OpenVirtualToxLab--a platform for generating and exchanging in silico toxicity data

MetSim: Integrated Programmatic Access and Pathway Management for Xenobiotic Metabolism Simulators

Xenobiotic metabolism is a key consideration in evaluating the hazards and risks posed by environmental chemicals. A number of software tools exist that are capable of simulating metabolites, but each reports its predictions in a different format and with varying levels of detail. This makes comparing the performance and coverage of the tools a practical challenge. To address this shortcoming, we developed a metabolic simulation framework called MetSim, which comprises three main components. A graph-based schema was developed to allow metabolism information to be harmonized. The schema was implemented in MongoDB to store and retrieve metabolic graphs for subsequent analysis. MetSim currently includes an application programming interface for four metabolic simulators: BioTransformer, the OECD Toolbox, EPA's chemical transformation simulator (CTS), and tissue metabolism simulator (TIMES). Lastly, MetSim provides functions to help evaluate simulator performance for specific data sets. In this study, a set of 112 drugs with 432 reported metabolites were compiled, and predictions were made using the 4 simulators. Fifty-nine of the 112 drugs were taken from the Small Molecule Pathway Database, with the remainder sourced from the literature. The human models within BioTransformer and CTS (Phase I only) and the rat models within TIMES and the OECD Toolbox (Phase I only) were used to make predictions for the chemicals in the data set. The recall and precision (recall, precision) ranked in order of highest recall for each individual tool were CTS (0.54, 0.017), BioTransformer (0.50, 0.008), Toolbox in vitro (0.40, 0.144), TIMES in vivo (0.40, 0.133), Toolbox in vivo (0.40, 0.118), and TIMES in vitro (0.39, 0.128). Combining all of the model predictions together increased the overall recall (0.73, 0.008). MetSim enabled insights into the performance and coverage of in silico metabolic simulators to be more efficiently derived, which in turn should aid future efforts to evaluate other data sets.

A battery of in silico models application for pesticides exerting reproductive health effects: Assessment of performance and prioritization of mechanistic studies

Given the high attention to endocrine disrupting chemicals (EDC), there is an urgent need for the development of rapid and reliable approaches for the screening of large numbers of chemicals with respect to their endocrine disruption potential. This study aimed at the assessment of the correlation between the predicted results of a battery of in silico tools and the reported observed adverse effects from in vivo reproductive toxicity studies. We used VirtualToxLab (VTL) software and the EndocrineDisruptome (ED) online tool to evaluate the binding affinities to nuclear receptors of 17 pesticides, 7 of which were classified as reprotoxic substances under Regulation (EC) No 1272/2008 on the classification, labelling and packaging of substances and mixtures (CLP). Then, we aligned the results of the in silico modelling with data from ToxCast assays and in vivo reproductive toxicity studies. We combined results from different in silico tools in two different ways to improve the characteristics of their predictive performance. Reproductive toxicity can be caused by various mechanisms; however, in this study, we demonstrated that the use of a battery of in silico tools for assessing the binding to nuclear receptors can be useful for identifying hazardous compounds and for prioritizing further studies.

Development of novel ligands against SARS-CoV-2 Mpro enzyme: an in silico and in vitro Study

BACKGROUND

Despite tremendous efforts made by scientific community during the outbreak of COVID-19 pandemic, this disease still remains as a public health concern. Although different types of vaccines were globally used to reduce the mortality, emergence of new variants of SARS-CoV-2 is a challenging issue in COVID-19 pharmacotherapy. In this context, target therapy of SARS-CoV-2 by small ligands is a promising strategy.

METHODS

In this investigation, we applied ligand-based virtual screening for finding novel molecules based on nirmatrelvir structure. Various criteria including drug-likeness, ADME, and toxicity properties were applied for filtering the compounds. The selected candidate molecules were subjected to molecular docking and dynamics simulation for predicting the binding mode and binding free energy, respectively. Then the molecules were experimentally evaluated in terms of antiviral activity against SARS-CoV-2 and toxicity assessment.

RESULTS

The results demonstrated that the identified compounds showed inhibitory activity towards SARS-CoV-2 Mpro .

CONCLUSION

In summary, the introduced compounds may provide novel scaffold for further structural modification and optimization with improved anti SARS-CoV-2 Mpro activity.

Stability of aspartame in the soft drinks: Identification of the novel phototransformation products and their toxicity evaluation

Photolytic transformation of aspartame - a widely used artificial sweetener - under the simulated sunlight was studied for the first time. The experiments were conducted in pH range of 2.5 - 7.0 and in eight soft drinks available in the market. The highest degradation rate in the tested buffered solutions was observed under the neutral pH conditions. Irradiation of the soft drinks resulted in significantly (up to tenfold) faster degradation of aspartame, regardless of its initial concentration in the beverage. Such considerable acceleration of decomposition, not reported for aspartame so far, was ascribed to influence of the co-occurring ingredients, which can act as the photosensitizers. These findings indicate that some formulations may be particularly unfavorable in the context of aspartame photostability. Qualitative analysis of the studied processes revealed formation of six phototransformation products including three previously not described. In silico estimation of toxicity showed that some of the identified photoproducts, including the novel phenolic derivatives, may be more harmful than the parent compound. Taking into account relatively extensive formation of those products in the soft drinks, such finding may be particularly important from the food safety point of view.

Cathepsins and SARS-CoV-2 infection: From pathogenic factors to potential therapeutic targets

Coronavirus disease-19 (COVID-19) is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection. The COVID-19 pandemic began in March 2020 and has wrought havoc on health and economic systems worldwide. Efficacious treatment for COVID-19 is lacking: Only preventive measures as well as symptomatic and supportive care are available. Preclinical and clinical studies have indicated that lysosomal cathepsins might contribute to the pathogenesis and disease outcome of COVID-19. Here, we discuss cutting-edge evidence on the pathological roles of cathepsins in SARS-CoV-2 infection, host immune dysregulations, and the possible underlying mechanisms. Cathepsins are attractive drug targets because of their defined substrate-binding pockets, which can be exploited as binding sites for pharmaceutical enzyme inhibitors. Accordingly, the potential modulatory strategies of cathepsin activity are discussed. These insights could shed light on the development of cathepsin-based interventions for COVID-19.

In silico profiling of endocrine-disrupting potential of bisphenol analogues and their halogenated transformation products

Due to its endocrine-disrupting properties, bisphenol A (BPA) is being phased out from plastics, thermal paper and epoxy resins, and its replacements are being introduced into the market. Bisphenols are released into the environment, where they can undergo halogenation. Unlike BPA, the endocrine-disrupting potential of BPA analogues and their halogenated transformation products has not been extensively studied. The aim of this study was to evaluate the endocrine-disrupting potential of 18 BPA analogues and their halogenated derivatives by calculating affinities for 14 human nuclear receptors utilizing the Endocrine Disruptome and VirtualToxLab™ in silico tools. Our simulations identified AR, ERs, and GR as the most favorable targets of bisphenols and their derivatives. Several BPA analogues displayed a higher predicted potential for endocrine disruption than BPA. Our models highlighted BPZ and BPPH as the most hazardous in terms of predicted endocrine activities. Halogenation, in general, was predicted to increase the binding affinity of bisphenols for AR, ERβ, MR, GR, PPARγ, and TRβ. Notably, mono- or 2,2'-di-halogenated bisphenols exhibited the highest potential for endocrine disruption. In vitro corroboration of the obtained results should be the next milestone in evaluating the safety of BPA substitutes and their halogenated transformation products.

Discovery of Novel HIV Protease Inhibitors Using Modern Computational Techniques

The human immunodeficiency virus type 1 (HIV-1) has continued to be a global concern. With the new HIV incidence, the emergence of multi-drug resistance and the untoward side effects of currently used anti-HIV drugs, there is an urgent need to discover more efficient anti-HIV drugs. Modern computational tools have played vital roles in facilitating the drug discovery process. This research focuses on a pharmacophore-based similarity search to screen 111,566,735 unique compounds in the PubChem database to discover novel HIV-1 protease inhibitors (PIs). We used an in silico approach involving a 3D-similarity search, physicochemical and ADMET evaluations, HIV protease-inhibitor prediction (IC50/percent inhibition), rigid receptor-molecular docking studies, binding free energy calculations and molecular dynamics (MD) simulations. The 10 FDA-approved HIV PIs (saquinavir, lopinavir, ritonavir, amprenavir, fosamprenavir, atazanavir, nelfinavir, darunavir, tipranavir and indinavir) were used as reference. The in silico analysis revealed that fourteen out of the twenty-eight selected optimized hit molecules were within the acceptable range of all the parameters investigated. The hit molecules demonstrated significant binding affinity to the HIV protease (PR) when compared to the reference drugs. The important amino acid residues involved in hydrogen bonding and п-п stacked interactions include ASP25, GLY27, ASP29, ASP30 and ILE50. These interactions help to stabilize the optimized hit molecules in the active binding site of the HIV-1 PR (PDB ID: 2Q5K). HPS/002 and HPS/004 have been found to be most promising in terms of IC50/percent inhibition (90.15%) of HIV-1 PR, in addition to their drug metabolism and safety profile. These hit candidates should be investigated further as possible HIV-1 PIs with improved efficacy and low toxicity through in vitro experiments and clinical trial investigations.

Molecular Characterization of Estrogen Receptor Agonists during Sewage Treatment Processes Using Effect-Directed Analysis Combined with High-Resolution Full-Scan Screening

Endocrine-disrupting potential was evaluated during the sewage treatment process using in vitro bioassays. Aryl hydrocarbon receptor (AhR)-, androgen receptor (AR)-, glucocorticoid receptor (GR)-, and estrogen receptor (ER)-mediated activities were assessed over five steps of the treatment process. Bioassays of organic extracts showed that AhR, AR, and GR potencies tended to decrease through the sewage treatment process, whereas ER potencies did not significantly decrease. Bioassays on reverse-phase high-performance liquid chromatography fractions showed that F5 (log K_OW 2.5-3.0) had great ER potencies. Full-scan screening of these fractions detected two novel ER agonists, arenobufagin and loratadine, which are used pharmaceuticals. These compounds accounted for 3.3-25% of the total ER potencies and 4% of the ER potencies in the final effluent. The well-known ER agonists, estrone and 17β-estradiol, accounted for 60 and 17% of the ER potencies in F5 of the influent and primary treatment, respectively. Fourier transform ion cyclotron resonance mass spectrometry analysis showed that various molecules were generated during the treatment process, especially CHO and CHOS (C: carbon, H: hydrogen, O: oxygen, and S: sulfur). This study documented that widely used pharmaceuticals are introduced into the aquatic environments without being removed during the sewage treatment process.

Identification of AhR agonists in sediments of the Bohai and Yellow Seas using advanced effect-directed analysis and in silico prediction

Novel aryl hydrocarbon receptor (AhR) agonists were identified in coastal sediments in the Yellow and Bohai Seas by use of a combination of effect-directed analysis (EDA) and in silico prediction. A total of 125 sediments were screened for AhR-mediated potencies using H4IIE-luc bioassay. Great potencies were observed in organic extracts, mid-polar fraction (F2), and subfractions of F2 (F2.6-F2.9) of sediments collected from Nantong, Qinhuangdao, and Yancheng. Less than 15% AhR potencies could be explained by detected dioxin-like PAHs. Full-scan screening analysis was conducted for the more potent fractions using GC-QTOFMS to investigate the presence of unmonitored AhR agonists. A five-step prioritization strategy was applied; 92 candidate compounds satisfied all criteria. Among these chemicals, thirteen were evaluated for AhR efficacy. Six compounds; benz[b]anthracene, 6-methylchrysene, 2-methylbenz[a]anthracene, 1-methylbenz[a]anthracene, 1,12-dimethylbenzo[c]phenanthrene, and indeno[1,2,3-cd]fluoranthene, exhibited significant AhR-mediated efficacies. 1,12-dimethylbenzo[c]phenanthrene and indeno[1,2,3-cd]fluoranthene were identified as novel AhR agonists. Potency balance analysis showed that the six newly identified AhR agonists explained 0.4-100% of the total AhR-mediated potencies determined. Overall, combining EDA and in silico prediction applied in this study demonstrated the benefits of assessing the potential toxic effects of previously unidentified AhR agonists in sediments from the coasts of China and Korea.

Photodegradation of phthalic acid esters under simulated sunlight: Mechanism, kinetics, and toxicity change

The photodegradation of two phthalic acid esters (PAEs), dimethyl phthalate (DMP) and di-n-octyl phthalate (DOP), under simulated sunlight in aqueous or organic phases (n-hexane (HEX) and dichloromethane (DCM)) was investigated. The mean photodegradation rates were ranked by half-lives as follows: DOP in DCM (3.77 h) < DMP in DCM (9.62 h) < DOP in H₂O (3.99 days) < DMP in H₂O (19.2 days) < DOP in HEX (21.0 days) < DMP in HEX (>30 days). Compound-specific stable isotope analysis (CSIA) combined with intermediate analysis was employed to explore the involved initial photoreaction mechanism. C-O bond cleavage, chlorine radical adduction to the aromatic ring, competing reactions of chlorine radical adduction to the aromatic ring and side chain, and a singlet oxygen-mediated pathway were mainly responsible for initial photodegradation mechanism of PAEs in H₂O, DMP in DCM, DOP in DCM, and DOP in HEX, respectively. Furthermore, distinct isotope fractionation patterns of PAEs photodegradation open the possibility of using CSIA to differentiate the involved solvents in the field. More toxic and recalcitrant intermediates emerged during the photodegradation of DMP in DCM, while the risk to human health was reduced during the photochemical transformation of DOP in organic solvents.

Biofunctionalized Nanomaterials: Alternative for Encapsulation Process Enhancement

In recent years, interest in the development of nanometric materials with specific characteristics has grown; however, there are few scientific contributions that associate encapsulation methodologies and matrices with the particle objective (metabolic directions, type of administration, biological impact, and biocompatibility). This review focuses on describing the benefits and disadvantages of different techniques for designing custom particles and alternatives for the biofunctionalization nanomaterials regarding the biological impact of a nanomaterial with potential use in foods known as nutraceuticals. The study of optical properties, physicochemical factors, and characteristics such as rheological can predict its stability in the application matrix; however, not only should the characterization of a nanocomposite with applications in food be considered, but also the biological impact that it may present.

Identification of novel polar aryl hydrocarbon receptor agonists accumulated in liver of black-tailed gulls in Korea using advanced effect-directed analysis

Although bioaccumulation of persistent organic pollutants in seabirds has been examined, few studies have been conducted to identify previously unidentified substances. Here, aryl hydrocarbon receptor (AhR) agonists were identified in livers of black-tailed gulls from South Korea using effect-directed analysis combined with full-scan screening analysis. Significant AhR-mediated potencies were observed in the polar fractions of liver extracts using H4IIE-luc bioassay. Eight known polar AhR agonists accounted for 11-20% of the total AhR-mediated potencies in the polar fractions; hydrocortisone and rutaecarpine were the major contributors. Twenty-two AhR agonist candidates in the polar fractions were identified using liquid chromatography-quadrupole time-of-flight mass spectrometry during a six-step selection process. Of these, [10]-gingerol, angelicin, corticosterone, eupatilin, etofenprox, oxadixyl, and tretinoin were identified as novel AhR agonists. The contribution to potencies increased with inclusion of novel AhR agonists (27-52%); corticosterone and [10]-gingerol contributed significantly. Quantitative structure-activity relationship suggested that the novel AhR agonists have other potential toxic effects, including carcinogenicity and mutagenicity. Polar AhR agonists have been used for pharmaceuticals and pesticides. Some novel AhR agonists have log K_OW > 2 and log K_OA ≥ 6, which indicates that these compounds can be biomagnified in air-breathing organisms, such as seabirds.

Bioavailability and Safety of Dihydroquercetin (Review)

Dihydroquercetin (DHQ) is a bioflavonoid with high antioxidant, capillary-protective, and anti-inflammatory activity. DHQ has previously been used for treating Middle East respiratory syndrome coronavirus (MERS-CoV) infection and is currently considered a potential regulator of oxidative stress as part of COVID-19 multipurpose therapy. DHQ has a high safety profile but low bioavailability that limits its use. Innovative techniques (liposomization, crystal engineering, etc.) can be used to increase its bioavailability.

Development and evaluation of peptidomimetic compounds against SARS-CoV-2 spike protein: an in silico and in vitro study

Background: Coronavirus disease 2019 (COVID‐19) as global pandemic disease has been adversely affecting public health and social life with considerable loss of human life worldwide. Therefore, there is an urgent need for developing novel therapeutics to combat COVID‐19. The causative agent of COVID‐19 is SARS‐CoV‐2 which targets human angiotensin converting enzyme 2 (ACE2) as cellular receptor via its spike (S) protein. In this context, interfering with the binding of SARS‐CoV‐2 S protein to target molecules could provide a promising strategy to find novel therapeutic agents against SARS‐CoV‐2. The purpose of the current study was to identify potential peptidomimetics against S protein with a combination of structure‐based virtual screening methods and in vitro assays. Methods: The candidates were inspected in terms of ADME properties, drug‐likeness, as well as toxicity profiles. Additionally, molecular docking and dynamics simulations were performed to predict binding of the studied ligands to spike protein. Results: Biological evaluation of the compounds revealed that PM2 molecule exhibits some antiviral activity. Conclusion: In summary, this study highlights the importance of combining in silico and in vitro techniques in order to identify antiviral compound to tackle COVID‐19 and presents a new scaffold that may be structurally optimized for improved antiviral activity.

Effect-directed identification of novel aryl hydrocarbon receptor-active aromatic compounds in coastal sediments collected from a highly industrialized area

In this study, we identified major aryl hydrocarbon receptor (AhR) agonists in the sediments from Yeongil Bay (n = 6) using effect-directed analysis. Using the H4IIE-luc bioassays, great AhR-mediated potencies were found in aromatic fractions (F2) of sediment organic extracts from silica gel column chromatography and sub-fractions (F2.6-F2.8) from reverse phase-HPLC. Full-scan mass spectrometric analysis using GC-QTOFMS was conducted to identify novel AhR agonists in highly potent fractions, such as F2.6-F2.8 of S1 (Gumu Creek). Selection criteria for AhR-active compounds consisted of three steps, including matching factor of NIST library (≥70), aromatic structures, and the number of aromatic rings (≥4). Fifty-nine compounds were selected as tentative AhR agonist candidates, with the AhR-mediated activity being assessed for six compounds for which standard materials were available commercially. Of these compounds, 20-methylcholanthrene, 7-methylbenz[a]anthracene, 10-methylbenz[a]pyrene, and 7,12-dimethylbenz[a]anthracene exhibited significant AhR-mediated potency. Relative potency values of these compounds were determined relative to benzo[a]pyrene to be 3.2, 1.4, 1.2, and 0.2, respectively. EPA positive matrix factorization modeling indicated that the sedimentary AhR-active aromatic compounds primarily originated from coal combustion and vehicle emissions. Potency balance analysis indicated that four novel AhR agonists explained 0.007% to 1.7% of bioassay-derived AhR-mediated potencies in samples.

In Silico Models for Predicting Acute Systemic Toxicity

In this chapter, we give a brief overview of the regulatory requirements for acute systemic toxicity information in the European Union, and we review structure-based computational models that are available and potentially useful in the assessment of acute systemic toxicity. Emphasis is placed on quantitative structure-activity relationship (QSAR) models implemented by means of a range of software tools. The most recently published literature models for acute systemic toxicity are also discussed, and perspectives for future developments in this field are offered.

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.

Protective Role of Quercetin in Carbon Tetrachloride Induced Toxicity in Rat Brain: Biochemical, Spectrophotometric Assays and Computational Approach

Carbon tetrachloride (CCL4) induces oxidative stress by free radical toxicities, inflammation, and neurotoxicity. Quercetin (Q), on the other hand, has a role as anti-inflammatory, antioxidant, antibacterial, and free radical-scavenging. This study explored protection given by quercetin against CCL4 induced neurotoxicity in rats at given concentrations. Male Wistar rats were divided into four groups Group C: control group; Group CCL4: given a single oral dose of 1 mL/kg bw CCL4; Group Q: given a single i.p injection of 100 mg/kg bw quercetin; and Group Q + CCL4: given a single i.p injection of 100 mg/kg bw quercetin before two hours of a single oral dose of 1 mL/kg bw CCL4. The results from brain-to-body weight ratio, morphology, lipid peroxidation, brain urea, ascorbic acid, reduced glutathione, sodium, and enzyme alterations (aspartate aminotransferase (AST), alanine aminotransferase (ALT), catalase, and superoxide dismutase) suggested alterations by CCL4 and a significant reversal of these parameters by quercetin. In silico analysis of quercetin with various proteins was conducted to understand the molecular mechanism of its protection. The results identified by BzScore4 D showed moderate binding between quercetin and the following receptors: glucocorticoids, estrogen beta, and androgens and weak binding between quercetin and the following proteins: estrogen alpha, Peroxisome proliferator-activated receptors (PPARγ), Herg k+ channel, Liver x, mineralocorticoid, progesterone, Thyroid α, and Thyroid β. Three-dimensional/four-dimensional visualization of binding modes of quercetin with glucocorticoids, estrogen beta, and androgen receptors was performed. Based on the results, a possible mechanism is hypothesized for quercetin protection against CCL4 toxicity in the rat brain.

Guided rational design with scaffold hopping leading to novel histamine H3 receptor ligands

During the past decades, histamine H₃ receptors have received widespread attention in pharmaceutical research due to their involvement in pathophysiology of several diseases such as neurodegenerative disorders. In this context, blocking of these receptors is of paramount importance in progression of such diseases. In the current investigation, novel histamine H₃ receptor ligands were designed by exploiting scaffold-hopping drug-design strategy. We inspected the designed molecules in terms of ADME properties, drug-likeness, as well as toxicity profiles. Additionally molecular docking and dynamics simulation studies were performed to predict binding mode and binding free energy calculations, respectively. Among the designed structures, we selected compound d2 and its demethylated derivative as examples for synthesis and affinity measurement. In vitro binding assays of the synthesized molecules demonstrated that d2 has lower binding affinity (K_i = 2.61 μM) in radioligand displacement assay to hH₃R than that of demethylated form (K_i = 12.53 μM). The newly designed compounds avoid of any toxicity predictors resulted from extended in silico and experimental studies, can offer another scaffold for histamine H₃R antagonists for further structure-activity relationship studies.

Photochemical transformation of fentanyl under the simulated solar radiation - Enhancement of the process by heterogeneous photocatalysis and in silico analysis of toxicity

In this study the photochemical transformation of fentanyl-a very potent opioid drug-under simulated solar radiation was investigated for the first time. This pharmaceutical is frequently detected in various environment samples at concentrations that should be regarded as potentially harmful. Nevertheless, to date, no drug phototransformation products (TPs) have been reported. Considering fentanyl's exceptionally high toxicity, knowledge of the properties of these potential TPs is essential in order to properly assess its pollution impact. In this study, all photolytic experiments were performed using a xenon lamp (D65 filter) and RP-UHPLC coupled with the ESI-high-resolution tandem mass spectrometry. The phototransformation of fentanyl in natural river water and the application of heterogeneous photocatalysis as a possible way of decontaminating water were also investigated. Fentanyl turned out to be photostable, but twenty-six previously unreported TPs (formed mainly as a consequence of hydroxylation and oxidation) were found and characterized. The applied catalysts-TiO₂ and ZnO-showed very high effectiveness, and the presence of the natural water matrix further increased the photodecomposition rate (up to 600 times) relative to direct photolysis. Importantly, the almost complete degradation of the parent compound as well as its TPs after 16 min of irradiation indicated that heterogeneous photocatalysis can be considered an efficient way of treatment of fentanyl-contaminated water. The computational analysis of toxicity showed that fentanyl may be more harmful to rodents and aquatic species than its TPs. However, some of these products are probably more mutagenic and developmentally toxic. Additionally, one product in particular may be a strong estrogenic compound, proving the importance of assessing TPs' toxic properties. The evaluation of bioaccumulation, bioconcentration and biodegradability revealed that fentanyl possesses unfavorable properties compared to TPs.

Evidence of increased estrogenicity upon metabolism of Bisphenol F - Elucidation of the key metabolites

The increasing concern over bisphenol A (BPA) has directed much attention toward bisphenol F (BPF) and bisphenol S (BPS) as BPA alternatives for the development of "BPA-free" products. Consequently, BPS and BPF were frequently detected in surface water, sediment, sewage effluent, indoor dust, and even in food and biological fluids in humans. Thus, environmental researches start to focus on the potential environmental risks of BPA alternatives. While the estrogenically active metabolites and the specific estrogenically active structure are still unknown. In this study, the MTT assay on acute cytotoxicity and the recombinant transactivation assay were carried out to determine whether BPF and BPS are suitable alternatives to BPA. Our results show that the cytotoxic and estrogenic activities of BPS and BPF are lower than those of BPA. However, after the addition of a rat liver homogenate to simulate mammal metabolism, BPF exhibited higher estrogenic activity than BPA. To identify the chemical structures and estrogen receptor binding affinities of active estrogenic metabolites, LC-MS, MetaPrint2D(-React), and VirtualToxLab were integrated. The observed results indicated that the para-hydroxylated BPF and BPF-OCH₃ might have strong ER binding affinities. These results demonstrate that metabolization is important to consider upon investigating endocrine disruption of chemicals getting into contact with humans, such as in dental sealing or food packaging. Alternatives to potentially hazardous substances should be thoroughly tested prior to use.

Computer-aided screening for potential TMPRSS2 inhibitors: a combination of pharmacophore modeling, molecular docking and molecular dynamics simulation approaches

Transmembrane serine protease 2 (TMPRSS2) has been established as one of the host proteins that facilitate entry of coronaviruses into host cells. One of the approaches often employed towards preventing the entry and proliferation of viruses is computer-aided inhibition studies to identify potent compounds that can inhibit activity of viral targets in the host through binding at the active site. In this study, we developed a pharmacophore model of reportedly potent drugs against severe acute respiratory syndrome coronaviruses 1 and 2 (SARS-CoV-1 and -2). The model was used to screen the ZINC database for commercially available compounds having similar features with the experimentally tested drugs. The top 3000 compounds retrieved were docked into the active sites of a homology-modelled TMPRSS2. Docking scores of the top binders were validated and the top-ranked compounds were subjected to ADME, Lipinski's and medicinal Chemistry property predictions for druglikeness analyses. Two lead compounds, ZINC64606047 and ZINC05296775, were identified having binding affinities higher than those of the reference inhibitors, favorable interactions with TMPRSS2 active site residues and good ADME and medicinal chemistry properties. Molecular dynamics simulation was used to assess the stability and dynamics of the interactions of these compounds with TMPRSS2. Binding free energy and contribution energy evaluations were determined using MMPBSA method. Analyses of the trajectory dynamics collectively established further that the lead compounds bound and interacted stably with active site residues of TMPRSS2. Nonetheless, experimental studies are needed to further assess the potentials of these compounds as possible therapeutics against coronaviruses.Communicated by Ramaswamy H. Sarma.

Novel polar AhR-active chemicals detected in sediments of an industrial area using effect-directed analysis based on in vitro bioassays with full-scan high resolution mass spectrometric screening

Studies investigating aryl hydrocarbon receptor (AhR)-active compounds in the environment typically focus on non- and mid-polar substances, such as PAHs; while, information on polar AhR agonists remains limited. Here, we identified polar AhR agonists in sediments collected from the inland creeks of an industrialized area (Lake Sihwa, Korea) using effect-directed analysis combined with full-scan screening analysis (FSA; using LC-QTOFMS). Strong AhR-mediated potencies were observed for the polar and latter fractions of RP-HPLC (F3.5-F3.8) from sediment organic extracts in the H4IIE-luc in vitro bioassays. FSA was performed on the corresponding fractions. Twenty-eight tentative AhR agonists were chosen using a five-step process. Toxicological confirmation using bioassay revealed that canrenone, rutaecarpine, ciprofloxacin, mepanipyrim, genistein, protopine, hydrocortisone, and medroxyprogesterone were significantly active. The relative potencies of these AhR-active compounds compared to that of benzo[a]pyrene ranged from 0.00002 to 2.0. Potency balance analysis showed that polar AhR agonists explained, on average, ~6% of total AhR-mediated potencies in samples. Some novel polar AhR agonists also exhibited endocrine-disrupting potentials capable of binding to estrogen and glucocorticoid receptors, as identified by QSAR modeling. In conclusion, the focused studies on distributions, sources, fate, and ecotoxicological effects of novel polar AhR agonists in the environment are necessary.

Trends in predictive biodegradation for sustainable mitigation of environmental pollutants: Recent progress and future outlook

The feasibility of in-silico techniques, together with the computational framework, has been applied to predictive bioremediation aiming to clean-up contaminants, toxicity evaluation, and possibilities for the degradation of complex recalcitrant compounds. Emerging contaminants from different industries have posed a significant hazard to the environment and public health. Given current bioremediation strategies, it is often a failure or inadequate for sustainable mitigation of hazardous pollutants. However, clear-cut vital information about biodegradation is quite incomplete from a conventional remediation techniques perspective. Lacking complete information on bio-transformed compounds leads to seeking alternative methods. Only scarce information about the transformed products and toxicity profile is available in the published literature. To fulfill this literature gap, various computational or in-silico technologies have emerged as alternating techniques, which are being recognized as in-silico approaches for bioremediation. Molecular docking, molecular dynamics simulation, and biodegradation pathways predictions are the vital part of predictive biodegradation, including the Quantitative Structure-Activity Relationship (QSAR), Quantitative structure-biodegradation relationship (QSBR) model system. Furthermore, machine learning (ML), artificial neural network (ANN), genetic algorithm (GA) based programs offer simultaneous biodegradation prediction along with toxicity and environmental fate prediction. Herein, we spotlight the feasibility of in-silico remediation approaches for various persistent, recalcitrant contaminants while traditional bioremediation fails to mitigate such pollutants. Such could be addressed by exploiting described model systems and algorithm-based programs. Furthermore, recent advances in QSAR modeling, algorithm, and dedicated biodegradation prediction system have been summarized with unique attributes.

Discovery of potent Covid-19 main protease inhibitors using integrated drug-repurposing strategy

The emergence and rapid spreading of novel SARS-CoV-2 across the globe represent an imminent threat to public health. Novel antiviral therapies are urgently needed to overcome this pandemic. Given the significant role of the main protease of Covid-19 for virus replication, we performed a drug-repurposing study using the recently deposited main protease structure, 6LU7. For instance, pharmacophore- and e-pharmacophore-based hypotheses such as AARRH and AARR, respectively, were developed using available small molecule inhibitors and utilized in the screening of the DrugBank repository. Further, a hierarchical docking protocol was implemented with the support of the Glide algorithm. The resultant compounds were then examined for their binding free energy against the main protease of Covid-19 by means of the Prime-MM/GBSA algorithm. Most importantly, the machine learning-based AutoQSAR algorithm was used to predict the antiviral activities of resultant compounds. The hit molecules were also examined for their drug-likeness and toxicity parameters through the QikProp algorithm. Finally, the hit compounds activity against the main protease was validated using molecular dynamics simulation studies. Overall, the present analysis yielded two potential inhibitors (DB02986 and DB08573) that are predicted to bind with the main protease of Covid-19 better than currently used drug molecules such as N3 (cocrystallized native ligand), lopinavir, and ritonavir.

The molecular interaction of human anti-apoptotic proteins and in silico ADMET, drug-likeness and toxicity computation of N-cyclohexylmethacrylamide

Cancer is an uncontrolled growth of normal cells and apoptosis has an important role in cancer progression and cancer treatment. Antiapoptotic proteins are overexpressed in several tumors including breast, brain, lung cancer cells. The protein-ligand interaction has a critical role in drug designing. The present study aims to evaluate the interaction of synthesized N-cyclohexylmethacrylamide (NCMA) with proteins using in silico molecular docking and toxicity analyses. The NCMA monomer was synthesized and characterized by our team, previously. Kinetics stability, binding affinities and toxic potential of protein-NCMA complex were examined with the aid of molecular simulation. The toxicity results of this study indicate that NCMA is a sample with low toxic potential. According to the docking results, NCMA may be a drug active substance with chemical modifications and toxicity results support this situation. The drug-likeness and ADMET parameters were screened properties of NCMA.

Computational evaluation of endocrine activity of biocidal active substances

Exposure to endocrine disrupting chemicals is an important public health concern although only a few endocrine disruption chemicals have been identified so far. To speed up their identification, in silico toxicological models appear to be the most appropriate, since the potential endocrine disruption of a large number of compounds can be estimated in a short time. In this study three in silico models (Endocrine disruptome software, VirtualToxLab and COSMOS KNIME) have been used. In silico predictions of the endocrine disruption potential of biocidal active substances have been made and predictions then compared with the available in vitro experimental binding affinities to androgen, estrogen, glucocorticoid and thyroid receptors. The chosen models had similar accuracies (around 60%), while differences were shown between the models in specificity and sensitivity. VirtualToxLab was the most balanced model. Additionally, three combined models were prepared and evaluated. As expected, the majority rule approach model was more accurate and balanced. However, the positive consensus rule model, that improved the specificity of predictions (≥80% for all studied nuclear receptors) was more applicable. This reduction of false positive predictions is especially useful in the search for positive (active) compounds. On the other hand, the novel negative consensus rule model improved the specificity of prediction (≥80% for all studied nuclear receptors), giving good predictions of negative (inactive) compounds that can be excluded from further testing. The results obtained by these combined models have great added value, since they can significantly reduce further experimental testing.

Computational Selectivity Assessment of Protease Inhibitors against SARS-CoV-2

The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious global health threat. Since no specific therapeutics are available, researchers around the world screened compounds to inhibit various molecular targets of SARS-CoV-2 including its main protease (Mpro) essential for viral replication. Due to the high urgency of these discovery efforts, off-target binding, which is one of the major reasons for drug-induced toxicity and safety-related drug attrition, was neglected. Here, we used molecular docking, toxicity profiling, and multiple molecular dynamics (MD) protocols to assess the selectivity of 33 reported non-covalent inhibitors of SARS-CoV-2 Mpro against eight proteases and 16 anti-targets. The panel of proteases included SARS-CoV Mpro, cathepsin G, caspase-3, ubiquitin carboxy-terminal hydrolase L1 (UCHL1), thrombin, factor Xa, chymase, and prostasin. Several of the assessed compounds presented considerable off-target binding towards the panel of proteases, as well as the selected anti-targets. Our results further suggest a high risk of off-target binding to chymase and cathepsin G. Thus, in future discovery projects, experimental selectivity assessment should be directed toward these proteases. A systematic selectivity assessment of SARS-CoV-2 Mpro inhibitors, as we report it, was not previously conducted.

Assessment of the endocrine-disrupting potential of halogenated parabens: An in silico approach

Parabens are endocrine-disrupting chemicals present in a variety of pharmaceutical and personal care products. Due to their wide-spread use, significant amounts are also released into the aquatic domain of the environment. During water disinfection, parabens give rise to halogenated transformation products. As opposed to parabens, there is considerable lack of knowledge with regard to the endocrine-disrupting potential of their halogenated counterparts, which presents a challenge for regulatory decision making. We aimed to fill this knowledge gap by using the Endocrine Disruptome and VirtualToxLab™ to predict their endocrine-disrupting potential on the basis of calculated affinities for different nuclear receptors. The applied computational approach indicates a high probability of halogenated parabens binding to glucocorticoid, thyroid and aryl hydrocarbon receptors and suggests that disinfection is likely to form transformation products with more pronounced endocrine-disrupting activities than those of parent parabens. The obtained results not only highlight the need for additional in vitro/in vivo investigations of these chemicals as endocrine disruptors but also provide a means of guiding and prioritizing these future studies, in order to assess fully their hazard to human health.

Disruption of androgen receptor signaling by chlorpyrifos (CPF) and its environmental degradation products: a structural insight

Androgen-disruptors are chemicals that interfere with the biosynthesis, metabolism or function of endogenous androgens affecting normal male reproductive development and health. Several epidemiological studies have indicated a link between exposure to androgen disrupting chemicals with reduced sperm counts and increased infertility. The actions of androgens within target cells are transduced by the androgen receptors (ARs). Chlorpyrifos (CPF), a chlorinated organophosphorus pesticide, is known to cause impairment in both male and female reproductive systems. Recent publications have shown molecular interactions of CPF and its environmental degradation products with human progesterone receptor and human estrogen receptor. Exposure to CPF causes a marked reduction in sperm counts with lowering in serum testosterone level, which suggests possible molecular interaction of CPF with AR. The investigation to reveal the possibility and the extent of binding of CPF and some of its degradation products (chlorpyrifos-oxon [CPYO], desethyl chlorpyrifos [DEC], trichloromethoxypyridine [TMP] and trichloropyridinol [TCP]) with AR using molecular docking simulation are reported. The findings of the present docking, binding energy and molecular dynamics studies reveal that CPF and its degradation products may bind to ARs and act as a potent androgen disruptor.Communicated by Ramaswamy H. Sarma.

Nontargeted identification and predicted toxicity of new byproducts generated from UV treatment of water containing micropollutant 2-mercaptobenzothiazole

Comprehensive identification of byproducts including intermediate transformation products (TPs) of micropollutants in source water is challenging and paramount for assessment of drinking water quality and treatment technologies. Here, we have developed a nontargeted analysis strategy coupled with computational toxicity assessment to identify indistinguishable TPs including isomers with large differences in toxicity. The new strategy was applied to study the UV treatment of water containing micropollutant 2-mercaptobenzothiazole (2-MBT), and it enabled successful identification of a total of 22 organic TPs. Particularly, the structures of nine new TPs were identified for the first time; in addition, three isomers (P2, P3, and P4) were distinguished from the toxic contaminant 2-hydroxybenzothiazole (2-OH-BT). Computational assessments indicate that estrogenic activity of the three isomers (P2-P4) is higher than that of 2-OH-BT. Mass balance study shows that the 22 organic products accounted for 70% of the 2-MBT degraded, while 30% may degrade to inorganic products. Most TPs are resistant to UV photolysis. Computational toxicity assessment predicted the TPs to increase inhibition of human thyroperoxidase activity although they have lower aquatic toxicity compared to original 2-MBT. This study emphasizes the importance of monitoring the 2-MBT photodegradation products and the overall toxicity of finished water whose production included a UV light-based treatment process.

Multi-objective optimization methods in novel drug design

Introduction: In multi-objective drug design, optimization gains importance, being upgraded to a discipline that attracts its own research. Current strategies are broadly classified into single - objective optimization (SOO) and multi-objective optimization (MOO).Areas covered: Starting with SOO and the ways used to incorporate multiple criteria into it, the present review focuses on MOO techniques, their comparison, advantages, and restrictions. Pareto analysis and the concept of dominance stand in the core of MOO. The Pareto front, Pareto ranking, and limitations of Pareto-based methods, due to high dimensions and data uncertainty, are outlined. Desirability functions and the weighted sum approaches are described as stand-alone techniques to transform the MOO problem to SOO or in combination with pareto analysis and evolutionary algorithms. Representative applications in different drug research areas are also discussed.Expert opinion: Despite their limitations, the use of combined MOO techniques, as well as being complementary to SOO or in conjunction with artificial intelligence, contributes dramatically to efficient drug design, assisting decisions and increasing success probabilities. For multi-target drug design, optimization is supported by network approaches, while applicability of MOO to other fields like drug technology or biological complexity opens new perspectives in the interrelated fields of medicinal chemistry and molecular biology.

Triclocarban, Triclosan, Bromochlorophene, Chlorophene, and Climbazole Effects on Nuclear Receptors: An in Silico and in Vitro Study

BACKGROUND

Endocrine-disrupting chemicals can interfere with hormonal homeostasis and have adverse effects for both humans and the environment. Their identification is increasingly difficult due to lack of adequate toxicological tests. This difficulty is particularly problematic for cosmetic ingredients, because in vivo testing is now banned completely in the European Union.

OBJECTIVES

The aim was to identify candidate preservatives as endocrine disruptors by in silico methods and to confirm endocrine receptors' activities through nuclear receptors in vitro.

METHODS

We screened preservatives listed in Annex V in the European Union Regulation on cosmetic products to predict their binding to nuclear receptors using the Endocrine Disruptome and VirtualToxLab™ version 5.8 in silico tools. Five candidate preservatives were further evaluated for androgen receptor (AR), estrogen receptor (ER α ), glucocorticoid receptor (GR), and thyroid receptor (TR) agonist and antagonist activities in cell-based luciferase reporter assays in vitro in AR-EcoScreen, hER α -HeLa- 9903 , MDA-kb2, and GH3.TRE-Luc cell lines. Additionally, assays to test for false positives were used (nonspecific luciferase gene induction and luciferase inhibition).

RESULTS

Triclocarban had agonist activity on AR and ER α at 1 μ M and antagonist activity on GR at 5 μ M and TR at 1 μ M . Triclosan showed antagonist effects on AR, ER α , GR at 10 μ M and TR at 5 μ M , and bromochlorophene at 1 μ M (AR and TR) and at 10 μ M (ER α and GR). AR antagonist activity of chlorophene was observed [inhibitory concentration at 50% (IC50) IC 50 = 2.4 μ M ], as for its substantial ER α agonist at > 5 μ M and TR antagonist activity at 10 μ M . Climbazole showed AR antagonist (IC 50 = 13.6 μ M ), ER α agonist at > 10 μ M , and TR antagonist activity at 10 μ M .

DISCUSSION

These data support the concerns of regulatory authorities about the endocrine-disrupting potential of preservatives. These data also define the need to further determine their effects on the endocrine system and the need to reassess the risks they pose to human health and the environment. https://doi.org/10.1289/EHP6596.

Current development of integrated web servers for preclinical safety and pharmacokinetics assessments in drug development

In drug development, preclinical safety and pharmacokinetics assessments of candidate drugs to ensure the safety profile are a must. While in vivo and in vitro tests are traditionally used, experimental determinations have disadvantages, as they are usually time-consuming and costly. In silico predictions of these preclinical endpoints have each been developed in the past decades. However, only a few web-based tools have integrated different models to provide a simple one-step platform to help researchers thoroughly evaluate potential drug candidates. To efficiently achieve this approach, a platform for preclinical evaluation must not only predict key ADMET (absorption, distribution, metabolism, excretion and toxicity) properties but also provide some guidance on structural modifications to improve the undesired properties. In this review, we organized and compared several existing integrated web servers that can be adopted in preclinical drug development projects to evaluate the subject of interest. We also introduced our new web server, Virtual Rat, as an alternative choice to profile the properties of drug candidates. In Virtual Rat, we provide not only predictions of important ADMET properties but also possible reasons as to why the model made those structural predictions. Multiple models were implemented into Virtual Rat, including models for predicting human ether-a-go-go-related gene (hERG) inhibition, cytochrome P450 (CYP) inhibition, mutagenicity (Ames test), blood-brain barrier penetration, cytotoxicity and Caco-2 permeability. Virtual Rat is free and has been made publicly available at https://virtualrat.cmdm.tw/.

Identification and characterization of citalopram new metabolites with the use of UHPLC-Q-TOF technique: In silico toxicity assessment of the identified transformation products

In this study the metabolite profiling of citalopram with the use of human liver microsomes as well as the complementary photocatalytic method were established. This strategy allowed the detection of five metabolites of citalopram including 3-hydroxycitalopram and 3-oxocitalopram which were found as a new and not previously described metabolites of this drug The photocatalytic simulation of metabolism was carried out using tungsten (VI) oxide nanopowders with the different particle sizes, which allowed to examine the effect of this photocatalyst parameter on the mapping of metabolic processes. The accurate characterization of all observed structures was possible due to the use of ultra-high-pressure liquid chromatography and high-resolution mass spectrometry combined system as a highly useful technique in drug metabolism studies. In order to perform the toxicity prediction of citalopram and its metabolites, the acute toxicity to rodents, as well as genotoxicity, carcinogenicity, developmental toxicity and receptor-mediated toxicity was calculated basing on the in silico tools.

Novel bexarotene derivatives: Synthesis and cytotoxicity evaluation for glioma cells in 2D and 3D in vitro models

Glioblastoma (GBM) is an aggressive and lethal form of brain cancer with a high invasion capacity and a lack of effective chemotherapeutics. Retinoid bexarotene (BXR) inhibits the neurospheroidal colony formation and migration of primary glioblastoma cells but has side effects. To enhance the BXR glioblastoma selectivity and cytotoxicity, we chemically modified it at the carboxyl group with either nitroethanolamine (NEA) bearing a NO-donating group (a well-known bioactivity enhancer; BXR-NEA) or with a dopamine (DA) moiety (to represent the highly toxic for various tumor cells N-acyldopamine family; BXR-DA). These two novel compounds were tested in the 2D (monolayer culture) and 3D (multicellular tumor spheroids) in vitro models. Both BXR-DA and BXR-NEA were found to be more toxic for rat C6 and human U-87MG glioma cells than the initial BXR. After 24 h incubation of the cells (monolayer culture) with the drugs, the IC₅₀ values were in the range of 28-42, and 122-152 μM for BXR derivatives and BXR, respectively. The cell death occurred via apoptosis according to the annexin staining and caspase activation. The tumor spheroids demonstrated higher resistance to the treatment compared to that one of the monolayer cultures. BXR-DA and BXR-NEA were more specific against tumor cells than the parental drug, in particular the selectivity index was 1.8-2.7 vs. 1.3-1.5, respectively. Moreover, they inhibited cell migration more effectively than parental BXR according to a scratch assay. Cell spreading from the tumor spheroids was also inhibited. Thus, the obtained BXR derivatives could be promising for glioblastoma treatment.

Unexpected culprit of increased estrogenic effects: Oligomers in the photodegradation of preservative ethylparaben in water

Widespread occurrence of emerging organic contaminants (EOCs) in water have been explicitly associated with adverse effects on human health, therefore representing a major risk to public health. Especially the increased toxicity is frequently observed during the photodegradation of EOCs in natural water, and even wastewater treatment plants. However, the culprit of increased toxicity and formation mechanism has yet to be recognized regarding the estrogenic activity. In this study, by combining laboratory experiments with quantum chemical calculations, the induction of human estrogenic activity was investigated using the yeast two-hybrid reporter assay during the photodegradation of preservatives ethylparaben (EP), along with identification of toxic products and formation mechanisms. Results showed that the increase in estrogenic effect was induced by photochemically generated oligomers, rather than the expected OH-adduct. The maximum estrogenic activity corresponded to the major formation of oligomers, while OH-adducts were less than 12%. Two photochemically generated oligomers were found to contribute to estrogenic activity, produced from the cleavage of excited triplet state molecules and subsequent radical-radical reactions. Computational toxicology results showed that the increased estrogenic activity was attributed to oligomer [4-Hydroxy-isophthalic acid 1-ethyl ester 3-(4-hydroxy-phenyl)] and its EC₅₀ was lower than that of the parent EP. In contrast, OH-adducts exhibited higher EC₅₀ values than the parent EP, while still possessing estrogenic activity. Therefore, more attention should be paid to these photodegradation products of EOCs, including OH-adducts.

Potential Inhibitors for Novel Coronavirus Protease Identified by Virtual Screening of 606 Million Compounds

The rapid outbreak of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China followed by its spread around the world poses a serious global concern for public health. To this date, no specific drugs or vaccines are available to treat SARS-CoV-2 despite its close relation to the SARS-CoV virus that caused a similar epidemic in 2003. Thus, there remains an urgent need for the identification and development of specific antiviral therapeutics against SARS-CoV-2. To conquer viral infections, the inhibition of proteases essential for proteolytic processing of viral polyproteins is a conventional therapeutic strategy. In order to find novel inhibitors, we computationally screened a compound library of over 606 million compounds for binding at the recently solved crystal structure of the main protease (Mpro) of SARS-CoV-2. A screening of such a vast chemical space for SARS-CoV-2 Mpro inhibitors has not been reported before. After shape screening, two docking protocols were applied followed by the determination of molecular descriptors relevant for pharmacokinetics to narrow down the number of initial hits. Next, molecular dynamics simulations were conducted to validate the stability of docked binding modes and comprehensively quantify ligand binding energies. After evaluation of potential off-target binding, we report a list of 12 purchasable compounds, with binding affinity to the target protease that is predicted to be more favorable than that of the cocrystallized peptidomimetic compound. In order to quickly advise ongoing therapeutic intervention for patients, we evaluated approved antiviral drugs and other protease inhibitors to provide a list of nine compounds for drug repurposing. Furthermore, we identified the natural compounds (-)-taxifolin and rhamnetin as potential inhibitors of Mpro. Rhamnetin is already commercially available in pharmacies.

Multiple Bioassays and Targeted and Nontargeted Analyses to Characterize Potential Toxicological Effects Associated with Sediments of Masan Bay: Focusing on AhR-Mediated Potency

An enhanced, multiple lines of evidence approach was applied to assess potential toxicological effects associated with polluted sediments. Two in vitro bioassays (H4IIE-luc and Vibrio fischeri) and three in vivo bioassays (microalgae: Isochrysis galbana and Phaeodactylum tricornutum; zebrafish embryo: Danio rerio) were applied. To identify causative chemicals in samples, targeted analyses (polycyclic aromatic hydrocarbons (PAHs), styrene oligomers (SOs), and alkylphenols) and nontargeted full-scan screening analyses (FSA; GC- and LC-QTOFMS) were performed. First, great AhR-mediated potencies were observed in midpolar and polar fractions of sediment extracts, but known and previously characterized AhR agonists, including PAHs and SOs could not fully explain the total potencies of samples. Enoxolone was identified as a novel AhR agonist in a highly potent sediment fraction by use of FSA. Enoxolone has a relative potency of 0.13 compared to benzo[a]pyrene (1.0) in the H4IIE-luc bioassay. Nonylphenols associated with membrane damage that influenced the viability of the microalgae were also observed. Finally, inhibitions of bioluminescence of V. fischeri and lethality of D. rerio embryos were strongly related to nonpolar compounds. Overall, the present work addressed assay- and end point-specific variations and sensitivities for potential toxicities of mixture samples, warranting a significant utility of the "multiple lines of evidence" approach in ecological risk assessment.

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.

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.

Histamine H3 receptor ligands by hybrid virtual screening, docking, molecular dynamics simulations, and investigation of their biological effects

Histamine H₃ receptors (H₃ R), belonging to G-protein coupled receptors (GPCR) class A superfamily, are responsible for modulating the release of histamine as well as of other neurotransmitters by a negative feedback mechanism mainly in the central nervous system (CNS). These receptors have gained increased attention as therapeutic target for several CNS related neurological diseases. In the current study, we aimed to identify novel H₃ R ligands using in silico virtual screening methods. To this end, a combination of ligand- and structure-based approaches was utilized for screening of ZINC database on the homology model of human H₃ R. Structural similarity- and pharmacophore-based approaches were employed to generate compound libraries. Various molecular modeling methodologies such as molecular docking and dynamics simulation along with different drug likeness filtering criteria were applied to select anti-H₃ R ligands as promising candidate molecules based on different known parent lead compounds. In vitro binding assays of the selected molecules demonstrated three of them being active within the micromolar and submicromolar K_i range. The current integrated computational and experimental methods used in this work can provide new general insights for systematic hit identification for novel anti-H₃ R agents from large compound libraries.

Computational methods and tools to predict cytochrome P450 metabolism for drug discovery

In this review, we present important, recent developments in the computational prediction of cytochrome P450 (CYP) metabolism in the context of drug discovery. We discuss in silico models for the various aspects of CYP metabolism prediction, including CYP substrate and inhibitor predictors, site of metabolism predictors (i.e., metabolically labile sites within potential substrates) and metabolite structure predictors. We summarize the different approaches taken by these models, such as rule‐based methods, machine learning, data mining, quantum chemical methods, molecular interaction fields, and docking. We highlight the scope and limitations of each method and discuss future implications for the field of metabolism prediction in drug discovery.

Open-Access Activity Prediction Tools for Natural Products. Case Study: hERG Blockers

Interference with the hERG potassium ion channel may cause cardiac arrhythmia and can even lead to death. Over the last few decades, several drugs, already on the market, and many more investigational drugs in various development stages, have had to be discontinued because of their hERG-associated toxicity. To recognize potential hERG activity in the early stages of drug development, a wide array of computational tools, based on different principles, such as 3D QSAR, 2D and 3D similarity, and machine learning, have been developed and are reviewed in this chapter. The various available prediction tools Similarity Ensemble Approach, SuperPred, SwissTargetPrediction, HitPick, admetSAR, PASSonline, Pred-hERG, and VirtualToxLab™ were used to screen a dataset of known hERG synthetic and natural product actives and inactives to quantify and compare their predictive power. This contribution will allow the reader to evaluate the suitability of these computational methods for their own related projects. There is an unmet need for natural product-specific prediction tools in this field.

Using bisphenol A and its analogs to address the feasibility and usefulness of the CALUX-PPARγ assay to identify chemicals with obesogenic potential

Environmental chemical exposures have been implicated in the obesity epidemic as potential mis-regulators of a variety of metabolic pathways. As agonism of the peroxisome proliferator-activated nuclear hormone receptor γ (PPARγ) is one of the suspected mechanisms involved, a PPARγ screening assay may have relevance for the biodetection of such effects of environmental chemicals. To test this hypothesis, we established the PPARγ₂-CALUX® assay in-house and tested it against a number of known and suspected PPARγ modulators. Furthermore, we added a rat liver S9 metabolizing system to the protocol to introduce metabolic competence to the assay. Our results confirmed the responsiveness of the cell line to the known PPARγ agonists and antagonists: rosiglitazone, tributyltin, 15-deoxy-Δ^12,14-prostaglandin J2, GW9662 and diclofenac. These data are in agreement with previous studies in various models. Seven bisphenol analogs tested induced little to no agonist activity, but all demonstrated antagonistic properties. These findings were contrary to both our assumptions and literature reports. Addition of the S9-metabolizing system to each of these tests did not alter any of the measured activities. Taken together, it seems probable that there are additional obesogenic effects of these chemicals which would not be detected by this assay.