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MVsim is a toolset for quantifying and designing multivalent interactions

Author

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  • Bence Bruncsics

    (Budapest University of Technology and Economics)

  • Wesley J. Errington

    (University of Minnesota)

  • Casim A. Sarkar

    (University of Minnesota)

Abstract

Arising through multiple binding elements, multivalency can specify the avidity, duration, cooperativity, and selectivity of biomolecular interactions, but quantitative prediction and design of these properties has remained challenging. Here we present MVsim, an application suite built around a configurational network model of multivalency to facilitate the quantification, design, and mechanistic evaluation of multivalent binding phenomena through a simple graphical user interface. To demonstrate the utility and versatility of MVsim, we first show that both monospecific and multispecific multivalent ligand-receptor interactions, with their noncanonical binding kinetics, can be accurately simulated. Further, to illustrate the conceptual insights into multivalent systems that MVsim can provide, we apply it to quantitatively predict the ultrasensitivity and performance of multivalent-encoded protein logic gates, evaluate the inherent programmability of multispecificity for selective receptor targeting, and extract rate constants of conformational switching for the SARS-CoV-2 spike protein and model its binding to ACE2 as well as multivalent inhibitors of this interaction. MVsim and instructional tutorials are freely available at https://sarkarlab.github.io/MVsim/ .

Suggested Citation

  • Bence Bruncsics & Wesley J. Errington & Casim A. Sarkar, 2022. "MVsim is a toolset for quantifying and designing multivalent interactions," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32496-6
    DOI: 10.1038/s41467-022-32496-6
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    References listed on IDEAS

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    2. Maolin Lu & Xiaochu Ma & Luis R. Castillo-Menendez & Jason Gorman & Nirmin Alsahafi & Utz Ermel & Daniel S. Terry & Michael Chambers & Dongjun Peng & Baoshan Zhang & Tongqing Zhou & Nick Reichard & Ke, 2019. "Associating HIV-1 envelope glycoprotein structures with states on the virus observed by smFRET," Nature, Nature, vol. 568(7752), pages 415-419, April.
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