Discovery of a Novel Mutant-Selective Epidermal Growth Factor Receptor Inhibitor Using an Enabled Drug Discovery Platform.

Despite the success of first, second, and third generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) for non-small cell lung cancer with classical EGFR mutations (L858R or Exon 19 deletions), disease progression occurs due to the acquisition of T790M and C797S resistance. Herein, we report a physics-based computationally driven lead identification approach that identified structurally unique imidazo[3.2-]pyrazoles as reversible and wild-type-sparing EGFR TKIs of classical mutations bearing both T790M and C797S.

Optimization and Mechanistic Investigations of Novel Allosteric Activators of PKG1α.

Activation of PKG1α is a compelling strategy for the treatment of cardiovascular diseases. As the main effector of cyclic guanosine monophosphate (cGMP), activation of PKG1α induces smooth muscle relaxation in blood vessels, lowers pulmonary blood pressure, prevents platelet aggregation, and protects against cardiac stress. The development of activators has been mostly limited to cGMP mimetics and synthetic peptides.

Structural basis for isoform-specific inhibition of human CTPS1.

Cytidine triphosphate synthase 1 (CTPS1) is necessary for an effective immune response, as revealed by severe immunodeficiency in CTPS1-deficient individuals [E. Martin ], [] [510], [288-292] ([2014]). CTPS1 expression is up-regulated in activated lymphocytes to expand CTP pools [E.

Discovery of the First Non-cGMP Mimetic Small Molecule Activators of cGMP-Dependent Protein Kinase 1 α (PKG1α).

PKG1α is a central node in cGMP signaling. Current therapeutics that look to activate this pathway rely on elevation of cGMP levels and subsequent activation of PKG1α. Direct activation of PKG1α could potentially drive additional efficacy without associated side effects of blanket cGMP elevation.

MAIP: a web service for predicting blood-stage malaria inhibitors.

Malaria is a disease affecting hundreds of millions of people across the world, mainly in developing countries and especially in sub-Saharan Africa. It is the cause of hundreds of thousands of deaths each year and there is an ever-present need to identify and develop effective new therapies to tackle the disease and overcome increasing drug resistance. Here, we extend a previous study in which a number of partners collaborated to develop a consensus in silico model that can be used to identify novel molecules that may have antimalarial properties.

Development of indazole mineralocorticoid receptor antagonists and investigation into their selective late-stage functionalization.

The derivatization of pharmaceuticals is a core activity in the discovery and development of new medicines. Late-stage functionalization via modern CH functionalization chemistry has emerged as a powerful technique with which to diversify advanced pharmaceutical intermediates. We report herein a case study in late-stage functionalization towards the development of a new class of indazole-based mineralocorticoid receptor antagonists (MRA).

Accelerating the discovery of DGAT1 inhibitors through the application of parallel medicinal chemistry (PMC).

The parallel medicinal chemistry (PMC) was effectively applied to accelerate the optimization of diacylglycerol O-acyltransferase I (DGAT-1) inhibitors. Through a highly collaborative and iterative library design, synthesis and testing, a benzimidazole lead was rapidly and systematically advanced to a highly potent, selective and bioavailable DGAT1 inhibitor with the potential for further development.

Benzimidazole-based DGAT1 inhibitors with a [3.1.0] bicyclohexane carboxylic acid moiety.

Previously disclosed benzimidazole-based DGAT1 inhibitors containing a cyclohexane carboxylic acid moiety suffer from isomerization at the alpha position of the carboxylic acid group, generating active metabolites which exhibit DGAT1 inhibition comparable to the corresponding parent compounds. In this report, we describe the design, synthesis and profiling of benzimidazole-based DGAT1 inhibitors with a [3.1.

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort.

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds.

Performance of multiple docking and refinement methods in the pose prediction D3R prospective Grand Challenge 2016.

We describe the performance of multiple pose prediction methods for the D3R 2016 Grand Challenge. The pose prediction challenge includes 36 ligands, which represent 4 chemotypes and some miscellaneous structures against the FXR ligand binding domain. In this study we use a mix of fully automated methods as well as human-guided methods with considerations of both the challenge data and publicly available data.

Is Multitask Deep Learning Practical for Pharma?

Multitask deep learning has emerged as a powerful tool for computational drug discovery. However, despite a number of preliminary studies, multitask deep networks have yet to be widely deployed in the pharmaceutical and biotech industries. This lack of acceptance stems from both software difficulties and lack of understanding of the robustness of multitask deep networks.

Informing the Selection of Screening Hit Series with in Silico Absorption, Distribution, Metabolism, Excretion, and Toxicity Profiles.

High-throughput screening (HTS) has enabled millions of compounds to be assessed for biological activity, but challenges remain in the prioritization of hit series. While biological, absorption, distribution, metabolism, excretion, and toxicity (ADMET), purity, and structural data are routinely used to select chemical matter for further follow-up, the scarcity of historical ADMET data for screening hits limits our understanding of early hit compounds. Herein, we describe a process that utilizes a battery of in-house quantitative structure-activity relationship (QSAR) models to generate in silico ADMET profiles for hit series to enable more complete characterizations of HTS chemical matter.

Discovery of indazole aldosterone synthase (CYP11B2) inhibitors as potential treatments for hypertension.

We report the discovery and hit-to-lead optimization of a structurally novel indazole series of CYP11B2 inhibitors. Benchmark compound 34 from this series displays potent inhibition of CYP11B2, high selectivity versus related steroidal and hepatic CYP targets, and lead-like physical and pharmacokinetic properties. On the basis of these and other data, the indazole series was progressed to lead optimization for further refinement.

Shared Consensus Machine Learning Models for Predicting Blood Stage Malaria Inhibition.

The development of new antimalarial therapies is essential, and lowering the barrier of entry for the screening and discovery of new lead compound classes can spur drug development at organizations that may not have large compound screening libraries or resources to conduct high-throughput screens. Machine learning models have been long established to be more robust and have a larger domain of applicability with larger training sets. Screens over multiple data sets to find compounds with potential malaria blood stage inhibitory activity have been used to generate multiple Bayesian models.

Microscale High-Throughput Experimentation as an Enabling Technology in Drug Discovery: Application in the Discovery of (Piperidinyl)pyridinyl-1H-benzimidazole Diacylglycerol Acyltransferase 1 Inhibitors.

Miniaturization and parallel processing play an important role in the evolution of many technologies. We demonstrate the application of miniaturized high-throughput experimentation methods to resolve synthetic chemistry challenges on the frontlines of a lead optimization effort to develop diacylglycerol acyltransferase (DGAT1) inhibitors. Reactions were performed on ∼1 mg scale using glass microvials providing a miniaturized high-throughput experimentation capability that was used to study a challenging SAr reaction.

Discovery of Spirocyclic Aldosterone Synthase Inhibitors as Potential Treatments for Resistant Hypertension.

Herein we report the discovery and hit-to-lead optimization of a series of spirocyclic piperidine aldosterone synthase (CYP11B2) inhibitors. Compounds from this series display potent CYP11B2 inhibition, good selectivity versus related CYP enzymes, and lead-like physical and pharmacokinetic properties.

Discovery of Chromane Propionic Acid Analogues as Selective Agonists of GPR120 with Activity in Rodents.

GPR120 (FFAR4) is a fatty acid sensing G protein coupled receptor (GPCR) that has been identified as a target for possible treatment of type 2 diabetes. A selective activator of GPR120 containing a chromane scaffold has been designed, synthesized, and evaluated . Results of these efforts suggest that chromane propionic acid is a suitable tool molecule for further animal studies.

Discovery and Pharmacology of a Novel Class of Diacylglycerol Acyltransferase 2 Inhibitors.

DGAT2 plays a critical role in hepatic triglyceride production, and data suggests that inhibition of DGAT2 could prove to be beneficial in treating a number of disease states. This article documents the discovery and optimization of a selective small molecule inhibitor of DGAT2 as well as pharmacological proof of biology in a mouse model of triglyceride production.

Discovery of Triazole CYP11B2 Inhibitors with in Vivo Activity in Rhesus Monkeys.

Hit-to-lead efforts resulted in the discovery of compound 19, a potent CYP11B2 inhibitor that displays high selectivity vs related CYPs, good pharmacokinetic properties in rat and rhesus, and lead-like physical properties. In a rhesus pharmacodynamic model, compound 19 displays robust, dose-dependent aldosterone lowering efficacy, with no apparent effect on cortisol levels.

Discovery of Benzimidazole CYP11B2 Inhibitors with in Vivo Activity in Rhesus Monkeys.

We report the discovery of a benzimidazole series of CYP11B2 inhibitors. Hit-to-lead and lead optimization studies identified compounds such as 32, which displays potent CYP11B2 inhibition, high selectivity versus related CYP targets, and good pharmacokinetic properties in rat and rhesus. In a rhesus pharmacodynamic model, 32 produces dose-dependent aldosterone lowering efficacy, with no apparent effect on cortisol levels.

Pyrazoles as non-classical bioisosteres in prolylcarboxypeptidase (PrCP) inhibitors.

Bioisosteres are integral components of modern pharmaceutical research that allow structural optimization to maximize in vivo efficacy and minimize adverse effects by selectively modifying pharmacodynamic, pharmacokinetic and physicochemical properties. A recent medicinal chemistry campaign focused on identifying small molecule inhibitors of prolylcarboxypeptidase (PrCP) initiated an investigation into the use of pyrazoles as bioisosteres for amides. The results indicate that pyrazoles are suitable bioisosteric replacements of amide functional groups.

Identification and characterization of sebaceous gland atrophy-sparing DGAT1 inhibitors.

Inhibition of Diacylglycerol O-acyltransferase 1 (DGAT1) has been a mechanism of interest for metabolic disorders. DGAT1 inhibition has been shown to be a key regulator in an array of metabolic pathways; however, based on the DGAT1 KO mouse phenotype the anticipation is that pharmacological inhibition of DGAT1 could potentially lead to skin related adverse effects. One of the aims in developing small molecule DGAT1 inhibitors that target key metabolic tissues is to avoid activity on skin-localized DGAT1 enzyme.

Discovery and optimization of orally active cyclohexane-based prolylcarboxypeptidase (PrCP) inhibitors.

The synthesis, SAR, binding affinities and pharmacokinetic profiles are described for a series of cyclohexane-based prolylcarboxypeptidase (PrCP) inhibitors discovered by high throughput screening. Compounds show high levels of ex vivo target engagement in mouse plasma 20 h post oral dose.

Mutagenesis and functional studies with succinate dehydrogenase inhibitors in the wheat pathogen Mycosphaerella graminicola.

A range of novel carboxamide fungicides, inhibitors of the succinate dehydrogenase enzyme (SDH, EC 1.3.5.

QSAR Prediction of Passive Permeability in the LLC-PK1 Cell Line: Trends in Molecular Properties and Cross-Prediction of Caco-2 Permeabilities.

A QSAR model for predicting passive permeability (Papp ) was derived from Papp values measured in the LLC-PK1 cell line. The QSAR method and descriptor set that performed best in terms of cross-validation was random forest with a combination of AP, DP, and MOE_2D descriptors. The QSAR model was used to predict the Caco-2 cell permeability for 313 compounds described in the literature with good success.