Discovery of an Oral, Rule of 5 Compliant, Interleukin 17A Protein-Protein Interaction Modulator for the Potential Treatment of Psoriasis and Other Inflammatory Diseases.

Interleukin 17A (IL-17A) is an interleukin cytokine whose dysregulation is implicated in autoimmune disorders such as psoriasis, and monoclonal antibodies against the IL-17A pathway are now well-established and very effective treatments. This article outlines the work that led to the identification of 23 as an oral, small-molecule protein-protein interaction modulator (PPIm) clinical development candidate. Protein crystallography provided knowledge of the key binding interactions between small-molecule ligands and the IL-17A dimer, and this helped in the multiparameter optimization toward identifying an orally bioavailable, Rule of 5 compliant PPIm of IL-17A. Overlap of early ligands led to a series of benzhydrylglycine-containing compounds that allowed the identification of dimethylpyrazole as a key substituent that gave PPIm with oral bioavailability. Exploration of the amino acid portion of the structure then led to dicyclopropylalanine as a group that gave potent and metabolically stable compounds, including the development candidate 23.

Discovery of Clinical Candidate 4-[2-(5-Amino-1H-pyrazol-4-yl)-4-chlorophenoxy]-5-chloro-2-fluoro-N-1,3-thiazol-4-ylbenzenesulfonamide (PF-05089771): Design and Optimization of Diaryl Ether Aryl Sulfonamides as Selective Inhibitors of NaV1.7.

A series of acidic diaryl ether heterocyclic sulfonamides that are potent and subtype selective NaV1.7 inhibitors is described. Optimization of early lead matter focused on removal of structural alerts, improving metabolic stability and reducing cytochrome P450 inhibition driven drug-drug interaction concerns to deliver the desired balance of preclinical in vitro properties. Concerns over nonmetabolic routes of clearance, variable clearance in preclinical species, and subsequent low confidence human pharmacokinetic predictions led to the decision to conduct a human microdose study to determine clinical pharmacokinetics. The design strategies and results from preclinical PK and clinical human microdose PK data are described leading to the discovery of the first subtype selective NaV1.7 inhibitor clinical candidate PF-05089771 (34) which binds to a site in the voltage sensing domain.

From virtual to clinical: The discovery of PGN-1531, a novel antagonist of the prostanoid EP4 receptor.

In this Letter, we present the results of a hit-finding and lead optimization programme against the EP4 receptor (EP4R). In a short time period, we were able to discover five structurally diverse series of hit compounds using a combination of virtual screening methods. The most favoured hit, compound 6, was demonstrated to be a competitive antagonist of the EP4R. Compound 73 was identified following several rounds of optimization, which centred on improving both the primary EP4R affinity and selectivity against the related EP2R as well as the aqueous solubility. This work culminated in the preparation of PGN-1531, the sodium salt of 73, which showed a marked improvement in solubility (>10 mg/mL). PGN-1531 is a potent and selective antagonist at EP4Rs in vitro and in vivo, with the potential to alleviate the symptoms of migraine that result from cerebral vasodilatation.

Quantum mechanics/molecular mechanics modeling of regioselectivity of drug metabolism in cytochrome P450 2C9.

Cytochrome P450 enzymes (P450s) are important in drug metabolism and have been linked to adverse drug reactions. P450s display broad substrate reactivity, and prediction of metabolites is complex. QM/MM studies of P450 reactivity have provided insight into important details of the reaction mechanisms and have the potential to make predictions of metabolite formation. Here we present a comprehensive study of the oxidation of three widely used pharmaceutical compounds (S-ibuprofen, diclofenac, and S-warfarin) by one of the major drug-metabolizing P450 isoforms, CYP2C9. The reaction barriers to substrate oxidation by the iron-oxo species (Compound I) have been calculated at the B3LYP-D/CHARMM27 level for different possible metabolism sites for each drug, on multiple pathways. In the cases of ibuprofen and warfarin, the process with the lowest activation energy is consistent with the experimentally preferred metabolite. For diclofenac, the pathway leading to the experimentally observed metabolite is not the one with the lowest activation energy. This apparent inconsistency with experiment might be explained by the two very different binding modes involved in oxidation at the two competing positions. The carboxylate of diclofenac interacts strongly with the CYP2C9 Arg108 side chain in the transition state for formation of the observed metabolite-but not in that for the competing pathway. We compare reaction barriers calculated both in the presence and in the absence of the protein and observe a marked improvement in selectivity prediction ability upon inclusion of the protein for all of the substrates studied. The barriers calculated with the protein are generally higher than those calculated in the gas phase. This suggests that active-site residues surrounding the substrate play an important role in controlling selectivity in CYP2C9. The results show that inclusion of sampling (particularly) and dispersion effects is important in making accurate predictions of drug metabolism selectivity of P450s using QM/MM methods.

Subtype-selective targeting of voltage-gated sodium channels.

Voltage-gated sodium channels are key to the initiation and propagation of action potentials in electrically excitable cells. Molecular characterization has shown there to be nine functional members of the family, with a high degree of sequence homology between the channels. This homology translates into similar biophysical and pharmacological properties. Confidence in some of the channels as drug targets has been boosted by the discovery of human mutations in the genes encoding a number of them, which give rise to clinical conditions commensurate with the changes predicted from the altered channel biophysics. As a result, they have received much attention for their therapeutic potential. Sodium channels represent well-precedented drug targets as antidysrhythmics, anticonvulsants and local anaesthetics provide good clinical efficacy, driven through pharmacology at these channels. However, electrophysiological characterization of clinically useful compounds in recombinant expression systems shows them to be weak, with poor selectivity between channel types. This has led to the search for subtype-selective modulators, which offer the promise of treatments with improved clinical efficacy and better toleration. Despite developments in high-throughput electrophysiology platforms, this has proven very challenging. Structural biology is beginning to offer us a greater understanding of the three-dimensional structure of voltage-gated ion channels, bringing with it the opportunity to do real structure-based drug design in the future. This discipline is still in its infancy, but developments with the expression and purification of prokaryotic sodium channels offer the promise of structure-based drug design in the not too distant future.

Understanding CYP2D6 interactions.

Owing to the polymorphic nature of CYP2D6, clinically significant issues can arise when drugs rely on that enzyme either for clearance, or metabolism to an active metabolite. Available screening methods to determine if the compound is likely to cause drug-drug interactions, or is likely to be a victim of inhibition of CYP2D6 by other compounds will be described. Computational models and examples will be given on strategies to design out the CYP2D6 liabilities for both heme-binding compounds and non-heme-binding compounds.

Pharmacophoric fingerprint method (TOPP) for 3D-QSAR modeling: application to CYP2D6 metabolic stability.

The application of a new 3-point pharmacophore-fingerprinting package (TOPP, Triplets Of Pharmacophoric Points) to develop QSAR models is discussed. In the CYP2D6 metabolic stability case, these 3D pharmacophoric fingerprints have shown to be as valid as other 3D descriptors and 2D features. Interestingly, it was found in the 3D models that the use of more realistic substrate conformations, by an additional docking step, did not improve the statistical results significantly. A detailed analysis of the generated pharmacophoric hypotheses is consistent with the previously proposed dual interaction mode of substrates within the active site of CYP2D6.

Predicting penetration across the blood-brain barrier from simple descriptors and fragmentation schemes.

The ability to cross the blood brain barrier (BBB), sometimes expressed as BBB+ and BBB-, is a very important property in drug design. Several computational methods have been employed for the prediction of BBB-penetrating (BBB+) and nonpenetrating (BBB-) compounds with overall accuracies from 75 to 97%. However, most of these models use a large number of descriptors (67-199), and it is not easy to implement the models in order to predict values of BBB+/-. In this work, 19 simple molecular descriptors calculated from Algorithm Builder and fragmentation schemes were used for the analysis of 1593 BBB+/- data. The results show that hydrogen-bonding properties of compounds play a very important role in modeling BBB penetration. Several BBB models based on hydrogen-bonding properties, such as Abraham descriptors, polar surface area (PSA), and number of hydrogen bonding donors and acceptors, have been built using binomial-PLS analysis. The results show that the overall classification accuracy for a training set is over 90%, and overall prediction accuracy for a test set is over 95%.

Designing better drugs: predicting cytochrome P450 metabolism.

Many 3D ligand-based and structure-based computational approaches have been used to predict, and thus help explain, the metabolism catalyzed by the enzymes of the cytochrome P450 superfamily (P450s). P450s are responsible for >90% of the metabolism of all drugs, so the computational prediction of metabolism can help to design out drug-drug interactions in the early phases of the drug discovery process. Computational methodologies have focused on a few P450s that are directly involved in drug metabolism. The recently derived crystal structures for human P450s enable better 3D modelling of these important metabolizing enzymes. Models derived for P450s have evolved from simple comparisons of known substrates to more-elaborate experiments that require considerable computer power involving 3D overlaps and docking experiments. These models help to explain and, more importantly, predict the involvement of P450s in the metabolism of specific compounds and guide the drug-design process.

The discovery of tropane-derived CCR5 receptor antagonists.

The development of compound 1, a piperidine-based CCR5 receptor antagonist with Type I CYP2D6 inhibition, into the tropane-derived analogue 5, is described. This compound, which is devoid of CYP2D6 liabilities, is a highly potent ligand for the CCR5 receptor and has broad-spectrum activity against a range of clinically relevant HIV isolates. The identification of human ether a-go-go-related gene channel inhibition within this series is described and the potential for QTc interval prolongation discussed. Furthermore, structure activity relationship (SAR) around the piperidine moiety is also described.

Drug binding interactions in the inner cavity of HERG channels: molecular insights from structure-activity relationships of clofilium and ibutilide analogs.

Block of human ether-a-go-go related gene (hERG) K(+) channels by otherwise useful drugs is the most common cause of long QT syndrome, a disorder of cardiac repolarization that predisposes patients to potentially fatal arrhythmias. This undesirable long QT side effect has been a major reason for the withdrawal of medications from the pharmaceutical market. Understanding the molecular basis of hERG block is therefore essential to facilitate the design of safe drugs. Binding sites for hERG blockers have been mapped within the inner cavity of the channel and include aromatic residues in the S6 helix (Tyr-652, Phe-656) and residues in the pore helix (Thr-623, Ser-624, Val-625). We used mutagenesis of these residues, combined with an investigation of hERG block by close analogs of clofilium and ibutilide, to assess how specific alterations in drug structure affected potency and binding interactions. Although changing the basic nitrogen from quaternary to tertiary accelerated the onset of block, the IC(50) and kinetics for recovery from block were similar. In contrast, analogs with different para-substituents on the phenyl ring had significantly different potencies for wild-type hERG block. The highest potency was achieved with polar or electronegative para-substituents, whereas neutral para-substituents had potencies more than 100-fold lower. Results from mutagenesis and molecular modeling studies suggest that phenyl ring para-substituents influence drug interactions with Thr-623, Ser-624, and Tyr-652 and strongly affect binding affinity. Together, these findings suggest that modifying the para-substituent could be a useful strategy for reducing hERG potency and increasing the safety margin of compounds in development.

Surface-integral QSPR models: local energy properties.

Surface-integral models based on AM1 semiempirical molecular orbital calculations are presented for the free energies of solvation in water, n-octanol, and chloroform and for the enthalpy of solvation in water. A parametrized function of four local properties calculated at the isodensity surface (the molecular electrostatic potential, local ionization energy, electron affinity, and polarizability) is integrated over the triangulated surface area to obtain the target quantity. The resulting models give results only slightly less accurate than those reported for parametrized generalized Born/polar surface area models despite relying only on gas-phase calculations. The water and octanol free-energy models were validated by calculating the water-octanol partition coefficient for a test set of organic compounds with moderate success. The models lead to a local solvation energy, which can be projected onto the molecular isodensity surface and provides insight into "hot" areas for solvation in water or the other solvents.

Greater than the sum of its parts: combining models for useful ADMET prediction.

In silico ADMET (absorption, distribution, metabolism, excretion, and toxicity) models are important tools in combating late-stage attrition in the drug discovery process. This work shows how ADMET models can be combined to tailor predictions depending on one's needs. We demonstrate how the judicious use of data and considered combination of predictions can produce models that provide truly useful answers. This approach is illustrated with the prediction of hERG channel blocking and cytochrome P450 2D6 inhibition, where combination of two predictive models (with >80% of compounds correctly predicted) resulted in models with even better predictive values (with >90% of compounds correctly predicted for those classes of interest).

In silico methods for predicting ligand binding determinants of cytochromes P450.

A large number of computational methodologies have been used to predict, and thus help explain, the metabolism catalysed by the enzymes of the cytochrome P450 superfamily (P450s). A summary of the methodologies and resulting models is presented. This shows that investigations so far have focused on just a few of the many P450s, mainly those that are involved in drug metabolism. The models have evolved from simple comparisons of known substrates to more elaborate models requiring considerable computer power. These help to explain and, more importantly, predict the involvement of P450s in the metabolism of specific compounds.

Structural determinants of HERG channel block by clofilium and ibutilide.

Block of human ether-a-go-go related gene (HERG) K(+) channels by a variety of medications has been linked to acquired long QT syndrome, a disorder of cardiac repolarization that predisposes to lethal arrhythmias. The drug-binding site is composed of residues that face into the central cavity of the channel. Two aromatic residues located on the S6 domain (Tyr652 and Phe656) are particularly important structural determinants of drug block. The role of pore helix residues (Thr623, Ser624, Val625) is less clear. In this study, we compared the pharmacological properties of two structurally related compounds, ibutilide and clofilium. Both compounds are charged amines with a single phenyl ring. Clofilium, a chlorobenzene derivative, is a potent blocker of HERG channels, but has a remarkably slower time course for recovery from block than ibutilide, a methanesulfonanilide. The difference in the rate of recovery from block can be explained simply by variation in drug trapping. There is little recovery from clofilium block with D540K HERG channels that permit untrapping at hyperpolarized potentials. Alanine-scanning mutagenesis of the S6 domain and a portion of the pore helix revealed that the binding site residues were the same for both compounds. However, S624A, located at the base of the pore helix, was the only HERG mutation that enabled rapid recovery from clofilium block. In summary, the pore helix residues are important components of the HERG drug binding site, and may be particularly important for drugs with polar substituents, such as a halogen (e.g., clofilium) or a methanesulfonamide (e.g., ibutilide).

New molecular descriptors based on local properties at the molecular surface and a boiling-point model derived from them.

New molecular descriptors based on statistical descriptions of the local ionization potential, local electron affinity, and the local polarizability at the surface of the molecule are proposed. The significance of these descriptors has been tested by calculating them for the Maybridge database in addition to our set of 26 descriptors reported previously. The new descriptors show little correlation with those already in use. Furthermore, the principal components of the extended set of descriptors for the Maybridge data show that especially the descriptors based on the local electron affinity extend the variance in our set of descriptors, which we have previously shown to be relevant to physical properties. The first nine principal components are shown to be most significant. As an example of the usefulness of the new descriptors, we have set up a QSPR model for boiling points using both the old and new descriptors.

Genetic basis for differential activities of fluconazole and voriconazole against Candida krusei.

Invasive infections caused by Candida krusei are a significant concern because this organism is intrinsically resistant to fluconazole. Voriconazole is more active than fluconazole against C. krusei in vitro. One mechanism of fluconazole resistance in C. krusei is diminished sensitivity of the target enzyme, cytochrome P450 sterol 14alpha-demethylase (CYP51), to inhibition by this drug. We investigated the interactions of fluconazole and voriconazole with the CYP51s of C. krusei (ckCYP51) and fluconazole-susceptible Candida albicans (caCYP51). We found that voriconazole was a more potent inhibitor of both ckCYP51 and caCYP51 in cell extracts than was fluconazole. Also, the ckCYP51 was less sensitive to inhibition by both drugs than was caCYP51. These results were confirmed by expressing the CYP51 genes from C. krusei and C. albicans in Saccharomyces cerevisiae and determining the susceptibility of the transformants to voriconazole and fluconazole. We constructed homology models of the CYP51s of C. albicans and C. krusei based on the crystal structure of CYP51 from Mycobacterium tuberculosis. These models predicted that voriconazole is a more potent inhibitor of both caCYP51 and ckCYP51 than is fluconazole, because the extra methyl group of voriconazole results in a stronger hydrophobic interaction with the aromatic amino acids in the substrate binding site and more extensive filling of this site. Although there are multiple differences in the predicted amino acid sequence of caCYP51 and ckCYP51, the models of the two enzymes were quite similar and the mechanism for the relative resistance of ckCYP51 to the azoles was not apparent.

Development of a combined protein and pharmacophore model for cytochrome P450 2C9.

A combined protein and pharmacophore model for cytochrome P450 2C9 (CYP2C9) has been derived using various computational chemistry techniques. A combination of pharmacophore modeling (using 31 metabolic pathways for 27 substrates), protein modeling (using the rabbit CYP2C5/3 crystal structure), and molecular orbital calculations was used to derive a model that incorporated steric, electronic, and chemical stability properties. The initial pharmacophore model (based on a subset of 17 metabolic pathways for 16 substrates) and the protein model used to construct the combined model were derived independently and showed a large degree of complementarity. The combined model is in agreement with experimental results concerning the substrates used to derive the model and with site-directed mutagenesis data available for CYP2C9. The model has been successfully used to predict the metabolism of substrates not used to construct the model, of which four examples are discussed in detail. The model has also been successful in explaining the differences in substrate specificity between CYP2C9 and CYP2C19.