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

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

Relationship between Hot Spot Residues and Ligand Binding Hot Spots in Protein–Protein Interfaces

In the context of protein–protein interactions, the term “hot spot” refers to a residue or cluster of residues that makes a major contribution to the binding free energy, as determined by alanine scanning mutagenesis. In contrast, in pharmaceutical research, a hot spot is a site on a target protein that has high propensity for ligand binding and hence is potentially important for drug discovery. Here we examine the relationship between these two hot spot concepts by comparing alanine scanning data for a set of 15 proteins with results from mapping the protein surfaces for sites that can bind fragment-sized small molecules. We find the two types of hot spots are largely complementary; the residues protruding into hot spot regions identified by computational mapping or experimental fragment screening are almost always themselves hot spot residues as defined by alanine scanning experiments. Conversely, a residue that is found by alanine scanning to contribute little to binding rarely interacts with hot spot regions on the partner protein identified by fragment mapping. In spite of the strong correlation between the two hot spot concepts, they fundamentally differ, however. In particular, while identification of a hot spot by alanine scanning establishes the potential to generate substantial interaction energy with a binding partner, there are additional topological requirements to be a hot spot for small molecule binding. Hence, only a minority of hot spots identified by alanine scanning represent sites that are potentially useful for small inhibitor binding, and it is this subset that is identified by experimental or computational fragment screening

Transient lensing from a photoemitted electron gas imaged by ultrafast electron microscopy

Excited charge carriers, such as photoelectrons, play an important role in fundamental and technological fields. Here the authors employ an ultrafast electron microscope to directly visualize the cyclotron oscillations and oblate-to-prolate shape change of a photoemitted electron gas from a laser-excited copper surface

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

Comprehensive Experimental and Computational Analysis of Binding Energy Hot Spots at the NF-κB Essential Modulator/IKKβ Protein–Protein Interface

We report a comprehensive analysis of binding energy hot spots at the protein–protein interaction (PPI) interface between nuclear factor kappa B (NF-κB) essential modulator (NEMO) and IκB kinase subunit β (IKKβ), an interaction that is critical for NF-κB pathway signaling, using experimental alanine scanning mutagenesis and also the FTMap method for computational fragment screening. The experimental results confirm that the previously identified NEMO binding domain (NBD) region of IKKβ contains the highest concentration of hot-spot residues, the strongest of which are W739, W741, and L742 (ΔΔ<i>G</i> = 4.3, 3.5, and 3.2 kcal/mol, respectively). The region occupied by these residues defines a potentially druggable binding site on NEMO that extends for ∼16 Å to additionally include the regions that bind IKKβ L737 and F734. NBD residues D738 and S740 are also important for binding but do not make direct contact with NEMO, instead likely acting to stabilize the active conformation of surrounding residues. We additionally found two previously unknown hot-spot regions centered on IKKβ residues L708/V709 and L719/I723. The computational approach successfully identified all three hot-spot regions on IKKβ. Moreover, the method was able to accurately quantify the energetic importance of all hot-spot residues involving direct contact with NEMO. Our results provide new information to guide the discovery of small-molecule inhibitors that target the NEMO/IKKβ interaction. They additionally clarify the structural and energetic complementarity between “pocket-forming” and “pocket-occupying” hot-spot residues, and further validate computational fragment mapping as a method for identifying hot spots at PPI interfaces

Hematologically important mutations: The autosomal forms of chronic granulomatous disease (third update)

Chronic granulomatous disease (CGD) is an immunodeficiency disorder affecting about 1 in 250,000 individuals. CGD patients suffer from severe, recurrent bacterial and fungal infections. The disease is caused by mutations in the genes encoding the components of the leukocyte NADPH oxidase. This enzyme produces superoxide, which is subsequently metabolized to hydrogen peroxide and other reactive oxygen species (ROS). These products are essential for intracellular killing of pathogens by phagocytic leukocytes (neutrophils, eosinophils, monocytes and macrophages). The leukocyte NADPH oxidase is composed of five subunits, four of which are encoded by autosomal genes. These are CYBA, encoding p22(phox), NCF1, encoding p47(phox), NCF2, encoding p67(phox) and NCF4, encoding p40(phox). This article lists all mutations identified in these genes in CGD patients. In addition, cytochrome b(558) chaperone-1 (CYBC1), recently recognized as an essential chaperone protein for the expression of the X-linked NADPH oxidase component gp91(phox) (also called Nox2), is encoded by the autosomal gene CYBC1. Mutations in this gene also lead to CGD. Finally, RAC2, a small GTPase of the Rho family, is needed for activation of the NADPH oxidase, and mutations in the RAC2 gene therefore also induce CGD-like symptoms. Mutations in these last two genes are also listed in this article