Discovery of Potent Inhibitors of 11ß-Hydroxysteroid Dehydrogenase Type 1 Using a Novel Growth-Based Protocol of in Silico Screening and Optimization in CONTOUR.

With the continuous progress in ultralarge virtual libraries which are readily accessible, it is of great interest to explore this large chemical space for hit identification and lead optimization using reliable structure-based approaches. In this work, a novel growth-based screening protocol has been designed and implemented in the structure-based design platform CONTOUR. The protocol was used to screen the ZINC database in silico and optimize hits to discover 11ß-HSD1 inhibitors. In contrast to molecular docking, the virtual screening process makes significant improvements in computational efficiency without losing chemical equities through partitioning 1.8 million ZINC compounds into fragments, docking fragments to form key hydrogen bonds with anchor residues, reorganizing molecules into molecular fragment trees using matched fragments and common substructures, and then regrowing molecules with the help of developed intelligent growth features inside the protein binding site to find hits. The growth-base screening approach is validated by the high hit rate. A total of 50 compounds have been selected for testing; of these, 15 hits having diverse scaffolds are found to inhibit 11ß-HSD1 with IC50 values of less than 1 µM in a biochemical enzyme assay. The best hit which exhibits an enzyme IC50 of 33 nM is further developed to a novel series of bicyclic 11ß-HSD1 inhibitors with the best inhibition of enzyme IC50 of 3.1 nM. The final lead candidate exhibits IC50 values of 7.2 and 21 nM in enzyme and adipocyte assays, respectively, displayed greater than 1000-fold of selectivity over 11ß-HSD2 and two other related hydroxysteroid dehydrogenases, and can serve as good starting points for further optimization to develop clinical candidates.

Conformational control in structure-based drug design.

In structure-based drug design, the basic goal is to design molecules that fit complementarily to a given binding pocket. Since such computationally modeled molecules may not adopt the intended bound conformation outside the binding pocket, one challenge is to ensure that the designed ligands adopt similar low energy conformations both inside and outside of the binding pocket. Computational chemistry methods and conformational preferences of small molecules from PDB and Cambridge Structural Database (CSD) can be used to predict the bound structures of the designed molecules. Herein, we review applications of conformational control in structure-based drug design using selected examples from the recent medicinal chemistry literature. The main purpose is to highlight some intriguing conformational features that can be applied to other drug discovery programs.

Discovery of BI 135585, an in vivo efficacious oxazinanone-based 11ß hydroxysteroid dehydrogenase type 1 inhibitor.

A potent, in vivo efficacious 11ß hydroxysteroid dehydrogenase type 1 (11ß HSD1) inhibitor (11j) has been identified. Compound 11j inhibited 11ß HSD1 activity in human adipocytes with an IC50 of 4.3nM and in primary human adipose tissue with an IC80 of 53nM. Oral administration of 11j to cynomolgus monkey inhibited 11ß HSD1 activity in adipose tissue. Compound 11j exhibited >1000× selectivity over other hydroxysteroid dehydrogenases, displays desirable pharmacodynamic properties and entered human clinical trials in 2011.

Brain penetrant liver X receptor (LXR) modulators based on a 2,4,5,6-tetrahydropyrrolo[3,4-c]pyrazole core.

Liver X receptor (LXR) agonists have been reported to lower brain amyloid beta (Aß) and thus to have potential for the treatment of Alzheimer's disease. Structure and property based design led to the discovery of a series of orally bioavailable, brain penetrant LXR agonists. Oral administration of compound 18 to rats resulted in significant upregulation of the expression of the LXR target gene ABCA1 in brain tissue, but no significant effect on Aß levels was detected.

Identification of spirooxindole and dibenzoxazepine motifs as potent mineralocorticoid receptor antagonists.

Mineralocorticoid receptor (MR) antagonists continue to be a prevalent area of research in the pharmaceutical industry. Herein we report the discovery of various spirooxindole and dibenzoxazepine constructs as potent MR antagonists. SAR analysis of our spirooxindole hit led to highly potent compounds containing polar solubilizing groups, which interact with the helix-11 region of the MR ligand binding domain (LBD). Various dibenzoxazepine moieties were also prepared in an effort to replace a known dibenzoxepane system which interacts with the hydrophobic region of the MR LBD. In addition, an X-ray crystal structure was obtained from a highly potent compound which was shown to exhibit both partial agonist and antagonist modes of action against MR.

The use of spirocyclic scaffolds in drug discovery.

Owing to their inherent three-dimensionality and structural novelty, spiro scaffolds have been increasingly utilized in drug discovery. In this brief review, we highlight selected examples from the primary medicinal chemistry literature during the last three years to demonstrate the versatility of spiro scaffolds. With recent progress in synthetic methods providing access to spiro building blocks, spiro scaffolds are likely to be used more frequently in drug discovery.

Structure-based design technology contour and its application to the design of renin inhibitors.

It is well-known that the structure-based design approach has had a measurable impact on the drug discovery process in identifying novel and efficacious therapeutic agents for a variety of disease targets. The de novo design approach has inherent potential to generate novel molecules that best fit into a protein binding site when compared to all of the computational methods applied to structure-based design. In its initial attempts, this approach did not achieve much success due to technical hurdles. More recently, the algorithmic advancements in the methodologies and clever strategies developed to design drug-like molecules have improved the success rate. We describe a state-of-the-art structure-based design technology called Contour and provide details of the algorithmic enhancements we have implemented. Contour was designed to create novel drug-like molecules by assembling synthetically viable fragments in the protein binding site using a high-resolution crystal structure of the protein. The technology consists of a sophisticated growth algorithm and a novel scoring function based on a directional model. The growth algorithm generates molecules by dynamically selecting only those fragments from the fragment library that are complementary to the binding site, and assembling them by sampling the conformational space for each attached fragment. The scoring function embodying the essential elements of the binding interactions aids in the rank ordering of grown molecules and helps identify those that have high probability of exhibiting activity against the protein target of interest. The application of Contour to identify inhibitors against human renin enzyme eventually leading to the clinical candidate VTP-27,999 will be discussed here.

Biphenyl/diphenyl ether renin inhibitors: filling the S1 pocket of renin via the S3 pocket.

Structure-based design led to the discovery of a novel class of renin inhibitors in which an unprecedented phenyl ring filling the S1 site is attached to the phenyl ring filling the S3 pocket. Optimization for several parameters including potency in the presence of human plasma, selectivity against CYP3A4 inhibition and improved rat oral bioavailability led to the identification of 8d which demonstrated antihypertensive efficacy in a transgenic rat model of human hypertension.

Optimization of orally bioavailable alkyl amine renin inhibitors.

Structure-guided drug design led to new alkylamine renin inhibitors with improved in vitro and in vivo potency. Lead compound 21a, has an IC(50) of 0.83nM for the inhibition of human renin in plasma (PRA). Oral administration of 21a at 10mg/kg resulted in >20h reduction of blood pressure in a double transgenic rat model of hypertension.

Spirocyclic ureas: orally bioavailable 11 beta-HSD1 inhibitors identified by computer-aided drug design.

Structure-guided drug design led to the identification of a class of spirocyclic ureas which potently inhibit human 11beta-HSD1 in vitro. Lead compound 10j was shown to be orally bioavailable in three species, distributed into adipose tissue in the mouse, and its (R) isomer 10j2 was efficacious in a primate pharmacodynamic model.

Discovery and optimization of adamantyl carbamate inhibitors of 11ß-HSD1.

Synthesis of 2-adamantyl carbamate derivatives of piperidines and pyrrolidines led to the discovery of 9a with an IC(50) of 15.2 nM against human 11ß-HSD1 in adipocytes. Optimization for increased adipocyte potency, metabolic stability and selectivity afforded 11k and 11l, both of which were >25% orally bioavailable in rat.

Design and optimization of renin inhibitors: Orally bioavailable alkyl amines.

Structure-based drug design led to the identification of a novel class of potent, low MW alkylamine renin inhibitors. Oral administration of lead compound 21l, with MW of 508 and IC(50) of 0.47nM, caused a sustained reduction in mean arterial blood pressure in a double transgenic rat model of hypertension.

Synthesis and biological activity of quinolinone and dihydroquinolinone p38 MAP kinase inhibitors.

Synthesis and biological activities of some quinolinone and dihydroquinolinone p38 MAP kinase inhibitors are reported. Modifications to the dihydroquinolinone pharmacophore revealed that dihydroquinolinone may be replaced with a quinolinone pharmacophore and lead to enhanced p38 inhibitory activity. From a study of C-7 substitutions by amino acid side chains, a very potent series of compounds in the p38 enzyme assays was identified. Translation of the in vitro activity into reasonable whole blood activity can be improved in this series of compounds by judicious modification of the physical properties at appropriate regions of the lead.

Discovery of a Novel, Orally Efficacious Liver X Receptor (LXR) ß Agonist.

This article describes the application of Contour to the design and discovery of a novel, potent, orally efficacious liver X receptor ß (LXRß) agonist (17). Contour technology is a structure-based drug design platform that generates molecules using a context perceptive growth algorithm guided by a contact sensitive scoring function. The growth engine uses binding site perception and programmable growth capability to create drug-like molecules by assembling fragments that naturally complement hydrophilic and hydrophobic features of the protein binding site. Starting with a crystal structure of LXRß and a docked 2-(methylsulfonyl)benzyl alcohol fragment (6), Contour was used to design agonists containing a piperazine core. Compound 17 binds to LXRß with high affinity and to LXRα to a lesser extent, and induces the expression of LXR target genes in vitro and in vivo. This molecule served as a starting point for further optimization and generation of a candidate which is currently in human clinical trials for treating atopic dermatitis.

A model for predicting likely sites of CYP3A4-mediated metabolism on drug-like molecules.

We have developed a rapid semiquantitative model for evaluating the relative susceptibilities of different sites on drug molecules to metabolism by cytochrome P450 3A4. The model is based on the energy necessary to remove a hydrogen radical from each site, plus the surface area exposure of the hydrogen atom. The energy of hydrogen radical abstraction is conventionally measured by AM1 semiempirical molecular orbital calculations. AM1 calculations show the following order of radical stabilities for the hydrogen atom abstractions: sp2 centers > heteroatom sp3 centers > carbon sp3 centers. Since AM1 calculations are too time intensive for routine work, we developed a statistical trend vector model, which is used to estimate the AM1 abstraction energy of a hydrogen atom from its local atomic environment. We carried out AM1 and trend vector calculations on 50 CYP3A4 substrates whose major sites of metabolism are known in the literature. A plot of the lowest hydrogen radical formation energy versus its sterically accessible surface area exposure for these 50 substrates shows that only those hydrogen atoms with solvent accessible surface area exposure > or = 8.0 A(2) are susceptible to CYP3A4-mediated metabolism. This approach forms the basis for our general model, which predicts sites on drugs that are susceptible to cytochrome P450 3A4-mediated hydrogen radical abstraction followed by a hydroxylation reaction. This model, in conjunction with specific enzyme site binding requirements, can aid in identifying possible sites of metabolism catalyzed by other cytochrome P450 enzymes.

Hybrid-designed inhibitors of p38 MAP kinase utilizing N-arylpyridazinones.

Imidazo[1,2-a]pyridyl N-arylpyridazinones were hybridized from the classic pyridinylimidazoles and the more recent dual hydrogen bond acceptors, resulting in a new structural class of selective p38 MAP kinase inhibitors.

A simple method for visualizing the differences between related receptor sites.

Pastor and Cruciani [J. Med. Chem. 38 (1995) 4637] and Kastenholz et al. [J. Med. Chem. 43 (2000) 3033] pioneered methods for comparing related receptors, with the ultimate goal of designing selective ligands. Such methods start with a reasonable superposition of high-resolution three-dimensional (3D) structures of the receptors. Next, molecular field maps are calculated for each receptor. Then the maps are analyzed to determine which map features are correlated with a particular subset of receptors. We present a method FLOGTV, based on the trend vector paradigm [J. Chem. Inf. Comput. Sci. 25 (1985) 64] to perform the analysis. This is mathematically simpler than the GRID/CPCA method of Kastenholz et al. and allows for the simultaneous comparison of many receptor structures. Also, the trend vector paradigm provides a method of selecting isopotential contours that are well above "noise". We demonstrate the method on four examples: HIV proteases versus two-domain acid proteases, thrombin versus trypsin and factor Xa, bacterial dihydrofolate reductases (DHFRs) versus vertebrate DHFRs, and P38 versus ERK protein kinases.

A simple method for visualizing the differences between related receptor sites.

Pastor and Cruciani [J. Med. Chem. 38 (1995) 4637] and Kastenholz et al. [J. Med. Chem. 43 (2000) 3033] pioneered methods for comparing related receptors, with the ultimate goal of designing selective ligands. Such methods start with a reasonable superposition of high-resolution three-dimensional (3D) structures of the receptors. Next, molecular field maps are calculated for each receptor. Then the maps are analyzed to determine which map features are correlated with a particular subset of receptors. We present a method FLOGTV, based on the trend vector paradigm [J. Chem. Inf. Comput. Sci. 25 (1985) 64] to perform the analysis. This is mathematically simpler than the GRID/CPCA method of Kastenholz et al. and allows for the simultaneous comparison of many receptor structures. Also, the trend vector paradigm provides a method of selecting isopotential contours that are well above "noise". We demonstrate the method on four examples: HIV proteases versus two-domain acid proteases, thrombin versus trypsin and factor Xa, bacterial dihydrofolate reductases (DHFRs) versus vertebrate DHFRs, and P38 versus ERK protein kinases.

The medicinal chemistry of liver X receptor (LXR) modulators.

LXRs have been of interest as targets for the treatment of atherosclerosis for over a decade. In recent years, LXR modulators have also garnered interest for potential use in the treatment of inflammation, Alzheimer's disease (AD), dermatological conditions, hepatic steatosis, and oncology. To date, no LXR modulator has successfully progressed beyond phase I clinical trials. In this Perspective, we summarize published medicinal chemistry efforts in the context of the available crystallographic data, druglikeness, and isoform selectivity. In addition, we discuss the challenges that need to be overcome before an LXR modulator can reach clinical use.

An electronic environment and contact direction sensitive scoring function for predicting affinities of protein-ligand complexes in Contour(®).

Contour(®) is a computational structure-based drug design technology that grows drug-like molecules by assembling context sensitive fragments in well-defined binding pockets. The grown molecules are scored by a novel empirical scoring function developed using high-resolution crystal structures of diverse classes of protein-ligand complexes and associated experimental binding affinities. An atomic model bearing features of the valence bond and VSEPR theories embodying their molecular electronic environment has been developed for non-covalent intermolecular interactions. On the basis of atomic hybridization and polarization states, each atom is modeled by features representing electron lone pairs, p-orbitals, and polar and non-polar hydrogens. A simple formal charge model was used to differentiate between polar and non-polar atoms. The interaction energy and the desolvation contribution of the protein-ligand association energy is computed as a linear sum of pair-wise interactions and desolvation terms. The pair-wise interaction energy captures short-range positive electrostatic interactions via hydrogen bonds, electrostatic repulsion of like charges, and non-bond contacts. The desolvation energy is estimated by calculating the energy required to desolvate interaction surfaces of the protein and the ligand in the complex. The scoring function predicts binding energies of a diverse set of protein-ligand complexes used for training with a correlation coefficient of 0.61. It also performs equally well in predicting association energies of a diverse validation set of protein-ligand complexes with a correlation coefficient of 0.57, which is equivalent to or better than 12 other scoring functions tested against this set including X-Score, GOLD, and DrugScore.