant, say ~1023, whereas a fairly muscular computer can only follow ~105-107 atoms at a time. To compensate, computational scientists typically replicate their simulation boxes infinitely in space. This creates a quandary for calculating forces across replication boxes. The simplest option, which is to neglect forces beyond a chosen cut-off, suffices for many interactions, is too crude for the particularly long-range interactions that occur between charges. To accurately account for these interactions, it is customary to use a clever 90-year-old (!) technique, called the Ewald sum.(1)

The problem with the Ewald sum is that it requires imposing a long-range periodicity that is inappropriately short for macromolecules.(2) To avoid artifacts, a number of alternatives have been suggested. One intuitive approach, called “force shifting”, smooths the interaction energy and its first derivative (the force) at the chosen cutoff. However, this creates new artifacts (see figure) when particles have very large or varying charges, as in some ionic liquids. Brandeis scientists Seyit Kale and Judith Herzfeld, have found that this problem can be solved by also smoothing the second derivative of the interaction energy (the acceleration).(3)  This approach performs virtually as well as the Ewald sum in a new reactive force field that they have been developing (see figure).

The neighbor frequencies for bulk water calculated with force shifting at a cutoff of 9 Å (red) and 12 Å (magenta) versus with the authors’ new approach at a 9 Å cutoff (blue) and the Ewald sum (black). The blue and black curves are virtually the same while the red and magenta curves contain artifacts. The inset shows a representation of a water molecule from the force field that the authors are developing.

  1. Ewald P (1921) The Berechnung optischer und elektrostatischer Gitterpotentiale. Ann. Phys. 369: 253-287.
  2. Hunenberger PH, McCammon JA (1999) Effect of artificial periodicity in simulations of biomolecules under Ewald boundary conditions: A continuum electrostatics study. Biophys. Chem. 78: 69-88.
  3. Kale S, Herzfeld J (2011) Pairwise Long-range Compensation for Strongly Ionic Systems. J. Chem. Theory Comput. 7: 3620-3624.
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