The polymer polydimethylsiloxane (PDMS) is widely used to build microfluidic devices compatible with cell culture. Whilst convenient in manufacture, PDMS has the disadvantage that it can absorb small ...molecules such as drugs. In microfluidic devices like “Organs-on-Chip”, designed to examine cell behavior and test the effects of drugs, this might impact drug bioavailability. Here we developed an assay to compare the absorption of a test set of four cardiac drugs by PDMS based on measuring the residual non-absorbed compound by High Pressure Liquid Chromatography (HPLC). We showed that absorption was variable and time dependent and not determined exclusively by hydrophobicity as claimed previously. We demonstrated that two commercially available lipophilic coatings and the presence of cells affected absorption. The use of lipophilic coatings may be useful in preventing small molecule absorption by PDMS.
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•Binding of different compounds to PDMS varies greatly.•Previous reported correlations of absorption and LogP values could not be repeated.•Topological polar surface area possibly related to compound absorption.•A lipid based coating partially obviates compound absorption.•Presence of cultured cells affects free drug concentration, but less than substrate.
G protein-coupled receptors (GPCRs) are the major drug target of medicines on the market today. Therefore, much research is and has been devoted to the elucidation of the function and ...three-dimensional structure of this large family of membrane proteins, which includes multiple conserved transmembrane domains connected by intra- and extracellular loops. In the last few years, the less conserved extracellular loops have garnered increasing interest, particularly after the publication of several GPCR crystal structures that clearly show the extracellular loops to be involved in ligand binding. This review will summarize the recent progress made in the clarification of the ligand binding and activation mechanism of class-A GPCRs and the role of extracellular loops in this process.
Four adenosine receptors have been cloned and characterized from several mammalian species. The receptors are named adenosine A(1), A(2A), A(2B), and A(3). The A(2A) and A(2B) receptors preferably ...interact with members of the G(s) family of G proteins and the A(1) and A(3) receptors with G(i/o) proteins. However, other G protein interactions have also been described. Adenosine is the preferred endogenous agonist at all these receptors, but inosine can also activate the A(3) receptor. The levels of adenosine seen under basal conditions are sufficient to cause some activation of all the receptors, at least where they are abundantly expressed. Adenosine levels during, e.g., ischemia can activate all receptors even when expressed in low abundance. Accordingly, experiments with receptor antagonists and mice with targeted disruption of adenosine A(1), A(2A), and A(3) expression reveal roles for these receptors under physiological and particularly pathophysiological conditions. There are pharmacological tools that can be used to classify A(1), A(2A), and A(3) receptors but few drugs that interact selectively with A(2B) receptors. Testable models of the interaction of these drugs with their receptors have been generated by site-directed mutagenesis and homology-based modelling. Both agonists and antagonists are being developed as potential drugs.
In the 10 years since our previous International Union of Basic and Clinical Pharmacology report on the nomenclature and classification of adenosine receptors, no developments have led to major ...changes in the recommendations. However, there have been so many other developments that an update is needed. The fact that the structure of one of the adenosine receptors has recently been solved has already led to new ways of in silico screening of ligands. The evidence that adenosine receptors can form homo- and heteromultimers has accumulated, but the functional significance of such complexes remains unclear. The availability of mice with genetic modification of all the adenosine receptors has led to a clarification of the functional roles of adenosine, and to excellent means to study the specificity of drugs. There are also interesting associations between disease and structural variants in one or more of the adenosine receptors. Several new selective agonists and antagonists have become available. They provide improved possibilities for receptor classification. There are also developments hinting at the usefulness of allosteric modulators. Many drugs targeting adenosine receptors are in clinical trials, but the established therapeutic use is still very limited.
G Protein-coupled receptors (GPCRs) are the most frequently exploited drug target family, moreover they are often found mutated in cancer. Here we used a dataset of mutations found in patient samples ...derived from the Genomic Data Commons and compared it to the natural human variance as exemplified by data from the 1000 genomes project. We explored cancer-related mutation patterns in all GPCR classes combined and individually. While the location of the mutations across the protein domains did not differ significantly in the two datasets, a mutation enrichment in cancer patients was observed among class-specific conserved motifs in GPCRs such as the Class A "DRY" motif. A Two-Entropy Analysis confirmed the correlation between residue conservation and cancer-related mutation frequency. We subsequently created a ranking of high scoring GPCRs, using a multi-objective approach (Pareto Front Ranking). Our approach was confirmed by re-discovery of established cancer targets such as the LPA and mGlu receptor families, but also discovered novel GPCRs which had not been linked to cancer before such as the P2Y Receptor 10 (P2RY10). Overall, this study presents a list of GPCRs that are amenable to experimental follow up to elucidate their role in cancer.
With the ongoing rapid growth of publicly available ligand–protein bioactivity data, there is a trove of valuable data that can be used to train a plethora of machine-learning algorithms. However, ...not all data is equal in terms of size and quality and a significant portion of researchers’ time is needed to adapt the data to their needs. On top of that, finding the right data for a research question can often be a challenge on its own. To meet these challenges, we have constructed the Papyrus dataset. Papyrus is comprised of around 60 million data points. This dataset contains multiple large publicly available datasets such as ChEMBL and ExCAPE-DB combined with several smaller datasets containing high-quality data. The aggregated data has been standardised and normalised in a manner that is suitable for machine learning. We show how data can be filtered in a variety of ways and also perform some examples of quantitative structure–activity relationship analyses and proteochemometric modelling. Our ambition is that this pruned data collection constitutes a benchmark set that can be used for constructing predictive models, while also providing an accessible data source for research.
Graphical Abstract
Background and Purpose
Drug‐induced arrhythmia due to blockade of the Kv11.1 channel (also known as the hERG K+ channel) is a frequent side effect. Previous studies have primarily focused on ...equilibrium parameters, i.e. affinity or potency, of drug candidates at the channel. The aim of this study was to determine the kinetics of the interaction with the channel for a number of known Kv11.1 blockers and to explore a possible correlation with the affinity or physicochemical properties of these compounds.
Experimental Approach
The affinity and kinetic parameters of 15 prototypical Kv11.1 inhibitors were evaluated in a number of 3H‐dofetilide binding assays. The lipophilicity (logKW‐C8) and membrane partitioning (logKW‐IAM) of these compounds were determined by means of HPLC analysis.
Key Results
A novel 3H‐dofetilide competition association assay was set up and validated, which allowed us to determine the binding kinetics of the Kv11.1 blockers used in this study. Interestingly, the compounds' affinities (Ki values) were correlated to their association rates rather than dissociation rates. Overall lipophilicity or membrane partitioning of the compounds were not correlated to their affinity or rate constants for the channel.
Conclusions and Implications
A compound's affinity for the Kv11.1 channel is determined by its rate of association with the channel, while overall lipophilicity and membrane affinity are not. In more general terms, our findings provide novel insights into the mechanism of action for a compound's activity at the Kv11.1 channel. This may help to elucidate how Kv11.1‐induced cardiotoxicity is governed and how it can be circumvented in the future.
The largest family of cell surface receptors involved in signal transduction, G protein coupled receptors (GPCRs), are one of the major targets for current drugs as well as new drug development. ...Ligands interacting with for e.g. adrenergic, histamine, adenosine, opioid, dopamine or serotonin receptors, constitute a large portion of currently used therapeutics. A common property of GPCRs is that upon activation (agonist binding) they transmit signals across the plasma membrane via an interaction with heterotrimeric G proteins. The corresponding activated G protein subsequently interacts with an intracellular effector system, such as adenylate cyclase or phospholipase C, leading to a wide variety of distinct physiological responses. Recent evidence suggests that GPCRs have the potential to be `active' even in the absence of an agonist. This exhibition of spontaneous receptor activity has led to the observation that various ligands, previously considered as antagonists with no intrinsic activity, actually can inhibit this spontaneous activity, appearing to possess 'negative intrinsic activity'. This phenomenon has been termed inverse agonism and the corresponding ligands are referred to as inverse agonists. Although intrinsic constitutive receptor activity and inverse agonism have unequivocally been demonstrated in vitro, (patho)physiological consequences are far from self-evident. Thus, in this review we should like to focus on the expression of inverse agonism under more 'physiological conditions', since it appears timely to address the physiological relevance and consequences of this new concept, both in GPCR research and drug discovery.
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CC chemokine receptor 2 (CCR2), a G protein-coupled receptor, plays a role in many cancer-related processes such as metastasis formation and immunosuppression. Since ∼ 20 % of human ...cancers contain mutations in G protein-coupled receptors, ten cancer-associated CCR2 mutants obtained from the Genome Data Commons were investigated for their effect on receptor functionality and antagonist binding. Mutations were selected based on either their vicinity to CCR2′s orthosteric or allosteric binding sites or their presence in conserved amino acid motifs. One of the mutant receptors, namely S101P2.63 with a mutation near the orthosteric binding site, did not express on the cell surface. All other studied mutants showed a decrease in or a lack of G protein activation in response to the main endogenous CCR2 ligand CCL2, but no change in potency was observed. Furthermore, INCB3344 and LUF7482 were chosen as representative orthosteric and allosteric antagonists, respectively. No change in potency was observed in a functional assay, but mutations located at F1163.28 impacted orthosteric antagonist binding significantly, while allosteric antagonist binding was abolished for L134Q3.46 and D137N3.49 mutants. As CC chemokine receptor 2 is an attractive drug target in cancer, the negative effect of these mutations on receptor functionality and drugability should be considered in the drug discovery process.
A vast number of marketed drugs act on G protein‐coupled receptors (GPCRs), the most successful category of drug targets to date. These drugs usually possess high target affinity and selectivity, and ...such combined features have been the driving force in the early phases of drug discovery. However, attrition has also been high. Many investigational new drugs eventually fail in clinical trials due to a demonstrated lack of efficacy. A retrospective assessment of successfully launched drugs revealed that their beneficial effects in patients may be attributed to their long drug‐target residence times (RTs). Likewise, for some other GPCR drugs short RT could be beneficial to reduce the potential for on‐target side effects. Hence, the compounds’ kinetics behavior might in fact be the guiding principle to obtain a desired and durable effect in vivo. We therefore propose that drug‐target RT should be taken into account as an additional parameter in the lead selection and optimization process. This should ultimately lead to an increased number of candidate drugs moving to the preclinical development phase and on to the market. This review contains examples of the kinetics behavior of GPCR ligands with improved in vivo efficacy and summarizes methods for assessing drug‐target RT.
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