Breathing and Tilting: Mesoscale Simulations Illuminate Influenza Glycoprotein Vulnerabilities

Casalino, Lorenzo; Seitz, Christian; Lederhofer, Julia; Tsybovsky, Yaroslav; Wilson, Ian A.; Kanekiyo, Masaru; Amaro, Rommie E.

doi:10.1021/acscentsci.2c00981

Cited by 39 publications

(48 citation statements)

References 143 publications

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“…Finally, all-atom studies reported good accord with hydrogen–deuterium mass spectroscopy, SAXS, and magic angle spinning solid-state NMR ,, data. In addition, the recent demonstration of antigenic sites on the influenza A surface glycoproteins is in accord with structural studies for that system, illustrating the predictive power of these simulations. Moreover, for coarse-grained models, validation has been performed by comparing the outcomes to all-atom simulations. , Overall, such comparisons generate confidence in simulation results for each model’s spatial and temporal regimes.…”

Section: Discussionsupporting

confidence: 54%

“…Among the largest systems studied to date with all-atom MD is the viral envelope of influenza A by Amaro and co-workers, , which included the glycoproteins hemagglutinin (HA) and neuraminidase (NA), the proton channel M2, and a phospholipid bilayer. NA cleaves sialic acid residues from host-cell receptors, thereby assisting in viral particle release.…”

Section: All-atom Molecular Dynamicsmentioning

confidence: 99%

“…In 2006, Freddolino et al 45 carried out one of the first simulations of a fully hydrated, all-atom, full virus particle for 95 4 0.01 2011 STNV 96 1.2 4 2012 Poliovirus 97 3−4 0.02 2012 HIV-1 32 64 0.2 2013 Poliovirus 98 6.5 0.2 2014 HBV 8 6 0.2 2016 PCV2 99, 100 1.9 0.05,0.02 2017 HIV-1 101 64 1.2 2017 HBV 46 6 1.1 2018 MS2 102 3.5 0.05 2019 Zika/dengue 103 12 0.12 2020 b Influenza A 104 160 0.12 2020 HBV 105 6 1 2021 HBV 106 6.5 0.6 2021 HBV 107 8 0.2 2021 SARS-CoV-2 108 305 0.2 2021 HIV-1 109 76 0.01 2021 RSV 33 1.8 0.02 2021 MVM 110 3 2.0 2022 Influenza A 111 160 0.9 2022 HIV-1 18 44−76 STMV (∼1M atoms, ∼40 ns). STMV is small (∼17 nm diameter), and the simulations, with and without a model for the viral genome, illustrated that without the incorporation of the RNA, severe instability of the capsid resulted.…”

Section: ■ All-atom Molecular Dynamicsmentioning

confidence: 99%

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Understanding Virus Structure and Dynamics through Molecular Simulations

Lynch

Pavlova

Fan

et al. 2023

J. Chem. Theory Comput.

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Viral outbreaks remain a serious threat to human and animal populations and motivate the continued development of antiviral drugs and vaccines, which in turn benefits from a detailed understanding of both viral structure and dynamics. While great strides have been made in characterizing these systems experimentally, molecular simulations have proven to be an essential, complementary approach. In this work, we review the contributions of molecular simulations to the understanding of viral structure, functional dynamics, and processes related to the viral life cycle. Approaches ranging from coarse-grained to all-atom representations are discussed, including current efforts at modeling complete viral systems. Overall, this review demonstrates that computational virology plays an essential role in understanding these systems.

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Section: Discussionsupporting

confidence: 54%

Section: All-atom Molecular Dynamicsmentioning

confidence: 99%

Section: ■ All-atom Molecular Dynamicsmentioning

confidence: 99%

See 1 more Smart Citation

Understanding Virus Structure and Dynamics through Molecular Simulations

Lynch

Pavlova

Fan

et al. 2023

J. Chem. Theory Comput.

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“…207 The Amaro group recently reported impressive mesoscale, all-atom MD simulations of two evolutionary-linked glycosylated influenza A virions. 208 The simulations reveal the main molecular motions of the principal surface antigenic targets of the influenza virus, hemagglutinin (HA), and neuraminidase (NA). Indeed, NA head tilting, HA ectodomain tilting, and HA head breathing are characterized at full atomistic resolution.…”

Section: Discussionmentioning

confidence: 99%

Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens

Guarra,

Colombo

2023

J. Chem. Theory Comput.

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The design of new biomolecules able to harness immune mechanisms for the treatment of diseases is a prime challenge for computational and simulative approaches. For instance, in recent years, antibodies have emerged as an important class of therapeutics against a spectrum of pathologies. In cancer, immune-inspired approaches are witnessing a surge thanks to a better understanding of tumor-associated antigens and the mechanisms of their engagement or evasion from the human immune system. Here, we provide a summary of the main state-of-the-art computational approaches that are used to design antibodies and antigens, and in parallel, we review key methodologies for epitope identification for both B- and T-cell mediated responses. A special focus is devoted to the description of structure- and physics-based models, privileged over purely sequence-based approaches. We discuss the implications of novel methods in engineering biomolecules with tailored immunological properties for possible therapeutic uses. Finally, we highlight the extraordinary challenges and opportunities presented by the possible integration of structure- and physics-based methods with emerging Artificial Intelligence technologies for the prediction and design of novel antigens, epitopes, and antibodies.

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“…Recent advances in molecular dynamics (MD) simulation methodologies (in particular, where they leverage machine learning algorithms for enhanced/efficient sampling) as well as access to ever increasing amounts of computational resources have meant that molecular simulation of entire viral particles has become tractable. In a recent issue of ACS Central Science , Amaro and co-workers characterize the dynamics of the two surface glycoproteins of influenza A using atomistic simulations of virion envelope models …”

mentioning

confidence: 99%