4.8 Article

MVsim is a toolset for quantifying and designing multivalent interactions

Journal

NATURE COMMUNICATIONS
Volume 13, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41467-022-32496-6

Keywords

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Funding

  1. National Laboratory ofArtificial Intelligence through the National Research Development and Innovation Office
  2. Ministry for Innovation and Technology
  3. National Research, Development, and Innovation Fund of Hungary [TKP2021-EGA-02]
  4. National Institutes of Health [R35GM136309, R01GM113985, R21EB022258]
  5. Institute for Engineering in Medicine at the University of Minnesota
  6. Office of Research Infrastructure Programs at the National Institutes of Health [S10OD021539]

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This article introduces an application suite called MVsim, which utilizes a configurational network model to facilitate the quantification, design, and mechanistic evaluation of multivalent binding phenomena. Research shows that MVsim can accurately simulate both monospecific and multispecific multivalent ligand-receptor interactions, providing conceptual insights into multivalent systems.
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/.

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