A uniquely stable trimeric model of SARS-CoV-2 spike transmembrane domain

International Journal of Molecular Sciences. 2022. Vol. 23(16). Article 9221.

Aliper E. T., Krylov Nikolay A., Nolde Dmitry E., Polyansky A. A., Efremov Roman G.

Understanding fusion mechanisms employed by SARS-CoV-2 spike protein entails realistic
transmembrane domain (TMD) models, while no reliable approaches towards predicting the 3D
structure of transmembrane (TM) trimers exist. Here, we propose a comprehensive computational
framework to model the spike TMD only based on its primary structure. We performed amino acid
sequence pattern matching and compared the molecular hydrophobicity potential (MHP) distribution
on the helix surface against TM homotrimers with known 3D structures and selected an appropriate
template for homology modeling. We then iteratively built a model of spike TMD, adjusting “dynamic
MHP portraits” and residue variability motifs. The stability of this model, with and without palmitoyl
modifications downstream of the TMD, and several alternative configurations (including a recent
NMR structure), was tested in all-atom molecular dynamics simulations in a POPC bilayer mimicking
the viral envelope. Our model demonstrated unique stability under the conditions applied and
conforms to known basic principles of TM helix packing. The original computational framework
looks promising and could potentially be employed in the construction of 3D models of TM trimers
for a wide range of membrane proteins.

Keywords: molecular hydrophobicity potential, молекулярный гидрофобный потенциал, transmembrane domain, трансмембранный домен, Моделирование молекулярной динамики, Molecular dynamics simulation, structure prediction, viral fusion protein, helical trimer, template-based modeling, Monte Carlo conformational search, предсказание структуры, вирусные белки слияния, тример из спиралей, моделирование на основании шаблона, конформационный поиск методом Монте-Карло

Publication based on the results of: Supercomputer technologies, theory and atomistic multiscale modeling in materials physics and life sciences (2022)