Dual Labeling of the CBP/p300 KIX Domain for 19 F NMR Leads to Identification of a New Small-Molecule Binding Site

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Abstract

Protein-Observed Fluorine NMR Spectroscopy (PrOF NMR) is an emerging technique for screening and characterizing small molecule-protein interactions. The choice of which amino acid to label for PrOF NMR can be critical for analysis. Here we report the first use of a protein containing two different fluoroaromatic amino acids for NMR studies. Using the KIX domain of the CBP/p300 as a model system, we examine ligand binding of several small molecules elaborated from our previous fragment screen and identify a new ligand binding site distinct from those used by native transcription factors. This site was further supported by computational modeling (FTMap and Schrödinger) and 1H- 15N HSQC/HMQC NMR spectroscopy. Metabolic labelling with multiple fluorinated amino acids provides useful probes for further studying ligand binding and has led to new insight for allosterically regulating transcription-factor protein interactions with small molecules.

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The FTMap family of web servers for determining and characterizing ligand-binding hot spots of proteins.

Dima Kozakov, Laurie Grove, David Hall … (2015)

FTMap is a computational mapping server that identifies binding hot spots of macromolecules-i.e., regions of the surface with major contributions to the ligand-binding free energy. To use FTMap, users submit a protein, DNA or RNA structure in PDB (Protein Data Bank) format. FTMap samples billions of positions of small organic molecules used as probes, and it scores the probe poses using a detailed energy expression. Regions that bind clusters of multiple probe types identify the binding hot spots in good agreement with experimental data. FTMap serves as the basis for other servers, namely FTSite, which is used to predict ligand-binding sites, FTFlex, which is used to account for side chain flexibility, FTMap/param, used to parameterize additional probes and FTDyn, for mapping ensembles of protein structures. Applications include determining the druggability of proteins, identifying ligand moieties that are most important for binding, finding the most bound-like conformation in ensembles of unliganded protein structures and providing input for fragment-based drug design. FTMap is more accurate than classical mapping methods such as GRID and MCSS, and it is much faster than the more-recent approaches to protein mapping based on mixed molecular dynamics. By using 16 probe molecules, the FTMap server finds the hot spots of an average-size protein in <1 h. As FTFlex performs mapping for all low-energy conformers of side chains in the binding site, its completion time is proportionately longer.

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Structural conservation of druggable hot spots in protein-protein interfaces.

Jerry Pelletier, Regina Cencic, Megan Grove … (2011)

Despite the growing number of examples of small-molecule inhibitors that disrupt protein-protein interactions (PPIs), the origin of druggability of such targets is poorly understood. To identify druggable sites in protein-protein interfaces we combine computational solvent mapping, which explores the protein surface using a variety of small "probe" molecules, with a conformer generator to account for side-chain flexibility. Applications to unliganded structures of 15 PPI target proteins show that the druggable sites comprise a cluster of binding hot spots, distinguishable from other regions of the protein due to their concave topology combined with a pattern of hydrophobic and polar functionality. This combination of properties confers on the hot spots a tendency to bind organic species possessing some polar groups decorating largely hydrophobic scaffolds. Thus, druggable sites at PPI are not simply sites that are complementary to particular organic functionality, but rather possess a general tendency to bind organic compounds with a variety of structures, including key side chains of the partner protein. Results also highlight the importance of conformational adaptivity at the binding site to allow the hot spots to expand to accommodate a ligand of drug-like dimensions. The critical components of this adaptivity are largely local, involving primarily low energy side-chain motions within 6 Å of a hot spot. The structural and physicochemical signature of druggable sites at PPI interfaces is sufficiently robust to be detectable from the structure of the unliganded protein, even when substantial conformational adaptation is required for optimal ligand binding.