Exploring pH Dependent Host/Guest Binding Affinities.
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ABSTRACT:
SUBMITTER: Paul TJ
PROVIDER: S-EPMC7442968 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A water-soluble cyclophane dimer having two disulfide groups as a reduction-responsive cleavable bond as well as several acidic and basic functional groups as a pH-responsive ionizable group 1 was successfully synthesized. It was found that 1 showed pH-dependent guest-binding behavior. That is, 1 strongly bound an anionic guest, 6-p-toluidinonaphthalene-2-sulfonate (TNS) with binding constant (K/M-1) for 1:1 host-guest complexes of 9.6 × 104 M-1 at pH 3.8, which was larger than those at pH 7.4 and 10.7 (6.0 × 104 and 2.4 × 104 M-1, respectively), indicating a favorable electrostatic interaction between anionic guest and net cationic 1. What is more, release of the entrapped guest molecules by 1 was easily controlled by pH stimulus. Large favorable enthalpies (ΔH) for formation of host-guest complexes were obtained under the pH conditions employed, suggesting that electrostatic interaction between anionic TNS and 1 was the most important driving force for host-guest complexation. Such contributions of ΔH for formation of host-guest complexes decreased along with increased pH values from acidic to basic solutions. Upon addition of dithiothreitol (DTT) as a reducing reagent to an aqueous PBS buffer (pH 7.4) containing 1 and TNS, the fluorescence intensity originating from the bound guest molecules decreased gradually. A treatment of 1 with DTT gave 2, having less guest-binding affinity by the cleavage of disulfide bonds of 1. Consequently, almost all entrapped guest molecules by 1 were released from the host. Moreover, such reduction-responsive cleavage of 1 and release of bound guest molecules was performed more rapidly in aqueous buffer at pH 10.7.
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Project description:Accurately predicting the binding affinities of small organic molecules to biological macromolecules can greatly accelerate drug discovery by reducing the number of compounds that must be synthesized to realize desired potency and selectivity goals. Unfortunately, the process of assessing the accuracy of current computational approaches to affinity prediction against binding data to biological macromolecules is frustrated by several challenges, such as slow conformational dynamics, multiple titratable groups, and the lack of high-quality blinded datasets. Over the last several SAMPL blind challenge exercises, host-guest systems have emerged as a practical and effective way to circumvent these challenges in assessing the predictive performance of current-generation quantitative modeling tools, while still providing systems capable of possessing tight binding affinities. Here, we present an overview of the SAMPL6 host-guest binding affinity prediction challenge, which featured three supramolecular hosts: octa-acid (OA), the closely related tetra-endo-methyl-octa-acid (TEMOA), and cucurbit[8]uril (CB8), along with 21 small organic guest molecules. A total of 119 entries were received from ten participating groups employing a variety of methods that spanned from electronic structure and movable type calculations in implicit solvent to alchemical and potential of mean force strategies using empirical force fields with explicit solvent models. While empirical models tended to obtain better performance than first-principle methods, it was not possible to identify a single approach that consistently provided superior results across all host-guest systems and statistical metrics. Moreover, the accuracy of the methodologies generally displayed a substantial dependence on the system considered, emphasizing the need for host diversity in blind evaluations. Several entries exploited previous experimental measurements of similar host-guest systems in an effort to improve their physical-based predictions via some manner of rudimentary machine learning; while this strategy succeeded in reducing systematic errors, it did not correspond to an improvement in statistical correlation. Comparison to previous rounds of the host-guest binding free energy challenge highlights an overall improvement in the correlation obtained by the affinity predictions for OA and TEMOA systems, but a surprising lack of improvement regarding root mean square error over the past several challenge rounds. The data suggests that further refinement of force field parameters, as well as improved treatment of chemical effects (e.g., buffer salt conditions, protonation states), may be required to further enhance predictive accuracy.
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