Improved AlphaFold modeling with implicit experimental information.

Machine-learning prediction algorithms such as AlphaFold and RoseTTAFold can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy. We hypothesized that by implicitly including new experimental information such as a density map, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt on the basis of experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We show that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for interpretation of crystallographic and electron cryo-microscopy maps.

Structural basis of SARS-CoV-2 Omicron immune evasion and receptor engagement.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant of concern evades antibody-mediated immunity that comes from vaccination or infection with earlier variants due to accumulation of numerous spike mutations. To understand the Omicron antigenic shift, we determined cryo-electron microscopy and x-ray crystal structures of the spike protein and the receptor-binding domain bound to the broadly neutralizing sarbecovirus monoclonal antibody (mAb) S309 (the parent mAb of sotrovimab) and to the human ACE2 receptor. We provide a blueprint for understanding the marked reduction of binding of other therapeutic mAbs that leads to dampened neutralizing activity. Remodeling of interactions between the Omicron receptor-binding domain and human ACE2 likely explains the enhanced affinity for the host receptor relative to the ancestral virus.

SARS-CoV-2 RBD antibodies that maximize breadth and resistance to escape.

An ideal therapeutic anti-SARS-CoV-2 antibody would resist viral escape1-3, have activity against diverse sarbecoviruses4-7, and be highly protective through viral neutralization8-11 and effector functions12,13. Understanding how these properties relate to each other and vary across epitopes would aid the development of therapeutic antibodies and guide vaccine design. Here we comprehensively characterize escape, breadth and potency across a panel of SARS-CoV-2 antibodies targeting the receptor-binding domain (RBD). Despite a trade-off between in vitro neutralization potency and breadth of sarbecovirus binding, we identify neutralizing antibodies with exceptional sarbecovirus breadth and a corresponding resistance to SARS-CoV-2 escape. One of these antibodies, S2H97, binds with high affinity across all sarbecovirus clades to a cryptic epitope and prophylactically protects hamsters from viral challenge. Antibodies that target the angiotensin-converting enzyme 2 (ACE2) receptor-binding motif (RBM) typically have poor breadth and are readily escaped by mutations despite high neutralization potency. Nevertheless, we also characterize a potent RBM antibody (S2E128) with breadth across sarbecoviruses related to SARS-CoV-2 and a high barrier to viral escape. These data highlight principles underlying variation in escape, breadth and potency among antibodies that target the RBD, and identify epitopes and features to prioritize for therapeutic development against the current and potential future pandemics.

Structure, Dynamics, Receptor Binding, and Antibody Binding of the Fully Glycosylated Full-Length SARS-CoV-2 Spike Protein in a Viral Membrane.

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mediates host cell entry by binding to angiotensin-converting enzyme 2 (ACE2) and is considered the major target for drug and vaccine development. We previously built fully glycosylated full-length SARS-CoV-2 S protein models in a viral membrane including both open and closed conformations of the receptor-binding domain (RBD) and different templates for the stalk region. In this work, multiple µs-long all-atom molecular dynamics simulations were performed to provide deeper insights into the structure and dynamics of S protein and glycan functions. Our simulations reveal that the highly flexible stalk is composed of two independent joints and most probable S protein orientations are competent for ACE2 binding. We identify multiple glycans stabilizing the open and/or closed states of the RBD and demonstrate that the exposure of antibody epitopes can be captured by detailed antibody-glycan clash analysis instead of commonly used accessible surface area analysis that tends to overestimate the impact of glycan shielding and neglect possible detailed interactions between glycan and antibodies. Overall, our observations offer structural and dynamic insights into the SARS-CoV-2 S protein and potentialize for guiding the design of effective antiviral therapeutics.

Circulating SARS-CoV-2 spike N439K variants maintain fitness while evading antibody-mediated immunity.

SARS-CoV-2 can mutate and evade immunity, with consequences for efficacy of emerging vaccines and antibody therapeutics. Here, we demonstrate that the immunodominant SARS-CoV-2 spike (S) receptor binding motif (RBM) is a highly variable region of S and provide epidemiological, clinical, and molecular characterization of a prevalent, sentinel RBM mutation, N439K. We demonstrate N439K S protein has enhanced binding affinity to the hACE2 receptor, and N439K viruses have similar in vitro replication fitness and cause infections with similar clinical outcomes as compared to wild type. We show the N439K mutation confers resistance against several neutralizing monoclonal antibodies, including one authorized for emergency use by the US Food and Drug Administration (FDA), and reduces the activity of some polyclonal sera from persons recovered from infection. Immune evasion mutations that maintain virulence and fitness such as N439K can emerge within SARS-CoV-2 S, highlighting the need for ongoing molecular surveillance to guide development and usage of vaccines and therapeutics.

Improving SARS-CoV-2 structures: Peer review by early coordinate release.

This work builds upon the record-breaking speed and generous immediate release of new experimental three-dimensional structures of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins and complexes, which are crucial to downstream vaccine and drug development. We have surveyed those structures to catch the occasional errors that could be significant for those important uses and for which we were able to provide demonstrably higher-accuracy corrections. This process relied on new validation and correction methods such as CaBLAM and ISOLDE, which are not yet in routine use. We found such important and correctable problems in seven early SARS-CoV-2 structures. Two of the structures were soon superseded by new higher-resolution data, confirming our proposed changes. For the other five, we emailed the depositors a documented and illustrated report and encouraged them to make the model corrections themselves and use the new option at the worldwide Protein Data Bank for depositors to re-version their coordinates without changing the Protein Data Bank code. This quickly and easily makes the better-accuracy coordinates available to anyone who examines or downloads their structure, even before formal publication. The changes have involved sequence misalignments, incorrect RNA conformations near a bound inhibitor, incorrect metal ligands, and cis-trans or peptide flips that prevent good contact at interaction sites. These improvements have propagated into nearly all related structures done afterward. This process constitutes a new form of highly rigorous peer review, which is actually faster and more strict than standard publication review because it has access to coordinates and maps; journal peer review would also be strengthened by such access.

Developing a Fully Glycosylated Full-Length SARS-CoV-2 Spike Protein Model in a Viral Membrane.

This technical study describes all-atom modeling and simulation of a fully glycosylated full-length SARS-CoV-2 spike (S) protein in a viral membrane. First, starting from PDB: 6VSB and 6VXX, full-length S protein structures were modeled using template-based modeling, de-novo protein structure prediction, and loop modeling techniques in GALAXY modeling suite. Then, using the recently determined most occupied glycoforms, 22 N-glycans and 1 O-glycan of each monomer were modeled using Glycan Reader & Modeler in CHARMM-GUI. These fully glycosylated full-length S protein model structures were assessed and further refined against the low-resolution data in their respective experimental maps using ISOLDE. We then used CHARMM-GUI Membrane Builder to place the S proteins in a viral membrane and performed all-atom molecular dynamics simulations. All structures are available in CHARMM-GUI COVID-19 Archive (http://www.charmm-gui.org/docs/archive/covid19) so that researchers can use these models to carry out innovative and novel modeling and simulation research for the prevention and treatment of COVID-19.