In Silico Design and Selection of New Tetrahydroisoquinoline-Based CD44 Antagonist Candidates.

CD44 promotes metastasis, chemoresistance, and stemness in different types of cancer and is a target for the development of new anti-cancer therapies. All CD44 isoforms share a common N-terminal domain that binds to hyaluronic acid (HA). Herein, we used a computational approach to design new potential CD44 antagonists and evaluate their target-binding ability. By analyzing 30 crystal structures of the HA-binding domain (CD44HAbd), we characterized a subdomain that binds to 1,2,3,4-tetrahydroisoquinoline (THQ)-containing compounds and is adjacent to residues essential for HA interaction. By computational combinatorial chemistry (CCC), we designed 168,190 molecules and compared their conformers to a pharmacophore containing the key features of the crystallographic THQ binding mode. Approximately 0.01% of the compounds matched the pharmacophore and were analyzed by computational docking and molecular dynamics (MD). We identified two compounds, Can125 and Can159, that bound to human CD44HAbd (hCD44HAbd) in explicit-solvent MD simulations and therefore may elicit CD44 blockage. These compounds can be easily synthesized by multicomponent reactions for activity testing and their binding mode, reported here, could be helpful in the design of more potent CD44 antagonists.

New approaches towards the synthesis of 1,2,3,4-tetrahydro isoquinoline-3-phosphonic acid (TicP).

Two new strategies for the efficient synthesis of racemic 1,2,3,4-tetrahydroisoquinoline-3-phosphonic acid (TicP) (±)-2 have been developed. The first strategy involves the electron-transfer reduction of the easily obtained α,ß-dehydro phosphonophenylalanine followed by a Pictet-Spengler cyclization. The second strategy involves a radical decarboxylation-phosphorylation reaction on 1,2,3,4-tetrahydroisoquinoline-3-carboxylic acid (Tic). In both strategies, the highly electrophilic N-acyliminium ion is formed as a key intermediate, and the target compound is obtained in good yield using mild reaction conditions and readily available starting materials, complementing existing methodologies and contributing to the easy accessibility of (±)-2 for further research.

Evidence That P-glycoprotein Inhibitor (Elacridar)-Loaded Nanocarriers Improve Epidermal Targeting of an Anticancer Drug via Absorptive Cutaneous Transporters Inhibition.

Because P-glycoprotein (P-gp) plays an absorptive role in the skin, its pharmacological inhibition represents a strategy to promote cutaneous localization of anticancer agents that serve as its substrates, improving local efficacy while reducing systemic exposure. Here, we evaluated the ability of a nanoemulsion (NE) coencapsulating a P-gp inhibitor (elacridar) with the antitumor drug paclitaxel to promote epidermal targeting. Loaded NE displayed a nanometric size (45.2 ± 4.0 nm) and negative zeta potential (-4.2 ± 0.8 mV). Elacridar improved NE ability to inhibit verapamil-induced ATPase activity of P-gp; unloaded NE-inhibited P-gp when used at a concentration of 1500 µM, while elacridar encapsulation decreased this concentration by 3-fold (p <0.05). Elacridar-loaded NE reduced paclitaxel penetration into the dermis of freshly excised mice skin and its percutaneous permeation by 1.5- and 1.7-fold (p <0.05), respectively at 6 h, whereas larger drug amounts (1.4-fold, p <0.05) were obtained in viable epidermis. Assessment of cutaneous distribution of a fluorescent paclitaxel derivative confirmed the smaller delivery into the dermis at elacridar presence. In conclusion, we have provided novel evidence that NE containing elacridar exhibited a clear potential for P-gp inhibition and enabled epidermal targeting of paclitaxel, which in turn, can potentially reduce adverse effects associated with systemic exposure to anticancer therapy.

Practical and Efficient Synthesis of α-Aminophosphonic Acids Containing 1,2,3,4-Tetrahydroquinoline or 1,2,3,4-Tetrahydroisoquinoline Heterocycles.

We report here a practical and efficient synthesis of α-aminophosphonic acid incorporated into 1,2,3,4-tetrahydroquinoline and 1,2,3,4-tetrahydroisoquinoline heterocycles, which could be considered to be conformationally constrained analogues of pipecolic acid. The principal contribution of this synthesis is the introduction of the phosphonate group in the N-acyliminium ion intermediates, obtained from activation of the quinoline and isoquinoline heterocycles or from the appropriate δ-lactam with benzyl chloroformate. Finally, the hydrolysis of phosphonate moiety with simultaneous cleavage of the carbamate afforded the target compounds.

Ligand/kappa-opioid receptor interactions: insights from the X-ray crystal structure.

During the past five years, the three-dimensional structures of 14 different G-protein coupled receptors (GPCRs) have been resolved by X-ray crystallography. The most recently published structures, those of the opioid receptors (ORs), are remarkably important in pain modulation, drug addiction, and mood disorders. These structures, confirmed previously proposed key interactions conferring potency and antagonistic properties, including the well-known interaction with Asp138, conserved in all aminergic GPCRs. In addition, crystallization of the opioid receptors highlighted the potential function of the ECL2 and ICL2 loops. We have previously reported a set of potent and selective kappa opioid receptor peptide agonists, of which ff(D-nle)r-NH2 is among the most potent and selective ones. These peptides were identified from the deconvolution of a 6,250,000 tetrapeptide combinatorial library. A derivative of this set is currently the subject of a phase 2 clinical trial in the United States. In this work, we describe comparative molecular modeling studies of kappa-OR peptide agonists with the co-crystallized antagonist, JDTic, and also report structure-activity relationships of 23 tetrapeptides. The overall binding and contact interactions are sound and interactions known to favor selectivity and potency were observed. Additional modeling studies will reveal conformational changes that the kappa-OR undergoes upon binding to these peptide agonists.

Tetrahydroisoquinolines acting as dopaminergic ligands. A molecular modeling study using MD simulations and QM calculations.

A molecular modeling study on 16 1-benzyl tetrahydroisoquinolines (BTHIQs) acting as dopaminergic ligands was carried out. By combining molecular dynamics simulations with ab initio and density functional theory (DFT) calculations, a simple and generally applicable procedure to evaluate the binding energies of BTHIQs interacting with the human dopamine D2 receptor (D2 DR) is reported here, providing a clear picture of the binding interactions of BTHIQs from both structural and energetic viewpoints. Molecular aspects of the binding interactions between BTHIQs and the D2 DR are discussed in detail. A significant correlation between binding energies obtained from DFT calculations and experimental pKi values was obtained, predicting the potential dopaminergic effect of non-synthesized BTHIQs.

A suitable preparation of N-sulfonyl-1,2,3,4-tetrahydroisoquinolines and their ring homologs with a reusable Preyssler heteropolyacid as catalyst.

The preparation of N-sulfonyl-1,2,3,4-tetrahydroisoquinolines, N-sulfonyl-2,3,4,5-tetrahydro-1H-2-benzazepines and N-sulfonyl-1,2,3,4,5,6-hexahydrobenzazocine was catalyzed by a Preyssler heteropolyacid, H(14)[NaP(5)W(30)O(110)], (PA), supported on silica (PASiO(2)40) with excellent yields by means of the Pictet-Spengler reaction of N-aralkylsulfonamides with s-trioxane. The reactions proceed with 0.5 mol% of silica-supported catalyst in toluene at 70°C. The catalyst can be recycled without appreciable loss of the catalytic activity.

Quantitative structure-activity relationship modeling of growth hormone secretagogues agonist activity of some tetrahydroisoquinoline 1-carboxamides.

Growth hormone secretagogue agonist activities for a data set of 45 tetrahydroisoquinoline 1-carboxamides were modeled using several kinds of molecular descriptors from dragon software. A linear model with six variables selected from a large pool of two-dimensional descriptors described 80% of cross-validation data variance. Similar results were found for a model obtained from a pool of three-dimensional descriptors. Size and hydrophilicity-related atomic properties such as mass, polarizability, and van der Waals volume were determined to be the most relevant for the differential growth hormone secretagogue agonist activities of the compounds studied. In addition, Artificial Neural Networks were trained using optimum variables from the linear models; however, they were found to overfit the data and resulted in similar or lower predictive power.