Impact of CYP2C19 Gene Variants on Long-Term Treatment with Atorvastatin in Patients with Acute Coronary Syndromes.

The effectiveness of lipid-lowering therapies may be insufficient in high-risk cardiovascular patients and depends on the genetic variability of drug-metabolizing enzymes. Customizing statin therapy, including treatment with atorvastatin, may improve clinical outcomes. Currently, there is a lack of guidelines allowing the prediction of the therapeutic efficacy of lipid-lowering statin therapy. This study aimed to determine the effects of clinically significant gene variants of CYP2C19 on atorvastatin therapy in patients with acute coronary syndromes. In total, 92 patients with a confirmed diagnosis of ST-elevation myocardial infarction (STEMI) or non-ST-elevation myocardial infarction (NSTEMI) were sequenced for target regions within the CYP2C19 gene on the Illumina Miniseq system. The CYP2C19 poor metabolizer phenotype (carriers of CYP2C19*2, CYP2C19*4, and CYP2C19*8 alleles) was detected in 29% of patients. These patients had significantly lower responses to treatment with atorvastatin than patients with the normal metabolizer phenotype. CYP2C19-metabolizing phenotype, patient age, and smoking increased the odds of undertreatment in patients (∆LDL-C (mmol/L) < 1). These results revealed that the CYP2C19 phenotype may significantly impact atorvastatin therapy personalization in patients requiring LDL lipid-lowering therapy.

Phosphorylation-dependent allosteric regulation of Cx43 gap junction inhibitor potency.

Physiological and pathological processes such as homeostasis, embryogenesis, development, tumorigenesis, and cell movement depend on the intercellular communication through gap junctions (GJIC). Connexin (Cx)-based GJ channels are formed of two apposing hemichannels in the contiguous cells and provide a direct pathway for electrical and metabolic intercellular communication. The main modulators of GJ conductance are transjunctional voltage, intracellular pH, Ca2+, Mg2+, and phosphorylation. Chemical modulators of GJIC are being used in cases of various intercellular communication-dependent diseases. In this study, we used molecular docking, dual whole-cell patch-clamp, and Western blotting to investigate the impact of connexin phosphorylation on GJ chemical gating by α-pinene and other GJ inhibitors (octanol, carbenoxolone, mefloquine, intracellular pH, glycyrrhetinic acid, and sevoflurane) in HeLa cells expressing exogenous Cx43 (full length and truncated at amino acid 258) and other connexins typical of heart and/or nervous system (Cx36, Cx40, Cx45, and Cx47), and in cells expressing endogenous Cx43 (Novikoff and U-87). We found that Ca2+-regulated kinases, such as Ca2+/calmodulin-dependent kinase II, atypical protein kinase C, cyclin-dependent kinase, and Pyk2 kinase may allosterically modulate the potency of α-pinene through phosphorylation of Cx43 C-terminus. The identified new phenomenon was Cx isoform-, inhibitor-, and cell type-dependent. Overall, these results suggest that compounds, the potency of which depends on receptor phosphorylation, might be of particular interest in developing targeted therapies for diseases accompanied by high kinase activity, such as cardiac arrhythmias, epilepsy, stroke, essential tremor, inflammation, and cancer.

Evaluation of Cx43 Gap Junction Inhibitors Using a Quantitative Structure-Activity Relationship Model.

Gap junctions (GJs) made of connexin-43 (Cx43) are necessary for the conduction of electrical impulses in the heart. Modulation of Cx43 GJ activity may be beneficial in the treatment of cardiac arrhythmias and other dysfunctions. The search for novel GJ-modulating agents using molecular docking allows for the accurate prediction of binding affinities of ligands, which, unfortunately, often poorly correlate with their potencies. The objective of this study was to demonstrate that a Quantitative Structure-Activity Relationship (QSAR) model could be used for more precise identification of potent Cx43 GJ inhibitors. Using molecular docking, QSAR, and 3D-QSAR, we evaluated 16 known Cx43 GJ inhibitors, suggested the monocyclic monoterpene d-limonene as a putative Cx43 inhibitor, and tested it experimentally in HeLa cells expressing exogenous Cx43. The predicted concentrations required to produce 50% of the maximal effect (IC50) for each of these compounds were compared with those determined experimentally (pIC50 and eIC50, respectively). The pIC50ies of d-limonene and other Cx43 GJ inhibitors examined by our QSAR and 3D-QSAR models showed a good correlation with their eIC50ies (R = 0.88 and 0.90, respectively) in contrast to pIC50ies obtained from molecular docking (R = 0.78). However, molecular docking suggests that inhibitor potency may depend on their docking conformation on Cx43. Searching for new potent, selective, and specific inhibitors of GJ channels, we propose to perform the primary screening of new putative compounds using the QSAR model, followed by the validation of the most suitable candidates by patch-clamp techniques.

A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19.

In this study we have developed a method based on Flux Balance Analysis to identify human metabolic enzymes which can be targeted for therapeutic intervention against COVID-19. A literature search was carried out in order to identify suitable inhibitors of these enzymes, which were confirmed by docking calculations. In total, 10 targets and 12 bioactive molecules have been predicted. Among the most promising molecules we identified Triacsin C, which inhibits ACSL3, and which has been shown to be very effective against different viruses, including positive-sense single-stranded RNA viruses. Similarly, we also identified the drug Celgosivir, which has been successfully tested in cells infected with different types of viruses such as Dengue, Zika, Hepatitis C and Influenza. Finally, other drugs targeting enzymes of lipid metabolism, carbohydrate metabolism or protein palmitoylation (such as Propylthiouracil, 2-Bromopalmitate, Lipofermata, Tunicamycin, Benzyl Isothiocyanate, Tipifarnib and Lonafarnib) are also proposed.

The effect of nutmeg essential oil constituents on Novikoff hepatoma cell viability and communication through Cx43 gap junctions.

Essential oils from plants are a potential source of molecules having anti-inflammatory, anticancer, cardiotropic, and other activities. However, most of these effects lack mechanistic explanations and structure-activity relationship testing. In the present study, we: 1) identified the nutmeg essential oil (NEO) composition; 2) using molecular docking, we determined the putative regulatory binding sites on the connexin 43 (Cx43) that is responsible for gap junction-dependent intercellular communication (GJIC) in the majority of tissues; 3) examined the effect of NEO and its three constituents - sabinene, α-pinene, and α-copaene - on GJ conductance and gating in Novikoff cells expressing endogenous Cx43; and 4) verified whether NEO effects on GJIC correlated with its action on Novikoff cell viability, proliferation, and colony formation capability. Our results revealed NEO and its constituents as potent and efficient Cx43 GJ inhibitors acting by slow gating mechanism. In addition, NEO reduced Novikoff hepatoma cell viability, proliferation, and colony formation capability; however, this was achieved at higher doses and was unrelated to its effects on GJIC.

Molecular basis for potentiation of Cx36 gap junction channel conductance by n-alcohols and general anesthetics.

In our recent study, we have demonstrated that short carbon chain n-alcohols (up to octanol) stimulated while long carbon chain n-alcohols inhibited the conductance of connexin (Cx) 36 (Cx36) gap junction (GJ) channels. In contrast, GJ channels composed of other types of Cxs all were inhibited by n-alcohols independent of their carbon chain length. To identify the putative structural domains of Cx36, responsible for the dual effect of n-alcohols, we performed structural modeling of Cx36 protein docking with hexanol and isoflurane that stimulated as well as nonanol and carbenoxolone that inhibited the conductance of Cx36 GJs and revealed their multiple common docking sites and a single pocket accessible only to hexanol and isoflurane. The pocket is located in the vicinity of three unique cysteine residues, namely C264 in the fourth, and C92 and C87 in the second transmembrane domain of the neighboring Cx36 subunits. To examine the hypothesis that disulphide bonding might be involved in the stimulatory effect of hexanol and isoflurane, we generated cysteine substitutions in Cx36 and demonstrated by a dual whole-cell patch-clamp technique that in HeLa (human cervix carcinoma cell line) and N2A (mouse neuroblastoma cell line) cells these mutations reversed the stimulatory effect of hexanol and isoflurane to inhibitory one, typical of other Cxs that lack respective cysteines and a specific docking pocket for these compounds. Our findings suggest that the stimulatory effect of hexanol and isoflurane on Cx36 GJ conductance could be achieved by re-shuffling of the inter-subunit disulphide bond between C264 and C92 to the intra-subunit one between C264 and C87.

Genome scale metabolic models as tools for drug design and personalized medicine.

In this work we aim to show how Genome Scale Metabolic Models (GSMMs) can be used as tools for drug design. By comparing the chemical structures of human metabolites (obtained using their KEGG indexes) and the compounds contained in the DrugBank database, we have observed that compounds showing Tanimoto scores higher than 0.9 with a metabolite, are 29.5 times more likely to bind the enzymes metabolizing the considered metabolite, than ligands chosen randomly. By using RNA-seq data to constrain a human GSMM it is possible to obtain an estimation of its distribution of metabolic fluxes and to quantify the effects of restraining the rate of chosen metabolic reactions (for example using a drug that inhibits the enzymes catalyzing the mentioned reactions). This method allowed us to predict the differential effects of lipoamide analogs on the proliferation of MCF7 (a breast cancer cell line) and ASM (airway smooth muscle) cells respectively. These differential effects were confirmed experimentally, which provides a proof of concept of how human GSMMs could be used to find therapeutic windows against cancer. By using RNA-seq data of 34 different cancer cell lines and 26 healthy tissues, we assessed the putative anticancer effects of the compounds in DrugBank which are structurally similar to human metabolites. Among other results it was predicted that the mevalonate pathway might constitute a good therapeutic window against cancer proliferation, due to the fact that most cancer cell lines do not express the cholesterol transporter NPC1L1 and the lipoprotein lipase LPL, which makes them rely on the mevalonate pathway to obtain cholesterol.

Predicting Isoform-specific Binding Selectivities of Benzensulfonamides Using QSAR and 3D-QSAR.

BACKGROUND: Design of isoform-specific inhibitors is a major challenge in the new therapeutic agents development. METHODS: The article describes the development of a robust selectivity for CA XII QSAR and 3DQSAR models of 40 benzenesulfonamide derivatives bearing pyrimidine moieties using PHASE module of Schrödinger for 3D-QSAR or E-DRAGON and R software for 2D-QSAR. Two QSAR protocols were explored: traditional (affinity) and selectivity (affinity ratio) based. RESULTS: A total of 25 2D and 3D-QSAR models were developed using a training set of 30 compounds using the two protocols for 6 CA isoforms. A new ad hoc descriptor T(OH..Cl) was created targeting CA XII affinity. Satisfactory results were obtained in terms of model quality expressed statistically as F, R2 and R2ADJ. Developed models were analyzed using different statistical validation techniques, both by using the Leave One Out (LOO) criterion, and by applying a model on a test set. The Applicability Domains of the 2D-QSAR models were determined. Two PHASE (affinity and selectivity) 3D-QSAR models were rationalized by manual docking of the ligands into the X-ray crystal structures. The affinity and selectivity based protocols were compared. CONCLUSION: This study provides insights for designing sulfonamide compounds with a better isoform selectivity.

Comparison of Performance of Docking, LIE, Metadynamics and QSAR in Predicting Binding Affinity of Benzenesulfonamides.

The design of inhibitors specific for one relevant carbonic anhydrase isozyme is the major challenge in the new therapeutic agents development. Comparative computational chemical structure and biological activity relationship studies on a series of carbonic anhydrase II inhibitors, benzenesulfonamide derivatives, bearing pyrimidine moieties are reported in this paper using docking, Linear Interaction Energy (LIE), Metadynamics and Quantitative Structure Activity Relationship (QSAR) methods. The computed binding affinities were compared with the experimental data with the goal to explore strengths and weaknesses of various approaches applied to the investigated carbonic anhydrase/inhibitor system. From the tested methods initially only QSAR showed promising results (R2=0.83-0.89 between experimentally determined versus predicted pKd values.). Possible reasons for this performance were discussed. A modification of the LIE method was suggested which used an alternative LIE-like equation yielding significantly improved results (R2 between the experimentally determined versus the predicted ΔG(bind) improved from 0.24 to 0.50).

Synthesis and antiproliferative activity of α-branched α,ß-unsaturated ketones in human hematological and solid cancer cell lines.

A series of α-branched α,ß-unsaturated ketones were prepared via boron trifluoride etherate mediated reaction between arylalkynes and carboxaldehydes. The evaluation of the antiproliferative activity over hematological (NB4) and solid cancer (A549, MCF-7) cell lines provided a structure-activity relationship. 5-Parameter QSAR equations were built which were able to explain 80%-92% of the variance in activity. The resulting selective lead compound showed IC50 value 0.6 µM against the hematological cell line and did not cause apoptosis, but blocked cell cycle in G0/G1. Moreover, it was demonstrated that this compound enhances and accelerates retinoic acid induced granulocytic differentiation.