Xeon e5 2680

Manufactured by NVIDIA

The Xeon E5-2680 is a high-performance server processor from Intel. It features up to 8 cores, 16 threads, and a base clock speed of 2.7 GHz. The Xeon E5-2680 is designed to provide efficient performance for a wide range of server and workstation applications.

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Gtx 780ti, by NVIDIA (3 mentions) Tesla p100, by NVIDIA (1 mentions) Geforce gtx 1070, by NVIDIA (1 mentions) Rtx 3090, by NVIDIA (1 mentions) Tesla k80, by NVIDIA (1 mentions)

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Xeon(R) CPU E5-2680 v4 (2 citations)

6 protocols using xeon e5 2680

GPU-accelerated Structural Simulation Evaluation

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Evaluation was performed on a headless GPU server with an Intel Xeon E5-2680, 256 GB of RAM and one Nvidia Tesla P100 with 16 GB of memory. The P100 includes 56 streaming multiprocessors (SM) each with 24 kB of L1 cache.
As a baseline, each dataset was also simulated using the iterative solver in the commercially available software Abaqus. Datasets were not re-meshed for this purpose. The simulation was performed in parallel on a workstation with 16 CPU cores and 128 GB of RAM. The linear solver was configured to use the iterative method with convergence criterion of 5.0×10⁻³ for the average flux norm and 1.0×10⁻² for displacement corrections.

Schlinkmann C., Roland M., Wolff C., Trampert P., Slusallek P., Diebels S, & Dahmen T. (2020). A GPU-based caching strategy for multi-material linear elastic FEM on regular grids. PLoS ONE, 15(10), e0240813.

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Molecular Dynamics Simulation of PDI-hVKORC1 Complex

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All trajectories were performed using the AMBER ff14SB force field with the PMEMD module of AMBER 16 and AMBER 18 [36 (link)] (GPU-accelerated versions) running on a local hybrid server (Ubuntu, LTS 14.04, 252 GB RAM, 2× CPU Intel Xeon E5-2680, and Nvidia GTX 780ti) and on the supercomputer JEAN ZAY at IDRIS.
Each fully relaxed PDI-hVKORC1 complex inserted into the solvated bilayer lipid membrane was simulated during the 0.52 µs MD trajectory. A time step of 2 fs was used to integrate the equations of motion based on the Leap-Frog algorithm [44 (link)]. Coordinate files were recorded every 1 ps. Neighbour searching was performed by the Verlet algorithm [45 (link)]. The Particle Mesh Ewald (PME) method [46 ] with a cut-off of 9.0 Å was used to treat long-range electrostatic interactions at every time step. The van der Waals interactions were modelled using a 6–12 Lennard–Jones potential. The initial velocities were reassigned according to the Maxwell–Boltzmann distribution.

Stolyarchuk M., Botnari M, & Tchertanov L. (2024). Vitamin K Epoxide Reductase Complex–Protein Disulphide Isomerase Assemblies in the Thiol–Disulphide Exchange Reactions: Portrayal of Precursor-to-Successor Complexes. International Journal of Molecular Sciences, 25(8), 4135.

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Peptide-NLRP3/ASC Interaction Modeling

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Peptides optimized based on the aforementioned properties underwent molecular docking against the PYD of NLRP3 (PDB ID: 2NAQ) and ASC (PDB ID: 3J63) to evaluate their binding capabilities. Clusters with the highest population were examined to select representative solutions based on their docking score and root mean square deviation (RMSD) after clustering the docked solutions. Subsequently, the study employed MD simulations to obtain a thorough comprehension of protein-peptide interactions at an atomic level. MD simulations were conducted using GROMACS 2021.2 [67] on an Intel Xeon E5–2680 system with an Nvidia GeForce GTX 1070 graphics processing unit, as described in our previous research [68] , [69] (link).
Interacting residues between the peptide and PYD were identified using a threshold distance of 4.0 Å. Subsequently, we analyzed the computed averages and fluctuations of the interatomic distances of selected residues throughout the entire MD trajectories. Evaluation of the binding affinity of the optimized peptide with the PYD of NLRP3 and ASC involved the extraction of frames from MD trajectories and determination of the binding free energy by applying the molecular mechanics Poisson–Boltzmann surface area (MMPBSA) method, which has been previously described [70] (link).

Ahmad B., Achek A., Farooq M, & Choi S. (2023). Accelerated NLRP3 inflammasome-inhibitory peptide design using a recurrent neural network model and molecular dynamics simulations. Computational and Structural Biotechnology Journal, 21, 4825-4835.

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Molecular Dynamics Simulations of Mutated hVKORC1

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The conventional Molecular Dynamics (MD) trajectories of each homology model of mutated hVKORC1 were generated using the AMBER ff14SB force field with the PMEMD module of AMBER 16 and AMBER 18 (GPU-accelerated versions) [52 (link)] proceeding on a local hybrid server (Ubuntu, LTS 14.04, 252 GB RAM, 2x CPU Intel Xeon E5-2680 and Nvidia GTX 780ti) and the supercomputer JEAN ZAY at IDRIS.
A time step of 2 fs was used to integrate the equations of motion based on the Leap-Frog algorithm [57 (link)]. The Particle Mesh Ewald (PME) method, with a cut-off of 22 Å, was used to treat long-range electrostatic interactions at every time step. The van der Waals interactions were modelled using a 6–12 Lennard–Jones potential. The initial velocities were reassigned according to the Maxwell–Boltzmann distribution. For the molecular complexes, to prevent the separation of the PDI protein from hVKORC1 and to bring them together, the distances between a restrained harmonic distance were introduced to the S⋯S atom pair (the sulphur atoms from C37 of PDI and C43 of hVKORC1), which was varied in a stepwise manner as in [5 (link)]. During each step (100 ns), the constraints were maintained, and then removed, to fully relax the systems. For each system, three 0.5 µs trajectories were carried out with different starting velocities. The coordinates were recorded every 10 ps.

Botnari M, & Tchertanov L. (2024). Synergy of Mutation-Induced Effects in Human Vitamin K Epoxide Reductase: Perspectives and Challenges for Allo-Network Modulator Design. International Journal of Molecular Sciences, 25(4), 2043.

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High-Performance Computing for Bioinformatics Research

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Our analyses were performed on an Ubuntu 18.04 machine and the Colorado Summit compute cluster. The desktop CPU used was an AMD Ryzen 7 3800xt processor with 16 cores and access to 64 GB of RAM, and the desktop GPU used was an Nvidia RTX 3090. The Summit cluster used Intel Xeon E5-2680 CPUs and NVidia Tesla K80 GPUs. From initiating data download to finishing all analyses and generating all figures, the full Snakemake [35 (link)] pipeline took around one month to run.

Heil B.J., Crawford J, & Greene C.S. (2023). The effect of non-linear signal in classification problems using gene expression. PLOS Computational Biology, 19(3), e1010984.

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Molecular Dynamics Simulation of KIT-KID Complexes

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All trajectories were produced using the AMBER ff99SB force field with the PMEMD module of AMBER 16 and AMBER 18 [51 (link)] (GPU-accelerated versions) running on a local hybrid server (Ubuntu, LTS 14.04, 252 GB RAM, 2× CPU Intel Xeon E5-2680 and Nvidia GTX 780ti) and the supercomputer JEAN ZAY at IDRIS.
The multiple extended trajectories were generated for each equilibrated system: two 2-µs trajectories for KIT with KID, four 1.8-µs replicas for cleaved KID (KID^C) and two 1.8-µs replicas for cleaved KID with the restrained distance (10 Å) between the Cα-atoms of terminal residues, F689 and D768 (KID^CR).
A time step of 2 fs was used to integrate the equations of motion based on the Leap-Frog method. Coordinate files were recorded every 1 ps. Neighbour searching was performed by the Verlet algorithm [56 (link)]. The Particle Mesh Ewald (PME) method, with a cut-off of 10 Å, was used to treat long-range electrostatic interactions at every time step. The van der Waals interactions were modelled using a 6–12 Lennard–Jones potential. The initial velocities were reassigned according to the Maxwell–Boltzmann distribution. Coordinates were recorded every 1 ps.

Ledoux J., Trouvé A, & Tchertanov L. (2021). Folding and Intrinsic Disorder of the Receptor Tyrosine Kinase KIT Insert Domain Seen by Conventional Molecular Dynamics Simulations. International Journal of Molecular Sciences, 22(14), 7375.

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