Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergent Betacoronavirus strains
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Abstract
Comparative functional analysis of the dynamic interactions between various Betacoronavirus mutant strains and broadly utilized target proteins such as ACE2 and CD26, is crucial for a more complete understanding of zoonotic spillovers of viruses that cause diseases such as COVID-19. Here, we employ machine learning to replicated sets of nanosecond scale GPU accelerated molecular dynamics simulations to statistically compare and classify atom motions of these target proteins in both the presence and absence of different endemic and emergent strains of the viral receptor binding domain (RBD) of the S spike glycoprotein. Machine learning was used to identify functional binding dynamics that are evolutionarily conserved from bat CoV-HKU4 to human endemic/emergent strains. Conserved dynamics regions of ACE2 involve both the N-terminal helices, as well as a region of more transient dynamics encompassing K353, Q325 and a novel motif AAQPFLL 386-92 that appears to coordinate their dynamic interactions with the viral RBD at N501. We also demonstrate that the functional evolution of Betacoronavirus zoonotic spillovers involving ACE2 interaction dynamics are likely pre-adapted from two precise and stable binding sites involving the viral bat progenitor strain’s interaction with CD26 at SAMLI 291-5 and SS 333-334. Our analyses further indicate that the human endemic strains hCoV-HKU1 and hCoV-OC43 have evolved more stable N-terminal helix interactions through enhancement of an interfacing loop region on the viral RBD, whereas the highly transmissible SARS-CoV-2 variants (B.1.1.7, B.1.351 and P.1) have evolved more stable viral binding via more focused interactions between the viral N501 and ACE2 K353 alone.
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SciScore for 10.1101/2020.09.11.293258: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Some potential limitations of MD simulations as a probative method for functional molecular evolution are its many implicit simplifying computational assumptions, its complex and inherently stochastic nature, and vary high computational expense (i.e. due to femtosecond time steps). Specifically, computational sampling of even the accelerated MD method employed here has strict hardware limitations, and even on modern graphics cards our …
SciScore for 10.1101/2020.09.11.293258: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Some potential limitations of MD simulations as a probative method for functional molecular evolution are its many implicit simplifying computational assumptions, its complex and inherently stochastic nature, and vary high computational expense (i.e. due to femtosecond time steps). Specifically, computational sampling of even the accelerated MD method employed here has strict hardware limitations, and even on modern graphics cards our simulations can typically have a cumulative runtime of several weeks to generate the proper statistical replication to compare physical time frames of only several hundreds of nanoseconds. In addition, MD simulations always involve some simplification of physics within the system being studied as it invariably ignores atomic charge regulation, bond motions in the solvent, charge screening during interaction, and other macromolecular crowding effects. Insight into long-term micro-millisecond dynamics in large explicit solvent systems are still limited by currently available hardware, even when creative algorithms for accelerating MD simulations are used. Glycosylation is another aspect of coronavirus spike protein biology that is not fully captured by our MD simulations, mainly due to lack of glycosylation in the functional binding interface of most of our key starting structures. We would argue that while these post-translational modifications can have in immediate impacts on dynamics, their probable lack of heritability may also minimize their ...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on page 27. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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