diff --git a/joss.06129/10.21105.joss.06129.crossref.xml b/joss.06129/10.21105.joss.06129.crossref.xml new file mode 100644 index 0000000000..ea21be0836 --- /dev/null +++ b/joss.06129/10.21105.joss.06129.crossref.xml @@ -0,0 +1,326 @@ + + + + 20240717081112-408074357331fb39ed9fca0bf14b1a0226239117 + 20240717081112 + + JOSS Admin + admin@theoj.org + + The Open Journal + + + + + Journal of Open Source Software + JOSS + 2475-9066 + + 10.21105/joss + https://joss.theoj.org + + + + + 07 + 2024 + + + 9 + + 99 + + + + dms-viz: Structure-informed visualizations for deep +mutational scanning and other mutation-based datasets + + + + William W. + Hannon + https://orcid.org/0000-0002-6014-4749 + + + Jesse D. + Bloom + https://orcid.org/0000-0003-1267-3408 + + + + 07 + 17 + 2024 + + + 6129 + + + 10.21105/joss.06129 + + + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + + + + Software archive + 10.5281/zenodo.12693853 + + + GitHub review issue + https://github.com/openjournals/joss-reviews/issues/6129 + + + + 10.21105/joss.06129 + https://joss.theoj.org/papers/10.21105/joss.06129 + + + https://joss.theoj.org/papers/10.21105/joss.06129.pdf + + + + + + Fitness effects of mutations to SARS-CoV-2 +proteins + Bloom + Virus Evolution + 2 + 9 + 10.1093/ve/vead055 + 2057-1577 + 2023 + Bloom, J. D., & Neher, R. A. +(2023). Fitness effects of mutations to SARS-CoV-2 proteins. Virus +Evolution, 9(2), vead055. +https://doi.org/10.1093/ve/vead055 + + + Open Science Discovery of Potent Non-Covalent +SARS-CoV-2 Main Protease Inhibitors + Boby + 10.1101/2020.10.29.339317 + 2023 + Boby, M. L., Fearon, D., Ferla, M., +Filep, M., Koekemoer, L., Robinson, M. C., The COVID Moonshot +Consortium, Chodera, J. D., Lee, A. A., London, N., von Delft, A., & +von Delft, F. (2023). Open Science Discovery of Potent Non-Covalent +SARS-CoV-2 Main Protease Inhibitors (p. 2020.10.29.339317). bioRxiv. +https://doi.org/10.1101/2020.10.29.339317 + + + A pseudovirus system enables deep mutational +scanning of the full SARS-CoV-2 spike + Dadonaite + Cell + 6 + 186 + 10.1016/j.cell.2023.02.001 + 1097-4172 + 2023 + Dadonaite, B., Crawford, K. H. D., +Radford, C. E., Farrell, A. G., Yu, T. C., Hannon, W. W., Zhou, P., +Andrabi, R., Burton, D. R., Liu, L., Ho, D. D., Chu, H. Y., Neher, R. +A., & Bloom, J. D. (2023). A pseudovirus system enables deep +mutational scanning of the full SARS-CoV-2 spike. Cell, 186(6), +1263–1278.e20. +https://doi.org/10.1016/j.cell.2023.02.001 + + + MaveDB: An open-source platform to distribute +and interpret data from multiplexed assays of variant +effect + Esposito + Genome Biology + 1 + 20 + 10.1186/s13059-019-1845-6 + 1474-760X + 2019 + Esposito, D., Weile, J., Shendure, +J., Starita, L. M., Papenfuss, A. T., Roth, F. P., Fowler, D. M., & +Rubin, A. F. (2019). MaveDB: An open-source platform to distribute and +interpret data from multiplexed assays of variant effect. Genome +Biology, 20(1), 223. +https://doi.org/10.1186/s13059-019-1845-6 + + + An Atlas of Variant Effects to understand the +genome at nucleotide resolution + Fowler + Genome Biology + 1 + 24 + 10.1186/s13059-023-02986-x + 1474-760X + 2023 + Fowler, D. M., Adams, D. J., Gloyn, +A. L., Hahn, W. C., Marks, D. S., Muffley, L. A., Neal, J. T., Roth, F. +P., Rubin, A. F., Starita, L. M., & Hurles, M. E. (2023). An Atlas +of Variant Effects to understand the genome at nucleotide resolution. +Genome Biology, 24(1), 147. +https://doi.org/10.1186/s13059-023-02986-x + + + Deep mutational scanning: A new style of +protein science + Fowler + Nature Methods + 8 + 11 + 10.1038/nmeth.3027 + 1548-7105 + 2014 + Fowler, D. M., & Fields, S. +(2014). Deep mutational scanning: A new style of protein science. Nature +Methods, 11(8), 801–807. +https://doi.org/10.1038/nmeth.3027 + + + Dms-view: Interactive visualization tool for +deep mutational scanning data + Hilton + Journal of Open Source +Software + 52 + 5 + 10.21105/joss.02353 + 2475-9066 + 2020 + Hilton, S. K., Huddleston, J., Black, +A., North, K., Dingens, A. S., Bedford, T., & Bloom, J. D. (2020). +Dms-view: Interactive visualization tool for deep mutational scanning +data. Journal of Open Source Software, 5(52), 2353. +https://doi.org/10.21105/joss.02353 + + + Deep mutational scanning reveals the +functional constraints and evolutionary potential of the influenza A +virus PB1 protein + Li + 10.1101/2023.08.27.554986 + 2023 + Li, Y., Arcos, S., Sabsay, K. R., te +Velthuis, A. J. W., & Lauring, A. S. (2023). Deep mutational +scanning reveals the functional constraints and evolutionary potential +of the influenza A virus PB1 protein (p. 2023.08.27.554986). bioRxiv. +https://doi.org/10.1101/2023.08.27.554986 + + + Multiplex assessment of protein variant +abundance by massively parallel sequencing + Matreyek + Nature Genetics + 6 + 50 + 10.1038/s41588-018-0122-z + 1546-1718 + 2018 + Matreyek, K. A., Starita, L. M., +Stephany, J. J., Martin, B., Chiasson, M. A., Gray, V. E., Kircher, M., +Khechaduri, A., Dines, J. N., Hause, R. J., Bhatia, S., Evans, W. E., +Relling, M. V., Yang, W., Shendure, J., & Fowler, D. M. (2018). +Multiplex assessment of protein variant abundance by massively parallel +sequencing. Nature Genetics, 50(6), 874–882. +https://doi.org/10.1038/s41588-018-0122-z + + + Mapping the neutralizing specificity of human +anti-HIV serum by deep mutational scanning + Radford + Cell Host & Microbe + 7 + 31 + 10.1016/j.chom.2023.05.025 + 1934-6069 + 2023 + Radford, C. E., Schommers, P., +Gieselmann, L., Crawford, K. H. D., Dadonaite, B., Yu, T. C., Dingens, +A. S., Overbaugh, J., Klein, F., & Bloom, J. D. (2023). Mapping the +neutralizing specificity of human anti-HIV serum by deep mutational +scanning. Cell Host & Microbe, 31(7), 1200–1215.e9. +https://doi.org/10.1016/j.chom.2023.05.025 + + + NGL viewer: Web-based molecular graphics for +large complexes + Rose + Bioinformatics (Oxford, +England) + 21 + 34 + 10.1093/bioinformatics/bty419 + 1367-4811 + 2018 + Rose, A. S., Bradley, A. R., +Valasatava, Y., Duarte, J. M., Prlic, A., & Rose, P. W. (2018). NGL +viewer: Web-based molecular graphics for large complexes. Bioinformatics +(Oxford, England), 34(21), 3755–3758. +https://doi.org/10.1093/bioinformatics/bty419 + + + Deep Mutational Scanning of SARS-CoV-2 +Receptor Binding Domain Reveals Constraints on Folding and ACE2 +Binding + Starr + Cell + 5 + 182 + 10.1016/j.cell.2020.08.012 + 1097-4172 + 2020 + Starr, T. N., Greaney, A. J., Hilton, +S. K., Ellis, D., Crawford, K. H. D., Dingens, A. S., Navarro, M. J., +Bowen, J. E., Tortorici, M. A., Walls, A. C., King, N. P., Veesler, D., +& Bloom, J. D. (2020). Deep Mutational Scanning of SARS-CoV-2 +Receptor Binding Domain Reveals Constraints on Folding and ACE2 Binding. +Cell, 182(5), 1295–1310.e20. +https://doi.org/10.1016/j.cell.2020.08.012 + + + Prospective mapping of viral mutations that +escape antibodies used to treat COVID-19 + Starr + Science (New York, N.Y.) + 6531 + 371 + 10.1126/science.abf9302 + 1095-9203 + 2021 + Starr, T. N., Greaney, A. J., +Addetia, A., Hannon, W. W., Choudhary, M. C., Dingens, A. S., Li, J. Z., +& Bloom, J. D. (2021). Prospective mapping of viral mutations that +escape antibodies used to treat COVID-19. Science (New York, N.Y.), +371(6531), 850–854. +https://doi.org/10.1126/science.abf9302 + + + A biophysical model of viral escape from +polyclonal antibodies + Yu + Virus Evolution + 2 + 8 + 10.1093/ve/veac110 + 2057-1577 + 2022 + Yu, T. C., Thornton, Z. T., Hannon, +W. W., DeWitt, W. S., Radford, C. E., Matsen, F. A., & Bloom, J. D. +(2022). A biophysical model of viral escape from polyclonal antibodies. +Virus Evolution, 8(2), veac110. +https://doi.org/10.1093/ve/veac110 + + + + + + diff --git a/joss.06129/10.21105.joss.06129.pdf b/joss.06129/10.21105.joss.06129.pdf new file mode 100644 index 0000000000..592a782372 Binary files /dev/null and b/joss.06129/10.21105.joss.06129.pdf differ diff --git a/joss.06129/paper.jats/10.21105.joss.06129.jats b/joss.06129/paper.jats/10.21105.joss.06129.jats new file mode 100644 index 0000000000..767b3a0648 --- /dev/null +++ b/joss.06129/paper.jats/10.21105.joss.06129.jats @@ -0,0 +1,749 @@ + + +
+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +6129 +10.21105/joss.06129 + +dms-viz: Structure-informed +visualizations for deep mutational scanning and other mutation-based +datasets + + + +https://orcid.org/0000-0002-6014-4749 + +Hannon +William W. + + + + + +https://orcid.org/0000-0003-1267-3408 + +Bloom +Jesse D. + + + + + + + +Molecular and Cellular Biology Graduate Program, University +of Washington, Seattle, Washington 98109, United States of +America + + + + +Basic Sciences and Computational Biology, Fred Hutchinson +Cancer Research Center, Seattle, Washington 98109, United States of +America + + + + +Department of Genome Sciences, University of Washington, +Seattle, Washington 98109, United States of America + + + + +Howard Hughes Medical Institute, Seattle, Washington 98109, +United States of America + + + + +26 +10 +2023 + +9 +99 +6129 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2022 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +javascript +data visualization +molecular biology +protein biology +deep mutational scanning + + + + + + Summary and Purpose +

Many biological questions require an understanding of how mutations + impact a protein’s functions. Deep mutational scanning (DMS) offers an + approach to characterize the impact of a huge number of mutations in + parallel + (Fowler + & Fields, 2014). The wide application of DMS has greatly + increased the number of mutation-function datasets + (Fowler + et al., 2023). For instance, DMS has been used to determine how + mutations to viral proteins affect antibody escape + (Dadonaite + et al., 2023), receptor affinity + (Starr + et al., 2020), and essential functions such as viral genome + transcription and replication + (Li + et al., 2023). In some cases, the effects of mutations can also + be inferred from phylogenies of natural sequences + (Bloom + & Neher, 2023) + ([fig:figure1]).

+ +

Large mutation-associated datasets can be used to map + antibody footprints, assess the impact of mutations on protein + function, and identify patterns of selection from natural mutation + frequencies.

+ + +

The mutation-based data generated by these approaches is better + understood in the context of a protein’s 3D structure. However, + current approaches for visualizing mutation data in the context of a + protein’s structure are often cumbersome and require multiple steps + and software. To streamline the visualization of mutation-associated + data in the context of a protein structure, we developed a web-based + tool, dms-viz. With + dms-viz, users can straightforwardly visualize + mutation-based data such as those from DMS experiments in the context + of a 3D protein model in an interactive format. Visit + https://dms-viz.github.io/ + to use dms-viz.

+ + + Statement of Need +

We wanted dms-viz to provide the following + functionalities:

+ + +

Provide structural context: + dms-viz simplifies the process of + visualizing mutation data with structural context by superimposing + mutation measurements on a 3D protein structure. Additionally, it + provides extensive control over the visual representation of the + 3D structure.

+ + +

Accommodate diverse data types: Although analyzing + DMS data is a key goal of dms-viz, there + are many types of mutation data. The tool can handle diverse data + types via a command line interface that converts data into a + common format.

+ + +

Display multiple conditions: With + dms-viz, multiple experimental conditions + can be visualized concurrently; for instance, researchers can + easily visualize multiple antibody binding footprints from + polyclonal sera + (Yu + et al., 2022).

+ + +

Maximize customization: Every dataset has specific + needs for visual representation. Recognizing this, + dms-viz offers customization with filters + (which are important for navigating large and possibly noisy + datasets), and tooltips, ensuring that nuances are + communicated.

+ + +

Create compact interactive visualizations: + dms-viz creates compact interactive views + that can be incorporated into HTML presentation slides (e.g., + https://slides.com/).

+ + +

Share findings with ease: Users of + dms-viz can generate shareable URL links to + their visualizations. They can also save and share their + JSON specification files, ensuring that + data can be accessed by others.

+ + +

Preserve data privacy: + dms-viz allows users to visualize + proprietary structures and analyze sensitive data in their browser + without uploading their datasets to a remote server or storing + them in a public repository.

+ + +

Our group previously created a tool called + dms-view + (Hilton + et al., 2020) that has some of the functionalities listed + above. However, we designed dms-viz to be more + customizable and comprehensive to handle a wider diversity of + experimental designs and questions.

+ + + Design and Usage +

Using dms-viz involves three components. + First, using the command line tool + configure-dms-viz, available as a Python + package on PyPI + (https://pypi.org/project/configure-dms-viz/), + the user formats their data into a JSON + specification file (see the + documentation + for details on the JSON schema). Then, the user + uploads this specification file to + dms-viz.github.io, a web-based interface + written in Javascript, D3.js, and + NGL.js + (Rose + et al., 2018). Finally, the specification file can either be + shared directly or hosted remotely to generate a shareable URL link + ([fig:figure2]).

+ +

(1) The user formats their data using the command line + tool configure-dms-viz. (2) The user takes + the resulting JSON specification file and + uploads it to dms-viz.github.io. (3) The user + shares their results with a JSON file, a URL + link, or a static + image.

+ + +

Upon uploading the specification file to + dms-viz, users will see a visualization + composed of four components, as illustrated in + [fig:figure3].

+ + +

Context plot: Located at the top + of the visualization, it allows users to zoom into specific sites + on the Focus plot while maintaining an overview + of the entire dataset.

+ + +

Focus plot: This plot shows a + summarized view of the user’s data. Every measured protein site is + represented as a point providing a summary statistic of the + effects of mutations at that site, and adjacent sites are + connected with lines.

+ + +

Detail heatmap: If the user is + interested in the measurements for every mutation at a site, they + can click on that site in the Focus plot. This + will populate a heatmap with each mutation measurement at that + site.

+ + +

Interactive structure: When the + user wants structural context for a given set of sites, they can + drag a brush over the corresponding points in the + Focus plot. This action will highlight those + sites on an interactive 3D protein model.

+ + +

To ensure the visualization remains compact, all configuration + options are tucked away in a collapsible sidebar. See the + documentation at + https://dms-viz.github.io/dms-viz-docs/ + for more information about how to use dms-viz + along with detailed tutorials and examples.

+ +

dms-viz provides a compact + interface for exploring mutation-associated data, in this case, + mutation-escape from the constituents of a therapeutic antibody + cocktail measured by DMS of the SARS-CoV-2 receptor binding domain + (RBD) + (Starr + et al., 2021). In this example, the structure shown is the + SARS-CoV-2 RBD bound to both antibodies in the therapeutic cocktail + (PDB: + 6XDG).

+ + + + + Examples +

For additional scientific background and a walkthrough of the code + that generates these visualizations, visit the + documentation.

+ + 1. Mapping the neutralization profile of antibodies and sera + against HIV envelope +

Radford et al. + (2023) + mapped mutations to HIV envelope (Env) that affect neutralization by + polyclonal human serum using a pseudotyping-based deep mutational + scanning platform + (Radford + et al., 2023). See how dms-viz can be + used to interactively visualize datasets with multiple antibody + footprints on a single summary plot + here.

+ + + 2. Using mutation-fitness data to augment structure-guided + drug design +

Bloom and Neher estimated the fitness effects of mutations to all + SARS-CoV-2 proteins by analyzing millions of human SARS-CoV-2 + sequences + (Bloom + & Neher, 2023). See how dms-viz + can be used to enhance structure-guided drug design by merging this + data with structural views of a viral target like the SARS-CoV-2 + main protease (Mpro) in complex with a bound ligand such as + MAT-POS-e194df51-1 from the COVID Moonshot project + (Boby + et al., 2023) + here.

+ + + 3. Visualizing the pathogenicity of genetic variants of an + important tumor suppressor +

Matreyek et al. + (2018) + used variant abundance by massively parallel sequencing (VAMP-seq) + to characterize the effect of thousands of mutations on the + intracellular abundance of PTEN, a tumor suppressor that is + inactivated in many cancers + (Matreyek + et al., 2018). See how dms-viz can be + used to identify clinically relevant mutations in human proteins + here.

+ + + + Conclusion +

dms-viz is a valuable addition to the suite + of computational tools available for analyzing, sharing, and + visualizing mutation-based datasets, which includes + MaveDB, + ProtVar, + and many others + (Esposito + et al., 2019). We designed dms-viz as a + practical and user-friendly approach to visualizing + mutation-associated data in the context of protein structures. Because + dms-viz is capable of handling various data + types and has options for both sharing and privacy, it should apply to + the visualization of a wide range of datasets.

+ + + Code Availability + + +

The visualization is available at + https://dms-viz.github.io/

+ + +

The documentation is available at + https://dms-viz.github.io/dms-viz-docs/

+ + +

The source code for dms-viz.github.io is + available at + https://github.com/dms-viz/dms-viz.github.io

+ + +

The source code for configure-dms-viz is + available at + https://github.com/dms-viz/configure_dms_viz

+ + + + + Acknowledgements +

This project was envisioned as the successor to + dms-view. Thank you to Dr. Sarah Hilton and + Dr. John Huddleston for laying this groundwork and for providing + helpful input. Thank you to the Bloom lab for providing data and + guidance. The research reported here was supported in part by NIAID of + the National Institutes of Health under award number U19AI171399. The + content is solely the responsibility of the authors and does not + necessarily represent the official views of the National Institutes of + Health. The work of JDB was supported in part by the NIH/NIAID under + grants R01AI141707 and contract 75N93021C00015. JDB is an Investigator + of the Howard Hughes Medical Institute.

+ + + Disclosures +

JDB is on the scientific advisory boards of Apriori Bio, Aerium + Therapeutics, Invivyd, and the Vaccine Company. JDB receives royalty + payments as an inventor on Fred Hutch licensed patents related to deep + mutational scanning of viral proteins.

+ + + + + + + + + BloomJesse D. + NeherRichard A. + + Fitness effects of mutations to SARS-CoV-2 proteins + Virus Evolution + 2023 + 9 + 2 + 2057-1577 + 10.1093/ve/vead055 + 37727875 + vead055 + + + + + + + BobyMelissa L. + FearonDaren + FerlaMatteo + FilepMihajlo + KoekemoerLizbé + RobinsonMatthew C. + The COVID Moonshot Consortium + ChoderaJohn D. + LeeAlpha A. + LondonNir + von DelftAnnette + von DelftFrank + + Open Science Discovery of Potent Non-Covalent SARS-CoV-2 Main Protease Inhibitors + bioRxiv + 202309 + 20231024 + 10.1101/2020.10.29.339317 + 2020.10.29.339317 + + + + + + + DadonaiteBernadeta + CrawfordKatharine H. D. + RadfordCaelan E. + FarrellAriana G. + YuTimothy C. + HannonWilliam W. + ZhouPanpan + AndrabiRaiees + BurtonDennis R. + LiuLihong + HoDavid D. + ChuHelen Y. + NeherRichard A. + BloomJesse D. + + A pseudovirus system enables deep mutational scanning of the full SARS-CoV-2 spike + Cell + 202303 + 186 + 6 + 1097-4172 + 10.1016/j.cell.2023.02.001 + 36868218 + 1263 + 1278.e20 + + + + + + EspositoDaniel + WeileJochen + ShendureJay + StaritaLea M. + PapenfussAnthony T. + RothFrederick P. + FowlerDouglas M. + RubinAlan F. + + MaveDB: An open-source platform to distribute and interpret data from multiplexed assays of variant effect + Genome Biology + 201911 + 20240515 + 20 + 1 + 1474-760X + 10.1186/s13059-019-1845-6 + 223 + + + + + + + FowlerDouglas M. + AdamsDavid J. + GloynAnna L. + HahnWilliam C. + MarksDebora S. + MuffleyLara A. + NealJames T. + RothFrederick P. + RubinAlan F. + StaritaLea M. + HurlesMatthew E. + + An Atlas of Variant Effects to understand the genome at nucleotide resolution + Genome Biology + 202307 + 24 + 1 + 1474-760X + 10.1186/s13059-023-02986-x + 37394429 + 147 + + + + + + + FowlerDouglas M. + FieldsStanley + + Deep mutational scanning: A new style of protein science + Nature Methods + 201408 + 11 + 8 + 1548-7105 + 10.1038/nmeth.3027 + 25075907 + 801 + 807 + + + + + + HiltonSarah K. + HuddlestonJohn + BlackAllison + NorthKhrystyna + DingensAdam S. + BedfordTrevor + BloomJesse D. + + Dms-view: Interactive visualization tool for deep mutational scanning data + Journal of Open Source Software + 2020 + 5 + 52 + 2475-9066 + 10.21105/joss.02353 + 34189395 + 2353 + + + + + + + LiYuan + ArcosSarah + SabsayKimberly R. + te VelthuisAartjan J. W. + LauringAdam S. + + Deep mutational scanning reveals the functional constraints and evolutionary potential of the influenza A virus PB1 protein + bioRxiv + 202308 + 20231014 + 10.1101/2023.08.27.554986 + 2023.08.27.554986 + + + + + + + MatreyekKenneth A. + StaritaLea M. + StephanyJason J. + MartinBeth + ChiassonMelissa A. + GrayVanessa E. + KircherMartin + KhechaduriArineh + DinesJennifer N. + HauseRonald J. + BhatiaSmita + EvansWilliam E. + RellingMary V. + YangWenjian + ShendureJay + FowlerDouglas M. + + Multiplex assessment of protein variant abundance by massively parallel sequencing + Nature Genetics + Nature Publishing Group + 201806 + 20240515 + 50 + 6 + 1546-1718 + 10.1038/s41588-018-0122-z + 874 + 882 + + + + + + RadfordCaelan E. + SchommersPhilipp + GieselmannLutz + CrawfordKatharine H. D. + DadonaiteBernadeta + YuTimothy C. + DingensAdam S. + OverbaughJulie + KleinFlorian + BloomJesse D. + + Mapping the neutralizing specificity of human anti-HIV serum by deep mutational scanning + Cell Host & Microbe + 202307 + 31 + 7 + 1934-6069 + 10.1016/j.chom.2023.05.025 + 37327779 + 1200 + 1215.e9 + + + + + + RoseAlexander S. + BradleyAnthony R. + ValasatavaYana + DuarteJose M. + PrlicAndreas + RosePeter W. + + NGL viewer: Web-based molecular graphics for large complexes + Bioinformatics (Oxford, England) + 201811 + 34 + 21 + 1367-4811 + 10.1093/bioinformatics/bty419 + 29850778 + 3755 + 3758 + + + + + + StarrTyler N. + GreaneyAllison J. + HiltonSarah K. + EllisDaniel + CrawfordKatharine H. D. + DingensAdam S. + NavarroMary Jane + BowenJohn E. + TortoriciM. Alejandra + WallsAlexandra C. + KingNeil P. + VeeslerDavid + BloomJesse D. + + Deep Mutational Scanning of SARS-CoV-2 Receptor Binding Domain Reveals Constraints on Folding and ACE2 Binding + Cell + 202009 + 182 + 5 + 1097-4172 + 10.1016/j.cell.2020.08.012 + 32841599 + 1295 + 1310.e20 + + + + + + StarrTyler N. + GreaneyAllison J. + AddetiaAmin + HannonWilliam W. + ChoudharyManish C. + DingensAdam S. + LiJonathan Z. + BloomJesse D. + + Prospective mapping of viral mutations that escape antibodies used to treat COVID-19 + Science (New York, N.Y.) + 202102 + 371 + 6531 + 1095-9203 + 10.1126/science.abf9302 + 33495308 + 850 + 854 + + + + + + YuTimothy C. + ThorntonZorian T. + HannonWilliam W. + DeWittWilliam S. + RadfordCaelan E. + MatsenFrederick A. + BloomJesse D. + + A biophysical model of viral escape from polyclonal antibodies + Virus Evolution + 2022 + 8 + 2 + 2057-1577 + 10.1093/ve/veac110 + 36582502 + veac110 + + + + + +
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