Sequential ligand- and structure-based virtual screening approach for the identification of potential G protein-coupled estrogen receptor-1 (GPER-1) modulators

GPER binding site detection and description: A flavonoid-based docking and molecular dynamics simulations study

Flavonoids, a phenolic compounds class widely distributed in the plant kingdom, have attracted much interest for their implications on several health and disease processes. Usually, the consumption of this type of compounds is approximately 1 g/d, primarily obtained from cereals, chocolate, and dry legumes ensuring its beneficial role in maintaining the homeostasis of the human body. In this context, in cancer disease prominent data points to the role of flavonoids as adjuvant treatment aimed at the regression of the disease. GPER, an estrogen receptor on the cell surface, has been postulated as a probable orchestrator of the beneficial effects of several flavonoids through modulation/inhibition of various mechanisms that lead to cancer progression. Therefore, applying pocket and cavity protein detection and docking and molecular dynamics simulations (MD), we generate, from a cluster composed of 39 flavonoids, crucial insights into the potential role as GPER ligands, of Puerarin, Isoquercetin, Kaempferol 3-O-glucoside and Petunidin 3-O-glucoside, aglycones whose sugar moiety delimits a new described sugar-acceptor sub-cavity into the cavity binding site on the receptor, as well as of the probable activation mechanism of the receptor and the pivotal residues involved in it. Altogether, our results shed light on the potential use of the aforementioned flavonoids as GPER ligands and for further evaluations in in vitro and in vivo assays to elucidate their probable anti-cancer activity.

The identification of cianidanol as a selective estrogen receptor beta agonist and evaluation of its neuroprotective effects on Parkinson's disease models

AIM

The present study aims to identify selective estrogen receptor beta (ERβ) agonists and to evaluate the neuroprotective mechanism in Parkinson's disease (PD) models.

MAIN METHODS

In-silico studies were carried out using Maestro and GROMACS. Neuroprotective activity and apoptosis were evaluated using cytotoxicity assay and flow cytometry respectively. Gene expression studies were carried out by reverse transcription polymerase chain reaction. Motor and cognitive functions were assessed by actophotometer, rotarod, catalepsy, and elevated plus maze. The neuronal population in the substantia nigra and striatum of rats was assessed by hematoxylin and eosin staining.

KEY FINDINGS

Cianidanol was identified as a selective ERβ agonist through virtual screening. The cianidanol-ERβ complex is stable during the 200 ns simulation and was able to retain the interactions with key amino acid residues. Cianidanol (25 μM) prevents neuronal toxicity and apoptosis induced by rotenone in differentiated SH-SY5Y cells. Additionally, cianidanol (25 μM) increases the expression of ERβ, cathepsin D, and Nrf2 transcripts. The neuroprotective effects of cianidanol (25 μM) were reversed in the presence of a selective ERβ antagonist. In this study, we found that selective activation of ERβ could decrease the transcription of α-synuclein gene. Additionally, cianidanol (10, 20, 30 mg/kg, oral) improves the motor and cognitive deficit in rats induced by rotenone.

SIGNIFICANCE

Cianidanol shows neuroprotective action in PD models and has the potential to serve as a novel therapeutic agent for the treatment of PD.

Oestrogen receptor-independent actions of oestrogen in cancer

Oestrogen, the primary female sex hormone, plays a significant role in tumourigenesis. The major pathway for oestrogen is via binding to its receptor [oestrogen receptor (ERα or β)], followed by nuclear translocation and transcriptional regulation of target genes. Almost 70% of breast tumours are ER + , and endocrine therapies with selective ER modulators (tamoxifen) have been successfully applied. As many as 25% of tamoxifen-treated patients experience disease relapse within 5 years upon completion of chemotherapy. In such cases, the ER-independent oestrogen actions provide a plausible explanation for the resistance, as well as expands the existing horizon of available drug targets. ER-independent oestrogen signalling occurs via one of the following pathways: signalling through membrane receptors, oxidative catabolism giving rise to genotoxic metabolites, effects on mitochondria and redox balance, and induction of inflammatory cytokines. The current review focuses on the non-classical oestrogen signalling, its role in cancer, and its clinical significance.

Identification of potential drug candidates as TGR5 agonist to combat type II diabetes using in silico docking and molecular dynamics simulation studies

A cell surface bile acid receptor TGR5 being considered as a novel target for Type II diabetes found to be expressed in various tissues. A major role for TGR5 is to maintain blood sugar levels and increase in energy expenditure. These benefits make it a potential candidate for the treatment of type 2 diabetes, obesity and other metabolic disorder. To date, many novel TGR5 agonists have been synthesized and evaluated in the literature, but very few in silico computational studies have been reported. The discovery of a high-resolution crystal structure of TGR5 in 2020 provides an excellent opportunity for computational screening of potential agonists. In this study, we, therefore, aim to search novel, less toxic TGR5 agonists by iteratively analyzing molecular docking against TGR5 (PDB ID: 7CFN) by means of structure-based virtual screening. The docking score of the designed coumarin derivatives that have been docked successfully varies between -9.4 and -9.0 kcal/mol. The molecular docking and ADMET profile examinations of compounds D1, D5 and D15 revealed that these have a strong affinity for the active site residues of TGR5. In addition, molecular dynamics simulation (MDS) studies have shown the stability of compounds that bind to TGR5. It can be summarized that designed coumarin derivatives seem to have promising activity as TGR5 agonists.Communicated by Ramaswamy H. Sarma.

G Protein-Coupled Estrogen Receptor GPER: Molecular Pharmacology and Therapeutic Applications

The actions of estrogens and related estrogenic molecules are complex and multifaceted in both sexes. A wide array of natural, synthetic, and therapeutic molecules target pathways that produce and respond to estrogens. Multiple receptors promulgate these responses, including the classical estrogen receptors of the nuclear hormone receptor family (estrogen receptors α and β), which function largely as ligand-activated transcription factors, and the 7-transmembrane G protein-coupled estrogen receptor, GPER, which activates a diverse array of signaling pathways. The pharmacology and functional roles of GPER in physiology and disease reveal important roles in responses to both natural and synthetic estrogenic compounds in numerous physiological systems. These functions have implications in the treatment of myriad disease states, including cancer, cardiovascular diseases, and metabolic disorders. This review focuses on the complex pharmacology of GPER and summarizes major physiological functions of GPER and the therapeutic implications and ongoing applications of GPER-targeted compounds.

Novel antimicrobial agents targeting the Streptococcus mutans biofilms discovery through computer technology

Dental caries is one of the most prevalent and costly biofilm-associated infectious diseases worldwide. Streptococcus mutans (S. mutans) is well recognized as the major causative factor of dental caries due to its acidogenicity, aciduricity and extracellular polymeric substances (EPSs) synthesis ability. The EPSs have been considered as a virulent factor of cariogenic biofilm, which enhance biofilms resistance to antimicrobial agents and virulence compared with planktonic bacterial cells. The traditional anti-caries therapies, such as chlorhexidine and antibiotics are characterized by side-effects and drug resistance. With the development of computer technology, several novel approaches are being used to synthesize or discover antimicrobial agents. In this mini review, we summarized the novel antimicrobial agents targeting the S. mutans biofilms discovery through computer technology. Drug repurposing of small molecules expands the original medical indications and lowers drug development costs and risks. The computer-aided drug design (CADD) has been used for identifying compounds with optimal interactions with the target via silico screening and computational methods. The synthetic antimicrobial peptides (AMPs) based on the rational design, computational design or high-throughput screening have shown increased selectivity for both single- and multi-species biofilms. These methods provide potential therapeutic agents to promote targeted control of the oral microbial biofilms in the near future.

A multi-reference poly-conformational method for in silico design, optimization, and repositioning of pharmaceutical compounds illustrated for selected SARS-CoV-2 ligands

Background

This work presents a novel computational multi-reference poly-conformational algorithm for design, optimization, and repositioning of pharmaceutical compounds.

Methods

The algorithm searches for candidates by comparing similarities between conformers of the same compound and identifies target compounds, whose conformers are collectively close to the conformers of each compound in the reference set. Reference compounds may possess highly variable MoAs, which directly, and simultaneously, shape the properties of target candidate compounds.

Results

The algorithm functionality has been case study validated in silico, by scoring ChEMBL drugs against FDA-approved reference compounds that either have the highest predicted binding affinity to our chosen SARS-CoV-2 targets or are confirmed to be inhibiting such targets in-vivo. All our top scoring ChEMBL compounds also turned out to be either high-affinity ligands to the chosen targets (as confirmed in separate studies) or show significant efficacy, in-vivo, against those selected targets. In addition to method case study validation, in silico search for new compounds within two virtual libraries from the Enamine database is presented. The library's virtual compounds have been compared to the same set of reference drugs that we used for case study validation: Olaparib, Tadalafil, Ergotamine and Remdesivir. The large reference set of four potential SARS-CoV-2 compounds has been selected, since no drug has been identified to be 100% effective against the virus so far, possibly because each candidate drug was targeting only one, particular MoA. The goal here was to introduce a new methodology for identifying potential candidate(s) that cover multiple MoA-s presented within a set of reference compounds.

Chemical Composition, Biological Activities and In Silico Analysis of Essential Oils of Three Endemic Prangos Species from Turkey

In this study, the essential oils (EOs) obtained from three endemic Prangos species from Turkey (P. heyniae, P. meliocarpoides var. meliocarpoides, and P. uechtritzii) were studied for their chemical composition and biological activities. β-Bisabolenal (12.2%) and caryophyllene oxide (7.9%) were the principal components of P. heyniae EO, while P. meliocarpoides EO contained sabinene (16.7%) and p-cymene (13.2%), and P. uechtritzii EO contained p-cymene (24.6%) and caryophyllene oxide (19.6%), as the most abundant components. With regard to their antioxidant activity, all the EOs were found to possess free radical scavenging potential demonstrated in both DPPH and ABTS assays (0.43–1.74 mg TE/g and 24.18–92.99 mg TE/g, respectively). Additionally, while no inhibitory activity was displayed by P. meliocarpoides and P. uechtritzii EOs against both cholinesterases (acetyl- and butyryl-cholinesterases). Moreover, all the EOs were found to act as inhibitors of tyrosinase (46.34–69.56 mg KAE/g). Molecular docking revealed elemol and α-bisabolol to have the most effective binding affinity with tyrosinase and amylase. Altogether, this study unveiled some interesting biological activities of these EOs, especially as natural antioxidants and tyrosinase inhibitors and hence offers stimulating prospects of them in the development of anti-hyperpigmentation topical formulations.

Prospect of Anterior Gradient 2 homodimer inhibition via repurposing FDA-approved drugs using structure-based virtual screening

Anterior Gradient 2 (AGR2) has recently been reported as a tumor biomarker in various cancers, i.e., breast, prostate and lung cancer. Predominantly, AGR2 exists as a homodimer via a dimerization domain (E60-K64); after it is self-dimerized, it helps FGF2 and VEGF to homo-dimerize and promotes the angiogenesis and the invasion of vascular endothelial cells and fibroblasts. Up till now, no small molecule has been discovered to inhibit the AGR2-AGR2 homodimer. Therefore, the present study was performed to prepare a validated 3D structure of AGR2 by homology modeling and discover a small molecule by screening the FDA-approved drugs library on AGR2 homodimer as a target protein. Thirteen different homology models of AGR2 were generated based on different templates which were narrowed down to 5 quality models sorted by their overall Z-scores. The top homology model based on PDB ID = 3PH9 was selected having the best Z-score and was further assessed by Verify-3D, ERRAT and RAMPAGE analysis. Structure-based virtual screening narrowed down the large library of FDA-approved drugs to ten potential AGR2-AGR2 homodimer inhibitors having FRED score lower than - 7.8 kcal/mol in which the top 5 drugs' binding stability was counter-validated by molecular dynamic simulation. To sum up, the present study prepared a validated 3D structure of AGR2 and, for the first time reported the discovery of 5 FDA-approved drugs to inhibit AGR2-AGR2 homodimer by using structure-based virtual screening. Moreover, the binding of the top 5 hits with AGR2 was also validated by molecular dynamic simulation. A validated 3D structure of Anterior Gradient 2 (AGR2) was prepared by homology modeling, which was used in virtual screening of FDA-approved drugs library for the discovery of prospective inhibitors of AGR2-AGR2 homodimer.

Binding of Androgen- and Estrogen-Like Flavonoids to Their Cognate (Non)Nuclear Receptors: A Comparison by Computational Prediction

Flavonoids are plant bioactives that are recognized as hormone-like polyphenols because of their similarity to the endogenous sex steroids 17β-estradiol and testosterone, and to their estrogen- and androgen-like activity. Most efforts to verify flavonoid binding to nuclear receptors (NRs) and explain their action have been focused on ERα, while less attention has been paid to other nuclear and non-nuclear membrane androgen and estrogen receptors. Here, we investigate six flavonoids (apigenin, genistein, luteolin, naringenin, quercetin, and resveratrol) that are widely present in fruits and vegetables, and often used as replacement therapy in menopause. We performed comparative computational docking simulations to predict their capability of binding nuclear receptors ERα, ERβ, ERRβ, ERRγ, androgen receptor (AR), and its variant ART877A and membrane receptors for androgens, i.e., ZIP9, GPRC6A, OXER1, TRPM8, and estrogens, i.e., G Protein-Coupled Estrogen Receptor (GPER). In agreement with data reported in literature, our results suggest that these flavonoids show a relevant degree of complementarity with both estrogen and androgen NR binding sites, likely triggering genomic-mediated effects. It is noteworthy that reliable protein-ligand complexes and estimated interaction energies were also obtained for some suggested estrogen and androgen membrane receptors, indicating that flavonoids could also exert non-genomic actions. Further investigations are needed to clarify flavonoid multiple genomic and non-genomic effects. Caution in their administration could be necessary, until the safe assumption of these natural molecules that are largely present in food is assured.

G protein-coupled estrogen receptor-1: homology modeling approaches and application in screening new GPER-1 modulators

G protein-coupled receptors (GPCRs) belong to the largest family of protein targets comprising over 800 members in which at least 500 members are the therapeutic targets. Among the GPCRs, G protein-coupled estrogen receptor-1 (GPER-1) has shown to have the ability in estrogen signaling. As GPER-1 plays a critical role in several physiological responses, GPER-1 has been considered as a potential therapeutic target to treat estrogen-based cancers and other non-communicable diseases. However, the progress in the understanding of GPER-1 structure and function is relatively slow due to the availability of a only a few selective GPER-1 modulators. As with many GPCRs, the X-ray crystal structure of GPER-1 is yet to be resolved and thus has led the researchers to search for new GPER-1 modulators using homology models of GPER-1. In this review, we aim to summarize various approaches used in the generation of GPER-1 homology model and their applications that have resulted in new GPER-1 ligands.

Natural bioactive compounds as a new source of promising G protein-coupled estrogen receptor (GPER) modulators: comprehensive in silico approach

Cancer ranks in second place among the cause of death worldwide. Cancer progress in multiple stages of carcinogenesis and metastasis programs through complex pathways. Sex hormones and their receptors are the major factors in promoting cancer progression. Among them, G protein-coupled estrogen receptor-1 (GPER) has shown to mediate cellular signaling pathways and cancer cell proliferation. However, the lack of GPER protein structure limited the search for new modulators. In this study, we curated an extensive database of natural products to discover new potential GPER modulators. We used a combination of virtual screening techniques to generate a homology model of GPER and subsequently used that for the screening of 30,926 natural products from a public database to identify potential active modulators of GPER. The best hits were further screened through the ADMET filter and confirmed by docking analysis. Moreover, molecular dynamics simulations of best hits were also carried out to assess the stability of the ligand-GPER complex. This study predicted several potential GPER modulators with novel scaffolds that could be further investigated and used as the core for the development of novel GPER modulators.Communicated by Ramaswamy H. Sarma.

Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches

Virtual screening (VS) is an outstanding cornerstone in the drug discovery pipeline. A variety of computational approaches, which are generally classified as ligand-based (LB) and structure-based (SB) techniques, exploit key structural and physicochemical properties of ligands and targets to enable the screening of virtual libraries in the search of active compounds. Though LB and SB methods have found widespread application in the discovery of novel drug-like candidates, their complementary natures have stimulated continued efforts toward the development of hybrid strategies that combine LB and SB techniques, integrating them in a holistic computational framework that exploits the available information of both ligand and target to enhance the success of drug discovery projects. In this review, we analyze the main strategies and concepts that have emerged in the last years for defining hybrid LB + SB computational schemes in VS studies. Particularly, attention is focused on the combination of molecular similarity and docking, illustrating them with selected applications taken from the literature.

Computer-Aided Ligand Discovery for Estrogen Receptor Alpha

Breast cancer (BCa) is one of the most predominantly diagnosed cancers in women. Notably, 70% of BCa diagnoses are Estrogen Receptor α positive (ERα+) making it a critical therapeutic target. With that, the two subtypes of ER, ERα and ERβ, have contrasting effects on BCa cells. While ERα promotes cancerous activities, ERβ isoform exhibits inhibitory effects on the same. ER-directed small molecule drug discovery for BCa has provided the FDA approved drugs tamoxifen, toremifene, raloxifene and fulvestrant that all bind to the estrogen binding site of the receptor. These ER-directed inhibitors are non-selective in nature and may eventually induce resistance in BCa cells as well as increase the risk of endometrial cancer development. Thus, there is an urgent need to develop novel drugs with alternative ERα targeting mechanisms that can overcome the limitations of conventional anti-ERα therapies. Several functional sites on ERα, such as Activation Function-2 (AF2), DNA binding domain (DBD), and F-domain, have been recently considered as potential targets in the context of drug research and discovery. In this review, we summarize methods of computer-aided drug design (CADD) that have been employed to analyze and explore potential targetable sites on ERα, discuss recent advancement of ERα inhibitor development, and highlight the potential opportunities and challenges of future ERα-directed drug discovery.

Identification of novel bacterial urease inhibitors through molecular shape and structure based virtual screening approaches

The enzyme urease is an essential colonizing factor of the notorious carcinogenic pathogen Helicobacter pylori (H. pylori), conferring acid resistance to the bacterium. Recently, antibiotic resistant strains have emerged globally with little to no alternative treatment available. In this study we propose novel urease inhibitors capable of controlling infection by H. pylori and other pathogenic bacteria. We employed hierarchal computational approaches to screen new urease inhibitors from commercial chemical databases followed by in vitro anti-urease assays. Initially ROCS shape-based screening was performed using o-chloro-hippurohydroxamic acid followed by molecular docking studies. Out of 1.83 million compounds, 1700 compounds were retrieved based on having a ROCS Tanimoto combo score in the range of values from 1.216 to 1.679. These compounds were further screened using molecular docking simulations and the 100 top ranked compounds were selected based on their Glide score. After structural classification of the top ranked compounds, eight compounds were selected and purchased for biological assays. The plausible binding modes of the most active compounds were also confirmed using molecular dynamics (MD) simulations. Compounds 1, 2 and 3 demonstrated good urease inhibitory properties (IC₅₀ = 0.32, 0.68 and 0.42 μM) compared to the other compounds. Enzyme kinetic studies revealed that compounds 1 and 3 are competitive inhibitors while 2 is a mixed type inhibitor of the urease enzyme. Cell based urease inhibition and MTT assay showed that these compounds blocked H. pylori urease activity, affecting bacterial growth and acid tolerance.

The enzyme urease is an essential colonizing factor of the notorious carcinogenic pathogen Helicobacter pylori (H. pylori), conferring acid resistance to the bacterium.