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Ligand rebinding: self-consistent mean-field theory and numerical simulations applied to surface plasmon resonance studies
Authors:Manoj Gopalakrishnan  Kimberly Forsten-Williams  Theresa R Cassino  Luz Padro  Thomas E Ryan  Uwe C Täuber
Institution:(1) Department of Physics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA;(2) Department of Chemical Engineering and Virginia Tech— Wake Forest University School of Biomedical Engineering and Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA;(3) Reichert Inc., 3374 Walden Avenue, Depew, NY, 14043, USA;(4) Present address: Max-Planck-Institut für Physik komplexer Systeme, Nöthnitzer Strasse 38, 01187 Dresden, Germany
Abstract:Rebinding of dissociated ligands from cell surface proteins can confound quantitative measurements of dissociation rates important for characterizing the affinity of binding interactions. This can be true also for in vitro techniques such as surface plasmon resonance (SPR). We present experimental results using SPR for the interaction of insulin-like growth factor-I (IGF-I) with one of its binding proteins, IGF binding protein-3 (IGFBP-3), and show that the dissociation, even with the addition of soluble heparin in the dissociation phase, does not exhibit the expected exponential decay characteristic of a 1:1 binding reaction. We thus consider the effect of (multiple) rebinding events and, within a self-consistent mean-field approximation, we derive the complete mathematical form for the fraction of bound ligands as a function of time. We show that, except for very low association rate and surface coverage, this function is nonexponential at all times, indicating that multiple rebinding events strongly influence dissociation even at early times. We compare the mean-field results with numerical simulations and find good agreement, although deviations are measurable in certain cases. Our analysis of the IGF-I–IGFBP-3 data indicates that rebinding is prominent for this system and that the theoretical predictions fit the experimental data well. Our results provide a means for analyzing SPR biosensor data where rebinding is problematic and a methodology to do so is presented.
Keywords:Surface plasmon resonance  Monte Carlo simulations  Insulin-like growth factor-I  Insulin-like growth factor binding protein-3  Mean-field theory
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