Figure 2 - uploaded by Gengbin Zheng
Content may be subject to copyright.
NAMD 2 hybrid force/spatial decomposition. Atoms are spatially decomposed into patches, which are represented on other nodes by proxies. Interactions between atoms are calculated by several classes of compute objects.
Source publication
NAMD is a fully featured, production molecular dynamics program for high performance simulation of large biomolecular systems. We have previously, at SC2000, presented scaling results for simulations with cutoff electrostatics on up to 2048 processors of the ASCI Red machine, achieved with an object-based hybrid force and spatial decomposition sche...
Context in source publication
Context 1
... the different types of forces (bond, electrostatic, constraint, etc.). Some compute objects require data from one patch, and only calculate interactions between atoms within that single patch. Other compute objects are responsible for interactions between atoms distributed among neighboring patches. Relationships among objects are illustrated in Fig. ...
Similar publications
Citations
... Nanoscale Molecular Dynamics (NAMD) 2.9 package, Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign, Urbana, IL, USA [46] with the CHARMM36 force field [47] was employed for simulations. A time step of 1.0 fs was used with particle mesh Ewald (PME) electrostatics under NPT conditions (constant pressure and temperature). ...
Exploring therapeutic options is crucial in the ongoing COVID-19 pandemic caused by SARS-CoV-2. Nirmatrelvir, which is a potent inhibitor that targets the SARS-CoV-2 Mpro, shows promise as an antiviral treatment. Additionally, Ivermectin, which is a broad-spectrum antiparasitic drug, has demonstrated effectiveness against the virus in laboratory settings. However, its clinical implications are still debated. Using computational methods, such as molecular docking and 100 ns molecular dynamics simulations, we investigated how Nirmatrelvir and Ivermectin interacted with SARS-CoV-2 Mpro(A). Calculations using density functional theory were instrumental in elucidating the behavior of isolated molecules, primarily by analyzing the frontier molecular orbitals. Our analysis revealed distinct binding patterns: Nirmatrelvir formed strong interactions with amino acids, like MET49, MET165, HIS41, HIS163, HIS164, PHE140, CYS145, GLU166, and ASN142, showing stable binding, with a root-mean-square deviation (RMSD) of around 2.0 Å. On the other hand, Ivermectin interacted with THR237, THR239, LEU271, LEU272, and LEU287, displaying an RMSD of 1.87 Å, indicating enduring interactions. Both ligands stabilized Mpro(A), with Ivermectin showing stability and persistent interactions despite forming fewer hydrogen bonds. These findings offer detailed insights into how Nirmatrelvir and Ivermectin bind to the SARS-CoV-2 main protease, providing valuable information for potential therapeutic strategies against COVID-19.
... Molecular dynamics (MD) simulations were conducted using the Nanoscale Molecular Dynamics (NAMD) 2.9 computational package [34] along with the CHARMM36 force field [35], using a time step of 1.0 fs. The model protein/ligand complexes were maintained under constant pressure and temperature conditions within the NPT ensemble at 300 K and 1 atm, respectively. ...
Exploring therapeutic options is crucial in the ongoing COVID-19 pandemic caused by SARS-CoV-2. Nirmatrelvir, a potent inhibitor targeting the SARS-CoV-2 Mpro, shows promise as an antiviral treatment. Additionally, Ivermectin, a broad-spectrum antiparasitic drug, has demonstrated effectiveness against the virus in laboratory settings. However, its clinical implications are still debated. Using computational methods such as molecular docking and 100 ns molecular dynamics simulations, we investigated how Nirmatrelvir and Ivermectin interact with SARS-CoV-2 Mpro(A). Calculations using density functional theory have been instrumental in elucidating the behavior of isolated molecules, primarily by analyzing the frontier molecular orbitals. Our analysis revealed distinct binding patterns: Nirmatrelvir formed strong interactions with amino acids like MET49, MET165, HIS41, HIS163, HIS164, PHE140, CYS145, GLU166, and ASN142, showing stable binding with a root mean square deviation (RMSD) of around 2.0 Å. On the other hand, Ivermectin interacted with THR237, THR239, LEU271, LEU272, and LEU287, displaying an RMSD of 1.87 Å, indicating enduring interactions. Both ligands stabilized Mpro(A), with Ivermectin showing stability and persistent interactions despite forming fewer hydrogen bonds. These findings offer detailed insights into how Nirmatrelvir and Ivermectin bind to the SARS-CoV-2 main protease, providing valuable information for potential therapeutic strategies against COVID-19.
... CHARMM27 is used for this study because it was efficiently utilized in previous studies on biomolecules 9 . It contains all parameters for our systems (carrier and drug) and it is complete for our complexes 27,28 . ...
Spherical nanocarriers can lead to a bright future to lessen problems of virus infected people. Spherical polyethylene glycol (PEG) and spherical silica (SiO2) are novel attractive nanocarriers as drug delivery agents, especially they are recently noticed to be reliable for antiviral drugs like anti-HIV, anti-covid-19, etc. Lamivudine (3TC) is used as a first line drug for antiviral therapy and the atomic view of 3TC-PEG/SiO2 complexes enable scientist to help improve treatment of patients with viral diseases. This study investigates the interactions of 3TC with Spherical PEG/SiO2, using molecular dynamics simulations. The mechanism of adsorption, the stability of systems and the drug concentration effect are evaluated by analyzing the root mean square deviation, the solvent accessible surface area, the radius of gyration, the number of hydrogen bonds, the radial distribution function, and Van der Waals energy. Analyzed data show that the compression of 3TC is less on PEG and so the stability is higher than SiO2; the position and intensity of the RDF peaks approve this stronger binding of 3TC to PEG as well. Our studies show that PEG and also SiO2 are suitable for loading high drug concentrations and maintaining their stability; therefore, spherical PEG/SiO2 can reduce drug dosage efficiently.
... Because each process has two downstream partners, LU's peak ingress volume counts two messages. • Alltoall: This MPI collective is important for applications that perform parallel Fast Fourier Transforms (FFT) such as pF3D [30], NAMD [31], and VASP [32]. SST implements MPI Alltoall through a multi-step ring exchange such that process N receives data from process N − i and sends data to process N + i in round i. ...
... 2 For each simulation, FLOP counts were measured for NAMD simulation runs of two different step counts. The results of the two simulation lengths were subtracted to eliminate NAMD startup operations, yielding an accurate estimate of the marginal FLOPs per step for a continuing simulation (Phillips et al., 2002). Using the FLOPs/step values computed for each simulation, overall FLOP rates were computed by dividing the FLOPs/step value by seconds/step performance data reported by NAMD internal application timers during production runs. ...
We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus obscure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized.
... The aqueous solution contained one molecule of PCI_Lip or L305A mutant and 16 substrate molecules. Next, an MD simulation (NAMD v.2.14 with standard CHARMM36 force field) was used to study their kinetic behaviors [21,22]. The temperature and pressure were set to 37 • C and 1 atm [23]. ...
In traditional cheese making, pregastric lipolytic enzymes of animal origin are used for the acceleration of ripening and the formation of spicy flavor compounds. Especially for cheese specialities, such as Pecorino, Provolone, or Feta, pregastric esterases (PGE) play an important role. A lipase from Pleurotus citrinopileatus could serve as a substitute for these animal-derived enzymes, thus offering vegetarian, kosher, and halal alternatives. However, the hydrolytic activity of this enzyme towards long-chain fatty acids is slightly too high, which may lead to off-flavors during long-term ripening. Therefore, an optimization via protein engineering (PE) was performed by changing the specificity towards medium-chain fatty acids. With a semi-rational design, possible mutants at eight different positions were created and analyzed in silico. Heterologous expression was performed for 24 predicted mutants, of which 18 caused a change in the hydrolysis profile. Three mutants (F91L, L302G, and L305A) were used in application tests to produce Feta-type brine cheese. The sensory analyses showed promising results for cheeses prepared with the L305A mutant, and SPME-GC-MS analysis of volatile free fatty acids supported these findings. Therefore, altering the chain length specificity via PE becomes a powerful tool for the replacement of PGEs in cheese making.
... FLOP counts were measured for each NAMD simulation with runs of two different step counts. The results of the two different simulation lengths were subtracted to eliminate counting of startup-associated operations, to provide an accurate estimate of the FLOPs per step for a continuing simulation (Phillips et al., 2002). ...
The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g. cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.
... 2 For each simulation, FLOP counts were measured for NAMD simulation runs of two different step counts. The results of the two simulation lengths were subtracted to eliminate NAMD startup operations, yielding an accurate estimate of the marginal FLOPs per step for a continuing simulation (Phillips et al., 2002). Using the FLOPs/step values computed for each simulation, overall 1 https://github.com/intel/msr-tools 2 https://github.com/TACC/tacc_stats . ...
We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus ob-scure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized.
ACM Reference Format
Abigail Dommer 1† , Lorenzo Casalino 1† , Fiona Kearns 1† , Mia Rosenfeld ¹ , Nicholas Wauer ¹ , Surl-Hee Ahn ¹ , John Russo, ² Sofia Oliveira ³ , Clare Morris ¹ , AnthonyBogetti ⁴ , AndaTrifan 5,6 , Alexander Brace 5,7 , TerraSztain 1,8 , Austin Clyde 5,7 , Heng Ma ⁵ , Chakra Chennubhotla ⁴ , Hyungro Lee ⁹ , Matteo Turilli ⁹ , Syma Khalid ¹⁰ , Teresa Tamayo-Mendoza ¹¹ , Matthew Welborn ¹¹ , Anders Christensen ¹¹ , Daniel G. A. Smith ¹¹ , Zhuoran Qiao ¹² , Sai Krishna Sirumalla ¹¹ , Michael O’Connor ¹¹ , Frederick Manby ¹¹ , Anima Anandkumar 12,13 , David Hardy ⁶ , James Phillips ⁶ , Abraham Stern ¹³ , Josh Romero ¹³ , David Clark ¹³ , Mitchell Dorrell ¹⁴ , Tom Maiden ¹⁴ , Lei Huang ¹⁵ , John McCalpin ¹⁵ , Christo- pherWoods ³ , Alan Gray ¹³ , MattWilliams ³ , Bryan Barker ¹⁶ , HarindaRajapaksha ¹⁶ , Richard Pitts ¹⁶ , Tom Gibbs ¹³ , John Stone ⁶ , Daniel Zuckerman ² *, Adrian Mulholland ³ *, Thomas MillerIII 11,12 *, ShantenuJha ⁹ *, Arvind Ramanathan ⁵ *, Lillian Chong ⁴ *, Rommie Amaro ¹ *. 2021. #COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy ofDeltaSARS-CoV-2 in a Respiratory Aerosol. In Supercomputing ‘21: International Conference for High Perfor-mance Computing, Networking, Storage, and Analysis . ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI
... FLOP counts were measured for each NAMD simulation with runs of two dierent step counts. The results of the two dierent simulation lengths were subtracted to eliminate counting of startup-associated operations, to provide an accurate estimate of the FLOPs per step for a continuing simulation (Phillips et al., 2002). ...
The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.
... FLOP counts were measured for each NAMD simulation with runs of two dierent step counts. The results of the two dierent simulation lengths were subtracted to eliminate counting of startup-associated operations, to provide an accurate estimate of the FLOPs per step for a continuing simulation (Phillips et al., 2002). ...
The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.
