Augmenting Hit Identification by Virtual Screening Techniques in Small Molecule Drug Discovery.

Two orthogonal approaches for hit identification in drug discovery are large-scale in vitro and in silico screening. In recent years, due to the emergence of new targets and a rapid increase in the size of the readily synthesizable chemical space, there is a growing emphasis on the integration of the two techniques to improve the hit finding efficiency. Here, we highlight three examples of drug discovery projects at Merck & Co., Inc., Kenilworth, NJ, USA in which different virtual screening (VS) techniques, each specifically tailored to leverage knowledge available for the target, were utilized to augment the selection of high-quality chemical matter for in vitro assays and to enhance the diversity and tractability of hits. Central to success is a fully integrated workflow combining in silico and experimental expertise at every stage of the hit identification process. We advocate that workflows encompassing VS as part of an integrated hit finding plan should be widely adopted to accelerate hit identification and foster cross-functional collaborations in modern drug discovery.

Cooperative effects and optimal halogen bonding motifs for self-assembling systems.

Halogen bonding, due to its directionality and tunable strength, is being increasingly utilized in self-assembling materials and crystal engineering. Using density functional theory (DFT) and molecular mechanics (OPLS/CM1Ax) calculations, multiply halogen bonded complexes of brominated imidazole and pyridine are investigated along with their potential in construction of self-assembling architectures. Dimers with 1-10 halogen bonds are considered and reveal maximal binding energies of 3-36 kcal/mol. Cooperative (nonadditive) effects are found in complexes that extend both along and perpendicular to the halogen bonding axes, with interaction energies depending on polarization, secondary interactions, and ring spacers. Four structural motifs were identified to yield optimal halogen bonding. For the largest systems, the excellent agreement found between the DFT and OPLS/CM1Ax results supports the utility of the latter approach for analysis and design of self-assembling supramolecular structures.

Optimization of brain-penetrant picolinamide derived leucine-rich repeat kinase 2 (LRRK2) inhibitors.

The discovery of potent, kinome selective, brain penetrant LRRK2 inhibitors is the focus of extensive research seeking new, disease-modifying treatments for Parkinson's disease (PD). Herein, we describe the discovery and evolution of a picolinamide-derived lead series. Our initial optimization efforts aimed at improving the potency and CLK2 off-target selectivity of compound 1 by modifying the heteroaryl C-H hinge and linker regions. This resulted in compound 12 which advanced deep into our research operating plan (ROP) before heteroaryl aniline metabolite 14 was characterized as Ames mutagenic, halting its progression. Strategic modifications to our ROP were made to enable early de-risking of putative aniline metabolites or hydrolysis products for mutagenicity in Ames. This led to the discovery of 3,5-diaminopyridine 15 and 4,6-diaminopyrimidine 16 as low risk for mutagenicity (defined by a 3-strain Ames negative result). Analysis of key matched molecular pairs 17 and 18 led to the prioritization of the 3,5-diaminopyridine sub-series for further optimization due to enhanced rodent brain penetration. These efforts culminated in the discovery of ethyl trifluoromethyl pyrazole 23 with excellent LRRK2 potency and expanded selectivity versus off-target CLK2.

Molecular Dynamics Simulations of a Conformationally Mobile Peptide-Based Catalyst for Atroposelective Bromination.

It is widely accepted that structural rigidity is required to achieve high levels of asymmetric induction in catalytic, enantioselective reactions. This fundamental design principle often does not apply to highly selective catalytic peptides that often exhibit conformational heterogeneity. As a result, these complex systems are particularly challenging to study both experimentally and computationally. Herein, we utilize molecular dynamics simulations to investigate the role of conformational mobility on the reactivity and selectivity exhibited by a catalytic, ß-turn-biased peptide in an atroposelective bromination reaction. By means of cluster analysis, multiple distinct conformers of the peptide and a catalyst-substrate complex were identified in the simulations, all of which were corroborated by experimental NMR measurements. The simulations also revealed that a shift in the conformational equilibrium of the peptidic catalyst occurs upon addition of substrate, and the degree of change varies among different substrates. On the basis of these data, we propose a correlation between the composition of the peptide conformational ensemble and its catalytic properties. Moreover, these findings highlight the importance of conformational dynamics in catalytic, asymmetric reactions mediated by oligopeptides, unveiled through high-level, state-of-the-art computational modeling.

Improved Description of Sulfur Charge Anisotropy in OPLS Force Fields: Model Development and Parameterization.

The atomic point-charge model used in most molecular mechanics force fields does not represent well the electronic anisotropy that is featured in many directional noncovalent interactions. Sulfur participates in several types of such interactions with its lone pairs and σ-holes. The current study develops a new model, via the addition of off-atom charged sites, for a variety of sulfur compounds in the OPLS-AA and OPLS/CM5 force fields to address the lack of charge anisotropy. Parameter optimization is carried out to reproduce liquid-state properties, torsional and noncovalent energetics from reliable quantum mechanical calculations, and electrostatic potentials. Significant improvements are obtained for computed free energies of hydration, reducing the mean unsigned errors from ca. 1.4 to 0.4-0.7 kcal/mol. Enhanced accuracy in directionality and energetics is also obtained for molecular complexes with sulfur-containing hydrogen and halogen bonds. Moreover, the new model reproduces the unusual conformational preferences of sulfur-containing compounds with 1,4-intramolecular chalcogen bonds. Transferability of the new force field parameters to cysteine and methionine is verified via molecular dynamic simulations of blocked dipeptides. The study demonstrates the effectiveness of using off-atom charge sites to address electronic anisotropy, and provides a parametrization methodology that can be applied to other systems.

Hydration Properties and Solvent Effects for All-Atom Solutes in Polarizable Coarse-Grained Water.

Due to the importance of water in chemical and biological systems, a coarse-grained representation of the solvent can greatly simplify the description of the system while retaining key thermodynamic properties of the medium. A multiscale solvation model that couples all-atom solutes and polarizable Martini coarse-grained water (AAX/CGS) is developed to reproduce free energies of hydration of organic solutes. Using Monte Carlo/free energy perturbation (MC/FEP) calculations, results from multiscale and all-atom simulations are compared. Improved accuracy is obtained with the AAX/CGS approach for hydrophobic and sulfur- or halogen-containing solutes, but larger deviations are found for polar solute molecules where hydrogen bonding is featured. Furthermore, solvent effects on conformational and tautomeric equilibria of AA solutes were investigated using AA, CG, and GB/SA solvent models. It is found that the CG solvent model can reproduce well the medium effects from experiment and AA simulations; however, the GB/SA solvent model fails in some cases. A 7-30-fold reduction in computational cost is found for the present AAX/CGS multiscale simulations compared to the AA alternative.