Identification of TAK-756, A Potent TAK1 Inhibitor for the Treatment of Osteoarthritis through Intra-Articular Administration.

Osteoarthritis (OA) is a chronic and degenerative joint disease affecting more than 500 million patients worldwide with no disease-modifying treatment approved to date. Several publications report on the transforming growth factor β-activated kinase 1 (TAK1) as a potential molecular target for OA, with complementary anti-catabolic and anti-inflammatory effects. We report herein on the development of TAK1 inhibitors with physicochemical properties suitable for intra-articular injection, with the aim to achieve high drug concentration at the affected joint, while avoiding severe toxicity associated with systemic inhibition.

Nonclassical Zwitterions as a Design Principle to Reduce Lipophilicity without Impacting Permeability.

The ionization of bioactive molecules impacts many ADME-relevant physicochemical properties, in particular, solubility, lipophilicity, and permeability. Ampholytes contain both acidic and basic groups and are distinguished as ordinary ampholytes and zwitterions. An influential review states that zwitterions only exist if the acidic p is significantly lower than the basic p.

Reactivities of acrylamide warheads toward cysteine targets: a QM/ML approach to covalent inhibitor design.

Covalent inhibition offers many advantages over non-covalent inhibition, but covalent warhead reactivity must be carefully balanced to maintain potency while avoiding unwanted side effects. While warhead reactivities are commonly measured with assays, a computational model to predict warhead reactivities could be useful for several aspects of the covalent inhibitor design process. Studies have shown correlations between covalent warhead reactivities and quantum mechanic (QM) properties that describe important aspects of the covalent reaction mechanism.

Quantitative and functional characterisation of extracellular vesicles after passive loading with hydrophobic or cholesterol-tagged small molecules.

Extracellular vesicles (EVs) are nanosized intercellular messengers that bear enormous application potential as biological drug delivery vehicles. Much progress has been made for loading or decorating EVs with proteins, peptides or RNAs using genetically engineered donor cells, but post-isolation loading with synthetic drugs and using EVs from natural sources remains challenging. In particular, quantitative and unambiguous data assessing whether and how small molecules associate with EVs versus other components in the samples are still lacking.

Lessons for Oral Bioavailability: How Conformationally Flexible Cyclic Peptides Enter and Cross Lipid Membranes.

Cyclic peptides extend the druggable target space due to their size, flexibility, and hydrogen-bonding capacity. However, these properties impact also their passive membrane permeability. As the "journey" through membranes cannot be monitored experimentally, little is known about the underlying process, which hinders rational design.

Integrated and automated high-throughput purification of libraries on microscale.

We herein report the development of an automation platform for rapid purification and quantification of chemical libraries including reformatting of chemical matter to 10 mM DMSO stock solutions. This fully integrated workflow features tailored conditions for preparative reversed-phase (RP) HPLC-MS on microscale based on analytical data, online fraction QC and CAD-based quantification as well as automated reformatting to enable rapid purification of chemical libraries. This automated workflow is entirely solution-based, eliminating the need to weigh or handle solids.

Polar/apolar interfaces modulate the conformational behavior of cyclic peptides with impact on their passive membrane permeability.

Cyclic peptides have the potential to vastly extend the scope of druggable proteins and lead to new therapeutics for currently untreatable diseases. However, cyclic peptides often suffer from poor bioavailability. To uncover design principles for permeable cyclic peptides, a promising strategy is to analyze the conformational dynamics of the peptides using molecular dynamics (MD) and Markov state models (MSMs).

Effect of Flexibility, Lipophilicity, and the Location of Polar Residues on the Passive Membrane Permeability of a Series of Cyclic Decapeptides.

Cyclic peptides have received increasing attention over the recent years as potential therapeutics for "undruggable" targets. One major obstacle is, however, their often relatively poor bioavailability. Here, we investigate the structure-permeability relationship of 24 cyclic decapeptides that share the same backbone N-methylation pattern but differ in their side chains.

ReSCoSS: a flexible quantum chemistry workflow identifying relevant solution conformers of drug-like molecules.

Conformational equilibria are at the heart of drug design, yet their energetic description is often hampered by the insufficient accuracy of low-cost methods. Here we present a flexible and semi-automatic workflow based on quantum chemistry, ReSCoSS, designed to identify relevant conformers and predict their equilibria across different solvent environments in the Conductor-like Screening Model for Real Solvents (COSMO-RS) framework. We demonstrate the utility and accuracy of the workflow through conformational case studies on several drug-like molecules from literature where relevant conformations are known.

Prediction of p Using Machine Learning Methods with Rooted Topological Torsion Fingerprints: Application to Aliphatic Amines.

The acid-base dissociation constant, p, is a key parameter to define the ionization state of a compound and directly affects its biopharmaceutical profile. In this study, we developed a novel approach for p prediction using rooted topological torsion fingerprints in combination with five machine learning (ML) methods: random forest, partial least squares, extreme gradient boosting, lasso regression, and support vector regression. With a large and diverse set of 14 499 experimental p values, p models were developed for aliphatic amines.

High accuracy quantum-chemistry-based calculation and blind prediction of macroscopic pKa values in the context of the SAMPL6 challenge.

Recent advances in the development of low-cost quantum chemical methods have made the prediction of conformational preferences and physicochemical properties of medium-sized drug-like molecules routinely feasible, with significant potential to advance drug discovery. In the context of the SAMPL6 challenge, macroscopic pKa values were blindly predicted for a set of 24 of such molecules. In this paper we present two similar quantum chemical based approaches based on the high accuracy calculation of standard reaction free energies and the subsequent determination of those pKa values via a linear free energy relationship.

Developing Collaborative QSAR Models Without Sharing Structures.

It is widely understood that QSAR models greatly improve if more data are used. However, irrespective of model quality, once chemical structures diverge too far from the initial data set, the predictive performance of a model degrades quickly. To increase the applicability domain we need to increase the diversity of the training set.

Benefit of Retraining pKa Models Studied Using Internally Measured Data.

The ionization state of drugs influences many pharmaceutical properties such as their solubility, permeability, and biological activity. It is therefore important to understand the structure property relationship for the acid-base dissociation constant pKa during the lead optimization process to make better-informed design decisions. Computational approaches, such as implemented in MoKa, can help with this; however, they often predict with too large error especially for proprietary compounds.

What is modulating solubility in simulated intestinal fluids?

The aim of this study was to understand which parameters are responsible for the selective modulation of compounds solubility in simulated intestinal fluids. The solubility of 25 chemically diverse reference compounds was measured in simulated intestinal fluid (FaSSIF-V2) and in aqueous phosphate and maleate buffers. Electrostatic interactions between compounds and the bio-relevant medium components seem to explain the different solubility behavior observed for acids and bases.