Combinatorial Pharmacophore Modeling of Multidrug and Toxin Extrusion Transporter 1 Inhibitors: a Theoretical Perspective for Understanding Multiple Inhibitory Mechanisms

Prediction of Inhibitory Activity against the MATE1 Transporter via Combined Fingerprint- and Physics-Based Machine Learning Models

Renal secretion plays an important role in excretion of drug from the kidney. Two major transporters known to be highly involved in renal secretion are MATE1/2 K and OCT2, the former of which is highly related to drug-drug interactions. Among published in silico models for MATE inhibitors, a previous model obtained a ROC-AUC value of 0.78 using high throughput percentage inhibition data [J. Med. Chem. 2013, 56(3), 781-795] which we aimed to improve upon here using a combined fingerprint and physics-based approach. To this end, we collected 225 publicly available compounds with pIC50 values against MATE1. Subsequently, on the one hand, we performed a physics-based approach using an Alpha-Fold protein structure, from which we obtained MM-GB/SA scores for those compounds. On the other hand, we built Random Forest (RF) and message passing neural network models using extended-connectivity fingerprints with radius 4 (ECFP4) and chemical structures as graphs, respectively, which also included MM-GB/SA scores as input variables. In a five-fold cross-validation with a separate test set, we found that the best predictivity for the hold-out test was observed in the RF model (including ECFP4 and MM-GB/SA data) with an ROC-AUC of 0.833 ± 0.036; while that of the MM-GB/SA regression model was 0.742. However, the MM-GB/SA model did not show a dependency of the performance on the particular chemical space being predicted. Additionally, via structural interaction fingerprint analysis, we identified interacting residues with inhibitor as identical for those with noninhibitors, including substrates, such as Gln49, Trp274, Tyr277, Tyr299, Ile303, and Tyr306. The similar binding modes are consistent with the observed similar IC50 value inhibitor when using different substrates experimentally, and practically, this can release the experimental scientists from bothering of selecting substrates for MATE1. Hence, we were able to build highly predictive classification models for MATE1 inhibitory activity with both ECFP4 and MM-GB/SA score as input features, which is fit-for-purpose for use in the drug discovery process.

A New Reaction Mode of 3-Halooxindoles: Acting as C-C-O Three-Atom Components for (3+3) Cycloaddition to Access Indolenine-Fused 2H-1,4-Oxathiines

Herein, we report an unprecedented implementation of 3-halooxindoles as C-C-O three-atom components for (3+3) cycloaddition with pyridinium 1,4-zwitterionic thiolates, affording structurally diverse indolenine-fused 2H-1,4-oxathiines in moderate to high yields. A combined experimental and computational mechanistic study suggests that the reaction proceeds through addition of a S conjugate to the o-azaxylylene intermediate, followed by O-Michael addition and a sequential retro-Michael addition/pyridine extrusion pathway.

Targeting the multidrug and toxin extrusion 1 gene (SLC47A1) sensitizes glioma stem cells to temozolomide

Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor, with an extremely poor prognosis due to resistance to standard-of-care treatments. Strong evidence suggests that the small population of glioma stem cells (GSCs) contributes to the aggressiveness of GBM. One of the mechanisms that promote GSC progression is the dysregulation of membrane transporters, which mediate the influx and efflux of substances to maintain cellular homeostasis. Here, we investigated the role of multidrug and toxin extrusion transporter gene SLC47A1 in GSCs. Results show that SLC47A1 is highly expressed in GSCs compared to non-stem cell glioma cells, and non-tumor cells. Additionally, in-silico analysis of public datasets showed that high SLC47A1 expression is linked to malignancy and a poor prognosis in glioma patients. Further, SLC47A1 expression is correlated with important biological processes and signaling pathways that support tumor growth. Meanwhile, silencing SLC47A1 by short-hairpin RNA (shRNA) influenced cell viability and self-renewal activity in GSCs. Interestingly, SLC47A1 shRNA knockdown or pharmacological inhibition potentiates the effect of temozolomide (TMZ) in GSC cells. The findings suggest that SLC47A1 could serve as a useful therapeutic target for gliomas.

Diversity-oriented and diastereoselective synthesis of diverse polycyclic thieno(2,3-b)-quinoline derivatives using a synergistic strategy

A cascade spiroannulation of 2-mercaptoquinoline-3-carbaldehydes with α,α-dicyanoalkenes as well as a cascade spiroannulation of 2-mercaptoquinoline-3-carbaldehydes aldehydes with α-bromocarbonyl compounds was investigated based on a synergistic strategy, providing a series of diverse spiro-fused heterocyclic compounds containing more different functional groups. The features of this strategy directed towards molecular complexity and diversity include step economy, mild conditions, and high bond-forming efficiency, but important polycyclic heterocyclic products, which could be transformed into potential biologically interesting heterocyclic structures.

Regio- and stereoselective synthesis and evaluation of densely functionalized bispiro[oxindole-isoxazole-indandione] hybrids as anticancer agents

This is the combination of three key pharmacophores through bispiro quaternary carbon atoms and evaluation of their anticancer activity.

Drug Transporters in the Kidney: Perspectives on Species Differences, Disease Status, and Molecular Docking

The kidneys are a pair of important organs that excretes endogenous waste and exogenous biological agents from the body. Numerous transporters are involved in the excretion process. The levels of these transporters could affect the pharmacokinetics of many drugs, such as organic anion drugs, organic cationic drugs, and peptide drugs. Eleven drug transporters in the kidney (OAT1, OAT3, OATP4C1, OCT2, MDR1, BCRP, MATE1, MATE2-K, OAT4, MRP2, and MRP4) have become necessary research items in the development of innovative drugs. However, the levels of these transporters vary between different species, sex-genders, ages, and disease statuses, which may lead to different pharmacokinetics of drugs. Here, we review the differences of the important transports in the mentioned conditions, in order to help clinicians to improve clinical prescriptions for patients. To predict drug-drug interactions (DDIs) caused by renal drug transporters, the molecular docking method is used for rapid screening of substrates or inhibitors of the drug transporters. Here, we review a large number of natural products that represent potential substrates and/or inhibitors of transporters by the molecular docking method.

Importance of the Azole Moiety of Cimetidine Derivatives for the Inhibition of Human Multidrug and Toxin Extrusion Transporter 1 (hMATE1)

Herein, we describe the design and synthesis of cimetidine analogs, as well as their inhibitory activity toward the human multidrug and toxin extrusion transporter 1 (hMATE1), which is related to nephrotoxicity of drugs. Cimetidine is the histamine H₂-receptor antagonist, but also inhibits hMATE1, which is known to cause renal impairment. We designed and synthesized cimetidine analogs to evaluate hMATE1 inhibitory activity to reveal whether the analogs could reduce the inhibition of hMATE1. The results showed that all analogs with an unsubstituted guanidino group exhibited hMATE1 inhibitory activity. On the other hand, there was a clear difference in the hMATE1 inhibitory activity for the other compounds. That is, compounds with a methylimidazole ring exhibited hMATE1 inhibition, while compounds with a phenyl ring did not. The results suggest that the ability to form hydrogen bonds at the azole moiety is strongly involved in the hMATE1 inhibition.

A silver-catalyzed stereoselective domino cycloisomerization-vinylogous aldol reaction of ortho-alkynylbenzaldehydes with 3-alkylidene oxindoles: an entry to functionalized isochromenes

A silver tetrafluoroborate catalyzed domino cycloisomerization-vinylogous aldol addition sequence on a multifunctional substrate such as ortho-alkynylbenzaldehydes yielding functionalized 1H-isochromenes in a single step with high yield and excellent diastereoselectivity (>19 : 1) is described. The reaction was well tolerated by alkyl, aryl, and unsubstituted alkynylbenzaldehydes, and furnished selective 6-endo-dig adducts exclusively without loss in the regio- as well as diastereoselectivity.

Rational drug design, synthesis, and biological evaluation of novel chiral tetrahydronaphthalene-fused spirooxindole as MDM2-CDK4 dual inhibitor against glioblastoma

Simultaneous inhibition of MDM2 and CDK4 may be an effective treatment against glioblastoma. A collection of chiral spirocyclic tetrahydronaphthalene (THN)-oxindole hybrids for this purpose have been developed. Appropriate stereochemistry in THN-fused spirooxindole compounds is key to their inhibitory activity: selectivity differed by over 40-fold between the least and most potent stereoisomers in time-resolved FRET and KINOMEscan® in vitro assays. Studies in glioblastoma cell lines showed that the most active compound ent-4g induced apoptosis and cell cycle arrest by interfering with MDM2 -P53 interaction and CDK4 activation. Cells treated with ent-4g showed up-regulation of proteins involved in P53 and cell cycle pathways. The compound showed good anti-tumor efficacy against glioblastoma xenografts in mice. These results suggested that rational design, asymmetric synthesis and biological evaluation of novel tetrahydronaphthalene fused spirooxindoles could generate promising MDM2-CDK4 dual inhibitors in glioblastoma therapy.

Dual inhibitors of SARS-CoV-2 proteases: pharmacophore and molecular dynamics based drug repositioning and phytochemical leads

SARS-related coronaviruses poses continual threat to humanity by rapidly mutating and emerging as severe pandemic outbreaks, including the current nCoV-19 pandemic. Hence a rapid drug repositioning and lead identification strategy are required to mitigate these outbreaks. We report a pharmacophore and molecular dynamics-based approach for drug repositioning and lead identification against dual targets (3CLp and PLp) of SARS-CoV-2. The pharmacophore model of 3CLp inhibitors was apolar with two aromatic and two H-bond acceptors, whereas that of PLp was relatively polar, bearing one aromatic and three H-bond acceptors. Pharmacophore-based virtual screening yielded six existing FDA-approved drugs and twelve natural products with both the pharmacophoric features. Among them are nelfinavir, tipranavir and licochalcone-D, which has shown better binding characteristics with both the proteases compared to lopinavir. The molecular dynamics revealed that the connecting loop (residues 176–199) of 3CLp is highly flexible, and hence, inhibitors should avoid high-affinity interactions with it. Lopinavir, due to its high affinity with the loop region, exhibited unstable binding. Further, the van der Waals size of the 3CLp inhibitors positively correlated with their binding affinity with 3CLp. However, the van der Waals size of a ligand should not cross a threshold of 572ų, beyond which the ligands are likely to make high-affinity interaction with the loop and suffer unstable binding as observed in the case of lopinavir. Similarly, the total polar surface area of the ligands were found to be negatively correlated with their binding affinity with PLp.

Current Advances in Studying Clinically Relevant Transporters of the Solute Carrier (SLC) Family by Connecting Computational Modeling and Data Science

Organic anion and cation transporting proteins (OATs, OATPs, and OCTs), as well as the Multidrug and Toxin Extrusion (MATE) transporters of the Solute Carrier (SLC) family are playing a pivotal role in the discovery and development of new drugs due to their involvement in drug disposition, drug-drug interactions, adverse drug effects and related toxicity. Computational methods to understand and predict clinically relevant transporter interactions can provide useful guidance at early stages in drug discovery and design, especially if they include contemporary data science approaches. In this review, we summarize the current state-of-the-art of computational approaches for exploring ligand interactions and selectivity for these drug (uptake) transporters. The computational methods discussed here by highlighting interesting examples from the current literature are ranging from semiautomatic data mining and integration, to ligand-based methods (such as quantitative structure-activity relationships, and combinatorial pharmacophore modeling), and finally structure-based methods (such as comparative modeling, molecular docking, and molecular dynamics simulations). We are focusing on promising computational techniques such as fold-recognition methods, proteochemometric modeling or techniques for enhanced sampling of protein conformations used in the context of these ADMET-relevant SLC transporters with a special focus on methods useful for studying ligand selectivity.

From indoles to 3,3′-biindolin-2-ones: copper-catalyzed oxidative homocoupling of indoles

A copper-catalyzed intermolecular oxidative homocoupling of indoles for the direct construction of valuable C3–C3 biindolyl scaffolds.

Organocatalytic Asymmetric Synthesis of Spiro-Bridged and Spiro-Fused Heterocyclic Compounds Containing Chromane, Indole, and Oxindole Moieties

Following the reactivity inversion strategy, two different two-step sequences were designed and successfully applied to the asymmetric synthesis of spiro-bridged and spiro-fused heterocyclic compounds, which combined chromane, indole, and oxindole, three potential pharmacophores, in one molecule. The power of these two organocatalytic pathways is underscored by mild reaction conditions and high efficiency in the production of synthetically challenging, but biologically important heterocyclic products, which could be transformed into more biologically interesting heterocyclic structures.

Integration of pharmacophore mapping and molecular docking in sequential virtual screening: towards the discovery of novel JAK2 inhibitors

An integrated sequential virtual screening protocol by combining molecular docking and pharmacophore mapping was successfully constructed to identify novel small-molecule inhibitors of JAK2.

ADMET Evaluation in Drug Discovery. 16. Predicting hERG Blockers by Combining Multiple Pharmacophores and Machine Learning Approaches

Blockade of human ether-à-go-go related gene (hERG) channel by compounds may lead to drug-induced QT prolongation, arrhythmia, and Torsades de Pointes (TdP), and therefore reliable prediction of hERG liability in the early stages of drug design is quite important to reduce the risk of cardiotoxicity-related attritions in the later development stages. In this study, pharmacophore modeling and machine learning approaches were combined to construct classification models to distinguish hERG active from inactive compounds based on a diverse data set. First, an optimal ensemble of pharmacophore hypotheses that had good capability to differentiate hERG active from inactive compounds was identified by the recursive partitioning (RP) approach. Then, the naive Bayesian classification (NBC) and support vector machine (SVM) approaches were employed to construct classification models by integrating multiple important pharmacophore hypotheses. The integrated classification models showed improved predictive capability over any single pharmacophore hypothesis, suggesting that the broad binding polyspecificity of hERG can only be well characterized by multiple pharmacophores. The best SVM model achieved the prediction accuracies of 84.7% for the training set and 82.1% for the external test set. Notably, the accuracies for the hERG blockers and nonblockers in the test set reached 83.6% and 78.2%, respectively. Analysis of significant pharmacophores helps to understand the multimechanisms of action of hERG blockers. We believe that the combination of pharmacophore modeling and SVM is a powerful strategy to develop reliable theoretical models for the prediction of potential hERG liability.

Lack of Influence of Substrate on Ligand Interaction with the Human Multidrug and Toxin Extruder, MATE1

Multidrug and toxin extruder (MATE) 1 plays a central role in mediating renal secretion of organic cations, a structurally diverse collection of compounds that includes ∼40% of prescribed drugs. Because inhibition of transport activity of other multidrug transporters, including the organic cation transporter (OCT) 2, is influenced by the structure of the transported substrate, the present study screened over 400 drugs as inhibitors of the MATE1-mediated transport of four structurally distinct organic cation substrates: the commonly used drugs: 1) metformin and 2) cimetidine; and two prototypic cationic substrates, 3) 1-methyl-4-phenylpyridinium (MPP), and 4) the novel fluorescent probe, N,N,N-trimethyl-2-[methyl(7-nitrobenzo[c][1,2,5]oxadiazol-4-yl)amino]ethanaminium iodide. Transport was measured in Chinese hamster ovary cells that stably expressed the human ortholog of MATE1. Comparison of the resulting inhibition profiles revealed no systematic influence of substrate structure on inhibitory efficacy. Similarly, IC50 values for 26 structurally diverse compounds revealed no significant influence of substrate structure on the kinetic interaction of inhibitor with MATE1. The IC50 data were used to generate three-dimensional quantitative pharmacophores that identified hydrophobic regions, H-bond acceptor sites, and an ionizable (cationic) feature as key determinants for ligand binding to MATE1. In summary, in contrast to the behavior observed with some other multidrug transporters, including OCT2, the results suggest that substrate identity exerts comparatively little influence on ligand interaction with MATE1.