Dietary Inhibitors of CYP3A4 Are Revealed Using Virtual Screening by Using a New Deep-Learning Classifier

An optimized CYP3A4-activatable fluorogenic sensor for in situ functional imaging and multi-dimensional inhibitor assessment

Cytochrome P450 3A4 (CYP3A4), one of the most important drug-metabolizing enzymes, plays a pivotal role in the oxidative metabolism of a wide range of non-polar xenobiotics and endogenous substances. Deciphering the dynamic changes in CYP3A4 activity under specific physiological or pathological conditions, as well as assessing the modulatory effects of therapeutic agents on CYP3A4, requires highly-efficient and reliable tools for sensing CYP3A4 activity within complex biological matrices. Herein, an integrated strategy was adopted for developing an optimized CYP3A4-activatable fluorogenic sensor that enables in situ detection of CYP3A4 activity in living systems without the interference of P-glycoprotein (P-gp), via integrating computer-aided substrate design, drug-likeness filtering, and biochemical assays. Following screening a range of 1,8-naphthalimide derivatives, N-cyclopropylmethyl-1,8-naphthalimide (NCN) was identified as an optimized fluorogenic substrate for CYP3A4, demonstrating exceptional isoform-specificity, single metabolite formation, ultrahigh sensitivity, high binding-affinity, improved cell-membrane permeability, and favorable bio-safety profiles. Notably, both NCN and its fluorogenic metabolite (HNCN) were identified as non-substrates of P-gp, which greatly facilitated in situ functional imaging of CYP3A4 activities in living systems, such as live cells and organs. It was also found that NCN was an orally bioavailable agent, which significantly facilitated the precise assessment of CYP3A4 inhibitors across multi-dimensional biological systems, including in vitro, ex vivo, and in vivo. Collectively, this work showcases an integrated strategy for the rational engineering of isoform-specific and orally bioavailable CYP3A4-activatable fluorogenic substrates for CYP3A4, with NCN emerging as a practical and reliable CYP3A4-activatable tool for in situ imaging and inhibitor assessment.

Identification of Food-Derived Electrophilic Chalcones as Nrf2 Activators Using Comprehensive Virtual Screening Techniques

Electrophilic compounds are bioactive components commonly found in foods that are capable of covalently modifying nucleophilic sites on biologically functional macromolecules. These compounds may elicit positive bioactivity or negative biotoxicity, posing significant challenges in terms of time and resource expenditure in the de novo characterization of their biological activity. In this study, we developed a database of 332 food-derived electrophilic compounds and used a semi-supervised k-nearest neighbors (KNN) machine learning model to predict their bioactivity. Molecular docking analysis identified the three chalcone compounds with the highest potential positive activity-4-hydroxyderricin (4HD), isoliquiritigenin (ISO), and butein. Furthermore, in cell experiments, treatment with 4HD, ISO, and butein significantly reduced reactive oxygen species (ROS) levels. An RT-qPCR analysis demonstrated that these chalcones significantly upregulated the mRNA expression of Nrf2 and its downstream antioxidant genes, including Nqo1, HO-1, Gsr, Gclc, and Gclm. ISO's cytoprotective and antioxidant effects were abolished following these findings, which highlight that 4HD, ISO, and butein are effective Nrf2 activators and suggest that comprehensive virtual technology is a promising strategy for identifying functional bioactive compounds.

Effects of Crocus sativus and its active constituents on cytochrome P450: a review

Cytochrome P450 (CYP) enzymes play an important role in the biotransformation of drugs and endogenous substances. Clinical medications and herbal remedies can either enhance or inhibit the activity of CYP enzymes, leading to potential drug interactions between herbal supplements and prescribed medications. Such interactions can lead to serious consequences, especially for drugs with a narrow therapeutic index, such as digoxin, warfarin, and cyclosporine A. In this review article, we provide an updated review of the impact of saffron, and its active constituents, safranal and crocin, on the 12 major human CYP enzymes and possible drug interactions between saffron and prescription drugs. The available evidence indicates that saffron and its active constituents affect the expression or activity of some CYP isoforms, including the CYP1A1/2, CYP3A4, and CYP2E1 subfamily. Considering the important role of these CYPs in the biotransformation of frequently prescribed medications and the activation of procarcinogen into carcinogenic metabolites, it can be expected that the consumption of saffron and its active constituents may influence the pharmacokinetics and toxicity of several substances. In particular, given the critical role of CYP3A4 in drug metabolism, and saffron's inhibitory impact on this CYP enzyme, it appears that saffron's most significant interaction is linked to its inhibition of CYP3A4. In addition, the inhibitory effect of saffron on CYP1A1/2, and CYP2E1 expression can play a role in the chemopreventive effect of this herbal medicine. Additional research is crucial for evaluating the clinical significance of these interactions in patients who consume saffron along with prescription drugs and determining the dose that can lead to drug interactions.

Interaction of Phyllanthus amarus extract and its lignans with human xenobiotic receptors, drug metabolizing enzymes and drug transporters

ETHNOPHARMACOLOGICAL RELEVANCE

Phyllanthus amarus is ethnomedicinally used to treat gallbladder stones, kidney stones and chronic liver diseases. P. amarus is gaining popularity as an ingredient in many botanical dietary supplements.

AIM OF THE STUDY

To evaluate the interaction of P. amarus extract and its lignans with human xenobiotic sensing receptors (PXR and AhR) and their downstream genes.

MATERIALS AND METHODS

Activation of PXR and AhR was measured by reporter gene assays. Gene expression analysis was performed in hepatic (HepG2) and intestinal (LS174T) cells by RT-PCR. CYP inhibition assays were carried out in baculosomes. The inhibitory effect on the ABC transporters (P-gp and BCRP) was investigated via rhodamine-123 and Hoechst 33342 uptake assays in Caco-2 and MDR-MDCK cells. Effect on CYP3A4 and CYP1A2 enzyme activity was measured in primary human hepatocytes.

RESULTS

P. amarus extract and its lignans activated AhR and PXR in respective reporter cells. Tested extract and lignans significantly increased CYP3A4 mRNA but inhibited CYP3A4 enzyme activity when tested in primary human hepatocytes and CYP3A4-specific baculosomes. In contrast, increased CYP1A2 mRNA was associated with increased CYP1A2 enzyme activity in hepatocytes. No inhibition of CYP1A2 activity was detected in baculosomes. A weak inhibitory effect on ABC-transporters was observed.

CONCLUSIONS

Results suggest that overconsumption of P. amarus or P. amarus-containing botanical supplements may change CYP homeostasis which could alter the pharmacokinetics of substrate drugs, thereby elevating the risk of herb-drug interactions (HDIs) when taken concomitantly with conventional medications. Further studies are warranted to strengthen the clinical relevance of these findings.

Effects of Berberis vulgaris, and its active constituent berberine on cytochrome P450: a review

The cytochrome P450 (CYP450) family is crucial for metabolizing drugs and natural substances. Numerous compounds, such as pharmaceuticals and dietary items, can influence CYP activity by either enhancing or inhibiting these enzymes, potentially leading to interactions between drugs or between drugs and food. This research explores the impact of barberry and its primary component "berberine" on key human CYP450 enzymes. The text discusses the effects of this plant on the 12 primary human CYP450 enzymes, with summarized data presented in tables. Berberine exerts an influence on the function of various CYP450 isoforms, including CYP3A4/5, CYP2D6, CYP2C9, CYP2E1, CYP1A1/2, and most isoforms within the CYP2B subfamily. Given the significant role of these CYP450 isoforms in metabolizing commonly used drugs and endogenous substances, as well as activating procarcinogens into carcinogenic metabolites, the influence of barberry and its active constituent on these enzymes may impact the pharmacokinetics and toxicity profiles of various compounds. More specifically, regarding the crucial role of CYP2D6 and CYP3A4 in metabolizing clinically used drugs, and the inhibitory effects of berberine on these two CYP450 isoforms, it seems that the most important drug interaction of berberine that should be considered is related to its inhibitory effect on CYP2D6 and CYP3A4. In conclusion, due to the impact of barberry on multiple CYP450 isoforms, healthcare providers should conduct thorough consultations and investigations to ensure patient safety and prevent any potential adverse interactions before recommending the consumption of these herbs. Additional research, particularly clinical trials is crucial for preventing any potentially adverse interactions in patients who consume this herb.

Design and investigation of interactions of novel peptide conjugates of purine and pyrimidine derivatives with EGFR and its mutant T790M/L858R: an in silico and laboratory study

Peptide-based therapeutics have been gaining attention due to their ability to actively target tumor cells. Additionally, several varieties of nucleotide derivatives have been developed to reduce cell proliferation and induce apoptosis of tumor cells. In this work, we have developed novel peptide conjugates with newly designed purine analogs and pyrimidine derivatives and explored the binding interactions with the kinase domain of wild-type EGFR and its mutant EGFR [L858R/ T790M] which are known to be over-expressed in tumor cells. The peptides explored included WNWKV (derived from sea cucumber) and LARFFS, which in previous work was predicted to bind to Domain I of EGFR. Computational studies conducted to explore binding interactions include molecular docking studies, molecular dynamics simulations and MMGBSA to investigate the binding abilities and stability of the complexes. The results indicate that conjugation enhanced binding capabilities, particularly for the WNWKV conjugates. MMGBSA analysis revealed nearly twofold higher binding toward the T790M/L858R double mutant receptor. Several conjugates were shown to have strong and stable binding with both wild-type and mutant EGFR. As a proof of concept, we synthesized pyrimidine conjugates with both peptides and determined the KD values using SPR analysis. The results corroborated with the computational analyses. Additionally, cell viability and apoptosis studies with lung cancer cells expressing the wild-type and double mutant proteins revealed that the WNWKV conjugate showed greater potency than the LARFFS conjugate, while LARFFS peptide alone showed poor binding to the kinase domain. Thus, we have designed peptide conjugates that show potential for further laboratory studies for developing therapeutics for targeting the EGFR receptor and its mutant T790M/L858R.

Relative synonymous codon usage and codon pair analysis of depression associated genes

Depression negatively impacts mood, behavior, and mental and physical health. It is the third leading cause of suicides worldwide and leads to decreased quality of life. We examined 18 genes available at the genetic testing registry (GTR) from the National Center for Biotechnological Information to investigate molecular patterns present in depression-associated genes. Different genotypes and differential expression of the genes are responsible for ensuing depression. The present study, investigated codon pattern analysis, which might play imperative roles in modulating gene expression of depression-associated genes. Of the 18 genes, seven and two genes tended to up- and down-regulate, respectively, and, for the remaining genes, different genotypes, an outcome of SNPs were responsible alone or in combination with differential expression for different conditions associated with depression. Codon context analysis revealed the abundance of identical GTG-GTG and CTG-CTG pairs, and the rarity of methionine-initiated codon pairs. Information based on codon usage, preferred codons, rare, and codon context might be used in constructing a deliverable synthetic construct to correct the gene expression level of the human body, which is altered in the depressive state. Other molecular signatures also revealed the role of evolutionary forces in shaping codon usage.

Computational and artificial intelligence-based approaches for drug metabolism and transport prediction

Drug metabolism and transport, orchestrated by drug-metabolizing enzymes (DMEs) and drug transporters (DTs), are implicated in drug-drug interactions (DDIs) and adverse drug reactions (ADRs). Reliable and precise predictions of DDIs and ADRs are critical in the early stages of drug development to reduce the rate of drug candidate failure. A variety of experimental and computational technologies have been developed to predict DDIs and ADRs. Recent artificial intelligence (AI) approaches offer new opportunities for better predicting and understanding the complex processes related to drug metabolism and transport. We summarize the role of major DMEs and DTs, and provide an overview of current progress in computational approaches for the prediction of drug metabolism, transport, and DDIs, with an emphasis on AI including machine learning (ML) and deep learning (DL) modeling.

In vitro activity of the novel Fe-cyclam complex against clinical multidrug-resistant bacterial isolates from Brazil

Aim: To evaluate the effect of a new Fe-cyclam complex on pathogenic bacterial species, including multidrug-resistant clinical specimens. Materials & methods: The complex [Fe(cyclam)ox]PF6 (D2) was tested in cytotoxicity and MIC tests. Clinical and reference strains of Gram-negative and Gram-positive bacteria were used. Considering Staphylococcus aureus strains, the profile of antimicrobial susceptibility and time-kill kinetics for D2 was performed. An in silico analysis for D2 was also performed. Results: D2 showed broad bacterial activity, mainly against specimens of Cutibacterium acnes, S. aureus, Pseudomonas aeruginosa and Acinetobacter baumannii. Low cytotoxicity in human cells was demonstrated. Conclusion: The tested compound proved to be a promising agent against resistant bacterial infections.

Ni2+ and Cu2+ complexes of N-(2,6-dichlorophenyl)-N-mesityl formamidine dithiocarbamate structural and functional properties as CYP3A4 potential substrates

Metal compounds continued to attract diverse applications due to their malleability in several capacities. In this study, we present our findings on the crystal structures and functional properties of Ni2+ and Cu2+ complexes of N'-(2,6-dichlorophenyl)-N-mesitylformamidine dithiocarbamate (L) comprising [Ni-(L)2] (1) and [Cu-(L)2] (2) with a four-coordinate metal center. We established the two complex structures through 1H and 13C nuclear magnetic resonance (NMR), elemental, and single-crystal X-ray analysis. The analyses showed that the two complexes are isomorphous, having P21/c as a space group and a unit-cell similarity index (π) of 0.002. The two complexes conform to a distorted square planar geometry around the metal centers. The calculated and experimental data, including bond lengths, angles, and NMR values, are similar. Hirshfeld surface analysis revealed the variational contribution of the different types of intermolecular contacts driven by the crystal lattice of the two solvated complexes. Our knowledge of the potential biological implication of these structures enabled us to probe the compounds as prospective CYP3A4 inhibitors. This approach mimics current trends in pharmaceutical design and biomedicine by incorporating potentially active molecules into various media to predict their biological efficacies. The simulations show appreciable binding of compounds 1 and 2 to CYP3A4 with average interaction energies of -97 and -87 kcal/mol, respectively. The protein attains at least five conformational states in the three studied models using a Gaussian Mixture Model-based clustering and free energy prediction. Electric field analysis shows the crucial residues to substrate binding at the active site, enabling CYP3A4 structure to function prediction. The predicted inhibition with these Ni2+ and Cu2+ complexes indicates that CYP3A4 overexpression in a diseased state like cancer would reduce, thereby increasing the chemotherapeutic compounds' shelf-lives for adsorption. This multidimensional study addresses various aspects of molecular metal electronics, including their application as substrate-mimicking inhibitors. The outcome would enable further research on bio-metal compounds of critical potential.

Virtual Screening of Nrf2 Dietary-Derived Agonists and Safety by a New Deep-Learning Model and Verified In Vitro and In Vivo

Nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is an essential regulatory target of antioxidants, but the lack of Nrf2 active site information has hindered discovery of new Nrf2 agonists from food-derived compounds by large-scale virtual screening. Two deep-learning models were separately trained to screen for Nrf2-agonists and safety. The trained models screened potentially active chemicals from approximately 70,000 dietary compounds within 5 min. Of the 169 potential Nrf2 agonists identified via deep-learning screening, 137 had not been reported before. Six compounds selected from the new Nrf2 agonists significantly increased (p < 0.05) the activity of Nrf2 on carbon tetrachloride (CCl₄)-intoxicated HepG2 cells (nicotiflorin (99.44 ± 18.5%), artemetin (97.91 ± 8.22%), daidzin (87.73 ± 3.77%), linonin (74.27 ± 5.73%), sinensetin (72.74 ± 10.41%), and tectoridin (77.78 ± 4.80%)), and their safety were demonstrated by an MTT assay. The safety and Nrf2 agonistic activity of nicotiflorin, artemetin, and daidzin were also reconfirm by a single-dose acute oral toxicity study and CCl₄-intoxicated rat assay.

A unified GCNN model for predicting CYP450 inhibitors by using graph convolutional neural networks with attention mechanism

Undesirable drug-drug interactions (DDIs) may lead to serious adverse side effects when more than two drugs are administered to a patient simultaneously. One of the most common DDIs is caused by unexpected inhibition of a specific human cytochrome P450 (CYP450), which plays a dominant role in the metabolism of the co-administered drugs. Therefore, a unified and reliable method for predicting the potential inhibitors of CYP450 family is extremely important in drug development. In this work, graph convolutional neural network (GCN) with attention mechanism and 1-D convolutional neural network (CNN) were used to extract the features of CYP ligands and the binding sites of CYP450 respectively, which were then combined to establish a unified GCN-CNN (GCNN) model for predicting the inhibitors of 5 dominant CYP isoforms, i.e., 1A2, 2C9, 2C19, 2D6, and 3A4. Overall, the established GCNN model showed good performances on the test samples and achieved better performances than the recently proposed iCYP-MFE model by using the same datasets. Based on the heat-map analysis of the resulting molecular graphs, the key structural determinants of the CYP inhibitors were further explored.

Computer-Aided (In Silico) Modeling of Cytochrome P450-Mediated Food–Drug Interactions (FDI)

Modifications of the activity of Cytochrome 450 (CYP) enzymes by compounds in food might impair medical treatments. These CYP-mediated food–drug interactions (FDI) play a major role in drug clearance in the intestine and liver. Inter-individual variation in both CYP expression and structure is an important determinant of FDI. Traditional targeted approaches have highlighted a limited number of dietary inhibitors and single-nucleotide variations (SNVs), each determining personal CYP activity and inhibition. These approaches are costly in time, money and labor. Here, we review computational tools and databases that are already available and are relevant to predicting CYP-mediated FDIs. Computer-aided approaches such as protein–ligand interaction modeling and the virtual screening of big data narrow down hundreds of thousands of items in databanks to a few putative targets, to which the research resources could be further directed. Structure-based methods are used to explore the structural nature of the interaction between compounds and CYP enzymes. However, while collections of chemical, biochemical and genetic data are available today and call for the implementation of big-data approaches, ligand-based machine-learning approaches for virtual screening are still scarcely used for FDI studies. This review of CYP-mediated FDIs promises to attract scientists and the general public.