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Isolation, Identification and Synthesis of Neolignans from Phoebe declinata Leaves: Molecular Modeling and Anticancer Evaluation
Abstract and Figures
Two series of neolignans, aristoligol (R1) and aristoligone (R2), had been isolated from P. declinata Nees (Lauraceae) plant leaves. Dichloromethane (D.C.M.) was used to isolate R1 and R2 using flask silica column chromatography as a stationary phase. Meanwhile, n-hexane, dichloromethane, and methanol were used as mobile phases. Moreover, the synthesis of compound R2 to produce acetyl aristoligol (R3) was also done in this study. Compound R2 was synthesized with a reducing agent in methanol (NaBH4/MeOH) to result in a transition compound, the reduced-aristoligol. The transition compound was acetylated with acetic anhydride and catalyzed by D.M.A.P. to produce compound R3. The molecular structure identification of all neolignans and their molecular weights was validated by 1 H-NMR, 13 C-NMR, 2D-NMR, and LC-MS. Further determination of their structure-activity relationship, including molecular modeling and in vitro antiproliferative activity against MCF-7 breast cancer cell lines, showed that compound R2 has the best binding affinity towards human estrogen receptor-1 (∆G =-6.7 kcal/mol, Ki = 1.21 x 10-5 M). The ADME properties showed that compound R2 is the best one but still less active compared to the standard cancer drug, doxorubicin (∆G =-8.1 kcal/mol and Ki = 1.14 x 10-6 M). Meanwhile, compound R1 has the highest activity to inhibit the MCF-7 cell proliferation, with a 25 µg/mL concentration, and the highest cytotoxic activity with IC50 was 35 µg/mL.
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Breast cancer is one of the leading causes of death in women worldwide. Breast cancer can be triggered due to physical, chemical, environmental factors and can be passed down from generation to generation through genetics. Therefore, recently, studies have been intensively conducted on the use of medicinal plants for the treatment of breast cancer as an alternative because they have minimal side effects compared to other chemotherapy. This review aims to describe medicinal plants and their active compounds that have the potential as anticancer therapy which has been carried out in silico studies with molecular anchoring methods. The method used in writing this article is a literature review both nationally and internationally over the last five years using the keywords breast cancer, molecular docking, herbal plants, anticancer, in databases such as PubMed, Cochrane, and Google Scholar. Herbal plants in in silico research that have high potential for further research as cancer therapy include 33 herbal plants with different active compounds and protein targets.
Phoebe is a well-known timber tree species that contains abundant metabolites characterized by flavonoids that are widely used in the pharmaceutical industry. Nevertheless, temporospatial flavonoid metabolism variations substantially impact the Phoebe industry. Thus, a metabolomics analysis was carried out and identified 465 metabolites (102 flavonoids) in P. bournei, revealing distinct distribution patterns among five studied organs, and most of the flavonoids were dominant in the leaves. Furthermore, three kaempferol glycoside derivatives were significantly accumulated in the leaves and showed higher contents in young leaves than in mature leaves and differences between spring and autumn. For instance, greater accumulation of kaempferol-7-O-rhamnoside was detected in spring, whereas higher contents of kaempferol-3-O-arabinofuranoside and kaempferol-3-O-rhamnoside were found in autumn. Integrated metabolomics and transcriptomics identified 20 transcription factors (TFs) and 12 structural genes that participate in kaempferol derivative synthesis and elucidated a potential regulatory mechanism in P. bournei. Of the identified genes, PbMYB211 might contribute significantly to the kaempferol-3-O-rhamnoside content by regulating the target structural gene PbUGT139, as revealed by transient overexpression analysis. Overall, this study illuminated the temporospatial accumulation of flavonoids among different organs, seasons, and developmental stages in P. bournei and elucidated a potential regulatory pathway of kaempferol-3-O-rhamnoside. The results provide important insights into harvest techniques and a theoretical basis for the comprehensive utilization of P. bournei.
Estrogens generated within endocrine organs and the reproductive system act as ligands
for at least three types of estrogen receptors. Estrogen receptors α (ERα) and β (ERβ) belong
to the so-called classical family of estrogen receptors, whereas the G protein-coupled
receptor GPR30, also known as GPER-1, has been described as a novel estrogen receptor
sited in the cell membrane of target cells. Furthermore, these receptors are under stimulation
of a family of exogenous estrogens, known as phytoestrogens, which are a diverse
group of non-steroidal plant compounds derived from plant food consumed by humans
and animals. Because phytoestrogens are omnipresent in our daily diet, they are becoming
increasingly important in both human health and disease. Recent evidence indicates that
in addition to classical estrogen receptors, phytoestrogens also activate GPER-1 a relevant
observation since GPER-1 is involved in several physiopathological disorders and especially
in estrogen-dependent diseases such as breast cancer.
The first estrogen receptors discovered were the classical ERα and ERβ, but from an evolutionary
point of view G protein-coupled receptors trace their origins in history to over a
billion years ago suggesting that estrogen receptors like GPER-1 may have been the targets
of choice for ancient phytoestrogens and/or estrogens.
This review provides a comprehensive and systematic literature search on phytoestrogens
and its relationship with classical estrogen receptors and GPER-1 including its role in breast
cancer, an issue still under discussion.
Lauraceae is a good source of lignans and neolignans, which are the most chemotaxonomic characteristics of many species of the family. This review describes 270 naturally occurring lignans and neolignans isolated from Lauraceae.
Background
Most breast cancers are estrogen dependent and were sensitive to endocrine therapy, and genistein (GEN) shows strong affinity with human oestrogen receptor beta (ERβ).
Purpose
The present study aimed to investigate the anticancer activity of GEN in breast cancer cell lines that constitutively expressing ERβ1 in vitro and in vivo.
Methods
MCF-7/ERβ1 and MDA-MB-231/ERβ1 cell sub-lines were established through lentiviral infection. Then, cells were treated with increasing concentrations of GEN (10⁻⁶ mol/l, 10⁻⁵ mol/l and 10⁻⁴ mol/l) for 48 h, and cell proliferation, cell cycle analyses were performed to investigate different biological characteristics of ERβ1-overexpressing cell lines. Studies in vivo were also performed to investigate the effects of dietary GEN on MCF-7/ERβ1 and MDA-MB-231/ERβ1 cells implanted mice.
Results
Results showed that compared to parental cells, GEN inhibited the proliferation ability of MCF-7/ERβ1 cells to a greater extent, especially at high concentrations. MDA-MB-231 cells were also inhibited by high doses of GEN, but the overexpressed ERβ1 did not enhance the anti-proliferative effect on MDA-MB-231 cells. ERβ1 arrested cells in G2/M phase, and GEN arrested cells in G0/G1, which led to a combinatorial effect on cell cycle blockade. Furthermore, ERβ1 increased the anti-tumour activity of dietary GEN in MCF-7/ERβ1 subcutaneous tumour models. Our data indicated that ERβ1 increased the anticancer efficacy of GEN in MCF-7 cells by affecting cell cycle transition.
Conclusion
As a result, GEN could be a potential therapeutic agent for ERβ1-positive cancer.
The absorption, distribution, metabolism and excretion properties are important for drugs, and prediction of these properties in advance will save the cost of drug discovery substantially. The ability to penetrate the blood–brain barrier is critical for drugs targeting central nervous system, which is represented by the ratio of its concentration in brain and in blood. Herein, a quantitative structure–property relationship study was carried out to predict blood–brain partitioning coefficient (logBB) of a data set consisting of 287 compounds. Four different methods including support vector machine, multivariate linear regression, multivariate adaptive regression splines and random forest were employed to build prediction models with 116 molecular descriptors selected by Boruta algorithm. The RF model had best performance in training set (R2 = 0.938), test set (R2 = 0.840) and tenfold cross-validation (Q2 = 0.788). Finally, we found that the polar surface area and octanol–water partition coefficient have the greatest influence on blood–brain partitioning. Results suggest that the proposed model is a useful and practical tool to predict the logBB values of drug candidates.
To improve the production yield of (+)-pinoresinol (Pin), (+)-pinoresinol monoglucoside (PMG), and (+)-pinoresinol diglucoside (PDG), different methods were conducted, including co-culture with resveratrol-producing Alternaria sp. MG1 spores and addition of Tu-chung in a medium at the start of cultivation, ultrasound treatment (40 kHZ, 10 min) on 5-day culture, and addition of ethanol and sodium butyrate on Day 3, followed by cultivation for an additional period of 2 days. At the end of the cultivation period (5 days), the liquid phase was collected for product analysis. Cells were collected for the determination of gene expression levels and then used in bioconversion using resting cells for another period of 2 days. The liquid phase was measured to determine the output of the target products and the expression levels of the key genes related to the biosynthesis of these compounds. Consequently, co-culture with Alternaria MG1 and addition of Tu-chung bark in the medium efficiently increased Pin, PMG, and PDG production yield in the biosynthesis systems using potato dextrose broth medium and resting cells of Phomopsis sp. XP-8. The key genes related to the biosynthesis of these compounds were significantly upregulated. However, in the majority of cases, the addition of ethanol and sodium butyrate, and ultrasound treatment decreased the production yield of Pin, PMG, and PDG. The change in production yield was not consistently accompanied by a change in gene expression.
A Preliminary Investigation of The Alkaloid of Phoebe Lanceolata
Successful drug discovery projects require control and optimization of compound properties related to pharmacokinetics, pharmacodynamics and safety. While volume and chemotype coverage of public and corporate ADME-Tox databases are constantly growing, deep neural nets (DNN) emerged as transformative artificial intelligence technology to analyse those challenging data. Relevant features are automatically identified, while appropriate data can also be combined to multitask networks to evaluate hidden trends between multiple ADME-Tox parameters for implicitly correlated datasets. Here we describe a novel, fully industrialized approach to parametrize and optimize the setup, training, application and visual interpretation of DNNs to model ADME-Tox data. Investigated properties include microsomal lability in different species, passive permeability in Caco-2/TC7 cells, and logD. Statistical models are developed using up to 50,000 compounds from public or corporate databases. Both the choice of DNN hyperparameters as well as type and quantity of molecular descriptors were found to be important for successful DNN modelling. Alternate learning of multiple ADME-Tox properties, resulting in a multitask approach, performs statistical superior on most studied datasets in comparison to DNN single-task models and also provides a scalable method to predict ADME-Tox properties from heterogeneous data. For example, predictive quality using external validation sets was improved from R² of 0.6 to 0.7 comparing single-task and multitask DNN networks from human metabolic lability data. Besides statistical evaluation, a new visualization approach is introduced to interpret DNN models termed ‘response map’, which is useful to detect local property gradients based on structure fragmentation and derivatization. This method is successfully applied to visualize fragmental contributions to guide further design in drug discovery programs, as illustrated by CRCX3 antagonists and renin inhibitors, respectively.
The essential oil were extracted from the leaf of Phoebe bournei (Hemsl.) Yang by a hydrothermal method and then analyzed by gas chromatography–mass spectrometry. The leaf oil mainly included α-copaene (5.44%), α-muurolene (7.32%), δ-cadinene (11.44%), 1s-calamenene (5.18%). Phoebe bournei (Hemsl.) Yang leaf essential oil had significant inhibitory activity against Epidermophyton floccosum and Microsporum gypseum, the potential antitumor activity towards leukemia, breast, and colon cancer cell lines was good. Phoebe bournei (Hemsl.) Yang leaf essential oil had weaker activity on the four tested bacteria, it exhibited a certain role in promoting glucose uptake by adipocytes.
Present work aimed to synthesize some unique bi-heterocyclic benzamides as lead compounds for the in vitro inhibition of urease enzyme, followed by in silico studies. These targeted benzamides were synthesized in good yields through a multi-step protocol and their structures were confirmed by IR, ¹H NMR, ¹³C NMR, EI-MS and elemental analysis. The in vitro screening results showed that most of the ligands exhibited good inhibitory potentials against the urease. Chemo-informatics analysis envisaged that all these compounds obeyed the Lipinski's rule. Molecular docking results showed that 7h exhibited good binding energy value (−8.40 kcal/mol) and was bound within the active region of urease enzyme. From the present investigation, it was inferred that some of these potent urease inhibitors might serve as novel templates in drug designing.
CXCR4 is a G protein-coupled receptor that interacts with its cognate ligand CXCL12 to synchronize many physiological responses and pathological processes. Disruption of the CXCL12-CXCR4 circuitry by small molecule antagonists has emerged as a promising strategy for cancer intervention. We previously disclosed a hit-to-lead effort that led to the discovery of a series of tetrahydroisoquinoline-based CXCR4 antagonists exemplified by the lead compound TIQ15. Herein, we describe our medicinal chemistry efforts toward the redesign of TIQ15 as a result of high mouse microsomal clearance, potent CYP2D6 inhibition, and poor membrane permeability. Guided by the in vitro ADME data of TIQ15, structural modifications were executed to provide compound 12a which demonstrated a reduced potential for first-pass metabolism while maintaining the CXCR4 potency. Subsequent SAR studies and multiparameter optimization of 12a resulted in the identification of compound 25o, a highly potent, selective, and metabolically stable CXCR4 antagonist possessing good intestinal permeability and low risk of CYP-mediated drug-drug interactions.