Endocrine Disruption at the Androgen Receptor: Employing Molecular Dynamics and Docking for Improved Virtual Screening and Toxicity Prediction

Risk assessment and environmental consequences of the use of the Allium-derived compound propyl-propane thiosulfonate (PTSO) in agrifood applications

The organosulfur compound propyl-propane thiosulfonate (PTSO), mainly found in Allium cepa, has a promising use in the agrifood industry. To confirm its safety for livestock, consumers, and environment, toxicological assessment is needed. In this regard, endocrine-disrupting chemicals (EDCs) are in the spotlight of research. Therefore, as part of the risk assessment of PTSO, in the present work, an in vivo study was performed in mice exposed to PTSO to investigate its potential reproductive toxicity considering fertility, genetic and endocrine endpoints. Five-weeks-old CD1 mice (80 males, 80 females) were exposed for 11 or 16 weeks (males or females, respectively) to different doses of PTSO (0, 14, 28 and 55 mg PTSO/kg b.w./day; 20 animals per group and sex) through the food pellets. No clinical observations or mortality and no changes in absolute organ weights and relative organ weights/body weight or brain ratios occurred during the study. The estrous cycle did not undergo any significant toxicologically relevant change. Most of the sex hormones displayed normal values. Some alterations in the expression of some genes related to reproduction is only observed in females, but they do not appear to have consequences in the development of sex organs. Docking results showed the impossibility of stable binding to estrogen and androgen receptors. Considering all the results obtained, the safe profile of PTSO can be confirmed for different agrifood applications at the conditions assayed.

Weight of evidence for cross-species conservation of androgen receptor-based biological activity

The U.S. Environmental Protection Agency's Endocrine Disruptor Screening Program (EDSP) is tasked with assessing chemicals for their potential to perturb endocrine pathways, including those controlled by androgen receptor (AR). To address challenges associated with traditional testing strategies, EDSP is considering in vitro high-throughput screening assays to screen and prioritize chemicals more efficiently. The ability of these assays to accurately reflect chemical interactions in nonmammalian species remains uncertain. Therefore, a goal of the EDSP is to evaluate how broadly results can be extrapolated across taxa. To assess the cross-species conservation of AR-modulated pathways, computational analyses and systematic literature review approaches were used to conduct a comprehensive analysis of existing in silico, in vitro, and in vivo data. First, molecular target conservation was assessed across 585 diverse species based on the structural similarity of ARs. These results indicate that ARs are conserved across vertebrates and are predicted to share similarly susceptibility to chemicals that interact with the human AR. Systematic analysis of over 5000 published manuscripts was used to compile in vitro and in vivo cross-species toxicity data. Assessment of in vitro data indicates conservation of responses occurs across vertebrate ARs, with potential differences in sensitivity. Similarly, in vivo data indicate strong conservation of the AR signaling pathways across vertebrate species, although sensitivity may vary. Overall, this study demonstrates a framework for utilizing bioinformatics and existing data to build weight of evidence for cross-species extrapolation and provides a technical basis for extrapolating hAR-based data to prioritize hazard in nonmammalian vertebrate species.

DeepAR: a novel deep learning-based hybrid framework for the interpretable prediction of androgen receptor antagonists

Drug resistance represents a major obstacle to therapeutic innovations and is a prevalent feature in prostate cancer (PCa). Androgen receptors (ARs) are the hallmark therapeutic target for prostate cancer modulation and AR antagonists have achieved great success. However, rapid emergence of resistance contributing to PCa progression is the ultimate burden of their long-term usage. Hence, the discovery and development of AR antagonists with capability to combat the resistance, remains an avenue for further exploration. Therefore, this study proposes a novel deep learning (DL)-based hybrid framework, named DeepAR, to accurately and rapidly identify AR antagonists by using only the SMILES notation. Specifically, DeepAR is capable of extracting and learning the key information embedded in AR antagonists. Firstly, we established a benchmark dataset by collecting active and inactive compounds against AR from the ChEMBL database. Based on this dataset, we developed and optimized a collection of baseline models by using a comprehensive set of well-known molecular descriptors and machine learning algorithms. Then, these baseline models were utilized for creating probabilistic features. Finally, these probabilistic features were combined and used for the construction of a meta-model based on a one-dimensional convolutional neural network. Experimental results indicated that DeepAR is a more accurate and stable approach for identifying AR antagonists in terms of the independent test dataset, by achieving an accuracy of 0.911 and MCC of 0.823. In addition, our proposed framework is able to provide feature importance information by leveraging a popular computational approach, named SHapley Additive exPlanations (SHAP). In the meanwhile, the characterization and analysis of potential AR antagonist candidates were achieved through the SHAP waterfall plot and molecular docking. The analysis inferred that N-heterocyclic moieties, halogenated substituents, and a cyano functional group were significant determinants of potential AR antagonists. Lastly, we implemented an online web server by using DeepAR (at http://pmlabstack.pythonanywhere.com/DeepAR ). We anticipate that DeepAR could be a useful computational tool for community-wide facilitation of AR candidates from a large number of uncharacterized compounds.

Synthesis of hydrocortisone esters targeting androgen and glucocorticoid receptors in prostate cancer in vitro

Androgen and glucocorticoid receptors have been recently described as key players in processes related to prostate cancer and mainly androgen receptor's inactivation was shown as an effective way for the prostate cancer treatment. Unfortunately, androgen deprivation therapy usually loses its effectivity and the disease frequently progresses into castration-resistant prostate cancer with poor prognosis. The role of the glucocorticoid receptor is associated with the mechanism of resistance; therefore, pharmacological targeting of glucocorticoid receptor in combination with antiandrogen treatment was shown as an alternative approach in the prostate cancer treatment. We introduce here the synthesis of novel 17α- and/or 21-ester or carbamate derivatives of hydrocortisone and evaluation of their biological activity towards androgen and glucocorticoid receptors in different prostate cancer cell lines. A 17α-butyryloxy-21-(alkyl)carbamoyloxy derivative 14 was found to diminish the transcriptional activity of both receptors (in single-digit micromolar range), with comparable potency to enzalutamide towards the androgen receptor, but weaker potency compared to mifepristone towards the glucocorticoid receptor. Lead compound inhibited proliferation and the formation of cell colonies in both androgen and glucocortiocid receptors-positive prostate cancer cell lines in low micromolar concentrations. Candidate compound 14 showed to interact with both receptors in cells and inhibited the translocation of receptors to nucleus and their activation phoshorylation. Moreover, binding to receptor's ligand binding domains was assessed by molecular modelling. Lead compound also induced the accumulation of cells in G1 phase and its combination with enzalutamide was shown to be more effective than enzalutamide alone.

A-ring-fused pyrazoles of dihydrotestosterone targeting prostate cancer cells via the downregulation of the androgen receptor

High expression of the androgen receptor (AR) and the disruption of its regulation are strongly responsible for the development of prostate cancer (PCa). Therapeutically relevant non-steroidal or steroidal antiandrogens are able to block the AR effect by eliminating AR-mediated signalling. Herein we report the synthesis of novel steroidal pyrazoles derived from the natural sex hormone 5α-dihydrotestosterone (DHT). 2-Ethylidene or 2-(hetero)arylidene derivatives of DHT obtained by regioselective Claisen-Schmidt condensation with acetaldehyde or (hetero)aromatic aldehydes in alkaline ethanol were reacted with monosubstituted hydrazines to give A-ring-fused 1,5-disubstituted pyrazoles as main or exclusive products, depending on the reaction conditions applied. Spontaneous or 2,3-dichloro-5,6-dicyanobenzoquinone (DDQ)-induced oxidation of the primarily formed pyrazolines resulted in the desired products in moderate to good yields, while 17-oxidation also occurred by using the Jones reagent as a strong oxidant. Transcriptional activity of the AR in a reporter cell line was examined for all novel compounds, and several previously synthesized similar DHT-based pyrazoles with differently substituted heteroring were also included to obtain information about the structure-activity relationship. Two specific regioisomeric groups of derivatives significantly diminished the transcriptional activity of the AR in reporter cell line in 10 μM concentration, and displayed reasonable antiproliferative activity in AR-positive PCa cell lines. Lead compound (3d) was found to be a potent AR antagonist (IC₅₀ = 1.18 μM), it generally suppressed AR signalling in time and dose dependent manner, moreover, it also led to a sharp decrease in wt-AR protein level probably caused by proteasomal degradation. We confirmed the antiproliferative activity of 3d in AR-positive PCa cell lines (with GI₅₀ in low micromolar ranges), and its cellular, biochemical and in silico binding in AR ligand-binding domain. Moreover, compound 3d was shown to be potent even ex vivo in patient-derived tissues, which highlights the therapeutic potential of A-ring-fused pyrazoles.

Computational pharmacology and computational chemistry of 4-hydroxyisoleucine: Physicochemical, pharmacokinetic, and DFT-based approaches

Computational pharmacology and chemistry of drug-like properties along with pharmacokinetic studies have made it more amenable to decide or predict a potential drug candidate. 4-Hydroxyisoleucine is a pharmacologically active natural product with prominent antidiabetic properties. In this study, ADMETLab 2.0 was used to determine its important drug-related properties. 4-Hydroxyisoleucine is compliant with important drug-like physicochemical properties and pharma giants' drug-ability rules like Lipinski's, Pfizer, and GlaxoSmithKline (GSK) rules. Pharmacokinetically, it has been predicted to have satisfactory cell permeability. Blood-brain barrier permeation may add central nervous system (CNS) effects, while a very slight probability of being CYP2C9 substrate exists. None of the well-known toxicities were predicted in silico, being congruent with wet lab results, except for a "very slight risk" for respiratory toxicity predicted. The molecule is non ecotoxic as analyzed with common indicators such as bioconcentration and LC₅₀ for fathead minnow and daphnia magna. The toxicity parameters identified 4-hydroxyisoleucine as non-toxic to androgen receptors, PPAR-γ, mitochondrial membrane receptor, heat shock element, and p53. However, out of seven parameters, not even a single toxicophore was found. The density functional theory (DFT) study provided support to the findings obtained from drug-like property predictions. Hence, it is a very logical approach to proceed further with a detailed pharmacokinetics and drug development process for 4-hydroxyisoleucine.

Quick and efficient quantitative predictions of androgen receptor binding affinity for screening Endocrine Disruptor Chemicals using 2D-QSAR and Chemical Read-Across

Endocrine Disruptor Chemicals are synthetic or natural molecules in the environment that promote adverse modifications of endogenous hormone regulation in humans and/or in animals. In the present research, we have applied two-dimensional quantitative structure-activity relationship (2D-QSAR) modeling to analyze the structural features of these chemicals responsible for binding to the androgen receptors (logRBA) in rats. We have collected the receptor binding data from the EDKB database (https://www.fda.gov/science-research/endocrine-disruptor-knowledge-base/accessing-edkb-database) and then employed the DTC-QSAR tool, available from https://dtclab.webs.com/software-tools, for dataset division, feature selection, and model development. The final partial least squares model was evaluated using various stringent validation criteria. From the model, we interpreted that hydrophobicity, steroidal nucleus, bulkiness and a hydrogen bond donor at an appropriate position contribute to the receptor binding affinity, while presence of electron rich features like aromaticity and polar groups decrease the receptor binding affinity. Additionally we have also performed chemical Read-Across predictions using Read-Across-v3.1 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home, and the results for the external validation metrics were found to be better than the QSAR-derived predictions. The best quality of external predictions emerged from the q-RASAR approach which combines both read-across and QSAR. To explore the essential features responsible for the receptor binding, pharmacophore mapping, molecular docking along with molecular dynamics simulation were also performed, and the results are in accordance with the QSAR/q-RASAR findings.

Effects of endocrine active contaminating pesticides on RACK1 expression and immunological consequences in THP-1 cells

We have previously demonstrated that RACK1, which expression is under steroid hormone control, plays an important role in the activation of immune cells and its expression can be useful to evaluate the immunotoxic profile of endocrine disrupting chemicals (EDCs). Hence, we investigated the effects of three contaminating and persistent pesticides: the fungicide vinclozolin (VIN), the herbicide atrazine (ATR) and the insecticide cypermethrin (CYP) on RACK1 expression and on innate immune response. VIN resulted in modest alteration of RACK1 while ATR and CYP reduced in a dose dependent manner RACK1 expression, ultimately leading to the decrease in lipopolysaccharide-induced IL-8 and TNF-α release and CD86 and CD54 surface marker expression. Moreover, our data indicate that, after exposure to EDCs, alterations of RACK1 expression can also occur with mechanisms not directly mediated by an interaction with a nuclear or membrane steroid receptors. Therefore, RACK1 could represent a useful EDCs screening tool to evaluate their immunotoxic potential and to dissect their mechanisms of action.

Hexaconazole exposure ravages biosynthesis pathway of steroid hormones: revealed by molecular dynamics and interaction

Widespread application of hexaconazole for agriculture purpose poses a threat to human health by disrupting normal endocrine homeostasis. To avoid adverse health effects on human, it is crucial to identify the effects of hexaconazole on key enzymes responsible for steroidal hormone synthesis. In view of this, present study was conducted to investigate the interaction mechanisms of hexaconazole with key enzymes in comparison with their food drug administration (FDA) approved inhibitor by molecular docking and molecular dynamics simulations. Results indicate that hexaconazole contacts with the active site of the key enzymes required for steroidal hormonal synthesis. Results pertaining to root-mean-square deviation, root-mean-square calculation, radius of gyration, hydrogen bonding and solvent accessible surface area exhibited that the interaction pattern and stability of interaction of hexaconazole was similar to enzyme specific inhibitor. In addition, ligand and enzyme complex interaction energy of hexaconazole was almost similar to key enzyme and FDA-approved enzyme specific inhibitor complex. This study offers a molecular level of understanding of hexaconazole with different enzymes required for steroidal hormonal synthesis. Findings of the study clearly suggest that hexaconazole has efficacy to stably interact with various enzyme required to progress the pathway of hormonal synthesis. If incessant exposure of hexaconazole occurs during agricultural work it may lead to ravage hormonal synthesis or potent endocrine disruption. The result of binding energy and complex interaction energy is depicted in the graphical abstract.

Phytochemical Compound Screening to Identify Novel Small Molecules against Dengue Virus: A Docking and Dynamics Study

The spread of the Dengue virus over the world, as well as multiple outbreaks of different serotypes, has resulted in a large number of deaths and a medical emergency, as no viable medications to treat Dengue virus patients have yet been found. In this paper, we provide an in silico virtual screening and molecular dynamics-based analysis to uncover efficient Dengue infection inhibitors. Based on a Google search and literature mining, a large phytochemical library was generated and employed as ligand molecules. In this investigation, the protein target NS2B/NS3 from Dengue was employed, and around 27 compounds were evaluated in a docking study. Phellodendroside (−63 kcal/mole), quercimeritrin (−59.5 kcal/mole), and quercetin-7-O-rutinoside (−54.1 kcal/mole) were chosen based on their binding free energy in MM-GBSA. The tested compounds generated numerous interactions at Lys74, Asn152, and Gln167 residues in the active regions of NS2B/NS3, which is needed for the protein’s inhibition. As a result, the stable mode of docked complexes is defined by various descriptors from molecular dynamics simulations, such as RMSD, SASA, Rg, RMSF, and hydrogen bond. The pharmacological properties of the compounds were also investigated, and no toxicity was found in computational ADMET properties calculations. As a result, this computational analysis may aid fellow researchers in developing innovative Dengue virus inhibitors.

Review of in silico studies dedicated to the nuclear receptor family: Therapeutic prospects and toxicological concerns

Being in the center of both therapeutic and toxicological concerns, NRs are widely studied for drug discovery application but also to unravel the potential toxicity of environmental compounds such as pesticides, cosmetics or additives. High throughput screening campaigns (HTS) are largely used to detect compounds able to interact with this protein family for both therapeutic and toxicological purposes. These methods lead to a large amount of data requiring the use of computational approaches for a robust and correct analysis and interpretation. The output data can be used to build predictive models to forecast the behavior of new chemicals based on their in vitro activities. This atrticle is a review of the studies published in the last decade and dedicated to NR ligands in silico prediction for both therapeutic and toxicological purposes. Over 100 articles concerning 14 NR subfamilies were carefully read and analyzed in order to retrieve the most commonly used computational methods to develop predictive models, to retrieve the databases deployed in the model building process and to pinpoint some of the limitations they faced.

In silico estrogen receptor alpha antagonist studies and toxicity prediction of Melia azedarach leaves bioactive ethyl acetate fraction

The estrogen hormone dependent accounts for a major cause in the incidence of women breast cancer. Thus, their receptor, especially the estrogen receptor α (ER-α), is becoming a target in endocrine treatment. These ligand-inducible nuclear functions are regulated by an array of phytochemical and synthetic compounds, such as 17 β-estradiol and tamoxifen (4-hydroxytamoxifen [4OHT]). The Chinaberry (Melia azedarach) leaves are known naturally for relieving internal and external diseases. Previous studies revealed the potency of Melia's ethanolic extract and ethyl acetate fractions as anticancer; furthermore, this study aimed to resolve possible ER-α antagonist's mechanism and safety from M. azedarach leaves ethyl acetate fraction contents. Melia's phytochemical content was analyzed with electrospray ionization liquid chromatography-mass spectrometry, while its ER-α antagonist's potency was investigated by in silico. The computational docking was used to 3ERT (a human ER-α-4OHT binding domain complex) with Autodock Vina and related programs. The results presented Energy binding (ΔG) of Melia's quercetin 3-O-(2'',6''-digalloyl)-β-D-galactopyranoside was similar to 4OHT, and lower than its agonist 17 β-estradiol. Furthermore, the toxicity prediction of these compounds were revealed safer than 4OHT. The Melia's leaves ethyl acetate fraction, therefore, is a potential pharmacological material for further studies.

A Multi-target Drug Designing for BTK, MMP9, Proteasome and TAK1 for the Clinical Treatment of Mantle Cell Lymphoma

BACKGROUND

Mantle cell lymphoma (MCL) is a type of non-Hodgkin lymphoma characterized by the mutation and overexpression of the cyclin D1 protein by the reciprocal chromosomal translocation t(11;14)(q13:q32).

AIM

The present study aims to identify potential inhibition of MMP9, Proteasome, BTK, and TAK1 and determine the most suitable and effective protein target for the MCL.

METHODOLOGY

Nine known inhibitors for MMP9, 24 for proteasome, 15 for BTK and 14 for TAK1 were screened. SB-3CT (PubChem ID: 9883002), oprozomib (PubChem ID: 25067547), zanubrutinib (PubChem ID: 135565884) and TAK1 inhibitor (PubChem ID: 66760355) were recognized as drugs with high binding capacity with their respective protein receptors. 41, 72, 102 and 3 virtual screened compounds were obtained after the similarity search with compound (PubChem ID:102173753), PubChem compound SCHEMBL15569297 (PubChem ID:72374403), PubChem compound SCHEMBL17075298 (PubChem ID:136970120) and compound CID: 71814473 with best virtual screened compounds.

RESULT

MMP9 inhibitors show commendable affinity and good interaction profile of compound holding PubChem ID:102173753 over the most effective established inhibitor SB-3CT. The pharmacophore study of the best virtual screened compound reveals its high efficacy based on various interactions. The virtual screened compound's better affinity with the target MMP9 protein was deduced using toxicity and integration profile studies.

CONCLUSION

Based on the ADMET profile, the compound (PubChem ID: 102173753) could be a potent drug for MCL treatment. Similar to the established SB-3CT, the compound was non-toxic with LD50 values for both the compounds lying in the same range.

In silico and in vitro assessment of androgen receptor antagonists

There is a growing concern for male reproductive health as studies suggest that there is a sharp increase in prostate cancer and other fertility related problems. Apart from lifestyle, pollutants are also known to negatively affect the reproductive system. In addition to many other compounds that have been shown to alter androgen signaling, several environmental pollutants are known to disrupt androgen signaling via binding to androgen receptor (AR) or indirectly affecting the androgen synthesis. We analyzed here the molecular mechanism of the interaction between the human AR Ligand Binding Domain (hAR-LBD) and two environmental pollutants, linuron (a herbicide) and procymidone (a pesticide), and compared with the steroid agonist dihydrotestosterone (DHT) and well-known hAR antagonists bicalutamide and enzalutamide. Using molecular docking and dynamics simulations, we showed that the co-activator interaction site of the hAR-LBD is disrupted in different ways by different ligands. Binding free energies of the ligands were also ordered in increasing order as follows: linuron, procymidone, DHT, bicalutamide, and enzalutamide. These data were confirmed by in vitro assays. Reporter assay with MDA-kb2 cells showed that linuron, procymidone, bicalutamide and enzalutamide can inhibit androgen mediated activation of luciferase activity. Gene expression analysis further showed that these compounds can inhibit the expression of prostate specific antigen (PSA) and microseminoprotein beta (MSMB) in prostate cell line LNCaP. Comparative analysis showed that procymidone is more potent than linuron in inhibiting AR activity. Furthermore, procymidone at 10 μM dose showed equivalent and higher activity to AR inhibitor enzalutamide and bicalutamide respectively.

Molecular docking and dynamics simulation to screen interactive potency and stability of fungicide tebuconazole with thyroid and sex hormone-binding globulin: Implications of endocrine and reproductive interruptions

Tebuconazole is a widely used fungicide in agriculture, and it may easily enter in the human food chain. In addition, tebuconzaol skin permeation coefficient (Log Kp) is -5.55 cm/s and it does not violate Lipinski's rule. It may mimic as a ligand for various endocrine and reproductive receptor leading to toxicological response or disease manifestation. We studied interactive potential of tebuconazole with thyroid and sex hormone-binding globulin. The main methods for this in silico analyses are molecular docking and molecular dynamic (MD) simulation. This paper explores how agriculture fungicide tebuconzaol exposure can be a risk for endocrine and reprotoxicity due to its stable interactive potency with thyroid and sex hormone-binding globulin (2CEO and 1D2S). Thyroid impairment is one of the most common endocrine issues in human health. In molecular docking analyses, tebuconazole exhibited binding potency of -6.28 kcal/mol with 2CEO compared to its native ligand thyroxin and inhibitor propylthiouracil which had the binding potency of -9.9 and -4.49 kcal/mol, respectively. The binding score of tebuconzaol with 1D2S was found to be -7.54 kcal/mol compared to native ligand dihydrotestosteron and inhibitor aminoglutethimide which exhibited the binding score of -6.84 and -11.41 kcal/mol, respectively. Therefore, each complex was subjected to MD simulation for comparative assessment of physical movement. The root mean square deviation (RMSD), root mean square fluctuation (RMSF), Radius of Gyration and hydrogen bonding exhibited that fluconazole had stable binding pattern with 2CEO and 1D2S which was almost similar to native ligand and its inhibitor. Study revealed that tebuconazole may lead to potent endocrine and reproductive disruptions.

Computational Assessment of Combination Therapy of Androgen Receptor-Targeting Compounds

The ligand-binding domain of the androgen receptor (AR) is a target for drugs against prostate cancer and offers three distinct binding sites for small molecules. Drugs acting on the orthosteric hormone binding site suffer from resistance mechanisms that can, in the worst case, reverse their therapeutic effect. While many allosteric ligands targeting either the activation function-2 (AF-2) or the binding function-3 (BF-3) have been reported, their potential for simultaneous administration with currently prescribed antiandrogens was disregarded. Here, we report results of 60 μs molecular dynamics simulations to investigate combinations of orthosteric and allosteric AR antagonists. Our results suggest BF-3 inhibitors to be more suitable in combination with classical antiandrogens as opposed to AF-2 inhibitors based on binding free energies and binding modes. As a mechanistic explanation for these observations, we deduced a structural adaptation of helix-12 involved in the formation of the AF-2 site by classical AR antagonists. Additionally, the changes were accompanied by an expansion of the orthosteric binding site. Considering our predictions, the selective combination of AR-targeting compounds may improve the treatment of prostate cancer.

The coronavirus disease 2019 main protease inhibitor from Andrographis paniculata (Burm. f) Ness

The coronavirus disease 2019 (COVID-19) pandemic has attracted worldwide attention. Andrographis paniculata (Burm. f) Ness (AP) is naturally used to treat various diseases, including infectious diseases. Its Andrographolide has been clinically observed for anti-HIV and has also in silico tested for COVID-19 main protease inhibitors. Meanwhile, the AP phytochemicals content also provides insight into the molecular structures diversity for the bioactive discovery. This study aims to find COVID-19 main protease inhibitor from AP by the molecular docking method and determine the toxicity profile of the compounds. The results obtained two compounds consisting of flavonoid glycosides 5,4'-dihydroxy-7-O-β -D-pyran-glycuronate butyl ester and andrographolide glycoside 3-O-β-D-glucopyranosyl-andrographolide have lower free binding energy and highest similarity in types of interaction with amino acid residues compared to its co-crystal ligands (6LU7) and Indinavir or Remdesivir. The toxicity prediction of the compounds also reveals their safety. These results confirm the probability of using AP phytochemical compounds as COVID-19 main protease inhibitors, although further research must be carried out.

High Content Screening Using New U2OS Reporter Cell Models Identifies Harmol Hydrochloride as a Selective and Competitive Antagonist of the Androgen Receptor

Prostate cancer is the most commonly diagnosed malignancy in men. Its growth mainly relies on the activity of the androgen receptor (AR), justifying the use of androgen deprivation therapy as a gold standard treatment for the metastatic disease. Inhibition of the androgen axis using second generation antagonists has improved patients’ survival, but is systematically confronted to resistance mechanisms, leading to a median survival that does not exceed 5 years. Counteracting this resistance has been the object of a large number of investigations, with a particular emphasis towards the identification of new AR inhibitors, whether they antagonize the receptor by a competitive or a non-competitive binding. To this end, many high content screens have been performed, to identify new non-steroidal AR antagonists, using a variety of approaches, but reported somewhat controversial results, depending on the approach and on the cell model that was used for screening. In our study, we used the U2OS osteosarcoma cells stably transfected with AR or ARv7 and a luciferase reporter as a previously validated model to screen the Prestwick Phytochemical library. The results of our screen identified ellipticine, harmol, and harmine hydrochloride as confirmed hits. Surprisingly, we could demonstrate that harmol hydrochloride, previously identified as a non-competitive inhibitor of AR or a weak inhibitor of androgen signaling, was actually a competitive antagonist of AR, which inhibits the growth of VCaP prostate cancer line, at concentrations for which it did not affect the growth of the AR negative DU145 and PC3 cells. Interestingly, we also report for the first time that harmol hydrochloride was selective for AR, as it could not alter the activity of other nuclear receptors, such as the glucocorticoid receptor (GR), the progesterone receptor (PR), or the mineralocorticoid receptor (MR). Additionally, we demonstrate that, conversely to enzalutamide, harmol hydrochloride did not show any agonistic activity towards the pregnane X receptor (PXR), a master regulator of drug metabolism. Together, our results shed light on the importance of the cellular context for the screening of new AR antagonists. They further indicate that some of the potential hits that were previously identified may have been overlooked.

Allosteric Binding Sites On Nuclear Receptors: Focus On Drug Efficacy and Selectivity

Nuclear receptors (NRs) are highly relevant drug targets in major indications such as oncologic, metabolic, reproductive, and immunologic diseases. However, currently, marketed drugs designed towards the orthosteric binding site of NRs often suffer from resistance mechanisms and poor selectivity. The identification of two superficial allosteric sites, activation function-2 (AF-2) and binding function-3 (BF-3), as novel drug targets sparked the development of inhibitors, while selectivity concerns due to a high conservation degree remained. To determine important pharmacophores and hydration sites among AF-2 and BF-3 of eight hormonal NRs, we systematically analyzed over 10 μ s of molecular dynamics simulations including simulations in explicit water and solvent mixtures. In addition, a library of over 300 allosteric inhibitors was evaluated by molecular docking. Based on our results, we suggest the BF-3 site to offer a higher potential for drug selectivity as opposed to the AF-2 site that is more conserved among the selected receptors. Detected similarities among the AF-2 sites of various NRs urge for a broader selectivity assessment in future studies. In combination with the Supplementary Material, this work provides a foundation to improve both selectivity and potency of allosteric inhibitors in a rational manner and increase the therapeutic applicability of this promising compound class.

ADMET properties of novel 5-O-benzoylpinostrobin derivatives

Background Prediction of the properties of absorption, distribution, metabolism, excretion, and toxicity (ADMET) from a compound is essential, especially for modified novel compounds. Previous research has successfully designed several modified compounds of 5-O-benzoyl derivatives from pinostrobin, a flavanone that has cytotoxic activity. This study aims to describe the properties of ADMET from the 5-O-benzoylpinostrobin derivative. Methods Prediction of the properties of ADMET was carried out using three web servers consisting of SwissADME, pkCSM, and ProTox-II. The observed parameters are divided into ADMET parameters. Results In general, absorption parameters indicate that the 5-O-benzoylpinostrobin derivative has lower water solubility than the parent pinostrobin. Distribution parameters show mixed results for distribution through the blood-brain barrier. Metabolism parameters showed different results with generally inhibitory activity shown in CYP2C19, CYP2C9, and CYP3A4. The excretion parameters showed a higher total clearance than pinostrobin except in the trifluoromethyl derivative. The toxicity parameters showed both pinostrobin and the 5-O-benzoylpinostrobin derivatives, including the class IV toxicity category with the lowest LD50 value indicated by the nitro derivative of 1500, with the possible target of the androgen receptor and prostaglandin G/H synthase 1. Conclusions Overall, the 5-O-benzoylpinostrobin derivative has the predicted ADMET profile that is relatively similar to pinostrobin, with the most noticeable difference being shown in the absorption parameters where all 5-O-benzoylpinostrobin derivatives have lower water solubility than pinostrobin.

In Silico Predictions of Endocrine Disruptors Properties

Endocrine-disrupting chemicals (EDCs) are a broad class of molecules present in our environment that are suspected to cause adverse effects in the endocrine system by interfering with the synthesis, transport, degradation, or action of endogenous ligands. The characterization of the harmful interaction between environmental compounds and their potential cellular targets and the development of robust in vivo, in vitro, and in silico screening methods are important for assessment of the toxic potential of large numbers of chemicals. In this context, computer-aided technologies that will allow for activity prediction of endocrine disruptors and environmental risk assessments are being developed. These technologies must be able to cope with diverse data and connect chemistry at the atomic level with the biological activity at the cellular, organ, and organism levels. Quantitative structure-activity relationship methods became popular for toxicity issues. They correlate the chemical structure of compounds with biological activity through a number of molecular descriptors (e.g., molecular weight and parameters to account for hydrophobicity, topology, or electronic properties). Chemical structure analysis is a first step; however, modeling intermolecular interactions and cellular behavior will also be essential. The increasing number of three-dimensional crystal structures of EDCs' targets has provided a wealth of structural information that can be used to predict their interactions with EDCs using docking and scoring procedures. In the present review, we have described the various computer-assisted approaches that use ligands and targets properties to predict endocrine disruptor activities.

Structural Dynamics of Agonist and Antagonist Binding to the Androgen Receptor

Androgen receptor (AR) is a steroid hormone nuclear receptor which upon binding its endogenous androgenic ligands (agonists), testosterone and dihydrotestosterone (DHT), alters gene transcription, producing a diverse range of biological effects. Antiandrogens, such as the pharmaceuticals bicalutamide and hydroxyflutamide, act as agonists in the absence of androgens and as antagonists in their presence or in high concentration. The atomic level mechanism of action by agonists and antagonists of AR is less well characterized. Therefore, in this study, multiple 1 μs molecular dynamics (MD), docking simulations, and perturbation-response analyses were performed to more fully explore the nature of interaction between agonist or antagonist and AR and the conformational changes induced in the AR upon interaction with different ligands. We characterized the mechanism of the ligand entry/exit and found that helix-12 and nearby structural motifs respond dynamically in that process. Modeling showed that the agonist and antagonist/agonist form a hydrogen bond with Thr877/Asn705 and that this interaction is absent for antagonists. Agonist binding to AR increases the mobility of residues at allosteric sites and coactivator binding sites, while antagonist binding decreases mobility at these important sites. A new site was also identified as a potential surface for allosteric binding. These results shed light on the effect of agonists and antagonists on the structure and dynamics of AR.

Overview of the effects of chemical mixtures with endocrine disrupting activity in the context of real-life risk simulation: An integrative approach (Review)

Research over the past years has indicated that chronic human exposure to very low doses of various chemical species in mixtures and administered via different routes (percutaneous, orally, etc.) should be the main focus of new biochemical and toxicological studies. Humans have daily contact with various chemicals, such as food additives, pesticides from fruits/vegetables, antibiotics (and other veterinary drugs) from meat, different types of preservatives from cosmetics, to name a few. Simultaneous exposure to this wide array of chemicals does not produce immediate effects, but summative effect/s over time that may be clinically manifested several years thereafter. Classical animal studies designed to test the toxic outcome of a single chemical are not suitable to assess, and then extrapolate to humans, the effects of a whole mixture of chemicals. Testing the aftermath of a combination of chemicals, at low doses, around or below the no observed adverse effect is stressed by many toxicologists. Thus, there is a need to reformulate the design of biochemical and toxicological studies in order to perform real-life risk simulation. This review discuss the potential use of computational methods as a complementary tool for in vitro and in vivo toxicity tests with a high predictive potential that could contribute to reduce animal testing, cost and time, when assessing the effects of chemical combinations. This review focused on the use of these methods to predict the potential endocrine disrupting activity of a mixture of chemicals.

New Insights into the Binding Mechanism of Co-regulator BUD31 to AR AF2 Site: Structural Determination and Analysis of the Mutation Effect

Introduction

Androgen Receptor (AR) plays a pivotal role in the development of male sex and contributes to prostate cancer growth. Different from other nuclear receptors that bind to the co-regulator LxxLL motif in coregulator peptide interaction, the AR Ligand Binding Domain (LBD) prefers to bind to the FxxLF motif. BUD31, a novel co-regulator with FxxLF motif, has been demonstrated to suppress wild-type and mutated AR-mediated prostate cancer growth.

Methods

To find out the interaction mechanisms of BUD31 with WT/T877A/W741L AR complex, molecular dynamics simulations were employed to study the complex BUD31 and WT/mutant ARs. The molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) results demonstrated that T877A and W741L point mutations can reduce the binding affinity between BUD31 and AR. The RMSF and dynamic cross-correlation analysis indicated that amino acid point mutations can affect the motions of loop residues in the AR structure.

Results

These results indicated that AR co-regulator binding site AF2 can serve as a target for drug discovery to solve the resistance problem.

Nuclear Receptors Database Including Negative Data (NR-DBIND): A Database Dedicated to Nuclear Receptors Binding Data Including Negative Data and Pharmacological Profile

Nuclear receptors (NRs) are transcription factors that regulate gene expression in various physiological processes through their interactions with small hydrophobic molecules. They constitute an important class of targets for drugs and endocrine disruptors and are widely studied for both health and environment concerns. Since the integration of negative data can be critical for accurate modeling of ligand activity profiles, we manually collected and annotated NRs interaction data (positive and negative) through a sharp review of the corresponding literature. 15 116 positive and negative interactions data are provided for 28 NRs together with 593 PDB structures in the freely available Nuclear Receptors Database Including Negative Data ( http://nr-dbind.drugdesign.fr ). The NR-DBIND contains the most extensive information about interaction data on NRs, which should bring valuable information to chemists, biologists, pharmacologists and toxicologists.