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Proximal charge effects on guest binding to a non-polar pocket.


ABSTRACT: Science still does not have the ability to accurately predict the affinity that ligands have for proteins. In an attempt to address this, the Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) series of blind predictive challenges is a community-wide exercise aimed at advancing computational techniques as standard predictive tools in rational drug design. In each cycle, a range of biologically relevant systems of different levels of complexity are selected to test the latest modeling methods. As part of this on-going exercise, and as a step towards understanding the important factors in context dependent guest binding, we challenged the computational community to determine the affinity of a series of negatively and positively charged guests to two constitutionally isomeric cavitand hosts: octa-acid 1, and exo-octa acid 2. Our affinity determinations, combined with molecular dynamics simulations, reveal asymmetries in affinities between host-guest pairs that cannot alone be explained by simple coulombic interactions, but also point to the importance of host-water interactions. Our work reveals the key facets of molecular recognition in water, emphasizes where improvements need to be made in modelling, and shed light on the complex problem of ligand-protein binding in the aqueous realm.

SUBMITTER: Suating P 

PROVIDER: S-EPMC7424593 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Proximal charge effects on guest binding to a non-polar pocket.

Suating Paolo P   Nguyen Thong T TT   Ernst Nicholas E NE   Wang Yang Y   Jordan Jacobs H JH   Gibb Corinne L D CLD   Ashbaugh Henry S HS   Gibb Bruce C BC  

Chemical science 20200317 14


Science still does not have the ability to accurately predict the affinity that ligands have for proteins. In an attempt to address this, the Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) series of blind predictive challenges is a community-wide exercise aimed at advancing computational techniques as standard predictive tools in rational drug design. In each cycle, a range of biologically relevant systems of different levels of complexity are selected to test the latest mode  ...[more]

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