Molecular dynamics of Middle East Respiratory Syndrome Coronavirus (MERS CoV) fusion heptad repeat trimers

Abstract
Structural studies related to Middle East Respiratory Syndrome Coronavirus (MERS CoV) infection process are so limited. In this study, molecular dynamics (MD) simulation was carried out to unravel changes in the MERS CoV heptad repeat domains (HRs) and factors affecting fusion state HR stability. Results indicated that HR trimer is more rapidly stabilized, having stable system energy and lowest root mean square deviations (RMSDs). While trimers were the predominant active form of CoVs HR, monomers were also discovered in both of viral and cellular membranes. In order to find the differences between S2 monomer and trimer molecular dynamics, S2 monomer were modelled and subjected to MD simulation. In contrast to S2 trimer, S2 monomer was unstable, having high RMSDs with major drifts above 8 Å. Fluctuation of HR residue positions revealed major changes in the C-terminal of HR2 and the linker coil between HR1 and HR2 in both monomer and trimer. Hydrophobic residues at the “a” and “d” positions of HR helices stabilize the whole system, having minimal changes in RMSD. The global distance test and contact area difference scores support instability of MERS CoV S2 monomer. Analysis of HR1-HR2 inter-residue contacts and interaction energy revealed three different energy scales along HR helices. Two strong interaction energies were identified at the start of the HR2 helix and at the C-terminal of HR2. The identified critical residues by MD simulation and residues at a and d position of HR helix were strong stabilizers of HRs recognition.

Citation
Kandeel M, Al-Taher A, Li H, Schwingenschlogl U, Alnazawi M (2018) Molecular dynamics of Middle East Respiratory Syndrome Coronavirus (MERS CoV) fusion heptad repeat trimers. Computational Biology and Chemistry. Available: http://dx.doi.org/10.1016/j.compbiolchem.2018.05.020.

Acknowledgements
This work was supported by a research grant from King Faisal University, Deanship of Scientific Research under grant number 171001. We thank the faculty of Veterinary Medicine at King Faisal University for providing computational facilities from the PC labs. The research reported in this publication was supported by funding from King Abdullah University (KAUST). For computer time, this research used the resources of the Supercomputing Laboratory at KAUST.

Publisher
Elsevier BV

Journal
Computational Biology and Chemistry

DOI
10.1016/j.compbiolchem.2018.05.020

Additional Links
http://www.sciencedirect.com/science/article/pii/S1476927118300926

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