Cytochrome c oxidases (Ccoxs) are the terminal enzymes of the respiratory chain in mitochondria and most bacteria. These enzymes couple dioxygen (O2) reduction to the generation of a transmembrane electrochemical proton gradient. Despite decades of research and the availability of a large amount of structural and biochemical data available for the A-type Ccox family, little is known about the channel(s) used by O2 to travel from the solvent/membrane to the heme a3-CuB binuclear center (BNC). Moreover, the identification of all possible O2 channels as well as the atomic details of O2 diffusion is essential for the understanding of the working mechanisms of the A-type Ccox. In this work, we determined the O2 distribution within Ccox from Rhodobacter sphaeroides, in the fully reduced state, in order to identify and characterize all the putative O2 channels leading towards the BNC. For that, we use an integrated strategy combining atomistic molecular dynamics (MD) simulations (with and without explicit O2 molecules) and implicit ligand sampling (ILS) calculations. Based on the 3D free energy map for O2 inside Ccox, three channels were identified, all starting in the membrane hydrophobic region and connecting the surface of the protein to the BNC. One of these channels corresponds to the pathway inferred from the X-ray data available, whereas the other two are alternative routes for O2 to reach the BNC. Both alternative O2 channels start in the membrane spanning region and terminate close to Y288I. These channels are a combination of multiple transiently interconnected hydrophobic cavities, whose opening and closure is regulated by the thermal fluctuations of the lining residues. Furthermore, our results show that, in this Ccox, the most likely (energetically preferred) routes for O2 to reach the BNC are the alternative channels, rather than the X-ray inferred pathway.

ATP-Binding Cassette transporters are ubiquitous membrane proteins that convert the energy from ATP-binding and hydrolysis into conformational changes of the transmembrane region to allow the translocation of substrates against their concentration gradient. Despite the large amount of structural and biochemical data available for this family, it is still not clear how the energy obtained from ATP hydrolysis in the ATPase domains is "transmitted" to the transmembrane domains. In this work, we focus our attention on the consequences of hydrolysis and inorganic phosphate exit in the maltose uptake system (MalFGK(2)E) from Escherichia coli. The prime goal is to identify and map the structural changes occurring during an ATP-hydrolytic cycle. For that, we use extensive molecular dynamics simulations to study three potential intermediate states (with 10 replicates each): an ATP-bound, an ADP plus inorganic phosphate-bound and an ADP-bound state. Our results show that the residues presenting major rearrangements are located in the A-loop, in the helical sub-domain, and in the "EAA motif" (especially in the "coupling helices" region). Additionally, in one of the simulations with ADP we were able to observe the opening of the NBD dimer accompanied by the dissociation of ADP from the ABC signature motif, but not from its corresponding P-loop motif. This work, together with several other MD studies, suggests a common communication mechanism both for importers and exporters, in which ATP-hydrolysis induces conformational changes in the helical sub-domain region, in turn transferred to the transmembrane domains via the "coupling helices".

Data analysis tasks at an Ocean Observatory require integrative and and domain-specialized use of database, workflow, visualization systems. We describe a platform to support these tasks developed as part of the cyberinfrastructure at the NSF Science and Technology Center for Coastal Margin Observation and Prediction integrating a provenance-aware workflow system, 3D visualization, and a remote query engine for large-scale ocean circulation models. We show how these disparate tools complement each other and give examples of real scientific insights delivered by the integrated system. We conclude that data management solutions for eScience require this kind of holistic, integrative approach, explain how our approach may be generalized, and recommend a broader, application-oriented research agenda to explore relevant architectures.

The Columbia River (CoRie) Observation Network includes an extensive array of fixed stations monitoring the Columbia River estuary and nearby coastal ocean. At each station, variable combinations of in-situ sensors measure one or more physical properties of water or atmosphere. Using a multi-scale data assimilation model, the CORIE modeling system integrates models and field controls to produce a simulation of 3D circulation, in a region centered in the estuary and plume. The CORIE data assimilation framework [1] combines observational data with numerical data models to produce an estimated system state for the physical process. To augment the fixed observational network, additional data is collected during periodical cruises of a mobile sensor station. Because these cruises are expensive and rare, an important goal for scientists is to sample data at points that most reduce the uncertainty of the data assimilation model. This is challenging, since the estuary environment is very dynamic, and therefore the optimal cruise path cannot be determined in advance. The goal of our system is to move the mobile station as the data assimilation proceeds in order to maximally reduce the uncertainty in the data assimilation process.

As part of an environmental observation and forecasting system, sensors deployed in the Columbia RIver Estuary (CORIE) gather information on physical dynamics and changes in estuary habi- tat. Of these, salinity sensors are particularly susceptible to bio- fouling, which gradually degrades sensor response and corrupts crit- ical data. Automatic fault detectors have the capability to identify bio-fouling early and minimize data loss. Complicating the devel- opment of discriminatory classi(cid:12)ers is the scarcity of bio-fouling onset examples and the variability of the bio-fouling signature. To solve these problems, we take a novelty detection approach that incorporates a parameterized bio-fouling model. These detectors identify the occurrence of bio-fouling, and its onset time as reliably as human experts. Real-time detectors installed during the sum- mer of 2001 produced no false alarms, yet detected all episodes of sensor degradation before the (cid:12)eld sta(cid:11) scheduled these sensors for cleaning. From this initial deployment through February 2003, our bio-fouling detectors have essentially doubled the amount of useful data coming from the CORIE sensors.

In this paper, we describe a set of 3D and 4D visualization tools and techniques for CORIE, a complex environmental observation and forecasting system (EOFS) for the Columbia River. The Columbia River, a complex and highly variable estuary, is the target of numerous cross-disciplinary ecosystem research projects and is at the heart of multiple sustainable development issues with long reaching implications for the Pacific Northwest. However, there has been until recently no comprehensive and objective system available for modeling this environment, and as a consequence, researchers and agencies have had inadequate tools for evaluating the effects of natural resource management decisions. CORIE was designed to address this gap and is a major step towards the vision of a scalable, multi-use, real-time EOFS. Although CORIE already had a rich set of visualization tools, most of them produced 2D visualizations and did not allow for interactive visualization. Our work adds advanced interactive 3D tools to CORIE, which can be used for further inspection of the simulated and measured data.

The availability of tremendous computation power coupled with widespread connectivity have fueled the development of real-time environmental observation and forecasting systems (EOFS).