Abstract

The nonstructural protein-1 (NSP1) of the severe acute respiratory syndrome-associated coronavirus 2 plays a crucial role in the translational shutdown and immune evasion inside host cells. Despite its known intrinsic disorder, the C-terminal domain (CTD) of NSP1 has been reported to form a double α-helical structure and block the 40S-ribosomal channel for mRNA translation. Experimental studies indicate that NSP1 CTD functions independently from the globular N-terminal region separated with a long linker domain, underscoring the necessity of exploring the standalone conformational ensemble. In this contribution, we utilize exascale computing resources to yield unbiased molecular dynamics simulation of NSP1 CTD in all-atom resolution starting from multiple initial seed structures. A data-driven approach elicits collective variables (CVs) that are significantly superior to conventional descriptors in capturing the conformational heterogeneity. The free energy landscape as a function of the CV space is estimated using the modified expectation maximized molecular dynamics. Originally developed by us for small peptides, here, we establish the efficacy of expectation maximized molecular dynamics in conjunction with data-driven CV space for a more complex and relevant biomolecular system. The results reveal the existence of two disordered metastable populations in the free energy landscape that are separated from the conformation resembling ribosomal subunit bound state by high kinetic barriers. Chemical shift correlation and secondary structure analysis capture significant differences among key structures of the ensemble. Altogether, these insights can underpin drug development studies and mutational experiments that help induce population shifts to alter translational blocking and understand its molecular basis in further detail.

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