title: Using Computational Modeling To Optimize the Design of Antibodies That Trap Viruses in Mucus.
abstract: Immunoglobulin G (IgG) antibodies that trap viruses in cervicovaginal mucus (CVM) via adhesive interactions between IgG-Fc and mucins have recently emerged as a promising strategy to block vaginally transmitted infections. The array of IgG bound to a virus particle appears to trap the virus by making multiple weak affinity bonds to the fibrous mucins that form the mucus gel. However, the antibody characteristics that maximize virus trapping and minimize viral infectivity remain poorly understood. Toward this goal, we developed a mathematical model that takes into account physiologically relevant spatial dimensions and time scales, binding, and unbinding rates between IgG and virions and between IgG and mucins, as well as the respective diffusivities of virions and IgG in semen and CVM. We then systematically explored the IgG-antigen and IgG-mucin binding and unbinding rates that minimize the flux of infectious HIV arriving at the vaginal epithelium. Surprisingly, contrary to common intuition that infectivity would drop monotonically with increasing affinities between IgG and HIV, and between IgG and mucins, our model suggests maximal trapping of HIV and minimal flux of HIV to the epithelium are achieved with IgG molecules that exhibit (i) rapid antigen binding (highkon) rather than very slow unbinding (lowkoff), that is, high-affinity binding to the virion, and (ii) relatively weak affinity with mucins. These results provide important insights into the design of more potent "mucotrapping" IgG for enhanced protection against vaginally transmitted infections. The model is adaptable to other pathogens, mucosal barriers, geometries, and kinetic and diffusional effects, providing a tool for hypothesis testing and producing quantitative insights into the dynamics of immune-mediated protection.
authors.affiliation: Departments of Mathematics and Applied Physical Science, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, United States.
authors.forename: Timothy
authors.initials: T
authors.lastname: Wessler
authors.affiliation: Departments of Mathematics and Applied Physical Science, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, United States.
authors.forename: Alex
authors.initials: A
authors.lastname: Chen
authors.affiliation: Mathematics Department, Tulane University, New Orleans, Louisiana 70118, United States.
authors.forename: Scott A
authors.initials: SA
authors.lastname: McKinley
authors.affiliation: Department of Biophysics, Johns Hopkins University, Baltimore, Maryland 21218, United States.
authors.forename: Richard
authors.initials: R
authors.lastname: Cone
authors.affiliation: Departments of Mathematics and Applied Physical Science, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, United States; UNC/NCSU Joint Department of Biomedical Engineering, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, United States.
authors.forename: Gregory
authors.initials: G
authors.lastname: Forest
authors.affiliation: Division of Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, United States; UNC/NCSU Joint Department of Biomedical Engineering, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, United States; Department of Microbiology & Immunology, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, United States.
authors.forename: Samuel K
authors.initials: SK
authors.lastname: Lai
keywords: HIV; IgG; cervicovaginal mucus; mucin; mucosal immunity; sexually transmitted infections