Estimating Receptor-Ligand Affinity
A key first step in the R&D of a new drug is the identification of potential lead compounds. Often, the function of the target molecule is known and it is possible to screen for new leads using assays based on inhibition. The development of these functional assays into high throughput methods is a time-consuming process that is critical to the success of the screen. However, as more targets are gleaned from genomics efforts, there will be more situations where the function is unknown or poorly understood; developing function-based screens in these situations will be problematic. Binding can be considered as a proxy for inhibition where if a compound binds tightly and specifically enough, it has a good chance of being a drug. Consequently, new instrumental methods that can substitute for functional assays will be needed as alternate screening tools.
To address this need, we have developed a method to rapidly characterize and quantify interactions of small molecules with target receptors based NMR derived diffusion coefficient (D). The D can be easily and rapidly measured using Pulse Field Gradient (PFG) NMR experiments. Interactions between compounds of varying size can result in significant changes in D. For example, in the case of receptor-ligand (biological receptor and small molecule) interaction, the ligand diffuses faster than the receptor and will have a high D. If the ligand binds to the receptor, its D will change proportional to the amount bound to the receptor. The observed diffusion coefficient (Dobs) for the ligand is a weighted average (fraction X D) of the diffusion coefficients of the ligand prior to the binding (Dfree) and after the binding (Dbound). By undertaking a titration adding ligand to a fixed amount of receptor, the ligand Dobs, which is a function of changing molar ratios of ligand:receptor, yields data that can be used to extract a dissociation constant (Kd).
Figure 1
Figure 1 is a titration of vancomycin with peptides containing d-Ala where the diffusion coefficient of the ligand is plotted against the ligand:peptide molar ratio. The Kd values obtained in this study are consistent with those on similar compounds determined by other methods. These results clearly show the agreement between the experimental and anticipated results and that diffusion indeed can be used to characterize and quantify binding. In addition, we have developed a faster protocol based on a single diffusion measurement of the ligand:receptor mixture that allows for higher throughput analysis and have demonstrated a strategy to use diffusion measurements in a competitive manner for binding site identification. Overall, diffusion-based NMR Profile methods show promise as a general lead identification tool and may be particularly useful in screening genomics targets where functional assays are not available.
 
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