Computer simulation of protein systems

Ligand binding to dihydrofolate reductase (DHFR) is discussed. This is an extremely important enzyme, as it is the target of several drugs (inhibitors) which are used clinically as antibacterials, antiprotozoals and in cancer chemotherapy. DHFR catalyzes the NADPH (reduced nicotinamide adenine dinucleotide phosphate) dependent reduction of dihydrofolate to tetrahydrofolate, which is used in several pathways of purine and pyrimidine iosynthesis, including that of thymidylate. Since DNA synthesis is dependent on a continuing supply of thymidylate, a blockade of DHFR resulting in a depletion of thymidylate can lead to the cessation of growth of a rapidly proliferating cell line. DHFR exhibits a significant species to species variability in its sensitivity to various inhibitors. For example, trimethoprim, an inhibitor of DHFR, binds to bacterial DHFR's 5 orders of magnitude greater than to vertebrate DHFR's. The structural mechanics, dynamics and energetics of a family of dihydrofolate reductases are studied to rationalize the basis for the inhibitor of these enyzmes and to understand the molecular basis of the difference in the binding constants between the species. This involves investigating the conformational changes induced in the protein on binding the ligand, the internal strain imposed by the enzyme on the ligand, the restriction of fluctuations in atom positions due to binding and the consequent change in entropy

Helicity Dependent and Independent Generalized Parton Distributions of the Nucleon in Lattice QCD

A complete description of the nucleon structure in terms of generalized parton distributions (GPDs) at twist 2 level requires the measurement/computation of the eight functions H, E, \tilde H, \tilde E, H_T, E_T, \tilde H_T and \tilde E_T, all depending on the three variables x, \xi and t. In this talk, we present and discuss our first steps in the framework of lattice QCD towards this enormous task. Dynamical lattice QCD results for the lowest three Mellin moments of the helicity dependent and independent GPDs are shown in terms of their corresponding generalized form factors. Implications for the transverse coordinate space structure of the nucleon as well as the orbital angular momentum (OAM) contribution of quarks to the nucleon spin are discussed in some detail.Comment: 5 pages, 5 figures, Talk presented by Ph.H. at Electron-Nucleus Scattering VIII, Elba, Italy, June 21-25, 2004; typos corrected, minor change in wording on p.4&

Particulate and water-soluble carbon measured in recent snow at Summit, Greenland

Water-soluble organic carbon (WSOC), waterinsoluble particulate organic carbon (WIOC), and particulate elemental carbon (EC) were measured simultaneously for the first time on the Greenland Ice Sheet in surface snow and in a 3-meter snow pit. Snow pit concentrations reveal that, on average, WSOC makes up the majority (89%) of carbonaceous species, followed by WIOC (10%) and EC (1%). The enhancement of OC relative to EC (ratio 99:1) in Greenland snow suggests that, along with atmospheric particulate matter, gaseous organics contribute to snow-phase OC. Comparison of summer surface snow concentrations in 2006 with past summer snow pit layers (2002 – 2005) found a significant depletion in WSOC (20 – 82%) and WIOC (46 – 65%) relative to EC for 3 of the 4 years. The apparent substantial loss of WSOC and WIOC in aged snow suggests that post-depositional processes, such as photochemical reactions, need to be considered in linking ice core records of organics to atmospheric concentrations. Citation: Hagler, G. S. W., M. H. Bergin, E. A. Smith, J. E. Dibb, C. Anderson, and E. J. Steig (2007), Particulate and water-soluble carbon measured in recent snow at Summit, Greenland, Geophys. Res. Lett., 34, L16505, doi:10.1029/2007GL030110

Point-light biological motion perception activates human premotor cortex

Motion cues can be surprisingly powerful in defining objects and events. Specifically, a handful of point-lights attached to the joints of a human actor will evoke a vivid percept of action when the body is in motion. The perception of point-light biological motion activates posterior cortical areas of the brain. On the other hand, observation of others' actions is known to also evoke activity in motor and premotor areas in frontal cortex. In the present study, we investigated whether point-light biological motion animations would lead to activity in frontal cortex as well. We performed a human functional magnetic resonance imaging study on a high-field-strength magnet and used a number of methods to increase signal, as well as cortical surface-based analysis methods. Areas that responded selectively to point-light biological motion were found in lateral and inferior temporal cortex and in inferior frontal cortex. The robust responses we observed in frontal areas indicate that these stimuli can also recruit action observation networks, although they are very simplified and characterize actions by motion cues alone. The finding that even point-light animations evoke activity in frontal regions suggests that the motor system of the observer may be recruited to "fill in" these simplified displays

Quark Contributions to Nucleon Momentum and Spin from Domain Wall fermion calculations

We report contributions to the nucleon spin and momentum from light quarks calculated using dynamical domain wall fermions with pion masses down to 300 MeV and fine lattice spacing a=0.084 fm. Albeit without disconnected diagrams, we observe that spin and orbital angular momenta of both u and d quarks are opposite, almost canceling in the case of the d quark, which agrees with previous calculations using a mixed quark action. We also present the full momentum dependence of n=2 generalized form factors showing little variation with the pion mass.Comment: 7 pages, 5 figures, NT-LBNL-11-020, MIT-CTP-4323. Presented at the 29th International Symposium on Lattice Field Theory (Lattice 2011), Squaw Valley, California, 10-16 Jul 201

Signal processing in local neuronal circuits based on activity-dependent noise and competition

We study the characteristics of weak signal detection by a recurrent neuronal network with plastic synaptic coupling. It is shown that in the presence of an asynchronous component in synaptic transmission, the network acquires selectivity with respect to the frequency of weak periodic stimuli. For non-periodic frequency-modulated stimuli, the response is quantified by the mutual information between input (signal) and output (network's activity), and is optimized by synaptic depression. Introducing correlations in signal structure resulted in the decrease of input-output mutual information. Our results suggest that in neural systems with plastic connectivity, information is not merely carried passively by the signal; rather, the information content of the signal itself might determine the mode of its processing by a local neuronal circuit.Comment: 15 pages, 4 pages, in press for "Chaos

Transverse Structure of Nucleon Parton Distributions from Lattice QCD

This work presents the first calculation in lattice QCD of three moments of spin-averaged and spin-polarized generalized parton distributions in the proton. It is shown that the slope of the associated generalized form factors decreases significantly as the moment increases, indicating that the transverse size of the light-cone quark distribution decreases as the momentum fraction of the struck parton increases.Comment: 4 pages, 1 figur

Towards Greener Solutions for Steering Angle Prediction

In this paper, we investigate the two most popular families of deep neural architectures (i.e., ResNets and Inception nets) for the autonomous driving task of steering angle prediction. This work provides preliminary evidence that Inception architectures can perform as well or better than ResNet architectures with less complexity for the autonomous driving task. Primary motivation includes support for further research in smaller, more efficient neural network architectures such that can not only accomplish complex tasks, such as steering angle predictions, but also produce less carbon emissions, or, more succinctly, neural networks that are more environmentally friendly. We look at various sizes of ResNet and InceptionNet models to compare results. Our derived models can achieve state-of-the-art results in terms of steering angle MSE