Signals for Low Scale Gravity in the Process γγ→ZZ\gamma \gamma \to ZZ

We investigate the sensitivity of future photon-photon colliders to low scale gravity scenarios via the process $\gamma\gamma \to ZZ$ where the Kaluza-Klein boson exchange contributes only when the initial state photons have opposite helicity. We contrast this with the situation for the process $\gamma \gamma \to \gamma \gamma$ where the $t$ and $u$ channel also contribute. We include the one-loop Standard Model background whose interference with the graviton exchange determines the experimental reach in measuring any deviation from the Standard Model expectations and explore how polarization can be exploited to enhance the signal over background. We find that a 1 TeV linear collider has an experimental reach to mass scale of about 4 TeV in this channel.Comment: 20 pages, 8 figure

Dynamical bunching and density peaks in expanding Coulomb clouds

Expansion dynamics of single-species, non-neutral clouds, such as electron bunches used in ultrafast electron microscopy, show novel behavior due to high acceleration of particles in the cloud interior. This often leads to electron bunching and dynamical formation of a density shock in the outer regions of the bunch. We develop analytic fluid models to capture these effects, and the analytic predictions are validated by PIC and N-particle simulations. In the space-charge dominated regime, two and three dimensional systems with Gaussian initial densities show bunching and a strong shock response, while one dimensional systems do not; moreover these effects can be tuned using the initial particle density profile and velocity chirp.Comment: 16 pages, 6 figures(spread over 18 png files); No changes to the text --- however I had mis-spelled Chong-Yu Ruan's first name in the metadata. (It was originally Chung-Yu). This typo has been addresse

Analysis of Binding Site Hot Spots on the Surface of Ras GTPase

We have recently discovered an allosteric switch in Ras, bringing an additional level of complexity to this GTPase whose mutants are involved in nearly 30% of cancers. Upon activation of the allosteric switch, there is a shift in helix 3/loop 7 associated with a disorder to order transition in the active site. Here, we use a combination of multiple solvent crystal structures and computational solvent mapping (FTMap) to determine binding site hot spots in the “off” and “on” allosteric states of the GTP-bound form of H-Ras. Thirteen sites are revealed, expanding possible target sites for ligand binding well beyond the active site. Comparison of FTMaps for the H and K isoforms reveals essentially identical hot spots. Furthermore, using NMR measurements of spin relaxation, we determined that K-Ras exhibits global conformational dynamics very similar to those we previously reported for H-Ras. We thus hypothesize that the global conformational rearrangement serves as a mechanism for allosteric coupling between the effector interface and remote hot spots in all Ras isoforms. At least with respect to the binding sites involving the G domain, H-Ras is an excellent model for K-Ras and probably N-Ras as well. Ras has so far been elusive as a target for drug design. The present work identifies various unexplored hot spots throughout the entire surface of Ras, extending the focus from the disordered active site to well-ordered locations that should be easier to target

Compact ring-based X-ray source with on-orbit and on-energy laser-plasma injection

We report here the results of a one week long investigation into the conceptual design of an X-ray source based on a compact ring with on-orbit and on-energy laser-plasma accelerator. We performed these studies during the June 2016 USPAS class "Physics of Accelerators, Lasers, and Plasma..." applying the art of inventiveness TRIZ. We describe three versions of the light source with the constraints of the electron beam with energy $1\,\rm{GeV}$ or $3\,\rm{GeV}$ and a magnetic lattice design being normal conducting (only for the $1\,\rm{GeV}$ beam) or superconducting (for either beam). The electron beam recirculates in the ring, to increase the effective photon flux. We describe the design choices, present relevant parameters, and describe insights into such machines.Comment: 4 pages, 1 figure, Conference Proceedings of NAPAC 201

Protein–protein docking by fast generalized Fourier transforms on 5D rotational manifolds

International audienceEnergy evaluation using fast Fourier transforms (FFTs) enables sampling billions of putative complex structures and hence revolutionized rigid protein–protein docking. However, in current methods, efficient acceleration is achieved only in either the translational or the rotational subspace. Developing an efficient and accurate docking method that expands FFT-based sampling to five rotational coordinates is an extensively studied but still unsolved problem. The algorithm presented here retains the accuracy of earlier methods but yields at least 10-fold speedup. The improvement is due to two innovations. First, the search space is treated as the product manifold SO(3)×(SO(3)∖S1), where SO(3) is the rotation group representing the space of the rotating ligand, and (SO(3)∖S1) is the space spanned by the two Euler angles that define the orientation of the vector from the center of the fixed receptor toward the center of the ligand. This representation enables the use of efficient FFT methods developed for SO(3). Second, we select the centers of highly populated clusters of docked structures, rather than the lowest energy conformations, as predictions of the complex, and hence there is no need for very high accuracy in energy evaluation. Therefore, it is sufficient to use a limited number of spherical basis functions in the Fourier space, which increases the efficiency of sampling while retaining the accuracy of docking results. A major advantage of the method is that, in contrast to classical approaches, increasing the number of correlation function terms is computationally inexpensive, which enables using complex energy functions for scoring

Computational characterization of protein hot spots

Thesis (Ph.D.)--Boston UniversityPLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at [email protected]. Thank you.Protein hot spots provide a large portion of the binding free energy during interact ions, and detecting and characterizing these hot spot regions provides insight that can be used in the development of novel drugs for t he purpose of regulating pathological pathways. In t his dissertation, I first compare t he FTMap algorithm, which detects hot spots by identifying locations where different simulated solvent-sized molecules are consistently found to have favorable interactions, to experimental methods that detect hot spots by alternative means. Specifically, I show that FTMap detects the hot spots detected by alanine scanning, and I discover two roles for residues near hot spots in protein-protein interaction (PPI) complexes. Furthermore, additional insights into the binding energetics of PPis are uniquely provided by FTMap, and these insights are important for drug-design. FTMap is then shown to detect the hot spots identified by successful fragment-screening experiments, and the additional sites detected by FTMap are shown to provide insight into the optimal regions for ligand extension for the molecules identified by t he fragment-screening experiment. Since binding sites are composed of multiple hot spots, we have recently used FTMap for binding site detection. I examine the highly accurate binding site detection algorithm, show that the success of this algorithm is a consequence of only a portion of the scoring protocol, and develop a faster protocol for binding site detection based on this insight. I also quantitate the improvement in precision obtained by using multiple probes and argue t hat the principle biophysical considerations in hot spot detection are hydrophobicity and complexity. Finally, I develop a functional-group clustering algorithm, which is informative for evaluation of the binding locations of pre-determined chemical moieties. I then provide evidence that other approaches employing FTMap results may lead to insight into selectivity. I conclude with a discussion on the nature of hot spots, and I suggest that evolutionary studies of protein divergence should provide insight into the emergence of chemical-selectivity thus providing biophysical insight into the factors that drive selectivity within hot spots.2031-01-0

Estimating genotype error rates from high-coverage next-generation sequence data.

Exome and whole-genome sequencing studies are becoming increasingly common, but little is known about the accuracy of the genotype calls made by the commonly used platforms. Here we use replicate high-coverage sequencing of blood and saliva DNA samples from four European-American individuals to estimate lower bounds on the error rates of Complete Genomics and Illumina HiSeq whole-genome and whole-exome sequencing. Error rates for nonreference genotype calls range from 0.1% to 0.6%, depending on the platform and the depth of coverage. Additionally, we found (1) no difference in the error profiles or rates between blood and saliva samples; (2) Complete Genomics sequences had substantially higher error rates than Illumina sequences had; (3) error rates were higher (up to 6%) for rare or unique variants; (4) error rates generally declined with genotype quality (GQ) score, but in a nonlinear fashion for the Illumina data, likely due to loss of specificity of GQ scores greater than 60; and (5) error rates increased with increasing depth of coverage for the Illumina data. These findings, especially (3)-(5), suggest that caution should be taken in interpreting the results of next-generation sequencing-based association studies, and even more so in clinical application of this technology in the absence of validation by other more robust sequencing or genotyping methods