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AI-driven prediction of SARS-CoV-2 variant binding trends from atomistic simulations
Open accessPreprint — published as 10.1140/epje/s10189-021-00119-5 · Paper page
Abstract
We present a novel technique to predict binding affinity trends between two molecules from atomistic molecular dynamics simulations. The technique uses a neural network algorithm applied to a series of images encoding the distance between two molecules in time. We demonstrate that our algorithm is capable of separating with high accuracy non-hydrophobic mutations with low binding affinity from those with high binding affinity. Moreover, we show high accuracy in prediction using a small subset of the simulation, therefore requiring a much shorter simulation time. We apply our algorithm to the binding between several variants of the SARS-CoV-2 spike protein and the human receptor ACE2.
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Markov state models of biomolecular conformational dynamics
Chodera, J. D., & Noé, F. (2014) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2014.04.002 · Cited by 776
Flagged first, then by citations
Research works printed but not linked: 67
- H. J. Maier , E. Bickerton , and P. Britton , Coronaviruses: Methods and Protocols, 1–282 (2015).https://doi.org/10.1007/978-1-4939-2438-7 · DOI
- 2016, Annu. Rev. Virol, 3, 237, 10.1146/annurev-virology-110615-042301 · DOI · Paper page
- 10.3390/v4061011 · DOI · Paper page
- 2005, Virology, 335, 176
- 10.1073/pnas.1708727114 · DOI
- 10.1128/JVI.77.16.8801-8811.2003 · DOI · Paper page
- 2019, Advances in Virus Research, 105, 94
- 10.1126/science.abb2507 · DOI · Paper page
- 10.1016/j.cell.2020.02.035 · DOI
- 2020, Nature, 581, 215, 10.1038/s41586-020-2180-5 · DOI · Paper page
- 10.1038/s41586-020-2179-y · DOI · Paper page
- 10.1016/j.cell.2020.05.034 · DOI
- 10.1126/science.abb2762 · DOI
- 10.1038/s41586-020-2012-7 · DOI · Paper page
- 2020, Cell, 182, 1295, 10.1016/j.cell.2020.08.012 · DOI · Paper page
- 2021, Cell Host and Microbe, 29, 44, 10.1016/j.chom.2020.11.007 · DOI · Paper page
- 2020, Pharmacology and Translational Science, 3, 1023, 10.1021/acsptsci.0c00113 · DOI
- 2020, ACS Central Science, 6, 1654, 10.1021/acscentsci.0c01236 · DOI
- C. Peng , et al, ChemrXiv (2020).https://doi.org/10.26434/chemrxiv.11877492.v1 · DOI
- 2020, Journal of Computer-Aided Molecular Design, 35, 195
- 2021, J. Phys. Chem. Lett, 21, 5494
- 10.1073/pnas.2008209117 · DOI
- 10.1021/acs.jmedchem.1c00311 · DOI
- 2020, Sci. R, 10, 14214
- 2021, Biophys. J, 120, 1072, 10.1016/j.bpj.2020.10.036 · DOI
- 2020, J. Phys. Chem. B, 140, 10034
- 2020, J. Chem. Inf. Model, 60, 5794, 10.1021/acs.jcim.0c00679 · DOI
- J. M. Delgado and N. Duro and D. M. Rogers and A. Tkatchenko and S. A. Pandit and S. Varma , Proteins, 1–11, (2021)https://doi.org/10.1002/prot.260865794-5802 · DOI
- 2020, J. Phys. Chem. B, 124, 7336, 10.1021/acs.jpcb.0c04511 · DOI
- 10.1038/nchem.2785 · DOI
- G. R. Bowman , V. S. Pande , F. Noé . Dordrecht: Springer Science and Business Media. 148(2014).
- 10.1063/1.1472510 · DOI
- 10.1016/S0006-3495(96)79552-8 · DOI
- 2017, Annu Rev Biophys, 46, 43, 10.1146/annurev-biophys-070816-033834 · DOI
- 2011, J. Comput. Chem, 13, 2810
- 2009, Biophys J, 7, 2004
- C. Chipot and A. Pohorille , Free Energy Calculations, Springer (2007). · DOI
- 2020, J. Phys. Chem. Lett, 11, 9656, 10.1021/acs.jpclett.0c03130 · DOI
- 2020, Lecture Notes in Physics, 968, 331, 10.1007/978-3-030-40245-7_16 · DOI
- L. Casalino , et al, BioRxiv (2020).https://doi.org/10.1101/2020.11.19.390187 · DOI
- 2019, Massive computational acceleration by using neural networks to emulate mechanismbased biological models, Nature Communications, 10, 19
- 2020, Predictive biology: modelling, understanding and harnessing microbial complexity, Nature Reviews Microbiology, 18, 507, 10.1038/s41579-020-0372-5 · DOI
- 2020, J. Phys. Chem. b, 124, 9103, 10.1021/acs.jpcb.0c05977 · DOI
- 2020, Journal of Chemical Information and Modeling, 60, 2766, 10.1021/acs.jcim.0c00026 · DOI
- 10.1016/j.bpj.2019.12.016 · DOI · Paper page
- 2019, Bioinformatics, 35, i269, 10.1093/bioinformatics/btz339 · DOI
- 10.1038/s41586-020-2179-y · DOI · Paper page
- 2016, J. Chem. Thory Comput, 12, 405, 10.1021/acs.jctc.5b00935 · DOI
- 2008, J. Chem. Thory Comput, 29, 1859, 10.1002/jcc.20945 · DOI · Paper page
- 10.1016/0263-7855(96)00018-5 · DOI · Paper page
- 10.1002/jcc.20289 · DOI · Paper page
- 2005, J. Chem. Phys, 153, 044130
- 10.1038/nmeth.4067 · DOI
- 10.1063/1.445869 · DOI
- 1993, J. Chem. Phys, 103, 4613
- 10.1063/1.467468 · DOI
- 10.1063/1.464397 · DOI
- 10.1063/1.470117 · DOI
- 10.1080/08927029108022142 · DOI
- 10.1016/0021-9991(77)90098-5 · DOI
- R. J. Gowers , et al. In S. Benthall and S. Rostrup , editors,Proceedings of the 15th Python in Science Conference, 98–105 (2016).
- 10.1002/jcc.21787 · DOI
- 2021, Collective colony growth is optimized by branching pattern formation in Pseudomonas aeruginosa, Molecular Systems Biology, 17, e10089, 10.15252/msb.202010089 · DOI
- G. Schreiber and G. Haran and H.-X. Zhou , Chem. Rev., 109, (2008). · DOI
- 10.1073/pnas.2133366100 · DOI
- 2019, Biochemistry, 58, 156, 10.1021/acs.biochem.8b00977 · DOI
- 2020, Nature Machine Intelligence, 2, 116, 10.1038/s42256-020-0149-6 · DOI · Paper page
Metadata
- Authors
- Capponi, S., Wang, S., Navarro, E. J., & Bianco, S.
- Affiliations
- University of California, San Francisco (US)
- Corresponding author
- Bianco, Simone
- Venue
- The European Physical Journal E
- Publisher
- openRxiv
- Published
- 2021-03-08
- Volume
- 44
- Issue
- 10
- Pages
- 123-123
- ISSN
- 1292-8941 (ISSN-L)
- PMC
- PMC8493367
- OpenAlex
- W3202379675
- Cited by
- 12
- References
- 1
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 3 · 2023: 1 · 2022: 3 · 2021: 1
- FWCI
- 0.63
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- The European Physical Journal E (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Springer Link (Chiba Institute of Technology) (submittedVersion)
- Funders
- National Science Foundation (1548297)
- Rensselaer Polytechnic Institute
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Keywords
- SARS-CoV-2 variants, spike protein, ACE2 receptor, protein-protein binding affinity, binding affinity prediction, artificial neural networks, molecular dynamics simulation, atomistic simulation
- MeSH terms
- Angiotensin-Converting Enzyme 2, SARS-CoV-2, Algorithms, Artificial Intelligence, Humans, Models, Molecular, Mutation, Protein Binding, Protein Conformation, Neural Networks, Computer, Molecular Dynamics Simulation, Spike Glycoprotein, Coronavirus
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