Moving Beyond Active-Site Detection: MixMD Applied to Allosteric Systems

Mixed-solvent molecular dynamics (MixMD) is a hotspot-mapping technique that relies on molecular dynamics simulations of proteins in binary solvent mixtures. Previous work on MixMD has established the technique’s effectiveness in capturing binding sites of small organic compounds. In this work, we show that MixMD can identify both competitive and allosteric sites on proteins. The MixMD approach embraces full protein flexibility and allows competition between solvent probes and water. Sites preferentially mapped by probe molecules are more likely to be binding hotspots. There are two important requirements for the identification of ligand-binding hotspots: (1) hotspots must be mapped at very high signal-to-noise ratio and (2) the hotspots must be mapped by multiple probe types. We have developed our mapping protocol around acetonitrile, isopropanol, and pyrimidine as probe solvents because they allowed us to capture hydrophilic, hydrophobic, hydrogen-bonding, and aromatic interactions. Charged probes were needed for mapping one target, and we introduce them in this work. In order to demonstrate the robust nature and wide applicability of the technique, a combined total of 5 μs of MixMD was applied across several protein targets known to exhibit allosteric modulation. Most notably, all the protein crystal structures used to initiate our simulations had no allosteric ligands bound, so there was no preorganization of the sites to predispose the simulations to find the allosteric hotspots. The protein test cases were ABL Kinase, Androgen Receptor, CHK1 Kinase, Glucokinase, PDK1 Kinase, Farnesyl Pyrophosphate Synthase, and Protein-Tyrosine Phosphatase 1B. The success of the technique is demonstrated by the fact that the top-four sites solely map the competitive and allosteric sites. Lower-ranked sites consistently map other biologically relevant sites, multimerization interfaces, or crystal-packing interfaces. Lastly, we highlight the importance of including protein flexibility by demonstrating that MixMD can map allosteric sites that are not detected in half the systems using FTMap applied to the same crystal structures

Large-Scale Validation of Mixed-Solvent Simulations to Assess Hotspots at Protein–Protein Interaction Interfaces

The ability to target protein–protein interactions (PPIs) with small molecule inhibitors offers great promise in expanding the druggable target space and addressing a broad range of untreated diseases. However, due to their nature and function of interacting with protein partners, PPI interfaces tend to extend over large surfaces without the typical pockets of enzymes and receptors. These features present unique challenges for small molecule inhibitor design. As such, determining whether a particular PPI of interest could be pursued with a small molecule discovery strategy requires an understanding of the characteristics of the PPI interface and whether it has hotspots that can be leveraged by small molecules to achieve desired potency. Here, we assess the ability of mixed-solvent molecular dynamic (MSMD) simulations to detect hotspots at PPI interfaces. MSMD simulations using three cosolvents (acetonitrile, isopropanol, and pyrimidine) were performed on a large test set of 21 PPI targets that have been experimentally validated by small molecule inhibitors. We compare MSMD, which includes explicit solvent and full protein flexibility, to a simpler approach that does not include dynamics or explicit solvent (SiteMap) and find that MSMD simulations reveal additional information about the characteristics of these targets and the ability for small molecules to inhibit the PPI interface. In the few cases were MSMD simulations did not detect hotspots, we explore the shortcomings of this technique and propose future improvements. Finally, using Interleukin-2 as an example, we highlight the advantage of the MSMD approach for detecting transient cryptic druggable pockets that exists at PPI interfaces

Substrate-Competitive Activity-Based Profiling of Ester Prodrug Activating Enzymes

Understanding the mechanistic basis of prodrug delivery and activation is critical for establishing species-specific prodrug sensitivities necessary for evaluating preclinical animal models and potential drug–drug interactions. Despite significant adoption of prodrug methodologies for enhanced pharmacokinetics, functional annotation of prodrug activating enzymes is laborious and often unaddressed. Activity-based protein profiling (ABPP) describes an emerging chemoproteomic approach to assay active site occupancy within a mechanistically similar enzyme class in native proteomes. The serine hydrolase enzyme family is broadly reactive with reporter-linked fluorophosphonates, which have shown to provide a mechanism-based covalent labeling strategy to assay the activation state and active site occupancy of cellular serine amidases, esterases, and thioesterases. Here we describe a modified ABPP approach using direct substrate competition to identify activating enzymes for an ethyl ester prodrug, the influenza neuraminidase inhibitor oseltamivir. Substrate-competitive ABPP analysis identified carboxylesterase 1 (CES1) as an oseltamivir-activating enzyme in intestinal cell homogenates. Saturating concentrations of oseltamivir lead to a four-fold reduction in the observed rate constant for CES1 inactivation by fluorophosphonates. WWL50, a reported carbamate inhibitor of mouse CES1, blocked oseltamivir hydrolysis activity in human cell homogenates, confirming CES1 is the primary prodrug activating enzyme for oseltamivir in human liver and intestinal cell lines. The related carbamate inhibitor WWL79 inhibited mouse but not human CES1, providing a series of probes for analyzing prodrug activation mechanisms in different preclinical models. Overall, we present a substrate-competitive activity-based profiling approach for broadly surveying candidate prodrug hydrolyzing enzymes and outline the kinetic parameters for activating enzyme discovery, ester prodrug design, and preclinical development of ester prodrugs