Estimation of drug binding parameters

Publisher Website
Google Scholar
Abstract
Many methods have been suggested and tested to estimate the association constants and binding capabilities of ligand-macromolecule interactions from experimental data. This problem is a subset of the general problem of parameter estimation for nonlinear algebraic models where both the independent and dependent variables are subject to measurement error. It is often difficult to anticipate the effect on the parameter estimates that is caused by error in the primary measurements. In this work, a computer algorithm is described which finds the maximum likelihood estimate for the true values of the parameters and also estimates for the values of the measurements. It is applied to experimental binding data in two examples for fitting the association constants and binding capacities.