Mapping SARS-CoV-2 antigenic relationships and serological responses.

During the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, multiple variants escaping preexisting immunity emerged, causing reinfections of previously exposed individuals. Here, we used antigenic cartography to analyze patterns of cross-reactivity among 21 variants and 15 groups of human sera obtained after primary infection with 10 different variants or after messenger RNA (mRNA)-1273 or mRNA-1273.351 vaccination. We found antigenic differences among pre-Omicron variants caused by substitutions at spike-protein positions 417, 452, 484, and 501. Quantifying changes in response breadth over time and with additional vaccine doses, our results show the largest increase between 4 weeks and >3 months after a second dose. We found changes in immunodominance of different spike regions, depending on the variant an individual was first exposed to, with implications for variant risk assessment and vaccine-strain selection.

Mapping SARS-CoV-2 antigenic relationships and serological responses.

During the SARS-CoV-2 pandemic, multiple variants escaping pre-existing immunity emerged, causing concerns about continued protection. Here, we use antigenic cartography to analyze patterns of cross-reactivity among a panel of 21 variants and 15 groups of human sera obtained following primary infection with 10 different variants or after mRNA-1273 or mRNA-1273.351 vaccination. We find antigenic differences among pre-Omicron variants caused by substitutions at spike protein positions 417, 452, 484, and 501. Quantifying changes in response breadth over time and with additional vaccine doses, our results show the largest increase between 4 weeks and >3 months post-2nd dose. We find changes in immunodominance of different spike regions depending on the variant an individual was first exposed to, with implications for variant risk assessment and vaccine strain selection.

Exploitation of the catalytic site and 150 cavity for design of influenza A neuraminidase inhibitors.

We report here the exploitation of the 150 cavity in the active site of influenza A viral neuraminidases for the design of novel C-6 triazole-containing Tamiflu derivatives. A general and convenient synthetic route was developed by utilizing a highly substituted cyclic Baylis-Hillman acetate as an active precursor for azide substitution via suprafacial allylic azide [3,3]-sigmatropic rearrangement. Virus replication inhibitory assays in vitro of these triazole derivatives containing either an amino or guanidino function indicated that the guanidinium compound showed the higher efficacy against a strain with N2 subtype at a concentration of 2 × 10(-5) M but did not inhibit replication of a strain with N1 subtype even at a concentration of 10(-4) M. In order to probe the nature of the enzyme-inhibitor interactions, molecular dynamics simulations were performed on complexes of these compounds with different neuraminidase enzymes. The results indicated that the candidate inhibitors occupy both the 150 cavity and catalytic site but with alternating occupancy.

The influence of 150-cavity binders on the dynamics of influenza A neuraminidases as revealed by molecular dynamics simulations and combined clustering.

Neuraminidase inhibitors are the main pharmaceutical agents employed for treatments of influenza infections. The neuraminidase structures typically exhibit a 150-cavity, an exposed pocket that is adjacent to the catalytic site. This site offers promising additional contact points for improving potency of existing pharmaceuticals, as well as generating entirely new candidate inhibitors. Several inhibitors based on known compounds and designed to interact with 150-cavity residues have been reported. However, the dynamics of any of these inhibitors remains unstudied and their viability remains unknown. This work reports the outcome of long-term, all-atom molecular dynamics simulations of four such inhibitors, along with three standard inhibitors for comparison. Each is studied in complex with four representative neuraminidase structures, which are also simulated in the absence of ligands for comparison, resulting in a total simulation time of 9.6 µs. Our results demonstrate that standard inhibitors characteristically reduce the mobility of these dynamic proteins, while the 150-binders do not, instead giving rise to many unique conformations. We further describe an improved RMSD-based clustering technique that isolates these conformations--the structures of which are provided to facilitate future molecular docking studies--and reveals their interdependence. We find that this approach confers many advantages over previously described techniques, and the implications for rational drug design are discussed.