Getting the MAX out of Computational Models: The Prediction of Unbound-Brain and Unbound-Plasma Maximum Concentrations

The objective of this work was to establish that unbound maximum concentrations may be reasonably predicted from a combination of computed molecular properties assuming subcutaneous (SQ) dosing. Additionally, we show that the maximum unbound plasma and brain concentrations may be projected from a mixture of in vitro absorption, distribution, metabolism, excretion experimental parameters in combination with computed properties (volume of distribution, fraction unbound in microsomes). Finally, we demonstrate the utility of the underlying equations by showing that the maximum total plasma concentrations can be projected from the experimental parameters for a set of compounds with data collected from clinical research

Getting the MAX out of Computational Models: The Prediction of Unbound-Brain and Unbound-Plasma Maximum Concentrations

The objective of this work was to establish that unbound maximum concentrations may be reasonably predicted from a combination of computed molecular properties assuming subcutaneous (SQ) dosing. Additionally, we show that the maximum unbound plasma and brain concentrations may be projected from a mixture of in vitro absorption, distribution, metabolism, excretion experimental parameters in combination with computed properties (volume of distribution, fraction unbound in microsomes). Finally, we demonstrate the utility of the underlying equations by showing that the maximum total plasma concentrations can be projected from the experimental parameters for a set of compounds with data collected from clinical research

Getting the MAX out of Computational Models: The Prediction of Unbound-Brain and Unbound-Plasma Maximum Concentrations

The objective of this work was to establish that unbound maximum concentrations may be reasonably predicted from a combination of computed molecular properties assuming subcutaneous (SQ) dosing. Additionally, we show that the maximum unbound plasma and brain concentrations may be projected from a mixture of in vitro absorption, distribution, metabolism, excretion experimental parameters in combination with computed properties (volume of distribution, fraction unbound in microsomes). Finally, we demonstrate the utility of the underlying equations by showing that the maximum total plasma concentrations can be projected from the experimental parameters for a set of compounds with data collected from clinical research

Measurement of Atropisomer Racemization Kinetics Using Segmented Flow Technology

When stable atropisomers are encountered by drug discovery teams, they can have important implications due to potential differences in their biological activity, pharmacokinetics, and toxicity. Knowledge of an atropisomer's activation parameters for interconversion is required to facilitate informed decisions on how to proceed. Herein, we communicate the development of a new method for the rapid measurement of atropisomer racemization kinetics utilizing segmented flow technology. This method leverages the speed, accuracy, low sample requirement, safety, and semiautomated nature of flow instrumentation to facilitate the acquisition of kinetics data required for experimentally probing atropisomer activation parameters. Measured kinetics data obtained for the atropo isomerization of AMPA antagonist CP-465021 using segmented flow and traditional thermal methods were compared to validate the method

Exploring Aromatic Chemical Space with NEAT: Novel and Electronically Equivalent Aromatic Template

In this paper, we describe a lead transformation tool, NEAT (<u>N</u>ovel and <u>E</u>lectronically equivalent <u>A</u>romatic <u>T</u>emplate), which can help identify novel aromatic rings that are estimated to have similar electrostatic potentials, dipoles, and hydrogen bonding capabilities to a query template; hence, they may offer similar bioactivity profiles. In this work, we built a comprehensive heteroaryl database, and precalculated high-level quantum mechanical (QM) properties, including electrostatic potential charges, hydrogen bonding ability, dipole moments, chemical reactivity, and othe properties. NEAT bioisosteric similarities are based on the electrostatic potential surface calculated by Brood, using the precalculated QM ESP charges and other QM properties. Compared with existing commercial lead transformation software, (1) NEAT is the only one that covers the comprehensive heteroaryl chemical space, and (2) NEAT offers a better characterization of novel aryl cores by using high-evel QM properties that are relevant to molecular interactions. NEAT provides unique value to medicinal chemists quickly exploring the largely uncharted aromatic chemical space, and one successful example of its application is discussed herein

Exploring Aromatic Chemical Space with NEAT: Novel and Electronically Equivalent Aromatic Template

In this paper, we describe a lead transformation tool, NEAT (<u>N</u>ovel and <u>E</u>lectronically equivalent <u>A</u>romatic <u>T</u>emplate), which can help identify novel aromatic rings that are estimated to have similar electrostatic potentials, dipoles, and hydrogen bonding capabilities to a query template; hence, they may offer similar bioactivity profiles. In this work, we built a comprehensive heteroaryl database, and precalculated high-level quantum mechanical (QM) properties, including electrostatic potential charges, hydrogen bonding ability, dipole moments, chemical reactivity, and othe properties. NEAT bioisosteric similarities are based on the electrostatic potential surface calculated by Brood, using the precalculated QM ESP charges and other QM properties. Compared with existing commercial lead transformation software, (1) NEAT is the only one that covers the comprehensive heteroaryl chemical space, and (2) NEAT offers a better characterization of novel aryl cores by using high-evel QM properties that are relevant to molecular interactions. NEAT provides unique value to medicinal chemists quickly exploring the largely uncharted aromatic chemical space, and one successful example of its application is discussed herein

Casein Kinase 1δ/ε Inhibitor PF-5006739 Attenuates Opioid Drug-Seeking Behavior

Casein kinase 1 delta (CK1δ) and casein kinase 1 epsilon (CK1ε) inhibitors are potential therapeutic agents for a range of psychiatric disorders. The feasibility of developing a CNS kinase inhibitor has been limited by an inability to identify safe brain-penetrant compounds with high kinome selectivity. Guided by structure-based drug design, potent and selective CK1δ/ε inhibitors have now been identified that address this gap, through the design and synthesis of novel 4-[4-(4-fluorophenyl)-1-(piperidin-4-yl)-1<i>H</i>-imidazol-5-yl]­pyrimidin-2-amine derivatives. PF-5006739 (<b>6</b>) possesses a desirable profile, with low nanomolar in vitro potency for CK1δ/ε (IC₅₀ = 3.9 and 17.0 nM, respectively) and high kinome selectivity. In vivo, <b>6</b> demonstrated robust centrally mediated circadian rhythm phase-delaying effects in both nocturnal and diurnal animal models. Further, <b>6</b> dose-dependently attenuated opioid drug-seeking behavior in a rodent operant reinstatement model in animals trained to self-administer fentanyl. Collectively, our data supports further development of <b>6</b> as a promising candidate to test the hypothesis of CK1δ/ε inhibition in treating multiple indications in the clinic

Azetidine and Piperidine Carbamates as Efficient, Covalent Inhibitors of Monoacylglycerol Lipase

Monoacylglycerol lipase (MAGL) is the main enzyme responsible for degradation of the endocannabinoid 2-arachidonoylglycerol (2-AG) in the CNS. MAGL catalyzes the conversion of 2-AG to arachidonic acid (AA), a precursor to the proinflammatory eicosannoids such as prostaglandins. Herein we describe highly efficient MAGL inhibitors, identified through a parallel medicinal chemistry approach that highlighted the improved efficiency of azetidine and piperidine-derived carbamates. The discovery and optimization of 3-substituted azetidine carbamate irreversible inhibitors of MAGL were aided by the generation of inhibitor-bound MAGL crystal structures. Compound <b>6</b>, a highly efficient and selective MAGL inhibitor against recombinant enzyme and in a cellular context, was tested in vivo and shown to elevate central 2-AG levels at a 10 mg/kg dose

Application of Structure-Based Design and Parallel Chemistry to Identify a Potent, Selective, and Brain Penetrant Phosphodiesterase 2A Inhibitor

Phosphodiesterase 2A (PDE2A) inhibitors have been reported to demonstrate in vivo activity in preclinical models of cognition. To more fully explore the biology of PDE2A inhibition, we sought to identify potent PDE2A inhibitors with improved brain penetration as compared to current literature compounds. Applying estimated human dose calculations while simultaneously leveraging synthetically enabled chemistry and structure-based drug design has resulted in a highly potent, selective, brain penetrant compound <b>71</b> (PF-05085727) that effects in vivo biochemical changes commensurate with PDE2A inhibition along with behavioral and electrophysiological reversal of the effects of NMDA antagonists in rodents. This data supports the ability of PDE2A inhibitors to potentiate NMDA signaling and their further development for clinical cognition indications

Application of Structure-Based Design and Parallel Chemistry to Identify a Potent, Selective, and Brain Penetrant Phosphodiesterase 2A Inhibitor

Phosphodiesterase 2A (PDE2A) inhibitors have been reported to demonstrate in vivo activity in preclinical models of cognition. To more fully explore the biology of PDE2A inhibition, we sought to identify potent PDE2A inhibitors with improved brain penetration as compared to current literature compounds. Applying estimated human dose calculations while simultaneously leveraging synthetically enabled chemistry and structure-based drug design has resulted in a highly potent, selective, brain penetrant compound <b>71</b> (PF-05085727) that effects in vivo biochemical changes commensurate with PDE2A inhibition along with behavioral and electrophysiological reversal of the effects of NMDA antagonists in rodents. This data supports the ability of PDE2A inhibitors to potentiate NMDA signaling and their further development for clinical cognition indications