The equilibrium dissociation constant (K
d) is a major characteristic of affinity complexes and
one of the
most frequently determined physicochemical parameters. Despite its
significance, the values of K
d obtained
for the same complex under similar conditions often exhibit considerable
discrepancies and sometimes vary by orders of magnitude. These inconsistencies
highlight the susceptibility of K
d determination
to large systematic errors, even when random errors are small. It
is imperative to both minimize and quantitatively assess the systematic
errors inherent in K
d determination. Traditionally, K
d values are determined through nonlinear regression
of binding isotherms. This analysis utilizes three variables: concentrations
of two reactants and a fraction R of unbound limiting
reactant. The systematic errors in K
d arise
directly from systematic errors in these variables. Therefore, to
maximize the accuracy of K
d, this study
thoroughly analyzes the sources of systematic errors within the three
variables, including (i) non-additive signals to
calculate R, (ii) mis-calibrated
experimental instruments, (iii) inaccurate calibration
parameters, (iv) insufficient incubation time, (v) unsaturated binding isotherm, (vi) impurities
in the reactants, and (vii) solute adsorption onto
surfaces. Through this analysis, we illustrate how each source contributes
to inaccuracies in the determination of K
d and propose strategies to minimize these contributions. Additionally,
we introduce a method for quantitatively assessing the confidence
intervals of systematic errors in concentrations, a crucial step toward
quantitatively evaluating the accuracy of K
d. While presenting original findings, this paper also reiterates
the fundamentals of K
d determination,
hence guiding researchers across all proficiency levels. By shedding
light on the sources of systematic errors and offering strategies
for their mitigation, our work will help researchers enhance the accuracy
of K
d determination, thereby making binding
studies more reliable and the conclusions drawn from such studies
more robust.
