Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergentBetacoronavirusstrains

Abstract

Comparative functional analysis of the binding interactions between various betacoronavirus strains and their potential human target proteins, such as ACE1, ACE2 and CD26, is critical to our future understanding and combating of COVID-19. Here, employing large replicate sets of GPU accelerated molecular dynamics simulations, we statistically compare atom fluctuations of the known human target proteins in both the presence and absence of different strains of the viral receptor binding domain (RBD) of the S spike glycoprotein. We identify a common interaction site between the N-terminal helices of ACE2 and the viral RBD in all strains (hCoV-OC43, hCoV-HKU1, MERS-CoV, SARS-CoV1, and SARS-CoV-2) and a second more dynamically complex RBD interaction site involving the ACE2 amino acid sites K353, Q325, and a novel motif, AAQPFLL (386-392) in the more recent cross-species spillovers (i.e. absent in hCoV-OC43). We use computational mutagenesis to further confirm the functional relevance of these sites. We propose a “one touch/two touch” model of viral evolution potentially involved in functionally facilitating binding interactions in zoonotic spillovers. We also observe these two touch sites governing RBD binding activity in simulations on hybrid models of the suspected viral progenitor, batCoV-HKU4, interacting with both the human SARS target, ACE2, and the human MERS target, CD26. Lastly, we confirm that the presence of a common hypertension drug (lisinopril) within the target site of SARS-CoV-2 bound models of ACE1 and ACE2 acts to enhance the RBD interactions at the same key sites in our proposed model. In the near future, we recommend that our comparative computational analysis identifying these key viral RBD-ACE2 binding interactions be supplemented with comparative studies of site-directed mutagenesis in order to screen for current and future coronavirus strains at high risk of zoonotic transmission to humans.STATEMENT OF SIGNIFICANCEWe generated structural models of the spike glycoprotein receptor binding domain from recent and past betacoronavirus outbreak strains aligned to the angiotensin 1 converting enzyme 2 protein, the primary target protein of the SARS-CoV-2 virus causing COVID 19. We then statistically compared computer simulated molecular dynamics of viral bound and unbound versions of each model to identify locations where interactions with each viral strain have dampened the atom fluctuations during viral binding. We demonstrate that all known strains of betacoronavirus are strongly interactive with the N-terminal helix region of ACE2. We also identify a more complex viral interaction with three novel sites that associates with more recent and deadly SARS strains, and also a bat progenitor strain HKU4.

RT-qPCR detection of SARS-CoV-2 mutations S 69-70 del, S N501Y and N D3L associated with variants of concern in Canadian wastewater samples

“…Assays were developed to detect B.1.1.7, B.1.351 and P.1 based on the high profile and global distribution of these lineages and their association with high SARS-CoV-2 transmissibility (Leung et al (2021); Ramanathan et al (2021)). The spike protein N501Y mutation consisting of an A->T at position 23063 alters one of the key contact residues within the receptor binding domain, leading to increased binding affinity to ACE2 in humans (Ramanathan et al (2021); Rynkiewicz et al (2021)). This mutation is found in B.1.1.7, B.1.351, and P.1; and is believed to have arisen independently in both lineages (Martin et al (2021)).…”

Structural biology in the time of COVID-19: perspectives on methods and milestones

“…Initial structure-prediction work using C-I-TASSER (Zhang, Zheng et al, 2020;Zhang, 2020) and AlphaFold from the DeepMind consortium (Jumper et al, 2020;Senior et al, 2020) was able to rapidly leverage the released genomes, determine protein sequences and create computational models that appeared in early February and March 2020. Molecular-dynamics simulations have massively extended the utility of experimental structural data, providing novel insights via the rapid analysis of in silico mutagenesis for many of the key viral proteins Rynkiewicz et al, 2021;Sheik Amamuddy et al, 2020) and the ability to model glycosylation of the spike protein Woo et al, 2020). Computational approaches have also helped to probe potential host-pathogen protein interactions (HPIs), contributing network-based and machine-learning-based assessments of putative interactions leveraging multiple HPI databases (Dey et al, 2020;Messina et al, 2020).…”

More than a year after the onset of the CoVid-19 pandemic in the UK: lessons learned from a minimalistic model capturing essential features including social awareness and policy making

“…Mutations on the spike protein, as is the case of the B1.1.7, can affect the stability of the binding, and hence the infective capability of the virus. Using a large number of molecular dynamics (MD) trajectories of different spike protein interactions with the human target protein (ACE2), a recent in-silico study has reported that mutations of the UK variant has greatly stabilised the interaction with the ACE2, which in turned has enhanced the binding stability (23). The study conjectures that the enhanced binding associated with the spike mutations of the B1.1.7 linage might be responsible for a higher transmissibility of the SARS-CoV-2 virus.…”