The nature of macromolecular interactions has been an area of deep interest for understanding many facets of biology. While a great deal of insight has been gained from structural knowledge, the contribution of protein dynamics to macromolecular interactions is not fully appreciated. This plays out from a thermodynamic perspective as the conformational entropy. The role of conformational entropy in macromolecular interactions has been difficult to address experimentally. Recently, an empirical calibration has been developed to quantify the conformational entropy of proteins using solution NMR relaxation methods. This method has been demonstrated in two distinct protein systems. The goal of this work is to expand this calibration to assess whether conformational entropy can be effectively quantified from NMR-derived protein dynamics. First, we demonstrate that NMR dynamics do not correlate well between the solid and solution states, suggesting that the relationship between the conformational entropy of proteins is limited to solution state-derived NMR dynamics. We hypothesize that this may be partially due to the role of hydration of the protein in its dynamics. Next, we expand our empirical calibration to over 30 distinct protein systems and demonstrated that the relationship between NMR dynamics and conformational entropy is both robust and general. Furthermore, we demonstrate that conformational entropy plays a significant role in macromolecular interactions. Using our empirical calibration, we then look to address if conformational entropy could be an important contribution to drug design. The latter process is often a brute force approach, and subsequent optimization of initial drug candidates is often a guess and check process. In silico drug design was thought to offer a more efficient and rational approach, but often relies on static structures. This minimizes or completely neglects the role that conformational entropy may play in binding. Here we experimentally determine the role of conformational entropy in the drug target p38a MAPK in binding to two potent inhibitors. We demonstrate evidence that conformational entropy may represent a tunable parameter in affinity optimization of lead compounds. This has important implications for lead optimization and strongly suggests that the role of conformational entropy be considered in drug design efforts.