Regulation of pulmonary surfactant by the adhesion GPCR GPR116/ADGRF5 requires a tethered agonist-mediated activation mechanism.

The mechanistic details of the tethered agonist mode of activation for the adhesion GPCR ADGRF5/GPR116 have not been completely deciphered. We set out to investigate the physiological importance of autocatalytic cleavage upstream of the agonistic peptide sequence, an event necessary for NTF displacement and subsequent receptor activation. To examine this hypothesis, we characterized tethered agonist-mediated activation of GPR116 in vitro and in vivo. A knock-in mouse expressing a non-cleavable GPR116 mutant phenocopies the pulmonary phenotype of GPR116 knock-out mice, demonstrating that tethered agonist-mediated receptor activation is indispensable for function in vivo. Using site-directed mutagenesis and species-swapping approaches, we identified key conserved amino acids for GPR116 activation in the tethered agonist sequence and in extracellular loops 2/3 (ECL2/3). We further highlight residues in transmembrane 7 (TM7) that mediate stronger signaling in mouse versus human GPR116 and recapitulate these findings in a model supporting tethered agonist:ECL2 interactions for GPR116 activation.

CAVIAR: a method for automatic cavity detection, description and decomposition into subcavities.

The accurate description of protein binding sites is essential to the determination of similarity and the application of machine learning methods to relate the binding sites to observed functions. This work describes CAVIAR, a new open source tool for generating descriptors for binding sites, using protein structures in PDB and mmCIF format as well as trajectory frames from molecular dynamics simulations as input. The applicability of CAVIAR descriptors is showcased by computing machine learning predictions of binding site ligandability. The method can also automatically assign subcavities, even in the absence of a bound ligand. The defined subpockets mimic the empirical definitions used in medicinal chemistry projects. It is shown that the experimental binding affinity scales relatively well with the number of subcavities filled by the ligand, with compounds binding to more than three subcavities having nanomolar or better affinities to the target. The CAVIAR descriptors and methods can be used in any machine learning-based investigations of problems involving binding sites, from protein engineering to hit identification. The full software code is available on GitHub and a conda package is hosted on Anaconda cloud.

5,5- and 5,6-Membered Spirocyclic Indolinone Hit-Finding Libraries.

The production of two libraries based on spirocyclic indolinones is described. These libraries were selected from numerous spirocyclic indolinone scaffolds with a library evaluation procedure used routinely at Novartis, based on computed physicochemical properties and measured properties of prototype compounds. The library production yielded 176 and 428 compounds that could be isolated in sufficient amounts and purities based on two closely related scaffolds. The novelty and diversity analysis of these libraries shows their complementarity to the chemical space covered by the structures of the PubChem database.

Building Compound Archives for the Future.

Will the targets of the future be covered by the compound libraries of today? This communication will cover a critical review of past strategies before turning to a new measure of diversity, protein pockets. A fingerprint descriptor for pockets will be described.

Evaluation of a semi-automated workflow for fragment growing.

Intelligent Automatic Design (IADE) is an expert system developed at Novartis to identify nonclassical bioisosteres. In addition to bioisostere searching, one could also use IADE to grow a fragment bound to a protein. Here we report an evaluation of IADE as a tool for fragment growing. Three examples from the literature served as test cases. In all three cases, IADE generated close analogues of the published compounds and reproduced their crystallographic binding modes. This exercise validated the use of the IADE system for fragment growing. We have also gained experience in optimizing the performance of IADE for this type of application.

The quest for novel chemical matter and the contribution of computer-aided de novo design.

Identifying novel chemical matter is the focus of many drug discovery efforts. Through these efforts, computer-based de novo design of drug-like molecules, which aim to build an entire molecule 'from scratch', has emerged as a valuable approach to identify novel chemical matter. In this paper, the author discusses the recent research efforts that aim to build, in silico, more chemically accessible molecules, sample more efficiently the chemical space and rank the proposed molecules. The author reviews de novo design algorithms developed between 2008 and 2010 and the issue of validation, and highlights some recent successful applications of de novo design to drug discovery projects. Although research has addressed the lack of synthetic accessibility of the molecules proposed by the first generation of de novo design tools, the lack of accurate scoring function remains a major limitation of structure-based de novo design. However, de novo design is a valuable approach to generate either chemical starting points or ideas.

New pyrazolo[1,5a]pyrimidines as orally active inhibitors of Lck.

A novel series of pyrazolo[1,5a]pyrimidines was optimized to target lymphocyte-specific kinase (Lck). An efficient synthetic route was developed and SAR studies toward activity and selectivity are described, leading to Lck inhibitors with enzymatic, cellular and in vivo potency.

Structure-based chemogenomics: analysis of protein family landscapes.

Analysis of the three-dimensional structures of protein ligand complexes provides valuable insight into both the common interaction patterns within a target family and the discriminating features between the different members of a target family. Knowledge of the common interaction patterns helps to design target family focused chemical libraries for hit finding, while the discriminating features can be exploited to optimize the selectivity profile of a lead compound against particular member of a target family. Herein, we review the computational tools which have been developed to analyze crystal structures of members of a target family.

Insight into the structural determinants for selective inhibition of matrix metalloproteinases.

The matrix metalloproteinase (MMP) family has been a pharmaceutical target for over 20 years. Despite massive research and development efforts, only one MMP inhibitor (Periostat) has been approved by the FDA for the treatment of periodontal disease. Possible reasons for the low success rate of MMP inhibitors in the clinic include unwanted side effects caused by their lack of selectivity, poor oral bioavailability and decreased potency in vivo. We review how three-dimensional structures (3D) of MMP inhibitor complexes as well as the inhibition profile of compounds screened on MMP can be used to guide the optimization of selectivity of MMP inhibitors. Analysis of MMP 3D structures provides a ranking of their pockets on the basis of opportunities for selective interactions. One can use inhibition data to build pharmacophore or quantitative structure-activity models (QSAR) for virtual screening of libraries of novel MMP inhibitors. Combining protein- and ligand-based approaches, we conclude that targeting a single pocket is not always sufficient to achieve the desired selectivity profile. Finally, we also outline novel series of selective MMP inhibitors that exploit differences in the intrinsic flexibility of the catalytic domain to form selective interactions with a given MMP.

Binding site of a novel Kv1.5 blocker: a "foot in the door" against atrial fibrillation.

Kv1.5 channel blockers prolong atrial action potentials and may prevent atrial flutter or fibrillation without affecting ventricular repolarization. Here we characterize the mechanisms of action of 2'-{[2-(4-methoxy-phenyl)-acetylamino]-methyl}-biphenyl-2-carboxylic acid (2-pyridin-3-yl-ethyl)-amide (AVE0118) on Kv1.5 channels heterologously expressed in Xenopus laevis oocytes. Whole cell currents in oocytes were recorded using the two-microelectrode voltage clamp technique. AVE0118 blocked Kv1.5 current in oocytes with an IC50 of 5.6 microM. Block was enhanced by higher rates of stimulation, consistent with preferential binding of the drug to the open state of the channel. Ala-scanning mutagenesis of the pore domain of Kv1.5 identified the amino acids Thr479, Thr480, Val505, Ile508, Val512, and Val516 as important residues for block by AVE0118. A homology model of the pore region of Kv1.5 predicts that these six residues face toward the central cavity of the channel. In addition, mutation of two other S6 residues (Ile502 and Leu510) that are predicted to face away from the central cavity also diminished drug block. All these putative drug-binding residues are highly conserved in other Kv channels, explaining our finding that AVE0118 also blocked Kv1.3, Kv2.1, Kv3.1, and Kv4.3 channels with similar potency. Docking of AVE0118 into the inner cavity of a Kv1.5 pore homology model predicted an unusual binding mode. The drug aligned with the inner S6 alpha-helical domain in a manner predicted to block the putative activation gate. This "foot-in-the-door" binding mode is consistent with the observation that the drug slowed the rate of current deactivation, causing a crossover of tail current traces recorded before and after drug treatment.

Matrix metalloproteinase target family landscape: a chemometrical approach to ligand selectivity based on protein binding site analysis.

To gain insight into the structural determinants for the matrix metalloproteinase (MMP) family, we characterized the binding sites of 56 MMP structures and one TACE (tumor necrosis factor alpha converting enzyme) structure using molecular interaction fields (MIFs). These MIFs were produced by two approaches: the GRID force field and the knowledge-based potential DrugScore. The subsequent statistical analysis using consensus principal component analysis (CPCA) for the entire binding site and each subpockets revealed both approaches to encode similar information about discriminating regions. However, the relative importance of the probes varied between both approaches. The CPCA models provided the following ranking of the six subpockets based on the opportunity for selective interactions with different MMPs: S1' > S2, S3, S3' > S1, S2'. The interpretation of these models agreed with experimental binding modes inferred from crystal structures or docking.

Knowledge-driven lead discovery.

Virtual screening encompasses several computational approaches which have proven valuable for identifying novel leads. These approaches rely on available information. Herein, we review recent successful applications of virtual screening. The extension of virtual screening methodologies to target families is also briefly discussed.

The discovery of Kv1.5 blockers as a case study for the application of virtual screening approaches.

Different virtual screening techniques are available as alternatives to high throughput screening. These different techniques have been rarely used together on the same target. We had the opportunity to do so in order to discover novel blockers of the voltage-dependent potassium channel Kv1.5, a potential target for the treatment of atrial fibrillation. Our corporate database was searched, using a protein-based pharmacophore, derived from a homology model, as query. As a result, 244 molecules were screened in vitro, 19 of them (7.8%) were found to be active. Five of them, belonging to five different chemical classes, exhibited IC50 values under 10 microM. The performance of this structure-based virtual screening protocol has been compared with those of similarity and ligand-based pharmacophore searches. The analysis of the results supports the conventional wisdom of using as many virtual screening techniques as possible in order to maximize the chance of finding as many chemotypes as possible.

Structural basis for the highly selective inhibition of MMP-13.

Inhibitors for matrix metalloproteinases (MMPs) are under investigation for the treatment of cancer, arthritis, and cardiovascular disease. Here, we report a class of highly selective MMP-13 inhibitors (pyrimidine dicarboxamides) that exhibit no detectable activity against other MMPs. The high-resolution X-ray structures of three molecules of this series bound to MMP-13 reveal a novel binding mode characterized by the absence of interactions between the inhibitors and the catalytic zinc. The inhibitors bind in the S1' pocket and extend into an additional S1' side pocket, which is unique to MMP-13. We analyze the determinants for selectivity and describe the rational design of improved compounds with low nanomolar affinity.

Computational methods for the identification and optimisation of high quality leads.

Lead identification and optimisation have evolved into multidimensional, multidisciplinary and information-driven processes. Herein, we review the contribution of computational chemistry to these processes. We focus on computational approaches developed for modelling biopharmaceutical properties, including in vitro activity, selectivity, absorption, distribution, metabolism, excretion and toxicity. Whenever possible, successful applications are mentioned.

Pharmacophore-based search, synthesis, and biological evaluation of anthranilic amides as novel blockers of the Kv1.5 channel.

The search for novel, potent Kv1.5 blockers based on an anthranilic amide scaffold employing a pharmacophore-based virtual screening approach is described. The synthesis and structure-activity relationships (SAR) with respect to inhibition of the Kv1.5 channel are discussed. The most potent compounds display sub-micromolar inhibition of Kv1.5 and no significant effect on the HERG channel. In addition, good oral bioavailability is demonstrated for compound 3i in rats.

Molecular basis for Kv1.5 channel block: conservation of drug binding sites among voltage-gated K+ channels.

Kv1.5 channels conduct the ultrarapid delayed rectifier current (IKur) that contributes to action potential repolarization of human atrial myocytes. Block of these channels has been proposed as a treatment for atrial arrhythmias. Here we report a novel and potent inhibitor of Kv1.5 potassium channels, N-benzyl-N-pyridin-3-yl-methyl-2-(toluene-4-sulfonylamino)-benzamide hydrochloride (S0100176), which exhibits features consistent with preferential block of the open state. The IC50 of S0100176 for Kv1.5 expressed in Xenopus oocytes was 0.7 microm. Ala-scanning mutagenesis within the pore helix and the S6 segment, regions that form the walls of the central cavity, was combined with voltage clamp analysis to identify point mutations that altered drug affinity. This approach identified Thr-479, Thr-480, Val-505, Ile-508, and Val-512 as the most important residues for block by S0100176. Mutations of these key residues to Ala or other amino acids caused marked changes in the IC50 of S0100176 (p<0.01). For example, the IC50 of S0100176 increased 362-fold for T480A, 26-fold for V505A, 150-fold for I508A, and 99-fold for V512A. We used modeling to dock S0100176 into the inner cavity of a Kv1.5 pore homology model that was generated based on the crystal structure of KcsA. The docking predicted that the five residues identified by the Ala scan were positioned less than 4.5 A from the compound. Based on the homology models, the positions of the five amino acids identified to interact with S0100176 face toward the central cavity and overlap with putative binding sites for other blockers and voltage-gated potassium channels.

Identification, synthesis, and activity of novel blockers of the voltage-gated potassium channel Kv1.5.

The voltage-gated potassium channel Kv1.5 is regarded as a promising target for the development of new atrial selective drugs with fewer side effects. In the present study the discovery of ortho,ortho-disubstituted bisaryl compounds as blockers of the Kv1.5 channel is presented. Several compounds of this new class were synthesized and screened for their ability to block Kv1.5 channels expressed in Xenopus oocytes. The observed structure-activity relationship (SAR) is described by a pharmacophore model that consists of three hydrophobic centers in a triangular arrangement. The hydrophobic centers are matched by a phenyl or pyridyl ring of the bisaryl core and both ends of the side chains. The most potent compounds (e.g., 17c and 17o) inhibited the Kv1.5 channel with sub-micromolar half-blocking concentrations and displayed 3-fold selectivity over Kv1.3 and no significant effect on the HERG channel and sodium currents. In addition, compounds 17c and 17m have already shown antiarrhythmic effects in a pig model.

Peroxisome proliferator-activated receptors target family landscape: a chemometrical approach to ligand selectivity based on protein binding site analysis.

The Peroxisome Proliferator-Activated Receptors (PPARs) are nuclear receptors which over the last couple of years have been the focus of considerable research efforts aiming to identify compounds with well-defined selectivity profiles for the treatment of metabolic diseases. The ligand binding domains (LBD) of the three known PPAR subtypes exhibit between 60 and 70% sequence identity. To gain insight into the structural determinants of selectivity for the PPAR subtypes, a set of 13 crystal structures of PPAR LBD were classified, using the GRID/CPCA approach. As a result, nearly all of the crystal structures of each different PPAR subtype were found clustered in different regions of the CPCA score plots, and hydrophobic as well as steric interactions were identified as the major determinants of PPAR subtypes selectivity. Furthermore, interpretation of the GRID/CPCA model in structural terms led to the identification of LBD regions which could be targeted to improve the selectivity for a given PPAR subtype. Our findings are consistent with published structure-activity relationships for PPAR ligands as well as with site-directed mutagenesis results.