SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome

Zimmerman, Maxwell I.; Porter, Justin R.; Ward, Michael D.; Singh, Sukrit; Vithani, Neha; Meller, Artur; Mallimadugula, Upasana L.; Kuhn, Catherine E.; Borowsky, Jonathan; Wiewiora, Rafal; Hurley, Matthew F. D.; Harbison, Aoife M; Fogarty, Carl A; Coffland, Joseph E.; Fadda, Elisa; Voelz, Vincent A.; Chodera, John D.; Bowman, Gregory R.

doi:10.1101/2020.06.27.175430

“…The significance of the distal regions is less well understood, though computational investigations support a potential allosteric role. 17,18 To study this further, we examined the correlated motions of each residue throughout the simulations. In the monomer simulation, the active site region was positively correlated to the distal site region, and negatively correlated to the region that connects the two, whereas the inverse was observed in the dimer simulation ( Figure 3, S2,3).…”

Section: Resultsmentioning

confidence: 99%

Elucidation of cryptic and allosteric pockets within the SARS-CoV-2 protease

Sztain

¹

,

Amaro

²

,

McCammon

³

2020

Preprint

View full text Add to dashboard Cite

The SARS-CoV-2 pandemic has rapidly spread across the globe, posing an urgent health concern. Many quests to computationally identify treatments against the virus rely on in silico small molecule docking to experimentally determined structures of viral proteins. One limit to these approaches is that protein dynamics are often unaccounted for, leading to overlooking transient, druggable conformational states. Using Gaussian accelerated molecular dynamics to enhance sampling of conformational space, we identified cryptic pockets within the SARS-CoV-2 main protease, including some within regions far from the active site and assed their druggability. These pockets can aid in virtual screening efforts to identify a protease inhibitor for the treatment of COVID-19.Abstract Figure

show abstract

“…Indeed, an optimal setup consists in producing first long adaptive non-polarizable simulation that can be further refined with polarizable potentials within additional adaptive iterations. That way, our approach could also use Folding@home COVID-19 community results 61 as input (or any available data shared on the Bioexcel/Molssi repository) in order to reinject a maximum of potentially new/useful information into COVID-19 research. Indeed, it is important to recall the importance of proposing accurate (and as much as possible converged) simulations of the COVID-19 targets.…”

Section: Discussionmentioning

confidence: 99%

High-Resolution Mining of SARS-CoV-2 Main Protease Conformational Space: Supercomputer-Driven Unsupervised Adaptive Sampling

Inizan¹,

Célerse²,

Adjoua³

et al. 2020

Preprint

View full text Add to dashboard Cite

We provide a new unsupervised adaptive sampling strategy capable of producing microsecondtimescale molecular dynamics (MD) simulations using many-body polarizable force fields (PFF) on modern supercomputers. The global exploration problem is decomposed into a set of separate MD trajectories that can be restarted within an iterative/selective process to achieve sufficient phase-space sampling within large biosystems, while accurate statistical properties can be obtained through debiasing. With this pleasingly parallel setup, the Tinker-HP package can be powered by an arbitrary large number of GPUs (Graphics Processing Unit) cards available on pre-exascale supercomputers, reducing to days explorations that would have taken years. We applied the approach to the urgent problem of the modeling of the SARS–CoV–2 Main protease (Mpro) dimer. A 15.14 microsecond high-resolution all-atom simulation (AMOEBA PFF) of its apo state is provided and compared to other available long-timescale non-PFF data. Noticeable differences are found between clustering analysis of the simulations, the AMOEBA adaptive results exhibiting a richer conformational space. Overall, our high-resolution AMOEBA structural analysis captures key experimental observations concerning the stability of the oxyanion hole, a marker of activity through the stability of different stacking and salt bridge interactions. A dissymmetry is found between the enzyme protomers that exhibit different volumes. One of them appears fully inactive while the other is "activable", exhibiting some partial activity features. This activity evaluation can be further traced back to the large flexibility of the C terminal domain, fully captured by AMOEBA but not seen in X-rays due to insufficient electron densities related to the domain high mobility. The C–terminal region of the fully inactive protomer is shown to oscillate between several states, one of them interacting with the other protomer active site, therefore potentially modulating down its activity. Overall, these results reinforce the experimental hypothesis of a full inactivation of the apo state and clearly capture the asymmetric nature of protomers. Additional analysis show that the cavities volumes of the active and distal sites are found to be larger in the most active protomer with AMOEBA. To a larger extend, the PFF finds significantly larger cavities than those obtained with classical, non-polarizable simulations. The consequences on druggability are discussed as additional potential druggable cryptic pockets are found. All data produced within this research are fully accessible to the community for further analysis.

show abstract

“…Indeed, an optimal setup consists in producing first long adaptive non-polarizable simulation that can be further refined with polarizable potentials within additional adaptive iterations. That way, our approach could also use Folding@home COVID-19 community results 62 as input (or any available data shared on the Bioexcel/Molssi repository) in order to reinject a maximum of potentially new/useful information into COVID-19 research. Indeed, it is important to recall the importance of proposing accurate (and as much as possible converged) simulations of the COVID-19 targets.…”

Section: Discussionmentioning

confidence: 99%

High-Resolution Mining of SARS-CoV-2 Main Protease Conformational Space: Supercomputer-Driven Unsupervised Adaptive Sampling

Inizan¹,

Célerse²,

Adjoua³

et al. 2020

Preprint

0

View full text Add to dashboard Cite

We provide a new unsupervised adaptive sampling strategy capable of producing microsecondtimescale molecular dynamics (MD) simulations using many-body polarizable force fields (PFF) on modern supercomputers. The global exploration problem is decomposed into a set of separate MD trajectories that can be restarted within an iterative/selective process to achieve sufficient phase-space sampling within large biosystems, while accurate statistical properties can be obtained through debiasing. With this pleasingly parallel setup, the Tinker-HP package can be powered by an arbitrary large number of GPUs (Graphics Processing Unit) cards available on pre-exascale supercomputers, reducing to days explorations that would have taken years. We applied the approach to the urgent problem of the modeling of the SARS–CoV–2 Main protease (Mpro) dimer. A 15.14 microsecond high-resolution all-atom simulation (AMOEBA PFF) of its apo state is provided and compared to other available long-timescale non-PFF data. Noticeable differences are found between clustering analysis of the simulations, the AMOEBA adaptive results exhibiting a richer conformational space. Overall, our high-resolution AMOEBA structural analysis captures key experimental observations concerning the stability of the oxyanion hole, a marker of activity through the stability of different stacking and salt bridge interactions. A dissymmetry is found between the enzyme protomers that exhibit different volumes. One of them appears fully inactive while the other is "activable", exhibiting some partial activity features. This activity evaluation can be further traced back to the large flexibility of the C terminal domain, fully captured by AMOEBA but not seen in X-rays due to insufficient electron densities related to the domain high mobility. The C–terminal region of the fully inactive protomer is shown to oscillate between several states, one of them interacting with the other protomer active site, therefore potentially modulating down its activity. Overall, these results reinforce the experimental hypothesis of a full inactivation of the apo state and clearly capture the asymmetric nature of protomers. Additional analysis show that the cavities volumes of the active and distal sites are found to be larger in the most active protomer with AMOEBA. To a larger extend, the PFF finds significantly larger cavities than those obtained with classical, non-polarizable simulations. The consequences on druggability are discussed as additional potential druggable cryptic pockets are found. All data produced within this research are fully accessible to the community for further analysis.

show abstract

SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome

Cited by 60 publications

References 80 publications

Elucidation of cryptic and allosteric pockets within the SARS-CoV-2 protease

Elucidation of cryptic and allosteric pockets within the SARS-CoV-2 protease

High-Resolution Mining of SARS-CoV-2 Main Protease Conformational Space: Supercomputer-Driven Unsupervised Adaptive Sampling

High-Resolution Mining of SARS-CoV-2 Main Protease Conformational Space: Supercomputer-Driven Unsupervised Adaptive Sampling

Contact Info

Product

Resources

About