Vant, J. W. | bioRxiv Science

bioRxiv2021

The Structure of ChAdOx1/AZD-1222 Reveals Interactions with CAR and PF4 with Implications for Vaccine-induced Immune Thrombotic Thrombocytopenia

Adenovirus derived vectors, based on chimpanzee adenovirus Y25 (ChAdOx1) and human adenovirus type 26 are proving critical in combatting the 2019 SARS-CoV-2 pandemic. Following emergency use authorisation, scale up in vaccine administration has inevitably revealed vaccine related adverse effects; too rare to observe even in large Phase-III clinical trials. These include vaccine-induced thrombotic thrombocytopenia (VITT), an ultra-rare adverse event in which patients develop life-threatening blood clots 5-24 days following vaccination. To investigate vector-host interactions of ChAdOx1 underpinning VITT we solved the structure of the ChAdOx1 capsid by CryoEM, and the structure of the primary receptor tropism determining fiber-knob protein by crystallography. These structural insights have enabled us to unravel key protein interactions involved in ChAdOx1 cell entry and a possible means by which it may generate misplaced immunity to platelet factor 4 (PF4), a protein involved in coagulation. We use in vitro cell binding assays to show that the fiber-knob protein uses coxsackie and adenovirus receptor (CAR) as a high affinity binding partner, while it does not form a stable interface with CD46. Computational simulations identified a putative mechanism by which the ChAdOx1 capsid interacts with PF4 by binding in the spaces between hexon proteins, with downstream implications for the causes of VITT. SummaryWe present the structure of the ChAdOx1 viral vector, derived from chimpanzee adenovirus Y25 at 4.2[A] resolution1. ChAdOx1 is in global use in the AstraZeneca vaccine, ChAdOx1 nCoV-19/AZD-1222, to combat the SARS-CoV-2 coronavirus pandemic. Recently observed, rare, adverse events make detailed mechanistic understanding of this vector key to informing proper treatment of affected patients and the development of safer viral vectors. Here, we determine a primary mechanism ChAdOx1 uses to attach to cells is coxsackie and adenovirus receptor (CAR), a protein which is identical in humans and chimpanzees. We demonstrate the vector does not form a stable CD46 interaction, a common species B adenovirus receptor, via its primary attachment protein. Further, we reveal the surface of the ChAdOx1 viral capsid has a strong electronegative potential. Molecular simulations suggest this charge, together with shape complementarity, are a mechanism by which an oppositely charged protein, platelet factor 4 (PF4) may bind the vector surface. PF4 is a key protein involved in the formation of blood clots2, and the target of auto-antibodies in heparin-induced immune thrombotic thrombocytopenia (HITT)3, an adverse reaction to heparin therapy which presents similarly to vaccine-induced immune thrombotic thrombocytopenia (VITT), a rare complication of ChAdOx1 nCoV-19 vaccination4-6. We propose a mechanism in which the ChAdOx1-PF4 complex may stimulate the production of antibodies against PF4, leading to delayed blood clot formation, as observed in VITT.

molecular biology↗

bioRxiv2020

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. Here, the 3-dimensional electron density of a protein, as it would be determined by cryo-EM or X-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work uses the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along reaction coordinates derived from electron densities can serve to induce conformational transitions between known intermediates. The simulated pathways appear reversible, with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein DataBank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution (~5 [A]) density information coupled to comparatively large structural transitions. Practical considerations for generating transitions with multiple intermediate atomic density distributions are also discussed.

biophysics↗