During the SARS-CoV-2 pandemic, multiple variants with differing amounts of escape from pre-existing immunity have emerged, causing concerns about continued protection. Here, we use antigenic cartography to quantify and visualize the antigenic relationships among 16 SARS-CoV-2 variants titrated against serum samples taken post-vaccination and post-infection with seven different variants. We find major antigenic differences caused by substitutions at positions 417, 452, 484, and possibly 501. B.1.1.529 (Omicron) showed the highest escape from all sera tested. Visualization of serological responses as antibody landscapes shows how reactivity clusters in different regions of antigenic space. We find changes in immunodominance of different spike regions depending on the variant an individual was exposed to, with implications for variant risk assessment and vaccine strain selection.

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The rapid spread of the Omicron SARS-CoV-2 variant (B.1.1.529) resulted in international efforts to quickly assess its escape from immunity generated by vaccines and previous infections. Numerous laboratories published Omicron neutralization data as preprints and reports. The understandable limitations and variability in such rapid reporting of early results however made it difficult to make definitive statements about the data. Here, we aggregate and analyze Omicron neutralization data from 23 reporting laboratories up to 2021-12-22. There are enough data to identify multiple trends and make two definitive points. First, in twice-vaccinated individuals, titer fold drop of Omicron relative to wild type is more than 19x, likely substantially more given the number of measurements below the limit of detection of the assay. Second, out to one month post third vaccination with an mRNA vaccine, or twice vaccinated after an earlier infection, the titer fold drop to Omicron is substantially less at approximately 7x. This substantially lower fold drop and somewhat higher titers after 3rd vaccination are strong early evidence for the utility of booster vaccination.

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.

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 9.6µs. 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.