Flooding enzymes: quantifying the contributions of interstitial water and cavity shape to ligand binding using extended linear response free energy calculations

Water Networks Repopulate Protein-Ligand Interfaces with Temperature

High-resolution crystal structures highlight the importance of water networks in protein-ligand interactions. However, as these are typically determined at cryogenic temperature, resulting insights may be structurally precise but not biologically accurate. By collecting 10 matched room-temperature and cryogenic datasets of the biomedical target Hsp90α, we identified changes in water networks that impact protein conformations at the ligand binding interface. Water repositioning with temperature repopulates protein ensembles and ligand interactions. We introduce Flipper conformational barcodes to identify temperature-sensitive regions in electron density maps. This revealed that temperature-responsive states coincide with ligand-responsive regions and capture unique binding signatures that disappear upon cryo-cooling. Our results have implications for discovering Hsp90 selective ligands, and, more generally, for the utility of hidden protein and water conformations in drug discovery.

Decrypting a Cryptic Allosteric Pocket in H. pylori Glutamate Racemase

One of our greatest challenges in drug design is targeting cryptic allosteric pockets in enzyme targets. Drug leads that do bind to these cryptic pockets are often discovered during HTS campaigns, and the mechanisms of action are rarely understood. Nevertheless, it is often the case that the allosteric pocket provides the best option for drug development against a given target. In the current studies we present a successful way forward in rationally exploiting the cryptic allosteric pocket of H. pylori glutamate racemase, an essential enzyme in this pathogen's life cycle. A wide range of computational and experimental methods are employed in a workflow leading to the discovery of a series of natural product allosteric inhibitors which occupy the allosteric pocket of this essential racemase. The confluence of these studies reveals a fascinating source of the allosteric inhibition, which centers on the abolition of essential monomer-monomer coupled motion networks.

Role of Displacing Confined Solvent in the Conformational Equilibrium of β-Cyclodextrin

This study investigates the role of hydration and its relationship to the conformational equilibrium of the host molecule β-cyclodextrin. Molecular dynamics simulations indicate that the unbound β-cyclodextrin exhibits two state behavior in explicit solvent due to the opening and closing of its cavity. In implicit solvent, these transitions are not observed, and there is one dominant conformation of β-cyclodextrin with an open cavity. Based on these observations, we investigate the hypothesis that the expulsion of thermodynamically unfavorable water molecules into the bulk plays an important role in controlling the accessibility of the closed macrostate at room temperature. We compare the results of the molecular mechanics analytical generalized Born plus nonpolar solvation approach to those obtained through grid inhomogeneous solvation theory analysis with explicit solvation to elucidate the thermodynamic forces at play. The work illustrates the use of continuum solvent models to tease out solvation effects related to the inhomogeneity and the molecular nature of water and demonstrates the key role of the thermodynamics of enclosed hydration in driving the conformational equilibrium of molecules in solution.

Changes in quaternary structure cause a kinetic asymmetry of glutamate racemase-catalyzed homocysteic acid racemization

Glutamate racemases (GR) catalyze the racemization of d- and l-glutamate and are targets for the development of antibiotics. We demonstrate that GR from the periodontal pathogen Fusobacterium nucleatum (FnGR) catalyzes the racemization of d-homocysteic acid (d-HCA), while l-HCA is a poor substrate. This enantioselectivity arises because l-HCA perturbs FnGR's monomer-dimer equilibrium toward inactive monomer. The inhibitory effect of l-HCA may be overcome by increasing the total FnGR concentration or by adding glutamate, but not by blocking access to the active site through site-directed mutagenesis, suggesting that l-HCA binds at an allosteric site. This phenomenon is also exhibited by GR from Bacillus subtilis, suggesting that enantiospecific, "substrate"-induced dissociation of oligomers to form inactive monomers may furnish a new inhibition strategy.

Bayesian Model Averaging for Ensemble-Based Estimates of Solvation-Free Energies

This paper applies the Bayesian Model Averaging statistical ensemble technique to estimate small molecule solvation free energies. There is a wide range of methods available for predicting solvation free energies, ranging from empirical statistical models to ab initio quantum mechanical approaches. Each of these methods is based on a set of conceptual assumptions that can affect predictive accuracy and transferability. Using an iterative statistical process, we have selected and combined solvation energy estimates using an ensemble of 17 diverse methods from the fourth Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) blind prediction study to form a single, aggregated solvation energy estimate. Methods that possess minimal or redundant information are pruned from the ensemble and the evaluation process repeats until aggregate predictive performance can no longer be improved. We show that this process results in a final aggregate estimate that outperforms all individual methods by reducing estimate errors by as much as 91% to 1.2 kcal mol^-1 accuracy. This work provides a new approach for accurate solvation free energy prediction and lays the foundation for future work on aggregate models that can balance computational cost with prediction accuracy.

Biosynthesis of a Novel Glutamate Racemase Containing a Site-Specific 7-Hydroxycoumarin Amino Acid: Enzyme-Ligand Promiscuity Revealed at the Atomistic Level

Glutamate racemase (GR) catalyzes the cofactor independent stereoinversion of l- to d-glutamate for biosynthesis of bacterial cell walls. Because of its essential nature, this enzyme is under intense scrutiny as a drug target for the design of novel antimicrobial agents. However, the flexibility of the enzyme has made inhibitor design challenging. Previous steered molecular dynamics (MD), docking, and experimental studies have suggested that the enzyme forms highly varied complexes with different competitive inhibitor scaffolds. The current study employs a mutant orthogonal tRNA/aminoacyl-tRNA synthetase pair to genetically encode a non-natural fluorescent amino acid, l-(7-hydroxycoumarin-4-yl) ethylglycine (7HC), into a region (Tyr53) remote from the active site (previously identified by MD studies as undergoing ligand-associated changes) to generate an active mutant enzyme (GR^Y53/7HC). The GR^Y53/7HC enzyme is an active racemase, which permitted us to examine the nature of these idiosyncratic ligand-associated phenomena. One type of competitive inhibitor resulted in a dose-dependent quenching of the fluorescence of GR^Y53/7HC, while another type of competitive inhibitor resulted in a dose-dependent increase in fluorescence of GR^Y53/7HC. In order to investigate the environmental changes of the 7HC ring system that are distinctly associated with each of the GR^Y53/7HC-ligand complexes, and thus the source of the disparate quenching phenomena, a parallel computational study is described, which includes essential dynamics, ensemble docking and MD simulations of the relevant GR^Y53/7HC-ligand complexes. The changes in the solvent exposure of the 7HC ring system due to ligand-associated GR changes are consistent with the experimentally observed quenching phenomena. This study describes an approach for rationally predicting global protein allostery resulting from enzyme ligation to distinctive inhibitor scaffolds. The implications for fragment-based drug discovery and high throughput screening are discussed.

Molecular recognition in chemical and biological systems

Structure-based ligand design in medicinal chemistry and crop protection relies on the identification and quantification of weak noncovalent interactions and understanding the role of water. Small-molecule and protein structural database searches are important tools to retrieve existing knowledge. Thermodynamic profiling, combined with X-ray structural and computational studies, is the key to elucidate the energetics of the replacement of water by ligands. Biological receptor sites vary greatly in shape, conformational dynamics, and polarity, and require different ligand-design strategies, as shown for various case studies. Interactions between dipoles have become a central theme of molecular recognition. Orthogonal interactions, halogen bonding, and amide⋅⋅⋅π stacking provide new tools for innovative lead optimization. The combination of synthetic models and biological complexation studies is required to gather reliable information on weak noncovalent interactions and the role of water.

Nexus between protein-ligand affinity rank-ordering, biophysical approaches, and drug discovery

The confluence of computational and biophysical methods to accurately rank-order the binding affinities of small molecules and determine structures of macromolecular complexes is a potentially transformative advance in the work flow of drug discovery. This viewpoint explores the impact that advanced computational methods may have on the efficacy of small molecule drug discovery and optimization, particularly with respect to emerging fragment-based methods.