Xinjun Hou

Moving beyond Rules: The Development of a Central Nervous System Multiparameter Optimization (CNS MPO) Approach To Enable Alignment of Druglike Properties

The interplay among commonly used physicochemical properties in drug design was examined and utilized to create a prospective design tool focused on the alignment of key druglike attributes. Using a set of six physicochemical parameters ((a) lipophilicity, calculated partition coefficient (ClogP); (b) calculated distribution coefficient at pH = 7.4 (ClogD); (c) molecular weight (MW); (d) topological polar surface area (TPSA); (e) number of hydrogen bond donors (HBD); (f) most basic center (pK(a))), a druglikeness central nervous system multiparameter optimization (CNS MPO) algorithm was built and applied to a set of marketed CNS drugs (N = 119) and Pfizer CNS candidates (N = 108), as well as to a large diversity set of Pfizer proprietary compounds (N = 11 303). The novel CNS MPO algorithm showed that 74% of marketed CNS drugs displayed a high CNS MPO score (MPO desirability score ≥ 4, using a scale of 0-6), in comparison to 60% of the Pfizer CNS candidates. This analysis suggests that this algorithm could potentially be used to identify compounds with a higher probability of successfully testing hypotheses in the clinic. In addition, a relationship between an increasing CNS MPO score and alignment of key in vitro attributes of drug discovery (favorable permeability, P-glycoprotein (P-gp) efflux, metabolic stability, and safety) was seen in the marketed CNS drug set, the Pfizer candidate set, and the Pfizer proprietary diversity set. The CNS MPO scoring function offers advantages over hard cutoffs or utilization of single parameters to optimize structure-activity relationships (SAR) by expanding medicinal chemistry design space through a holistic assessment approach. Based on six physicochemical properties commonly used by medicinal chemists, the CNS MPO function may be used prospectively at the design stage to accelerate the identification of compounds with increased probability of success.

Defining Desirable Central Nervous System Drug Space through the Alignment of Molecular Properties, in Vitro ADME, and Safety Attributes

As part of our effort to increase survival of drug candidates and to move our medicinal chemistry design to higher probability space for success in the Neuroscience therapeutic area, we embarked on a detailed study of the property space for a collection of central nervous system (CNS) molecules. We carried out a thorough analysis of properties for 119 marketed CNS drugs and a set of 108 Pfizer CNS candidates. In particular, we focused on understanding the relationships between physicochemical properties, in vitro ADME (absorption, distribution, metabolism, and elimination) attributes, primary pharmacology binding efficiencies, and in vitro safety data for these two sets of compounds. This scholarship provides guidance for the design of CNS molecules in a property space with increased probability of success and may lead to the identification of druglike candidates with favorable safety profiles that can successfully test hypotheses in the clinic.

Design and selection parameters to accelerate the discovery of novel central nervous system positron emission tomography (PET) ligands and their application in the development of a novel phosphodiesterase 2A PET ligand.

To accelerate the discovery of novel small molecule central nervous system (CNS) positron emission tomography (PET) ligands, we aimed to define a property space that would facilitate ligand design and prioritization, thereby providing a higher probability of success for novel PET ligand development. Toward this end, we built a database consisting of 62 PET ligands that have successfully reached the clinic and 15 radioligands that failed in late-stage development as negative controls. A systematic analysis of these ligands identified a set of preferred parameters for physicochemical properties, brain permeability, and nonspecific binding (NSB). These preferred parameters have subsequently been applied to several programs and have led to the successful development of novel PET ligands with reduced resources and timelines. This strategy is illustrated here by the discovery of the novel phosphodiesterase 2A (PDE2A) PET ligand 4-(3-[(18)F]fluoroazetidin-1-yl)-7-methyl-5-{1-methyl-5-[4-(trifluoromethyl)phenyl]-1H-pyrazol-4-yl}imidazo[5,1-f][1,2,4]triazine, [(18)F]PF-05270430 (5).

Structure-based design of novel human Pin1 inhibitors (I).

Pin1 is a member of the cis-trans peptidyl-prolyl isomerase family with potential anti-cancer therapeutic value. Here we report structure-based de novo design and optimization of novel Pin1 inhibitors. Without a viable lead from internal screenings, we designed a series of novel Pin1 inhibitors by interrogating and exploring a protein crystal structure of Pin1. The ligand efficiency of the initial concept molecule was optimized with integrated SBDD and parallel chemistry approaches, resulting in a more attractive lead series.

Identification of a Brain Penetrant PDE9A Inhibitor Utilizing Prospective Design and Chemical Enablement as a Rapid Lead Optimization Strategy

By use of chemical enablement and prospective design, a novel series of selective, brain penetrant PDE9A inhibitors have been identified that are capable of producing in vivo elevations of brain cGMP.

Structure-Based Design, Synthesis, and Biological Evaluation of Irreversible Human Rhinovirus 3C Protease Inhibitors. Part 7: Structure–Activity Studies of Bicyclic 2-Pyridone-Containing Peptidomimetics

The structure-based design, chemical synthesis, and biological evaluation of bicyclic 2-pyridone-containing human rhinovirus (HRV) 3C protease (3CP) inhibitors are described. An optimized compound is shown to exhibit antiviral activity when tested against a variety of HRV serotypes (EC(50)s ranging from 0.037 to 0.162 microM).

Design and Discovery of 6-[(3S,4S)-4-Methyl-1-(pyrimidin-2-ylmethyl)pyrrolidin-3-yl]-1-(tetrahydro-2H-pyran-4-yl)-1,5-dihydro-4H-pyrazolo[3,4-d]pyrimidin-4-one (PF-04447943), a Selective Brain Penetrant PDE9A Inhibitor for the Treatment of Cognitive Disorders

6-[(3S,4S)-4-Methyl-1-(pyrimidin-2-ylmethyl)pyrrolidin-3-yl]-1-(tetrahydro-2H-pyran-4-yl)-1,5-dihydro-4H-pyrazolo[3,4-d]pyrimidin-4-one (PF-04447943) is a novel PDE9A inhibitor identified using parallel synthetic chemistry and structure-based drug design (SBDD) and has advanced into clinical trials. Selectivity for PDE9A over other PDE family members was achieved by targeting key residue differences between the PDE9A and PDE1C catalytic site. The physicochemical properties of the series were optimized to provide excellent in vitro and in vivo pharmacokinetics properties in multiple species including humans. It has been reported to elevate central cGMP levels in the brain and CSF of rodents. In addition, it exhibits procognitive activity in several rodent models and synaptic stabilization in an amyloid precursor protein (APP) transgenic mouse model. Recent disclosures from clinical trials confirm that it is well tolerated in humans and elevates cGMP in cerebral spinal fluid of healthy volunteers, confirming that it is a quality pharmacological tool for testing clinical hypotheses in disease states associated with impairment of cGMP signaling or cognition.

Central Nervous System Multiparameter Optimization Desirability: Application in Drug Discovery

Significant progress has been made in prospectively designing molecules using the central nervous system multiparameter optimization (CNS MPO) desirability tool, as evidenced by the analysis reported herein of a second wave of drug candidates that originated after the development and implementation of this tool. This simple-to-use design algorithm has expanded design space for CNS candidates and has further demonstrated the advantages of utilizing a flexible, multiparameter approach in drug discovery rather than individual parameters and hard cutoffs of physicochemical properties. The CNS MPO tool has helped to increase the percentage of compounds nominated for clinical development that exhibit alignment of ADME attributes, cross the blood-brain barrier, and reside in lower-risk safety space (low ClogP and high TPSA). The use of this tool has played a role in reducing the number of compounds submitted to exploratory toxicity studies and increasing the survival of our drug candidates through regulatory toxicology into First in Human studies. Overall, the CNS MPO algorithm has helped to improve the prioritization of design ideas and the quality of the compounds nominated for clinical development.

Use of structure-based design to discover a potent, selective, in vivo active phosphodiesterase 10A inhibitor lead series for the treatment of schizophrenia.

Utilizing structure-based virtual library design and scoring, a novel chimeric series of phosphodiesterase 10A (PDE10A) inhibitors was discovered by synergizing binding site interactions and ADME properties of two chemotypes. Virtual libraries were docked and scored for potential binding ability, followed by visual inspection to prioritize analogs for parallel and directed synthesis. The process yielded highly potent and selective compounds such as 16. New X-ray cocrystal structures enabled rational design of substituents that resulted in the successful optimization of physical properties to produce in vivo activity and to modulate microsomal clearance and permeability.

Application of structure-based drug design and parallel chemistry to identify selective, brain penetrant, in vivo active phosphodiesterase 9A inhibitors.

Phosphodiesterase 9A inhibitors have shown activity in preclinical models of cognition with potential application as novel therapies for treating Alzheimers disease. Our clinical candidate, PF-04447943 (2), demonstrated acceptable CNS permeability in rats with modest asymmetry between central and peripheral compartments (free brain/free plasma = 0.32; CSF/free plasma = 0.19) yet had physicochemical properties outside the range associated with traditional CNS drugs. To address the potential risk of restricted CNS penetration with 2 in human clinical trials, we sought to identify a preclinical candidate with no asymmetry in rat brain penetration and that could advance into development. Merging the medicinal chemistry strategies of structure-based design with parallel chemistry, a novel series of PDE9A inhibitors was identified that showed improved selectivity over PDE1C. Optimization afforded preclinical candidate 19 that demonstrated free brain/free plasma ≥ 1 in rat and reduced microsomal clearance along with the ability to increase cyclic guanosine monophosphosphate levels in rat CSF.