CACHE Challenge #1: Targeting the WDR Domain of LRRK2, A Parkinson's Disease Associated Protein.

The CACHE challenges are a series of prospective benchmarking exercises to evaluate progress in the field of computational hit-finding. Here we report the results of the inaugural CACHE challenge in which 23 computational teams each selected up to 100 commercially available compounds that they predicted would bind to the WDR domain of the Parkinson's disease target LRRK2, a domain with no known ligand and only an apo structure in the PDB. The lack of known binding data and presumably low druggability of the target is a challenge to computational hit finding methods.

Structures of synaptic vesicle protein 2A and 2B bound to anticonvulsants.

Epilepsy is a common neurological disorder characterized by abnormal activity of neuronal networks, leading to seizures. The racetam class of anti-seizure medications bind specifically to a membrane protein found in the synaptic vesicles of neurons called synaptic vesicle protein 2 (SV2) A (SV2A). SV2A belongs to an orphan subfamily of the solute carrier 22 organic ion transporter family that also includes SV2B and SV2C.

Cyclobutane-bearing restricted anchoring residues enabled geometry-specific hydrocarbon peptide stapling.

Stapled peptides are regarded as the promising next-generation therapeutics because of their improved secondary structure, membrane permeability and metabolic stability as compared with the prototype linear peptides. Usually, stapled peptides are obtained by a hydrocarbon stapling technique, anchoring from paired olefin-terminated unnatural amino acids and the consequent ring-closing metathesis (RCM). To investigate the adaptability of the rigid cyclobutane structure in RCM and expand the chemical diversity of hydrocarbon peptide stapling, we herein described the rational design and efficient synthesis of cyclobutane-based conformationally constrained amino acids, termed ()-1-amino-3-(but-3-en-1-yl)cyclobutane-1-carboxylic acid (E) and ()-1-amino-3-(but-3-en-1-yl)cyclobutane-1-carboxylic acid (Z).

Design and Preclinical Characterization Program toward Asundexian (BAY 2433334), an Oral Factor XIa Inhibitor for the Prevention and Treatment of Thromboembolic Disorders.

Activated coagulation factor XI (FXIa) is a highly attractive antithrombotic target as it contributes to the development and progression of thrombosis but is thought to play only a minor role in hemostasis so that its inhibition may allow for decoupling of antithrombotic efficacy and bleeding time prolongation. Herein, we report our major efforts to identify an orally bioavailable, reversible FXIa inhibitor. Using a protein structure-based design approach, we identified a novel micromolar hit with attractive physicochemical properties.

Target 2035 - an update on private sector contributions.

Target 2035, an international federation of biomedical scientists from the public and private sectors, is leveraging 'open' principles to develop a pharmacological tool for every human protein. These tools are important reagents for scientists studying human health and disease and will facilitate the development of new medicines. It is therefore not surprising that pharmaceutical companies are joining Target 2035, contributing both knowledge and reagents to study novel proteins.

CACHE (Critical Assessment of Computational Hit-finding Experiments): A public-private partnership benchmarking initiative to enable the development of computational methods for hit-finding.

One aspirational goal of computational chemistry is to predict potent and drug-like binders for any protein, such that only those that bind are synthesized. In this Roadmap, we describe the launch of Critical Assessment of Computational Hit-finding Experiments (CACHE), a public benchmarking project to compare and improve small molecule hit-finding algorithms through cycles of prediction and experimental testing. Participants will predict small molecule binders for new and biologically relevant protein targets representing different prediction scenarios.

Target 2035 - update on the quest for a probe for every protein.

Twenty years after the publication of the first draft of the human genome, our knowledge of the human proteome is still fragmented. The challenge of translating the wealth of new knowledge from genomics into new medicines is that proteins, and not genes, are the primary executers of biological function. Therefore, much of how biology works in health and disease must be understood through the lens of protein function.

Machine Learning Applied to the Modeling of Pharmacological and ADMET Endpoints.

The well-known concept of quantitative structure-activity relationships (QSAR) has been gaining significant interest in the recent years. Data, descriptors, and algorithms are the main pillars to build useful models that support more efficient drug discovery processes with in silico methods. Significant advances in all three areas are the reason for the regained interest in these models.

Design, Synthesis, and Pharmacological Characterization of a Neutral, Non-Prodrug Thrombin Inhibitor with Good Oral Pharmacokinetics.

Despite extensive research on small molecule thrombin inhibitors for oral application in the past decades, only a single double prodrug with very modest oral bioavailability has reached human therapy as a marketed drug. We have undertaken major efforts to identify neutral, non-prodrug inhibitors. Using a holistic analysis of all available internal data, we were able to build computational models and apply these for the selection of a lead series with the highest possibility of achieving oral bioavailability.

Druggability Assessment for Selected Serine Proteases in a Pharmaceutical Industry Setting.

Target druggability assessment is an integral part of the early target characterization and selection process in pharmaceutical industry. Here, we investigate a set of five different serine proteases from the blood coagulation cascade. The aim of this study is twofold.

Bayer's in silico ADMET platform: a journey of machine learning over the past two decades.

Over the past two decades, an in silico absorption, distribution, metabolism, and excretion (ADMET) platform has been created at Bayer Pharma with the goal to generate models for a variety of pharmacokinetic and physicochemical endpoints in early drug discovery. These tools are accessible to all scientists within the company and can be a useful in assisting with the selection and design of novel leads, as well as the process of lead optimization. Here.

Structure-Permeability Relationship of Semipeptidic Macrocycles-Understanding and Optimizing Passive Permeability and Efflux Ratio.

We herein report the first thorough analysis of the structure-permeability relationship of semipeptidic macrocycles. In total, 47 macrocycles were synthesized using a hybrid solid-phase/solution strategy, and then their passive and cellular permeability was assessed using the parallel artificial membrane permeability assay (PAMPA) and Caco-2 assay, respectively. The results indicate that semipeptidic macrocycles generally possess high passive permeability based on the PAMPA, yet their cellular permeability is governed by efflux, as reported in the Caco-2 assay.

Prediction of Oral Bioavailability in Rats: Transferring Insights from in Vitro Correlations to (Deep) Machine Learning Models Using in Silico Model Outputs and Chemical Structure Parameters.

Oral administration of drug products is a strict requirement in many medical indications. Therefore, bioavailability prediction models are of high importance for prioritization of compound candidates in the drug discovery process. However, oral exposure and bioavailability are difficult to predict, as they are the result of various highly complex factors and/or processes influenced by the physicochemical properties of a compound, such as solubility, lipophilicity, or charge state, as well as by interactions with the organism, for instance, metabolism or membrane permeation.

An approach towards enhancement of a screening library: The Next Generation Library Initiative (NGLI) at Bayer - against all odds?

Pharmaceutical companies often refer to 'screening their library' when performing high-throughput screening (HTS) on a corporate compound collection to identify lead structures for small-molecule drug discovery programs. Characteristics of such a library, including the size, chemical space covered, and physicochemical properties, often determine the success of a screening campaign. Therefore, strategies to maintain and enhance the overall quality of screening collections are crucial to stay competitive and to cope with the 'novelty erosion' that is observed gradually.

Reliable and Performant Identification of Low-Energy Conformers in the Gas Phase and Water.

Prediction of compound properties from structure via quantitative structure-activity relationship and machine-learning approaches is an important computational chemistry task in small-molecule drug research. Though many such properties are dependent on three-dimensional structures or even conformer ensembles, the majority of models are based on descriptors derived from two-dimensional structures. Here we present results from a thorough benchmark study of force field, semiempirical, and density functional methods for the calculation of conformer energies in the gas phase and water solvation as a foundation for the correct identification of relevant low-energy conformers.

Computational Chemistry in the Pharmaceutical Industry: From Childhood to Adolescence.

Computational chemistry within the pharmaceutical industry has grown into a field that proactively contributes to many aspects of drug design, including target selection and lead identification and optimization. While methodological advancements have been key to this development, organizational developments have been crucial to our success as well. In particular, the interaction between computational and medicinal chemistry and the integration of computational chemistry into the entire drug discovery process have been invaluable.

Finerenone Impedes Aldosterone-dependent Nuclear Import of the Mineralocorticoid Receptor and Prevents Genomic Recruitment of Steroid Receptor Coactivator-1.

Aldosterone regulates sodium homeostasis by activating the mineralocorticoid receptor (MR), a member of the nuclear receptor superfamily. Hyperaldosteronism leads todeleterious effects on the kidney, blood vessels, and heart. Although steroidal antagonists such as spironolactone and eplerenone are clinically useful for the treatment of cardiovascular diseases, they are associated with several side effects.

Best of both worlds: combining pharma data and state of the art modeling technology to improve in Silico pKa prediction.

In a unique collaboration between a software company and a pharmaceutical company, we were able to develop a new in silico pKa prediction tool with outstanding prediction quality. An existing pKa prediction method from Simulations Plus based on artificial neural network ensembles (ANNE), microstates analysis, and literature data was retrained with a large homogeneous data set of drug-like molecules from Bayer. The new model was thus built with curated sets of ∼14,000 literature pKa values (∼11,000 compounds, representing literature chemical space) and ∼19,500 pKa values experimentally determined at Bayer Pharma (∼16,000 compounds, representing industry chemical space).

Binding Free Energy Calculations for Lead Optimization: Assessment of Their Accuracy in an Industrial Drug Design Context.

Correctly ranking compounds according to their computed relative binding affinities will be of great value for decision making in the lead optimization phase of industrial drug discovery. However, the performance of existing computationally demanding binding free energy calculation methods in this context is largely unknown. We analyzed the performance of the molecular mechanics continuum solvent, the linear interaction energy (LIE), and the thermodynamic integration (TI) approach for three sets of compounds from industrial lead optimization projects.

The lab oddity prevails: discovery of pan-CDK inhibitor (R)-S-cyclopropyl-S-(4-{[4-{[(1R,2R)-2-hydroxy-1-methylpropyl]oxy}-5-(trifluoromethyl)pyrimidin-2-yl]amino}phenyl)sulfoximide (BAY 1000394) for the treatment of cancer.

Lead optimization of a high-throughput screening hit led to the rapid identification of aminopyrimidine ZK 304709, a multitargeted CDK and VEGF-R inhibitor that displayed a promising preclinical profile. Nevertheless, ZK 304709 failed in phase I studies due to dose-limited absorption and high inter-patient variability, which was attributed to limited aqueous solubility and off-target activity against carbonic anhydrases. Further lead optimization efforts to address the off-target activity profile finally resulted in the introduction of a sulfoximine group, which is still a rather unusual approach in medicinal chemistry.

Discovery of BAY 94-8862: a nonsteroidal antagonist of the mineralocorticoid receptor for the treatment of cardiorenal diseases.

Aldosterone is a hormone that exerts manifold deleterious effects on the kidneys, blood vessels, and heart which can lead to pathophysiological consequences. Inhibition of the mineralocorticoid receptor (MR) is a proven therapeutic concept for the management of associated diseases. Use of the currently marketed MR antagonists spironolactone and eplerenone is restricted, however, due to a lack of selectivity in spironolactone and the lower potency and efficacy of eplerenone.

Utility of protein structures in overcoming ADMET-related issues of drug-like compounds.

The number of solved X-ray structures of proteins relevant for ADMET processes of drug molecules has increased remarkably over recent years. In principle, this development offers the possibility to complement the quantitative structure-property relationship (QSPR)-dominated repertoire of in silico ADMET methods with protein-structure-based approaches. However, the complex nature and the weak nonspecific ligand-binding properties of ADMET proteins take structural biology methods and current docking programs to the limit.

Rendezvous in chemical space? Comparing the small molecule compound libraries of Bayer and Schering.

Here, we compare the entire compound collections of Bayer HealthCare and Schering AG with respect to structural identities, similarities and physico-chemical properties. We discuss possible consequences stemming from unexpected findings in light of new collaborative models in pharmaceutical research.

Oral, direct thrombin and factor Xa inhibitors: the replacement for warfarin, leeches, and pig intestines?

To prevent thromboses after surgery, patients have until now had to inject themselves daily with heparin. For stroke prophylaxis in atrial fibrillation, patients take vitamin K antagonists of the coumarin type, which have a narrow therapeutic window and whose dosage must be regularly monitored. In order to improve the standard of therapy in thromboembolic diseases such as deep-vein thrombosis, pulmonary embolism, and stroke in atrial fibrillation, intensive research has been carried out over the last decade in the search for new, orally active thrombin and factor Xa inhibitors.