Harmonised high throughput microsomal stability assay

High-Throughput Drug Stability Assessment via Biomimetic Metalloporphyrin-Catalyzed Reactions Using Laser-Assisted Rapid Evaporative Ionization Mass Spectrometry (LA-REIMS)

Background: Building extensive drug candidate libraries as early in the development pipeline as possible, with high-throughput in vitro absorption, distribution, metabolism, and excretion (ADME) profiling, is crucial for the selection of lead compounds to guide subsequent research and production phases. Traditionally, the analysis of metabolic stability assays heavily relies on high-throughput LC-MS/MS (liquid chromatography tandem mass spectrometry) techniques to meet with the lead profiling demands. Laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS) is a quick and efficient technique for characterizing complex biological samples without laborious sample preparation. Objective: In this study, using an automated LA-REIMS well plate reader, achieving an 8 s per sample measurement time, the oxidative metabolic stability of active drug agents was assessed using biomimetic metalloporphyrin-based oxidative model reactions. Results: The results obtained using the novel LA-REIMS-based protocol were compared to and corroborated by those obtained using conventional HPLC-UV-MS (high performance liquid chromatography with ultra-violet detection coupled with mass spectrometry) measurements. Conclusions: LA-REIMS emerges as a promising technique, demonstrating potential suitability for semi-quantitative high-throughput metabolic stability in an optimized solvent environment.

A new workflow for the effective curation of membrane permeability data from open ADME information

Membrane permeability is an in vitro parameter that represents the apparent permeability (Papp) of a compound, and is a key absorption, distribution, metabolism, and excretion parameter in drug development. Although the Caco-2 cell lines are the most used cell lines to measure Papp, other cell lines, such as the Madin-Darby Canine Kidney (MDCK), LLC-Pig Kidney 1 (LLC-PK1), and Ralph Russ Canine Kidney (RRCK) cell lines, can also be used to estimate Papp. Therefore, constructing in silico models for Papp estimation using the MDCK, LLC-PK1, and RRCK cell lines requires collecting extensive amounts of in vitro Papp data. An open database offers extensive measurements of various compounds covering a vast chemical space; however, concerns were reported on the use of data published in open databases without the appropriate accuracy and quality checks. Ensuring the quality of datasets for training in silico models is critical because artificial intelligence (AI, including deep learning) was used to develop models to predict various pharmacokinetic properties, and data quality affects the performance of these models. Hence, careful curation of the collected data is imperative. Herein, we developed a new workflow that supports automatic curation of Papp data measured in the MDCK, LLC-PK1, and RRCK cell lines collected from ChEMBL using KNIME. The workflow consisted of four main phases. Data were extracted from ChEMBL and filtered to identify the target protocols. A total of 1661 high-quality entries were retained after checking 436 articles. The workflow is freely available, can be updated, and has high reusability. Our study provides a novel approach for data quality analysis and accelerates the development of helpful in silico models for effective drug discovery. Scientific Contribution: The cost of building highly accurate predictive models can be significantly reduced by automating the collection of reliable measurement data. Our tool reduces the time and effort required for data collection and will enable researchers to focus on constructing high-performance in silico models for other types of analysis. To the best of our knowledge, no such tool is available in the literature.

Preclinical characterization of CPL304110 as a potent and selective inhibitor of fibroblast growth factor receptors 1, 2, and 3 for gastric, bladder, and squamous cell lung cancer

Fibroblast Growth Factor Receptors (FGFRs) are a family of receptor tyrosine kinases expressed on a plethora of cell membranes. They play crucial roles in both embryonic development and adult tissue functions. There is an increasing amount of evidence that FGFR-mediated oncogenesis is mainly related to gene amplification, activating mutations, or translocation in tumors of various histological types. Dysregulation of FGFRs has been implicated in a wide variety of neoplasms, such as bladder, gastric, and lung cancers. Given their functional significance, FGFRs emerge as promising targets for cancer therapy. Here, we introduce CPL304100, an innovative and highly potent FGFR1-3 kinase inhibitor demonstrating excellent in vitro biological activity. Comprehensive analyses encompassed kinase assays, cell line evaluations, PK/PD studies surface plasmon resonance studies, molecular docking, and in vivo testing in mouse xenografts. CPL304110 exhibited a distinctive binding profile to FGFR1/2/3 kinase domains, accompanied by a good safety profile and favorable ADMET parameters. Selective inhibition of tumor cell lines featuring active FGFR signaling was observed, distinguishing it from cell lines lacking FGFR aberrations (FGFR1, 2, and 3). CPL304110 demonstrated efficacy in both FGFR-dependent cell lines and patient-derived tumor xenograft (PDTX) in vivo models. Comparative analyses with FDA-approved FGFR inhibitors, erdafitinib and pemigatinib, revealed certain advantages of CPL304110 in both in vitro and in vivo assessments. Encouraging preclinical results led the way for the initiation of a Phase I clinical trial (01FGFR2018; NCT04149691) to further evaluate CPL304110 as a novel anticancer therapy.

Harnessing the Role of HDAC6 in Idiopathic Pulmonary Fibrosis: Design, Synthesis, Structural Analysis, and Biological Evaluation of Potent Inhibitors

Idiopathic pulmonary fibrosis (IPF) is an interstitial lung disease characterized by a progressive-fibrosing phenotype. IPF has been associated with aberrant HDAC activities confirmed by our immunohistochemistry studies on HDAC6 overexpression in IPF lung tissues. We herein developed a series of novel hHDAC6 inhibitors, having low inhibitory potency over hHDAC1 and hHDAC8, as potential pharmacological tools for IPF treatment. Their inhibitory potency was combined with low in vitro and in vivo toxicity. Structural analysis of 6h and structure-activity relationship studies contributed to the optimization of the binding mode of the new molecules. The best-performing analogues were tested for their efficacy in inhibiting fibrotic sphere formation and cell viability, proving their capability in reverting the IPF phenotype. The efficacy of analogue 6h was also determined in a validated human lung model of TGF-β1-dependent fibrogenesis. The results highlighted in this manuscript may pave the way for the identification of first-in-class molecules for the treatment of IPF.

[Predict of metabolic stability of xenobiotics by the PASS and GUSAR programs]

Metabolic stability refers to the susceptibility of compounds to the biotransformation; it is characterized by such pharmacokinetic parameters as half-life (T1/2) and clearance (CL). Generally, these parameters are estimated by in vitro assays, which are based on cells or subcellular fractions (mainly liver microsomal enzymes) and serve as models of the processes occurring in living organisms. Data obtained from the experiments are used to build QSAR (Quantitative Structure-Activity Relationship) models. More than 8000 compounds with known CL and/or T1/2 values obtained in vitro using human liver microsomes were selected from the freely available ChEMBL v.27 database. GUSAR (General Unrestricted Structure-Activity Relationships) and PASS (Prediction of Activity Spectra for Substances) softwares were used to make quantitative and classification models. The quality of the models was evaluated using 5-fold cross-validation. Compounds were subdivided into "stable" and "unstable" by means of the following threshold parameters: T1/2 = 30 minutes, CL = 20 ml/min/kg. The accuracy of the models ranged from 0.5 (calculated in 5-fold CV on the test set for the half-life prediction quantitative model) to 0.96 (calculated in 5-fold CV on the test set for the clearance prediction classification model).

Selective Fatty Acid Amide Hydrolase Inhibitors as Potential Novel Antiepileptic Agents

Temporal lobe epilepsy is the most common form of epilepsy, and current antiepileptic drugs are ineffective in many patients. The endocannabinoid system has been associated with an on-demand protective response to seizures. Blocking endocannabinoid catabolism would elicit antiepileptic effects, devoid of psychotropic effects. We herein report the discovery of selective anandamide catabolic enzyme fatty acid amide hydrolase (FAAH) inhibitors with promising antiepileptic efficacy, starting from a further investigation of our prototypical inhibitor 2a. When tested in two rodent models of epilepsy, 2a reduced the severity of the pilocarpine-induced status epilepticus and the elongation of the hippocampal maximal dentate activation. Notably, 2a did not affect hippocampal dentate gyrus long-term synaptic plasticity. These data prompted our further endeavor aiming at discovering new antiepileptic agents, developing a new set of FAAH inhibitors (3a-m). Biological studies highlighted 3h and 3m as the best performing analogues to be further investigated. In cell-based studies, using a neuroblastoma cell line, 3h and 3m could reduce the oxinflammation state by decreasing DNA-binding activity of NF-kB p65, devoid of cytotoxic effect. Unwanted cardiac effects were excluded for 3h (Langendorff perfused rat heart). Finally, the new analogue 3h reduced the severity of the pilocarpine-induced status epilepticus as observed for 2a.

Towards a mechanistic understanding of reciprocal drug-microbiome interactions

Broad-spectrum antibiotics target multiple gram-positive and gram-negative bacteria, and can collaterally damage the gut microbiota. Yet, our knowledge of the extent of damage, the antibiotic activity spectra, and the resistance mechanisms of gut microbes is sparse. This limits our ability to mitigate microbiome-facilitated spread of antibiotic resistance. In addition to antibiotics, non-antibiotic drugs affect the human microbiome, as shown by metagenomics as well as in vitro studies. Microbiome-drug interactions are bidirectional, as microbes can also modulate drugs. Chemical modifications of antibiotics mostly function as antimicrobial resistance mechanisms, while metabolism of non-antibiotics can also change the drugs' pharmacodynamic, pharmacokinetic, and toxic properties. Recent studies have started to unravel the extensive capacity of gut microbes to metabolize drugs, the mechanisms, and the relevance of such events for drug treatment. These findings raise the question whether and to which degree these reciprocal drug-microbiome interactions will differ across individuals, and how to take them into account in drug discovery and precision medicine. This review describes recent developments in the field and discusses future study areas that will benefit from systems biology approaches to better understand the mechanistic role of the human gut microbiota in drug actions.

Retention-directed and selectivity controlled chromatographic resolution: Rapid post-hoc analysis of DMPK samples to achieve high-throughput LC-MS separation

High quality chromatographic separation underpins robustness in LC-MS, frequently the analytical method of choice for pharmaceutical drug discovery work. The potential improvements in chromatographic selectivity afforded by serial column coupling (SCC), provide a useful means to enhance the resolution of complex samples. In this work, we present a revised high-throughput form of SCC, in which just two individual mixed phase columns were coupled together and combined with a gradient-optimised, retention-directed ultra-high pressure method to achieve rapid separations, with no further method optimisation necessary. The overall performance was evaluated from an open access DMPK analytical working environment perspective; where in anticipation of bioanalytical or metabolite identification chromatography challenges, or with the knowledge that stronger resolution was required for in-vitro sample analysis, the methodology could be immediately implemented by the analyst. Retention-directed selection of a shallow SCC gradient method was successful in separating peaks throughout the chromatographic window, resulting in a runtime still congruent to high-throughput analyses (3.5 min). In-vitro assay sample interferences were resolved 44-72% of the time, and the overall resolving power for isomeric separations significantly improved against single column comparisons (1.7-fold mean R_S improvement). Over a sustained period of time in our laboratory, SCC methods have been used for metabolite identification and bioanalytical samples, where both convenience and effectiveness in solving analytical challenges has been consistently demonstrated. Examples that highlight SCC chromatography, and a guided discussion of the main high-throughput considerations, are included. The technique offers wide applicability, and we would recommend it as a toolbox consideration to the laboratory analyst.

Anticonvulsant and analgesic in neuropathic pain activity in a group of new aminoalkanol derivatives

As part of the presented research, thirteen new aminoalkanol derivatives were designed and obtained by chemical synthesis. In vivo studies (mice, i.p.) showed anticonvulsant activity (MES) of nine compounds, and in the case of one compound (R,S-trans-2-((2-(2,3,5-trimethylphenoxy)ethyl)amino)cyclohexan-1-ol, 4) both anticonvulsant (ED₅₀ MES = 15.67 mg/kg, TD₅₀ rotarod = 78.30 mg.kg, PI = 5.00) and analgesic activity (OXA-induced neuropathic pain, active at 15 mg/kg). For selected active compounds additional in vitro studies have been performed, including receptor studies (5-HT_1A), evaluation of antioxidant activity (DPPH assay), metabolism studies as well as safety panel (mutagenicity, safety in relation to the gastrointestinal flora, cytotoxicity towards astrocytes as well as impact on their proliferation and cell cycle).

Preclinical characterization of CPL302-253, a selective inhibitor of PI3Kδ, as the candidate for the inhalatory treatment and prevention of Asthma

Asthma is a common chronic inflammatory disease. Although effective asthma therapies are available, part of asthmatic population do not respond to these treatment options. In this work we present the result of development of CPL302-253 molecule, a selective PI3Kδ inhibitor. This molecule is intended to be a preclinical candidate for dry powder inhalation in asthma treatment. Studies we performed showed that this molecule is safe and effective PI3Kδ inhibitor that can impact many immune functions. We developed a short, 15-day HDM induced asthma mouse model, in which we showed that CPL302-253 is able to block inflammatory processes leading to asthma development in vivo.

Enhancement of the Antioxidant Activity and Neurotherapeutic Features through Pyridol Addition to Tetraazamacrocyclic Molecules

Alzheimer's and other neurodegenerative diseases are chronic conditions affecting millions of individuals worldwide. Oxidative stress is a consistent component described in the development of many neurodegenerative diseases. Therefore, innovative strategies to develop drug candidates that overcome oxidative stress in the brain are needed. To target these challenges, a new, water-soluble 12-membered tetraaza macrocyclic pyridinophane L4 was designed and produced using a building-block approach. Potentiometric data show that the neutral species of L4 provides interesting zwitterionic behavior at physiological pH, akin to amino acids, and a nearly ideal isoelectric point of 7.3. The copper(II) complex of L4 was evaluated by X-ray diffraction and cyclic voltammetry to show the potential modes of antioxidant activity derived, which was also demonstrated by 2,2-diphenyl-1-picrylhydrazyl and coumarin carboxylic acid antioxidant assays. L4 was shown to have dramatically enhanced antioxidant activity and increased biological compatibility compared to parent molecules reported previously. L4 attenuated hydrogen peroxide (H2O2)-induced cell viability loss more efficiently than precursor molecules in the mouse hippocampal HT-22 cell model. L4 also showed potent (fM) level protection against H2O2 cell death in a BV2 microglial cell culture. Western blot studies indicated that L4 enhanced the cellular antioxidant defense capacity via Nrf2 signaling activation as well. Moreover, a low-cost analysis and high metabolic stability in phase I and II models were observed. These encouraging results show how the rational design of lead compounds is a suitable strategy for the development of treatments for neurodegenerative diseases where oxidative stress plays a substantial role.

Dialing in on pharmacological features for a therapeutic antioxidant small molecule

The pyridinophane molecule L2 (3,6,9,15-tetraazabicyclo[9.3.1]penta-deca-1(15),11,13-trien-13-ol) has shown promise as a therapuetic for neurodegenerative diseases involving oxidative stress and metal ion misregulation. Protonation and metal binding stability constants with Mg2+, Ca2+, Cu2+, and Zn2+ ions were determined to further explore the therapeutic and pharmacological potential of this water soluble small molecule. These studies show that incorporation of an -OH group in position 4 of the pyridine ring decreases the pI values compared to cyclen and L1 (3,6,9,15-tetraazabicyclo[9.3.1]penta-deca-1(15),11,13-triene). Furthermore, this approach tunes the basicity of the tetra-aza macrocyclic ligand through the enhanced resonance stabilization of the -OH in position 4 and rigidity of the pyridine ring such that L2 has increased basicity compared to previously reported tetra-aza macrocycles. A metal binding preference for Cu2+, a redox cycling agent known to produce oxidative stress, indicates that this would be the in vivo metal target of L2. However, the binding constant of L2 with Cu2+ is moderated compared to cyclen due to the rigidity of the ligand and shows how ligand design can be used to tune metal selectivity. An IC50 = 298.0 μM in HT-22 neuronal cells was observed. Low metabolic liability was determined in both Phase I and II in vitro models. Throughout these studies other metal binding systems were used for comparison and as appropriate controls. The reactivity reported to date and pharmacological features described herein warrant further studies in vivo and the pursuit of L2 congeners using the knowledge that pyridine substitution in a pyridinophane can be used to tune the structure of the ligand and retain the positive therapeutic outcomes.

Data Curation can Improve the Prediction Accuracy of Metabolic Intrinsic Clearance

A key consideration at the screening stages of drug discovery is in vitro metabolic stability, often measured in human liver microsomes. Computational prediction models can be built using a large quantity of experimental data available from public databases, but these databases typically contain data measured using various protocols in different laboratories, raising the issue of data quality. In this study, we retrieved the intrinsic clearance (CLint ) measurements from an open database and performed extensive manual curation. Then, chemical descriptors were calculated using freely available software, and prediction models were built using machine learning algorithms. The models trained on the curated data showed better performance than those trained on the non-curated data and achieved performance comparable to previously published models, showing the importance of manual curation in data preparation. The curated data were made available, to make our models fully reproducible.