Pinned optically-aligned diagnostic dock for use on the Z facility.
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A hydrokinetic turbine system for harvesting energy from riverine and tidal sources, including a first floating dock, a marine hydrokinetic turbine mounted on the first floating dock, and a second floating dock. The system further includes a winch assembly mounted on the second floating dock and operationally connected to the first floating dock and a linkage assembly operationally connected to the first floating dock and to the second floating dock. The linkage assembly may be actuated to pull the first floating dock into contact with the second floating dock. The linkage assembly may be actuated to distance the first floating dock from the second floating dock, and the winch assembly may be energized to orient the first floating dock into a position wherein the marine hydrokinetic turbine is above the first floating dock and wherein the winch assembly may be energized to orient the first floating dock into a position wherein the marine hydrokinetic turbine is below the first floating dock.
Amyloid fibrils are thought to grow by a two-step dock-lock mechanism. However, previous simulations of fibril formation (i) overlook the bi-molecular nature of the docking step and obtain rates with first-order units, or (ii) superimpose the docked and locked states when computing the potential of mean force for association and thereby muddle the docking and locking steps. Here, we developed a simple microkinetic model with separate locking and docking steps and with the appropriate concentration dependences for each step. We constructed a simple model comprised of chiral dumbbells that retains qualitative aspects of fibril formation. We used rare events methods to predict separate docking and locking rate constants for the model. The rate constants were embedded in the microkinetic model, with the microkinetic model embedded in a population balance model for “bottom-up” multiscale fibril growth rate predictions. These were compared to “top-down” results using simulation data with the same model and multiscale framework to obtain maximum likelihood estimates of the separate lock and dock rate constants. We used the same procedures to extract separate docking and locking rate constants from experimental fibril growth data. Our multiscale strategy, embedding rate theories, and kinetic models in conservation laws should help to extract docking and locking rate constants from experimental data or long molecular simulations with correct units and without compromising the molecular description.
Exocytosis is a highly regulated, multistage process consisting of multiple functionally definable stages, including recruitment, targeting, tethering, priming, and docking of secretory vesicles with the plasma membrane, followed by calcium-triggered membrane fusion. The acrosome reaction of spermatozoa is a complex, calcium-dependent regulated exocytosis. Fusion at multiple sites between the outer acrosomal membrane and the cell membrane causes the release of the acrosomal contents and the loss of the membranes surrounding the acrosome. Not much is known about the molecules that mediate membrane docking in this particular fusion model. In neurons, the formation of the ternary RIM/Munc13/Rab3A complex has been suggested as a critical component of synaptic vesicles docking. Previously, we demonstrated that Rab3A localizes to the acrosomal region in human sperm, stimulates acrosomal exocytosis, and participates in an early stage during membrane fusion. Here, we report that RIM and Munc13 are also present in human sperm and localize to the acrosomal region. Like Rab3A, RIM and Munc13 participate in a prefusion step before the efflux of intra-acrosomal calcium. By means of a functional assay using antibodies and recombinant proteins, we show that RIM, Munc13 and Rab3A interplay during acrosomal exocytosis. Finally, we report by electron transmission microscopy that sequestering RIM and Rab3A alters the docking of the acrosomal membrane to the plasma membrane during calcium-activated acrosomal exocytosis. Our results suggest that the RIM/Munc13/Rab3 A complex participates in acrosomal exocytosis and that RIM and Rab3A have central roles in membrane docking. -- Highlights: Black-Right-Pointing-Pointer RIM and Munc13 are present in human sperm and localize to the acrosomal region. Black-Right-Pointing-Pointer RIM and Munc13 are necessary for acrosomal exocytosis. Black-Right-Pointing-Pointer RIM and Munc13 participate before the acrosomal calcium efflux. Black-Right-Pointing-Pointer RIM, Munc13 and Rab3A interplay in human sperm acrosomal exocytosis. Black-Right-Pointing-Pointer RIM and Rab3A have critical roles in membrane docking.
Background: Current techniques for ulnar collateral ligament (UCL) reconstruction do not reproduce the anatomic ulnar footprint of the UCL. The purpose of this study was to describe a novel UCL reconstruction technique that utilizes proximal-to-distal ulnar bone tunnels to better re-create the anatomy of the UCL and to compare the biomechanical profile at time zero among this technique, the native UCL, and the traditional docking technique. Hypothesis: The biomechanical profile of the anatomic technique is similar to the native UCL and traditional docking technique. Study Design: Controlled laboratory study. Methods: Ten matched cadaveric elbows were potted with the forearm in neutral rotation. The palmaris longus tendon graft was harvested, and bones were sectioned 14 cm proximal and distal to the elbow joint. Specimen testing included (1) native UCL testing performed at 90° of flexion with 0.5 N·m of valgus moment preload, (2) cyclic loading from 0.5 to 5 N·m of valgus moment for 1000 cycles at 1 Hz, and (3) load to failure at 0.2 mm/s. Elbows then underwent UCL reconstruction with 1 elbow of each pair receiving the classic docking technique using either anatomic (proximal to distal) or traditional (anterior to posterior) tunnel locations. Specimen testing was then repeated as described. Results: There were no differences in maximum load at failure between the anatomic and traditional tunnel location techniques (mean ± SD, 34.90 ± 10.65 vs 37.28 ± 14.26 N·m; P = .644) or when including the native UCL (45.83 ± 17.03 N·m; P = .099). Additionally, there were no differences in valgus angle after 1000 cycles across the anatomic technique (4.58°± 1.47°), traditional technique (4.08°± 1.28°), and native UCL (4.07°± 1.99°). The anatomic group and the native UCL had similar valgus angles at failure (24.13°± 5.86° vs 20.13°± 5.70°; P = .083), while the traditional group had a higher valgus angle at failure when compared with the native UCL (24.88°± 6.18° vs 19.44°± 5.86°; P = .015). Conclusion: In this cadaveric model, UCL reconstruction with the docking technique utilizing proximal-to-distal ulnar tunnels better restored the ulnar footprint while providing valgus stability comparable with reconstruction with the docking technique using traditional anterior-to-posterior ulnar tunnel locations. These results suggest that utilization of the anatomic tunnel location in UCL reconstruction has similar biomechanical properties to the traditional method at the time of initial fixation (ie, not accounting for healing after reconstruction in vivo) while keeping the ulnar tunnels farther from the ulnar nerve. Further studies are warranted to determine if an anatomically based UCL reconstruction results in differing outcomes than traditional reconstruction techniques. Clinical Relevance: Current UCL reconstruction techniques do not accurately re-create the ulnar UCL footprint. The UCL is a dynamic constraint to valgus loads at the elbow, and a more anatomic reconstruction may afford more natural joint kinematics. This more anatomic technique performs similarly to the traditional docking technique at time zero, and the results of this study may offer a starting point for future in vivo studies.
Abstract Structure‐based virtual high‐throughput screening involves docking chemical libraries to targets of interest. A parameter pertinent to the accuracy of the resulting pose is the root mean square deviation (RMSD) from a known crystallographic structure, i. e., the ‘docking power’. Here, using a popular algorithm, Autodock Vina, as a model program, we evaluate the effects of varying two common docking parameters: the box size (the size of docking search space) and the exhaustiveness of the global search (the number of independent runs starting from random ligand conformations) on the RMSD from the PDBbind v2017 refined dataset of experimental protein‐ligand complexes. Although it is clear that exhaustiveness is an important parameter, there is wide variation in the values used, with variation between 1 and >100. We, therefore, evaluated a combination of cubic boxes of different sizes and five exhaustiveness values (1, 8, 25, 50, 75, 100) within the range of those commonly adopted. The results show that the default exhaustiveness value of 8 performs well overall for most box sizes. In contrast, for all box sizes, but particularly for large boxes, an exhaustiveness value of 1 led to significantly higher median RMSD (mRMSD) values. The docking power was slightly improved with an exhaustiveness of 25, but the mRMSD changes little with values higher than 25. Therefore, although low exhaustiveness is computationally faster, the results are more likely to be far from reality, and, conversely, values >25 led to little improvement at the expense of computational resources. Overall, we recommend users to use at least the default exhaustiveness value of 8 for virtual screening calculations.
PECAN2, Pose Classification with 3D Atomic Network 2, presents an innovative approach to pose classification in computational modeling, particularly in the context of molecular docking. Traditional methods like docking, which rely on physics-based calculations, are prone to inaccuracies in predicting binding poses during experimental testing. While machine learning (ML) approaches, such as ML-driven pose classification, have been introduced to address these issues, they often depend on the availability of crystal structure data. In contrast, PECAN2 introduces a novel pose classification method that operates independently of crystal structures. Instead, it utilizes a 3D atomic neural network with Point Cloud Network (PCN) to establish correlations between docking scores and experimental data. This approach marks a departure from previous studies that heavily relied on crystal structures for labeling. The key innovation lies in the ability of PECAN2 to enhance the performance of molecular docking by filtering out false positives and false negatives through the correlation between docking scores and experimental data.
The first important step in a structure-based virtual screening is the judicious selection of a receptor protein. In cases where the holo protein receptor structure is unavailable, significant reduction in virtual screening performance has been reported. In this work, we present a robust method to generate reliable holo protein structure conformations from apo structures using molecular dynamics (MD) simulation with restraints derived from holo structure binding-site templates. We perform benchmark tests on two different datasets: 40 structures from a directory of useful decoy-enhanced (DUD-E) and 84 structures from the Gunasekaran dataset. Our results show successful refinement of apo binding-site structures toward holo conformations in 82% of the test cases. In addition, virtual screening performance of 40 DUD-E structures is significantly improved using our MD-refined structures as receptors with an average enrichment factor (EF), an EF1% value of 6.2 compared to apo structures with 3.5. Docking of native ligands to the refined structures shows an average ligand root mean square deviation (RMSD) of 1.97 Å (DUD-E dataset and Gunasekaran dataset) relative to ligands in the holo crystal structures, which is comparable to the self-docking (i.e., docking of the native ligand back to its crystal structure receptor) average, 1.34 Å (DUD-E dataset) and 1.36 Å (Gunasekaran dataset). On the other hand, docking to the apo structures yields an average ligand RMSD of 3.65 Å (DUD-E) and 2.90 Å (Gunasekaran). These results indicate that our method is robust and can be useful to improve virtual screening performance of apo structures.
The widespread Mn 2+ -sensing yybP-ykoY riboswitch controls the expression of bacterial Mn 2+ homeostasis genes. Here, we first determine the crystal structure of the ligand-bound yybP-ykoY riboswitch aptamer from Xanthomonas oryzae at 2.96 Å resolution, revealing two conformations with docked four-way junction (4WJ) and incompletely coordinated metal ions. In >100 µs of MD simulations, we observe that loss of divalents from the core triggers local structural perturbations in the adjacent docking interface, laying the foundation for signal transduction to the regulatory switch helix. Using single-molecule FRET, we unveil a previously unobserved extended 4WJ conformation that samples transient docked states in the presence of Mg 2+ . Only upon adding sub-millimolar Mn 2+ , however, can the 4WJ dock stably, a feature lost upon mutation of an adenosine contacting Mn 2+ in the core. These observations illuminate how subtly differing ligand preferences of competing metal ions become amplified by the coupling of local with global RNA dynamics.
A rational surface-engineering approach led to the crystal structure determination of ERK2–docking peptide complexes. Linear motifs normally bind with only medium binding affinity (K{sub d} of ∼0.1–10 µM) to shallow protein-interaction surfaces on their binding partners. The crystallization of proteins in complex with linear motif-containing peptides is often challenging because the energy gained upon crystal packing between symmetry mates in the crystal may be on a par with the binding energy of the protein–peptide complex. Furthermore, for extracellular signal-regulated kinase 2 (ERK2) the protein–peptide docking surface is comprised of a small hydrophobic surface patch that is often engaged in the crystal packing of apo ERK2 crystals. Here, a rational surface-engineering approach is presented that involves mutating protein surface residues that are distant from the peptide-binding ERK2 docking groove to alanines. These ERK2 surface mutations decrease the chance of ‘unwanted’ crystal packing of ERK2 and the approach led to the structure determination of ERK2 in complex with new docking peptides. These findings highlight the importance of negative selection in crystal engineering for weakly binding protein–peptide complexes.
Time-to-solution for structure-based screening of massive chemical databases for COVID-19 drug discovery has been decreased by an order of magnitude, and a virtual laboratory has been deployed at scale on up to 27,612 GPUs on the Summit supercomputer, allowing an average molecular docking of 19,028 compounds per second. Over one billion compounds were docked to two SARS-CoV-2 protein structures with full optimization of ligand position and 20 poses per docking, each in under 24 hours. GPU acceleration and high-throughput optimizations of the docking program produced 350× mean speedup over the CPU version (50× speedup per node). GPU acceleration of both feature calculation for machine-learning based scoring and distributed database queries reduced processing of the 2.4 TB output by orders of magnitude. The resulting 50× speedup for the full pipeline reduces an initial 43 day runtime to 21 hours per protein for providing high-scoring compounds to experimental collaborators for validation assays.