Structure-Based and Property-Driven Optimization of N-Aryl Imidazoles toward Potent and Selective Oral RORγt Inhibitors.

Retinoic acid receptor-related orphan receptor gamma-t (RORγt) is considered to be the master transcription factor for the development of Th17 cells that produce proinflammatory cytokines such as IL-17A. Overproportionate Th17 cell abundance is associated with the pathogenesis of many inflammatory conditions including psoriasis. In a high-throughput fluorescence resonance energy transfer (FRET) screen, we identified compound 1 as a hit with promising lipophilic efficiency (LipE). Using structure-based drug design based on a number of X-ray cocrystal structures, we morphed this hit class into potent imidazoles, exemplified by compound 3. To improve the poor absorption, distribution, metabolism, and excretion (ADME) properties of neutral imidazoles, we extended our ligands with carboxylic acid substituents toward a polar, water-rich area of the protein. This highly lipophilicity-efficient modification ultimately led to the discovery of compound 14, a potent and selective inhibitor of RORγt with good ADME properties and excellent in vivo pharmacokinetics. This compound showed good efficacy in an in vivo delayed-type hypersensitivity pharmacology model in rats.

Building New Bridges between In Vitro and In Vivo in Early Drug Discovery: Where Molecular Modeling Meets Systems Biology.

Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT.

Uncoupling the Structure-Activity Relationships of ß2 Adrenergic Receptor Ligands from Membrane Binding.

Ligand binding to membrane proteins may be significantly influenced by the interaction of ligands with the membrane. In particular, the microscopic ligand concentration within the membrane surface solvation layer may exceed that in bulk solvent, resulting in overestimation of the intrinsic protein-ligand binding contribution to the apparent/measured affinity. Using published binding data for a set of small molecules with the ß2 adrenergic receptor, we demonstrate that deconvolution of membrane and protein binding contributions allows for improved structure-activity relationship analysis and structure-based drug design. Molecular dynamics simulations of ligand bound membrane protein complexes were used to validate binding poses, allowing analysis of key interactions and binding site solvation to develop structure-activity relationships of ß2 ligand binding. The resulting relationships are consistent with intrinsic binding affinity (corrected for membrane interaction). The successful structure-based design of ligands targeting membrane proteins may require an assessment of membrane affinity to uncouple protein binding from membrane interactions.

Estimation of Solvation Entropy and Enthalpy via Analysis of Water Oxygen-Hydrogen Correlations.

A statistical-mechanical framework for estimation of solvation entropies and enthalpies is proposed, which is based on the analysis of water as a mixture of correlated water oxygens and water hydrogens. Entropic contributions of increasing order are cast in terms of a Mutual Information Expansion that is evaluated to pairwise interactions. In turn, the enthalpy is computed directly from a distance-based hydrogen bonding energy algorithm. The resulting expressions are employed for grid-based analyses of Molecular Dynamics simulations. In this first assessment of the methodology, we obtained global estimates of the excess entropy and enthalpy of water that are in good agreement with experiment and examined the method's ability to enable detailed elucidation of solvation thermodynamic structures, which can provide valuable knowledge toward molecular design.

Time-averaged distributions of solute and solvent motions: exploring proton wires of GFP and PfM2DH.

Proton translocation pathways of selected variants of the green fluorescent protein (GFP) and Pseudomonas fluorescens mannitol 2-dehydrogenase (PfM2DH) were investigated via an explicit solvent molecular dynamics-based analysis protocol that allows for direct quantitative relationship between a crystal structure and its time-averaged solute-solvent structure obtained from simulation. Our study of GFP is in good agreement with previous research suggesting that the proton released from the chromophore upon photoexcitation can diffuse through an extended internal hydrogen bonding network that allows for the proton to exit to bulk or be recaptured by the anionic chromophore. Conversely for PfM2DH, we identified the most probable ionization states of key residues along the proton escape channel from the catalytic site to bulk solvent, wherein the solute and high-density solvent crystal structures of binary and ternary complexes were properly reproduced. Furthermore, we proposed a plausible mechanism for this proton translocation process that is consistent with the state-dependent structural shifts observed in our analysis. The time-averaged structures generated from our analyses facilitate validation of MD simulation results and provide a comprehensive profile of the dynamic all-occupancy solvation network within and around a flexible solute, from which detailed hydrogen-bonding networks can be inferred. In this way, potential drawbacks arising from the elucidation of these networks by examination of static crystal structures or via alternate rigid-protein solvation analysis procedures can be overcome. Complementary studies aimed at the effective use of our methodology for alternate implementations (e.g., ligand design) are currently underway.