Isolation, characterization and in silico docking studies of synergistic estrogen receptor a anticancer polyphenols from Syzygium alternifolium (Wt.) Walp

ESR1 F404 Mutations and Acquired Resistance to Fulvestrant in ESR1-Mutant Breast Cancer

Fulvestrant is used to treat patients with hormone receptor-positive advanced breast cancer, but acquired resistance is poorly understood. PlasmaMATCH Cohort A (NCT03182634) investigated the activity of fulvestrant in patients with activating ESR1 mutations in circulating tumor DNA (ctDNA). Baseline ESR1 mutations Y537S are associated with poor outcomes and Y537C with good outcomes. Sequencing of baseline and EOT ctDNA samples (n = 69) revealed 3/69 (4%) patients acquired novel ESR1 F404 mutations (F404L, F404I, and F404V), in cis with activating mutations. In silico modeling revealed that ESR1 F404 contributes to fulvestrant binding to estrogen receptor-alpha (ERα) through a pi-stacking bond, with mutations disrupting this bond. In vitro analysis demonstrated that single F404L, E380Q, and D538G models were less sensitive to fulvestrant, whereas compound mutations D538G + F404L and E380Q + F404L were resistant. Several oral ERα degraders were active against compound mutant models. We have identified a resistance mechanism specific to fulvestrant that can be targeted by treatments in clinical development.

SIGNIFICANCE

Novel F404 ESR1 mutations may be acquired to cause overt resistance to fulvestrant when combined with preexisting activating ESR1 mutations. Novel combinations of mutations in the ER ligand binding domain may cause drug-specific resistance, emphasizing the potential of similar drug-specific mutations to impact the efficacy of oral ER degraders in development. This article is featured in Selected Articles from This Issue, p. 201.

Review green synthesis of silver nanoparticles by using plant extracts and their antimicrobial activity

Interest in the biosynthesis of nanoparticles has increased in the last era by researchers. Nanoparticles have several applications in different fields like optoelectronics, magnetic devices, drug delivery, and sensors. Nanoparticle synthesis by green methods is safe for the environment and should be explored and encouraged popularly since various plants' have the high extent to form these nanoparticles. Worldwide, UV spectroscopy, X-ray diffraction, Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM), Dynamic Light Scattering (DLS), Atomic Force Microscopy (AFM) besides Fourier Transform Infrared Spectroscopy (FTIR) are used in many ways for characterize nanoparticles. The most advantageous use of AgNPs is their great attribution to be used as antimicrobial agents. Finally, concept of AgNPs synthesis is deserved to be the modern technical and medical concern. The current review shows a complete comprehensive and analytical survey of the biosynthesis of AgNPs with a particular focus on their activities as antimicrobials and the possible theories of their effect on the microbial cell and all influenced secondary metabolites.

Phytochemical profiling and cytotoxic potential of Arnebia nobilis root extracts against hepatocellular carcinoma using in-vitro and in-silico approaches

Hepatocellular carcinoma is the fifth most prevalent cancer worldwide. The emergence of drug resistance and other adverse effects in available anticancer options are challenging to explore natural sources. The current study was designed to decipher the Arnebia nobilis (A. nobilis) extracts for detecting phytochemicals, in-vitro evaluation of antioxidative and cytotoxic potentials, and in-silico prediction of potent anticancer compounds. The phytochemical analysis revealed the presence of flavonoids, phenols, tannins, alkaloids, quinones, and cardiac glycosides, in the ethanol (ANE) and n-hexane (ANH) extracts of A. nobilis. ANH extract exhibited a better antioxidant potential to scavenge DPPH, nitric oxide and superoxide anion radicals than ANE extract, which showed better potential only against H2O2 radicals. In 24 h treatment, ANH extract revealed higher cytotoxicity (IC50 value: 22.77 µg/mL) than ANH extract (IC50 value: 46.74 µg/mL) on cancer (HepG2) cells without intoxicating the normal (BHK) cells using MTT assay. A better apoptotic potential was observed in ANH extract (49.10%) compared to ANE extract (41.35%) on HepG2 cells using the annexin V/PI method. GCMS analysis of ANH extract identified 35 phytocompounds, from which only 14 bioactive compounds were selected for molecular docking based on druggability criteria and toxicity filters. Among the five top scorers, deoxyshikonin exhibited the best binding affinities of - 7.2, - 9.2, - 7.2 and - 9.2 kcal/mol against TNF-α, TGF-βR1, Bcl-2 and iNOS, respectively, followed by ethyl cholate and 2-Methyl-6-(4-methylphenyl)hept-2-en-4-one along with their desirable ADMET properties. The phytochemicals of ANH extract could be used as a promising drug candidate for liver cancer after further validations.

Insights into the Pharmacological Effects of Flavonoids: The Systematic Review of Computer Modeling

Computer modeling is a method that is widely used in scientific investigations to predict the biological activity, toxicity, pharmacokinetics, and synthesis strategy of compounds based on the structure of the molecule. This work is a systematic review of articles performed in accordance with the recommendations of PRISMA and contains information on computer modeling of the interaction of classical flavonoids with different biological targets. The review of used computational approaches is presented. Furthermore, the affinities of flavonoids to different targets that are associated with the infection, cardiovascular, and oncological diseases are discussed. Additionally, the methodology of bias risks in molecular docking research based on principles of evidentiary medicine was suggested and discussed. Based on this data, the most active groups of flavonoids and lead compounds for different targets were determined. It was concluded that flavonoids are a promising object for drug development and further research of pharmacology by in vitro, ex vivo, and in vivo models is required.

Antiviral Properties of Polyphenols from Plants

Polyphenols are active substances against various types of viral infections. Researchers have characterized methods of how to isolate polyphenols without losing their potential to formulate pharmaceutical products. Researchers have also described mechanisms against common viral infections (i.e., influenza, herpes, hepatitis, rotavirus, coronavirus). Particular compounds have been discussed together with the plants in the biomass in which they occur. Quercetin, gallic acid and epigallocatechin are exemplary compounds that inhibit the growth cycle of viruses. Special attention has been paid to identify plants and polyphenols that can be efficient against coronavirus infections. It has been proven that polyphenols present in the diet and in pharmaceuticals protect us from viral infections and, in case of infection, support the healing process by various mechanisms, i.e., they block the entry into the host cells, inhibit the multiplication of the virus, seal blood vessels and protect against superinfection.

Chrysin alleviates alteration of bone-remodeling markers in ovariectomized rats and exhibits estrogen-like activity in silico

BACKGROUND

Evidences are beginning to accrue that flavonoids, particularly phytoestrogens, could have beneficial effects against several age-related diseases linked to estrogen deficiency including postmenopausal osteoporosis.

METHODS

In this study, the effect of chrysin on selected bone-remodeling markers in ovariectomized rats and its estrogen-like activity in silico were investigated.

RESULTS

The data indicated that administration of chrysin at 50 mg/kg and 100 mg/kg for 6 weeks to OVX rats significantly (p < 0.05) prevented body weight gain and partially reverse uterine weight loss. In addition, treatment of OVX rats significantly (p < 0.01) increased femur dry weight, femur ash weight, bone ash calcium, and phosphorous levels in a dose-dependent manner. However, there was significant (p < 0.001) decline in serum estradiol level in all OVX rats compared to the sham-operated group. Interestingly, administration of chrysin significantly (p < 0.05) reversed the reduction of estradiol induced by ovariectomy compared to untreated OVX rats. Moreover, administration of chrysin to OVX rats significantly (p < 0.05) suppressed excessive elevation of bone-remodeling markers expression compared to untreated OVX rats. Similarly, molecular docking analysis revealed that chrysin interacts with both α and β estrogen receptors with exothermic binding energies of -229.83 kcal/Mol and -252.72 kcal/Mol, respectively, and also fits perfectly into the active site of both α and β estrogen receptors.

CONCLUSION

This study demonstrated that chrysin exhibits potential antiosteoporotic effects against bone loss in OVX rats through enhanced bone mineral contents and preventing excessive elevation of bone-remodeling markers and bone-resorbing cytokine.

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

Predicting Meridian in Chinese traditional medicine using machine learning approaches

Plant-derived nature products, known as herb formulas, have been commonly used in Traditional Chinese Medicine (TCM) for disease prevention and treatment. The herbs have been traditionally classified into different categories according to the TCM Organ systems known as Meridians. Despite the increasing knowledge on the active components of the herbs, the rationale of Meridian classification remains poorly understood. In this study, we took a machine learning approach to explore the classification of Meridian. We determined the molecule features for 646 herbs and their active components including structure-based fingerprints and ADME properties (absorption, distribution, metabolism and excretion), and found that the Meridian can be predicted by machine learning approaches with a top accuracy of 0.83. We also identified the top compound features that were important for the Meridian prediction. To the best of our knowledge, this is the first time that molecular properties of the herb compounds are associated with the TCM Meridians. Taken together, the machine learning approach may provide novel insights for the understanding of molecular evidence of Meridians in TCM.

Identification by Molecular Docking ofHomoisoflavones from Leopoldia comosa as Ligands of Estrogen Receptors

The physiological responses to estrogen hormones are mediated within specific tissues by at least two distinct receptors, ERα and ERβ. Several natural and synthetic molecules show activity by interacting with these proteins. In particular, a number of vegetal compounds known as phytoestrogens shows estrogenic or anti-estrogenic activity. The majority of these compounds belongs to the isoflavones family and the most representative one, genistein, shows anti-proliferative effects on various hormone-sensitive cancer cells, including breast, ovarian and prostate cancer. In this work we describe the identification of structurally related homoisoflavones isolated from Leopoldia comosa (L.) Parl. (L. comosa), a perennial bulbous plant, potentially useful as hormonal substitutes or complements in cancer treatments. Two of these compounds have been selected as potential ligands of estrogen receptors (ERs) and the interaction with both isoforms of estrogen receptors have been investigated through molecular docking on their crystallographic structures. The results provide evidence of the binding of these compounds to the target receptors and their interactions with key residues of the active sites of the two proteins, and thus they could represent suitable leads for the development of novel tools for the dissection of ER signaling and the development of new pharmacological treatments in hormone-sensitive cancers.