Combating breast cancer with non-steroidal aromatase inhibitors (NSAIs): Understanding the chemico-biological interactions through comparative SAR/QSAR study

Triazoles in Medicinal Chemistry: Physicochemical Properties, Bioisosterism, and Application

Triazole demonstrates distinctive physicochemical properties, characterized by weak basicity, various dipole moments, and significant dual hydrogen bond acceptor and donor capabilities. These features are poised to play a pivotal role in drug-target interactions. The inherent polarity of triazole contributes to its lower logP, suggesting the potential improvement in water solubility. The metabolic stability of triazole adds additional value to drug discovery. Moreover, the metal-binding capacity of the nitrogen atom lone pair electrons of triazole has broad applications in the development of metal chelators and antifungal agents. This Perspective aims to underscore the unique physicochemical attributes of triazole and its application. A comparative analysis involving triazole isomers and other heterocycles provides guiding insights for the subsequent design of triazoles, with the hope of offering valuable considerations for designing other heterocycles in medicinal chemistry.

Endothelial dysfunction in breast cancer survivors on aromatase inhibitors: changes over time

BACKGROUND

Breast cancer is estimated to comprise about 290,560 new cases in 2022. Aromatase inhibitors (AIs) are recommended as adjuvant treatment for estrogen-receptor positive (ER+) breast carcinoma in postmenopausal women, which includes approximately two-thirds of all women with breast cancer. AIs inhibit the peripheral conversion of androgens to estrogen by deactivation of the aromatase enzyme, leading to a reduction in serum estrogen level in postmenopausal women with ER+ breast carcinoma. Estrogen is known for its cardiovascular (CV) protective properties through a variety of mechanisms including vasodilation of blood vessels and inhibition of vascular injury resulting in the prevention of atherosclerosis. In clinical trials and prospective cohorts, the long-term use of AIs can increase the risk for hypertension and hyperlipidemia. Studies demonstrate mixed results as to the impact of AIs on actual CV events and overall survival.

METHODS

A single arm longitudinal study of 14 postmenopausal women with ER+ breast cancer prescribed adjuvant AIs at the University of Minnesota (UMN). Subjects with a history of known tobacco use, hypertension, hyperlipidemia, and diabetes were excluded to eliminate potential confounding factors. Participants underwent routine labs, blood pressure assessments, and vascular testing at baseline (prior to starting AIs) and at six months. Vascular assessment was performed using the EndoPAT 2000 and HDI/PulseWave CR-2000 Cardiovascular Profiling System and pulse contour analysis on two occasions as previously described. Vascular measurements were conducted by one trained vascular technician. Assessments were performed in triplicate, and the mean indices were used for analyses. All subjects were on an AI at the follow-up visit. The protocol was approved by the UMN Institutional Review Board and all participants were provided written informed consent. Baseline and follow-up characteristics were compared using Wilcoxon signed-rank tests. Analyses were performed using R version 3.6.1 (R Foundation for Statistical Computing, Vienna, Austria).

RESULTS

After six months of AI treatment, EndoPAT® ratio declined to a median 1.12 (Q1: 0.85, Q3: 1.86; p = 0.045; Figure 1) and median estradiol levels decreased to 2 pg/mL (Q1: 2, Q3: 3; p=0.052). There was no evidence of association between change in EndoPAT® and change in estradiol level (p = 0.91). There were no statistically significant changes in small or large arterial elasticity.

CONCLUSIONS

We hypothesize that long-term use of AI can lead to persistent endothelial dysfunction, and further investigation is necessary. In our study, patients were on AI for approximately 5-10 years. As a result, we do not have data on whether these changes, such as EndoPAT® ratio and the elasticity of small and large arterial, are reversible with discontinuation of AI. These findings set the stage for a larger study to more conclusively determine the association between AI exposure and cardiovascular outcomes. Further studies should evaluate for multivariate associations withmodifiable risk factors for CV disease.

Design, synthesis, in vitro and in silico evaluation of indole-based tetrazole derivatives as putative anti-breast cancer agents

A series of new indole-tetrazole derivatives were designed and synthesized to develop potential anti-breast cancer agents. The compounds exhibited in vitro anti-proliferative activity against ER-α positive T-47D (IC50 = 3.82-24.43 μM), MCF-7 (IC50 = 3.08-22.65 μM), and ER-α negative MDA-MB-231 (IC50 = 7.69-19.4 μM) human breast cancer cell lines. Compounds 5d and 5f displayed significant anti-proliferative activity compared to bazedoxifene (IC50 = 14.23 ± 0.68 μM), with IC50 values of 10.00 ± 0.59 and 3.83 ± 0.74 μM, respectively, against the ER-α dominant T-47D cell line. Also, both compounds showed non-significant cytotoxicity against normal cells HEK-293. Further, the ER-α binding affinity of 5d and 5f was assessed through a fluorescence polarization-based competitive binding assay, where 5d and 5f have shown significant binding with IC50 = 5.826 and 110.6 nM, respectively, as compared to the standard drug bazedoxifene (IC50 = 339.2 nM). Western blot analysis confirmed that compound 5d reduced ER-α protein expression in T-47D cells, hindering its transactivation and signalling pathways. Additionally, a molecular docking study suggests that compounds 5d and 5f bind in such a fashion that induces conformational changes in the protein, culminating in their antagonistic effect. Pharmacokinetic profiles showed that the compounds possessed drug-like properties. Furthermore, molecular dynamics simulation studies establish the dynamic stability and conformational behaviour of the ER-α protein and ligand complex of both compounds. Additionally, 5d and 5f ensure biological feasibility as per their DFT analysis through HOMO-LUMO energy gap analysis. In conclusion, compounds 5d and 5f, exhibiting significant ER-α antagonistic activity, can act as potential lead compounds for anti-breast cancer therapies.

New 1,2,3-Triazole/1,2,4-triazole Hybrids as Aromatase Inhibitors: Design, Synthesis, and Apoptotic Antiproliferative Activity

A novel series of 1,2,3-triazole/1,2,4-triazole hybrids 5a, 5b, and 6a-i was designed and synthesized as antiproliferative agents targeting aromatase enzymes. The antiproliferative activity of the new hybrids against four cancer cells was studied using Erlotinib as a control. Compounds 6a and 6b demonstrated the highest antiproliferative activity among these hybrids, with GI50 values of 40 nM and 35 nM, respectively. Compound 6b was the most potent derivative, with a GI50 of 35 nM, comparable to Erlotinib's GI50 of 33 nM. Compound 6b inhibited all cancer cell lines with comparable efficacy to Erlotinib. Compounds 5a, 5b, and 6a-i were tested for inhibitory action against aromatase as a potential target for their antiproliferative activity. Results revealed that compounds 6a and 6b were the most potent aromatase inhibitors, with IC50 values of 0.12 ± 0.01 µM and 0.09 ± 0.01 µM, respectively, being more potent than the reference Ketoconazole (IC50 = 2.6 ± 0.20 µM) but less potent than Letrozole (IC50 = 0.002 ± 0.0002). These findings indicated that compounds 6a and 6b had significant aromatase inhibitory action and are potential antiproliferative candidates. The findings were further linked to molecular docking investigations, which gave models of strong interactions with the aromatase domain for inhibitors with high binding scores.

Design, synthesis, modeling studies and biological evaluation of pyrazole derivatives linked to oxime and nitrate moieties as nitric oxide donor selective COX-2 and aromatase inhibitors with dual anti-inflammatory and anti-neoplastic activities

Two new series of pyrazole derivatives 10a-f and 11a-f with selective COX-2 inhibition pharmacophore and oxime/nitrate moieties as NO donor moiety were designed, synthesized and tested for anti-inflammatory, cytotoxic activities and NO release. Compounds 10c, 11a, 11e were more selective for COX-2 isozyme (S.I. = 25.95, 22.52 and 21.54 respectively) in comparison to celecoxib (S.I. = 21.41). Regarding anti-cancer activity, all synthesized compounds were screened by the National Cancer Institute (NCI), Bethesda, USA for anticancer activity against 60 human cancer cell lines representing the following cancer types: leukemia, non-small cell lung, colon, CNS, melanoma, ovarian, renal, prostate, and breast cancers. Compounds 10c, 11a, 11e were found to be the most potent inhibitors on breast, ovarian and melanoma cell lines (MCF-7, IGROV1 and SK-MEL-5), compound 11a causing 79 % inhibition in case of MCF-7, 78.80 % inhibition in case of SK-MEL-5 and unexpected cell growth -26.22 % inhibition in case of IGROV1 (IC₅₀ = 3.12, 4.28, 4.13 μM respectively). On the other hand, compounds 10c and 11e showed lower inhibition on the same cell lines with IC₅₀ = 3.58, 4.58, 4.28 μM respectively for 10c, IC₅₀ = 3.43, 4.73, 4.43 μM respectively for 11e. Furthermore, DNA-flow cytometric analysis showed that compound 11a induces cell cycle arrest at G2/M phase leading to cell proliferation inhibition and apoptosis. Additionally, these derivatives examined against F180 fibroblasts to investigate their selectivity indexes. The pyrazole derivative with internal oxime 11a was the most potent compound against most used cell lines especially MCF-7, IGROV1 and SK-MEL-5 (IC₅₀ = 3.12, 4.28, 4.13 μM respectively) with 4.82-fold selectivity towards MCF-7 than F180 fibroblasts. Moreover, oxime derivative 11a showed potent aromatase inhibitory activity (IC₅₀ 16.50 μM) when compared with reference compound letrozole (IC₅₀ 15.60 μM). All compounds 10a-f and 11a-f released NO in a slow rate (0.73-3.88 %) and the six derivatives 10c, 10e, 11a, 11b, 11c and 11e were the highest NO releasers (3.88, 2.15, 3.27, 2.27, 2.55 and 3.74 % respectively). Herein structure based and ligand based studies were implemented to under stand and evaluate the compounds activity for further in vivo and preclinical studies. Docking mode of final designed compounds with celecoxib (ID: 3LN1) represented that their triazole ring adopted as the core aryl in Y shaped structure. Regarding aromatase enzyme inhibition, docking was carried out with ID: 1 M17. The internal oxime series was more active as anticancer because of their ability to form extra HBs with receptor cleft.

Identification of Non-steroidal Aromatase Inhibitors via In silico and In vitro Studies

INTRODUCTION

Breast cancer is the most common cancer affecting women worldwide, including Pakistan. More than half of breast cancer patients have hormone-dependent breast cancer, which is developed due to the over-production of estrogen (the main hormone in breast cancer).

METHOD

The biosynthesis of estrogen is catalyzed by the aromatase enzyme, which thus serves as a target for the treatment of breast cancer. During the current study, biochemical, computational, and STD-NMR methods were employed to identify new aromatase inhibitors. A series of phenyl-3- butene-2-one derivatives 1-9 were synthesized and evaluated for human placental aromatase inhibitory activity. Among them, four compounds 2, 3, 4, and 8 showed a moderate to weak inhibitory activity (IC50 = 22.6 - 47.9 µM), as compared to standard aromatase inhibitory drugs, letrozole (IC50 = 0.0147 ± 1.45 µM), anastrozole (IC50 = 0.0094 ± 0.91 µM), and exemestane (IC50 = 0.2 ± 0.032 µM). Kinetic studies on two moderate inhibitors, 4 and 8, revealed a competitive- and mixed-type of inhibition, respectively.

RESULT

Docking studies on all active compounds indicated their binding adjacent to the heme group and interaction with Met374, a critical residue of aromatase. STD-NMR further highlighted the interactions of these ligands with the aromatase enzyme.

CONCLUSION

STD-NMR-based epitope mapping indicated close proximity of the alkyl chain followed by an aromatic ring with the receptor (aromatase). These compounds were also found to be non-cytotoxic against human fibroblast cells (BJ cells). Thus, the current study has identified new aromatase inhibitors (compounds 4, and 8) for further pre-clinical and clinical research.

Computational method for aromatase-related proteins using machine learning approach

Human aromatase enzyme is a microsomal cytochrome P450 and catalyzes aromatization of androgens into estrogens during steroidogenesis. For breast cancer therapy, third-generation aromatase inhibitors (AIs) have proven to be effective; however patients acquire resistance to current AIs. Thus there is a need to predict aromatase-related proteins to develop efficacious AIs. A machine learning method was established to identify aromatase-related proteins using a five-fold cross validation technique. In this study, different SVM approach-based models were built using the following approaches like amino acid, dipeptide composition, hybrid and evolutionary profiles in the form of position-specific scoring matrix (PSSM); with maximum accuracy of 87.42%, 84.05%, 85.12%, and 92.02% respectively. Based on the primary sequence, the developed method is highly accurate to predict the aromatase-related proteins. Prediction scores graphs were developed using the known dataset to check the performance of the method. Based on the approach described above, a webserver for predicting aromatase-related proteins from primary sequence data was developed and implemented at https://bioinfo.imtech.res.in/servers/muthu/aromatase/home.html. We hope that the developed method will be useful for aromatase protein related research.

Exploration of structural requirements for azole chemicals towards human aromatase CYP19A1 activity: Classification modeling, structure-activity relationships and read-across study

Human aromatase, also called CYP19A1, plays a major role in the conversion of androgens into estrogens. Inhibition of aromatase is an important target for estrogen receptor (ER)-responsive breast cancer therapy. Use of azole compounds as aromatase inhibitors is widespread despite their low selectivity. A toxicological evaluation of commonly used azole-based drugs and agrochemicals with respect to CYP19A1is currently requested by the European Union- Registration, Evaluation, Authorization and Restriction of Chemicals (EU-REACH) regulations due to their potential as endocrine disruptors. In this connection, identification of structural alerts (SAs) is an effective strategy for the toxicological assessment and safe drug design. The present study describes the identification of SAs of azole-based chemicals as guiding experts to predict the aromatase activity. Total 21 SAs associated with aromatase activity were extracted from dataset of 326 azole-based drugs/chemicals obtained from Tox21 library. A cross-validated classification model having high accuracy (error rate 5%) was proposed which can precisely classify azole chemicals into active/inactive toward aromatase. In addition, mechanistic details and toxicological properties (agonism/antagonism) of azoles with respect to aromatase were explored by comparing active and inactive chemicals using structure-activity relationships (SAR). Lastly, few structural alerts were applied to form chemical categories for read-across applications.

Breast Cancer MCF-7 Cell Spheroid Culture for Drug Discovery and Development

In vitro 3D cancer spheroids (tumoroids) exhibit a drug resistance profile similar to that found in solid tumors. 3D spheroid culture methods recreate more physiologically relevant microenvironments for cells. Therefore, these models are more appropriate for cancer drug screening. We have recently developed a protocol for MCF-7 cell spheroid culture, and used this method to test the effects of different types of drugs on this estrogen-dependent breast cancer cell spheroid. Our results demonstrated that MCF-7 cells can grow spheroid in medium using a low attachment plate. We managed to grow one spheroid in each well, and the spheroid can grow over a month, the size of the spheroid can grow over a hundred times in volume. Our targeted drug experimental results suggest that estrogen sulfotransferase, steroid sulfatase, and G protein-coupled estrogen receptor may play critical roles in MCF-7 cell spheroid growth, while estrogen receptors α and β may not play an essential role in MCF-7 spheroid growth. Organoids are the miniatures of in vivo tissues and reiterate the in vivo microenvironment of a specific organ, best fit for the in vitro studies of diseases and drug development. Tumoroid, developed from cancer cell lines or patients’ tumor tissue, is the best in vitro model of in vivo tumors. 3D spheroid technology will be the best future method for drug development of cancers and other diseases. Our reported method can be developed clinically to develop personalized drugs when the patient’s tumor tissues are used to develop a spheroid culture for drug screening.

Sulfonamide derivatives as potential anti-cancer agents and their SARs elucidation

Currently, the arise of drug resistance and undesirable off-target effects of anti-cancer agents are major challenges for cancer treatment, which energizes medicinal chemists to develop more anti-cancer agents with high efficiency and low toxicity continuously. Sulfonamide derivatives are a class of promising compounds with diverse biological activities including anti-cancer, and parts of them have been marketed for cancer therapy, such as Belinostat, ABT-199 and Amsacrine. In this review, we summed up the recent advances of sulfonamide derivatives as potential anti-cancer agents based on the anti-cancer targets, such as aromatase, carbonic anhydrase (CA), anti-apoptotic B-cell lymphoma-2 (Bcl-2) proteins, topoisomerase and phosphatidylinositol 3-kinase (PI3K), and elucidated the corresponding structure-activity relationships (SARs) of most sulfonamide derivatives. We hope this review could provide a clear insight for medicinal chemists in the rational design of more potent and bio-target specific anti-cancer agents.

New azolyl-derivatives as multitargeting agents against breast cancer and fungal infections: synthesis, biological evaluation and docking study

Nonsteroidal aromatase inhibitors (NSAIs) are well-established drugs for the therapy of breast cancer. However, they display some serious side effects, and their efficacy can be compromised by the development of chemoresistance. Previously, we have reported different indazole-based carbamates and piperidine-sulphonamides as potent aromatase inhibitors. Starting from the most promising compounds, here we have synthesised new indazole and triazole derivatives and evaluated their biological activity as potential dual agents, targeting both the aromatase and the inducible nitric oxide synthase, being this last dysregulated in breast cancer. Furthermore, selected compounds were evaluated as antiproliferative and cytotoxic agents in the MCF-7 cell line. Moreover, considering the therapeutic diversity of azole-based compounds, all the synthesized compounds were also evaluated as antifungals on different Candida strains. A docking study, as well as molecular dynamics simulation, were carried out to shed light on the binding mode of the most interesting compound into the different target enzymes catalytic sites.

Nitrile-containing pharmaceuticals: target, mechanism of action, and their SAR studies

The nitrile group is an important functional group widely found in both pharmaceutical agents and natural products. More than 30 nitrile-containing pharmaceuticals have been approved by the FDA for the management of a broad range of clinical conditions in the last few decades. Incorporation of a nitrile group into lead compounds has gradually become a promising strategy in rational drug design as it can bring additional benefits including enhanced binding affinity to the target, improved pharmacokinetic profile of parent drugs, and reduced drug resistance. This paper reviews the existing drugs with a nitrile moiety that have been approved or in clinical trials, involving their targets, molecular mechanism of pharmacology and SAR studies, and classifies them into different categories based on their clinical usages.

Development of potential inhibitors of cell division protein kinase 2 by ligand based drug design

Cyclin-dependent kinases (CDKs) are commonly known by their role in cell cycle regulation which affects cancer mechanism. In many cancer types, CDKs show extreme activity or CDK inhibiting proteins are dysfunctional. Specifically, CDK2 plays an indispensable role in cell division especially in the G1/S phase and DNA damage repair. Therefore, it is important to find new potential CDK2 inhibitors. In this study, ligand-based drug design is used to design new potential CDK2 inhibitors. Y8 L ligand is obtained from the X-ray crystal structure of human CDK2 (PDB ID: 2XNB) (www.pdb.org) and used as a structure model. By adding hydrophilic and hydrophobic groups to the structure, a training set of 36 molecules is generated. Each molecule examined with Spartan’14 and optimized structures are used for docking to CDK2 structure by AutoDock and AutoDock Vina programs. Ligand-amino acid interactions are analysed with Discovery Studio Visualizer. Van der Waals, Pi-Pi T-shaped, alkyl, pi-alkyl, conventional hydrogen bond and carbon-hydrogen bond interactions are observed. By docking results and viewed interactions, some molecules are identified and discussed as potential CDK2 inhibitors. Additionally, 8 different QSAR descriptors obtained from Spartan’14, Preadmet and ALOGPS 2.1 programs are investigated with multiple linear regulation (MLR) analysis with SPSS program for their impact on affinity value.

Design, Synthesis and Biological Evaluation of Aromatase Inhibitors Based on Sulfonates and Sulfonamides of Resveratrol

A library of sulfonate and sulfonamide derivatives of Resveratrol was synthesized and tested for its aromatase inhibitory potential. Interestingly, sulfonate derivatives were found to be more active than sulfonamide bioisosteres with IC₅₀ values in the low micromolar range. The sulfonate analogues 1b–c and 1j exhibited good in vitro antiproliferative activity on the MCF7 cell line, evidenced by MTT and LDH release assays. Structure–activity relationships suggested that electronic and lipophilic properties could have a different role in promoting the biological response for sulfonates and sulfonamides, respectively. Docking studies disclosed the main interactions at a molecular level of detail behind the observed inhibition of the more active compounds whose chemical stability has been evaluated with nano-liquid chromatography. Finally, 1b–c and 1j were highlighted as sulfonates to be further developed as novel and original aromatase inhibitors.

α-naphthoflavone-derived cytochrome P450 (CYP)1B1 degraders specific for sensitizing CYP1B1-mediated drug resistance to prostate cancer DU145: Structure activity relationship

We previously discovered extrahepatic cytochrome P450 1B1 (CYP1B1) degraders able to overcome drug resistance toward docetaxel using a PROTACs technology, however, the underexplored structure activity relationships and poor water solubility posed a major hurdle in the development of CYP1B1 degraders. Herein, continuous efforts are made to develop more promising α-naphthoflavone (ANF)-derived chimeras for degrading CYP1B1. Guided by the strongest ANF-derived CYP1B1 degrader 3a we ever reported, 17 ANF analogues are designed and synthesized to evaluate the CYP1B1 degradation and resultant resistance reversal. In degrading CYP1B1 and sensitizing drug resistance, 4d with a 1, 5-cis triazole coupling mode at (C3') of B ring of ANF exhibited the similar potency as 3a carrying a 1, 4-trans triazole fragment at (C4') of B ring, but more obvious selectivity of 4d toward CYP1B1 over CYP1A2 is observed. When an oxygen was inserted into the linker of 4d, 4f demonstrated better water solubility, a more potent ability in degrading CYP1B1 and reversing drug resistance, and a promising selectivity. Collectively, a substitution position, an alkyne-azide cyclization and a liker type significantly affect the ability of ANF-thalidomide conjugates in eliminating drug resistance of CYP1B1-expressing DU145 (DU145/CY) cells to docetaxel via targeted CYP1B1 degradation.

Design, synthesis, in vitro and in silico studies of some novel thiazole-dihydrofuran derivatives as aromatase inhibitors

Aromatase inhibitors used against hormone-dependent breast cancer, especially in post-menopausal women, are very susceptible to the development of resistance due to their limited number and long-term use. In this study, it is aimed to obtain new aromatase inhibitors including thiazole and dihydrofuran ring systems. Synthesis of compounds (2a-2l) were performed according to literature methods. Their structures were elucidated by ¹H NMR, ¹³C NMR and APCI-MS spectroscopic methods. MTT test was carried out to assess the cell proliferation effects of the different compounds on two different pulmonary cell lines (A549, CCD-19Lu) and mammary cell line (MCF7). According to MTT assay, it was observed that the calculated IC₅₀ values of some compounds for the CCD-19Lu cell line were found higher than for the A549 and MCF7 cell lines. Considering the viability results, it was found that the selected compounds (2a, 2c, 2e, 2g, 2h, 2l) showed favourable safety profile and have anticancer activities. Apoptotic activities of the selected compounds were investigated by flow cytometry analysis. And were found that have apoptotic effects on cancerous cell lines. In the light of this information, the aromatase inhibition potentials of 2g and 2l compounds, which are the most active derivatives, were examined in vitro and it was determined that they showed a similar inhibition profile with letrazole. Interaction modes between aromatase enzyme and compounds 2g and 2l were investigated by docking studies. In conclusion, findings of these study indicate that compounds 2g and 2l possess significant anticancer activity.

A review on diverse heterocyclic compounds as the privileged scaffolds in non-steroidal aromatase inhibitors

Breast cancer, emerging malignancy is common among women due to overexpression of estrogen. Estrogens are biosynthesized from androgens by aromatase, a cytochrome P450 enzyme complex, and play a pivotal role in stimulating cell proliferation. Therefore, deprivation of estrogen by blocking aromatase is considered as the effective way for the inhibition and treatment of breast cancer. In recent years, various non-steroidal heterocyclic functionalities have been extensively developed and studied for their aromatase inhibition activity. This review provides information about the structural-activity relationship of heterocycles (Type II) towards aromatase. This aids the medicinal chemist around the significance of different heterocyclic moieties and helps to design potent aromatase inhibitors.

Polymorphism on human aromatase affects protein dynamics and substrate binding: spectroscopic evidence

Human aromatase is a member of the cytochrome P450 superfamily, involved in steroid hormones biosynthesis. In particular, it converts androgen into estrogens being therefore responsible for the correct sex steroids balance. Due to its capacity in producing estrogens it has also been considered as a promising target for breast cancer therapy. Two single-nucleotide polymorphisms (R264C and R264H) have been shown to alter aromatase activity and they have been associated to an increased or decreased risk for estrogen-dependent pathologies. Here, the effect of these mutations on the protein dynamics is investigated by UV/FTIR and time resolved fluorescence spectroscopy. H/D exchange rates were measured by FTIR for the three proteins in the ligand-free, substrate- and inhibitor-bound forms and the data indicate that the wild-type enzyme undergoes a conformational change leading to a more compact tertiary structure upon substrate or inhibitor binding. Indeed, the H/D exchange rates are decreased when a ligand is present. In the variants, the exchange rates in the ligand-free and -bound forms are similar, indicating that a structural change is lacking, despite the single amino acid substitution is located in the peripheral shell of the protein molecule. Moreover, the fluorescence lifetimes data show that the quenching effect on tryptophan-224 observed upon ligand binding in the wild-type, is absent in both variants. Since this residue is located in the catalytic pocket, these findings suggest that substrate entrance and/or retention in the active site is partially compromised in both mutants. A contact network analysis demonstrates that the protein structure is organized in two main clusters, whose connectivity is altered by ligand binding, especially in correspondence of helix-G, where the amino acid substitutions occur. Our findings demonstrate that SNPs resulting in mutations on aromatase surface modify the protein flexibility that is required for substrate binding and catalysis. The cluster analysis provides a rationale for such effect, suggesting helix G as a possible target for aromatase inhibition.

Comparing Machine Learning Models for Aromatase (P450 19A1)

Aromatase, or cytochrome P450 19A1, catalyzes the aromatization of androgens to estrogens within the body. Changes in the activity of this enzyme can produce hormonal imbalances that can be detrimental to sexual and skeletal development. Inhibition of this enzyme can occur with drugs and natural products as well as environmental chemicals. Therefore, predicting potential endocrine disruption via exogenous chemicals requires that aromatase inhibition be considered in addition to androgen and estrogen pathway interference. Bayesian machine learning methods can be used for prospective prediction from the molecular structure without the need for experimental data. Herein, the generation and evaluation of multiple machine learning models utilizing different sources of aromatase inhibition data are described. These models are applied to two test sets for external validation with molecules relevant to drug discovery from the public domain. In addition, the performance of multiple machine learning algorithms was evaluated by comparing internal five-fold cross-validation statistics of the training data. These methods to predict aromatase inhibition from molecular structure, when used in concert with estrogen and androgen machine learning models, allow for a more holistic assessment of endocrine-disrupting potential of chemicals with limited empirical data and enable the reduction of the use of hazardous substances.

QSAR models for the acute toxicity of 1,2,4-triazole fungicides to zebrafish (Danio rerio) embryos

In recent decades, the 1,2,4-triazole fungicides are widely used for crop diseases control, and their toxicity to wild lives and pollution to ecosystem have attracted more and more attention. However, how to quickly and efficiently evaluate the toxicity of these compounds to environmental organisms is still a challenge. In silico method, such like Quantitative Structure-Activity Relationship (QSAR), provides a good alternative to evaluate the environmental toxicity of a large number of chemicals. At the present study, the acute toxicity of 23 1,2,4-triazole fungicides to zebrafish (Danio rerio) embryos was firstly tested, and the LC₅₀ (median lethal concentration) values were used as the bio-activity endpoint to conduct QSAR modelling for these triazoles. After the comparative study of several QSAR models, the 2D-QSAR model was finally constructed using the stepwise multiple linear regression algorithm combining with two physicochemical parameters (logD and μ), an electronic parameter (Q_N1) and a topological parameter (X^vPC₄). The optimal model could be mathematically described as following: pLC₅₀ = -7.24-0.30X^vPC₄ + 0.76logD - 26.15Q_N1 - 0.08μ. The internal validation by leave-one-out (LOO) cross-validation showed that the R²_adj (adjusted noncross-validation squared correlation coefficient), Q² (cross-validation correlation coefficient) and RMSD (root-mean-square error) was 0.88, 0.84 and 0.17, respectively. The external validation indicated the model had a robust predictability with the q² (predictive squared correlation coefficient) of 0.90 when eliminated tricyclazole. The present study provided a potential tool for predicting the acute toxicity of new 1,2,4-triazole fungicides which contained an independent triazole ring group in their molecules to zebrafish embryos, and also provided a reference for the development of more environmentally-friendly 1,2,4-triazole pesticides in the future.

Estrogen receptor-positive (ER+) breast cancer treatment: Are multi-target compounds the next promising approach?

Endocrine therapy is currently the main therapeutic approach for estrogen receptor-positive (ER⁺) breast cancer, the most frequent subtype of breast cancer in women worldwide. For this subtype of tumors, the current clinical treatment includes aromatase inhibitors (AIs) and anti-estrogenic compounds, such as Tamoxifen and Fulvestrant, being AIs the first-line treatment option for post-menopausal women. Moreover, the recent guidelines also suggest the use of these compounds by pre-menopausal women after suppressing ovaries function. However, besides its therapeutic efficacy, the prolonged use of this type of therapies may lead to the development of several adverse effects, as well as, endocrine resistance, limiting the effectiveness of such treatments. In order to surpass this issues and clinical concerns, during the last years, several studies have been suggesting alternative therapeutic approaches, considering the function of aromatase, ERα and ERβ. Here, we review the structural and functional features of these three targets and their importance in ER⁺ breast cancer treatment, as well as, the current treatment strategies used in clinic, emphasizing the importance of the development of multi-target compounds able to simultaneously modulate these key targets, as a novel and promising therapeutic strategy for this type of cancer.

Recent Development in Indole Derivatives as Anticancer Agents for Breast Cancer

BACKGROUND

Breast Cancer (BC) is the second most common cause of cancer related deaths in women. Due to severe side effects and multidrug resistance, current therapies like hormonal therapy, surgery, radiotherapy and chemotherapy become ineffective. Also, the existing drugs for BC treatment are associated with several drawbacks such as poor oral bioavailability, non-selectivity and poor pharmacodynamics properties. Therefore, there is an urgent need for the development of more effective and safer anti BC agents.

OBJECTIVE

This article explored in detail the possibilities of indole-based heterocyclic compounds as anticancer agents with breast cancer as their major target.

METHODS

Recent literature related to indole derivatives endowed with encouraging anti BC potential is reviewed. With special focus on BC, this review offers a detailed account of multiple mechanisms of action of various indole derivatives: aromatase inhibitor, tubulin inhibitor, microtubule inhibitor, targeting estrogen receptor, DNA-binding mechanism, induction of apoptosis, inhibition of PI3K/AkT/NFkB/mTOR, and HDAC inhibitors, by which these derivatives have shown promising anticancer potential.

RESULTS

Exhaustive literature survey indicated that indole derivatives are associated with properties of inducing apoptosis and disturbing tubulin assembly. Indoles are also associated with the inhibition of NFkB/mTOR/PI3K/AkT and regulation of estrogen-mediated activity. Furthermore, indole derivatives have been found to modulate critical targets such as topoisomerase and HDAC. These derivatives have shown significant activity against breast cancer cells.

CONCLUSION

In BC, indole derivatives seem to be quite competent and act through various mechanisms that are well established in case of BC. This review has shown that indole derivatives can further be explored for the betterment of BC chemotherapy. A lot of potential is still hidden which demands to be discovered for upgrading BC chemotherapy.

Design and synthesis of α-naphthoflavone chimera derivatives able to eliminate cytochrome P450 (CYP)1B1-mediated drug resistance via targeted CYP1B1 degradation

Extrahepatic cytochrome P450 1B1 (CYP1B1), which is highly expressed in various tumors, is an attractive and potential target for cancer prevention, therapy, and reversal of drug resistance. CYP1B1 inhibition is the current predominant therapeutic paradigm to treating CYP1B1-mediated malignancy, but therapeutic effect has little success. Herein, we reported CYP1B1 degradation in place of CYP1B1 inhibition for reversing drug resistance toward docetaxel in CYP1B1-overexpressing prostate cancer cell line DU145 using a PROTAC strategy. Replacing chlorine atom of a CYP1B1 selective inhibitor we found previously with ethynyl, we got the resulting α-naphthoflavone derivative 5 which kept strong inhibition against CYP1B1 (IC₅₀ = 0.4 ± 0.2 nM) and high selectivity. Coupling of 5 with thalidomide derivatives of varying chain lengths afforded conjugates 6A-Dvia click reaction. In vitro cell-based assay indicated that 6C was more effective in eliminating drug resistance of CYP1B1-overexpressed DU145 cells compared with other analogues. Western blotting analysis showed CYP1B1 degradation was one main reason for the reversal of drug resistance to docetaxel and the effect was obtained in a concentration-dependent manner. This work is the first attempt to overcome CYP1B1-mediated drug resistance via CYP1B1 degradation instead of CYP1B1 inhibition, which could provide a new direction toward eliminating drug resistance.

Computational Studies in Drug Design Against Cancer

Background:

The application of in silico tools in the development of anti cancer drugs.

Objective:

The summing of different computer aided drug design approaches that have been applied in the development of anti cancer drugs.

Methods:

Structure based, ligand based, hybrid protein-ligand pharmacophore methods, Homology modeling, molecular docking aids in different steps of drug discovery pipeline with considerable saving in time and expenditure. In silico tools also find applications in the domain of cancer drug development.

Results:

Structure-based pharmacophore modeling aided in the identification of PUMA inhibitors, structure based approach with high throughput screening for the development of Bcl-2 inhibitors, to derive the most relevant protein-protein interactions, anti mitotic agents; I-Kappa-B Kinase β (IKK- β) inhibitor, screening of new class of aromatase inhibitors that can be important targets in cancer therapy.

Conclusion:

Application of computational methods in the design of anti cancer drugs was found to be effective.

Tetrazole hybrids with potential anticancer activity

Cancer is one of the main causes of death throughout the world. The anticancer agents are indispensable for the treatment of various cancers, but most of them currently on the market are not specific, resulting in series of side effects of chemotherapy. Moreover, the emergency of drug-resistance towards cancers has already increased up to alarming level in the recent decades. Therefore, it's imperative to develop novel anticancer candidates with excellent activity against both drug-susceptible and drug-resistant cancers, and low toxicity as well. Tetrazole is the bioisoster of carboxylic acid, and its derivatives demonstrated promising anticancer activity. Hybridization of tetrazole with other anticancer pharmacophores may provide novel candidates with anticancer potency. The present review described the anticancer activity of tetrazole hybrids, and the structure-activity relationship (SAR) is also discussed to provide an insight for rational designs of tetrazole anticancer candidates with higher efficiency.

Toward steroidal anticancer drugs: Non-parametric and 3D-QSAR modeling of 17-picolyl and 17-picolinylidene androstanes with antiproliferative activity on breast adenocarcinoma cells

The present study is aimed to analyze lipophilicity and ADMET profiles, and to develop field based 3D-QSAR and ligand-based pharmacophore hypothesis for a series of 17α-picolyl and 17(E)-picolinylidene androstane derivatives in order to give detailed structural insights and to highlight important binding features of novel androstane derivatives, as compounds with antiproliferative activity toward breast adenocarcinoma cells. This study can provide guidelines for the rational design of novel potent compounds. Sum of ranking differences (SRD), as a non-parametric method, was applied for compounds ranking. 3D-QSAR methods, including comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), were applied to predict the antiproliferative effect on breast adenocarcinoma cells and provide the regions in space where interactive fields may influence the activity. The compounds are ranked so the compounds with the most favorable ADME and lipophilicity features together with significant anticancer activity can be distinguished. The established 3D-QSAR model could be used for design of new compounds with antiproliferative activity on the human ER- breast adenocarcinoma cells. The pharmacophore model is able to accurately predict antiproliferative activity. Generally, the present study provides significant guidelines for further selection, synthesis and rational design of new highly potential androstane derivatives as anticancer drugs.

Machine learning for the prediction of molecular dipole moments obtained by density functional theory

Machine learning (ML) algorithms were explored for the fast estimation of molecular dipole moments calculated by density functional theory (DFT) by B3LYP/6-31G(d,p) on the basis of molecular descriptors generated from DFT-optimized geometries and partial atomic charges obtained by empirical or ML schemes. A database was used with 10,071 structures, new molecular descriptors were designed and the models were validated with external test sets. Several ML algorithms were screened. Random forest regression models predicted an external test set of 3368 compounds achieving mean absolute error up to 0.44 D. The results represent a significant improvement of the dipole moments calculated using empirical point charges located at the nucleus, even assuming the DFT-optimized geometry (root mean square error, RMSE, of 0.68 D vs. 1.53 D and R² = 0.87 vs. 0.66).

Towards understanding aromatase inhibitory activity via QSAR modeling

Aromatase is a rate-limiting enzyme for estrogen biosynthesis that is overproduced in breast cancer tissue. To block the growth of breast tumors, aromatase inhibitors (AIs) are employed to bind and inhibit aromatase in order to lower the amount of estrogen produced in the body. Although a number of synthetic aromatase inhibitors have been released for clinical use in the treatment of hormone-receptor positive breast cancer, these inhibitors may lead to undesirable side effects (e.g. increased rash, diarrhea and vomiting; effects on the bone, brain and heart) and therefore, the search for novel AIs continues. Over the past decades, there has been an intense effort in employing medicinal chemistry and quantitative structure-activity relationship (QSAR) to shed light on the mechanistic basis of aromatase inhibition. To the best of our knowledge, this article constitutes the first comprehensive review of all QSAR studies of both steroidal and non-steroidal AIs that have been published in the field. Herein, we summarize the experimental setup of these studies as well as summarizing the key features that are pertinent for robust aromatase inhibition.

Diverse classes of HDAC8 inhibitors: in search of molecular fingerprints that regulate activity

AIM

HDAC8 is one of the crucial enzymes involved in malignancy. Structural explorations of HDAC8 inhibitory activity and selectivity are required.

MATERIALS & METHODS

A mathematical framework was constructed to explore important molecular fragments responsible for HDAC8 inhibition. Bayesian classification models were developed on a large set of structurally diverse HDAC8 inhibitors.

RESULTS

This study helps to understand the structural importance of HDAC8 inhibitors. The hydrophobic aryl cap function is important for HDAC8 inhibition whereas benzamide moiety shows a negative impact on HDAC8 inhibition.

CONCLUSION

This work validates our previously proposed structural features for better HDAC8 inhibition. The comparative learning between the statistical and intelligent methods will surely enrich future drug design aspects of HDAC8 inhibitors.

Structural exploration of hydroxyethylamines as HIV-1 protease inhibitors: new features identified

The current study deals with chemometric modelling strategies (Naïve Bayes classification, hologram-based quantitative structure-activity relationship (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA)) to explore the important features of hydroxylamine derivatives for exerting potent human immunodeficiency virus-1 (HIV-1) protease inhibition. Depending on the statistically validated reliable and robust quantitative structure-activity relationship (QSAR) models, important and crucial structural features have been identified that may be responsible for enhancing the activity profile of these hydroxylamine compounds. Arylsulfonamide function along with methoxy or fluoro substitution is important for enhancing activity. Bulky steric substitution at the sulfonamide nitrogen disfavours activity whereas smaller hydrophobic substitution at the same position is found to be favourable. Apart from the crucial oxazolidinone moiety, pyrrolidine, cyclic urea and methyl ester functions are also responsible for increasing the HIV-1 protease inhibitory profile. Observations derived from these modelling studies may be utilized further in designing promising HIV-1 protease inhibitors of this class.

Discrete Fourier Transform-Based Multivariate Image Analysis: Application to Modeling of Aromatase Inhibitory Activity

We recently generalized the formerly alignment-dependent multivariate image analysis applied to quantitative structure-activity relationships (MIA-QSAR) method through the application of the discrete Fourier transform (DFT), allowing for its application to noncongruent and structurally diverse chemical compound data sets. Here we report the first practical application of this method in the screening of molecular entities of therapeutic interest, with human aromatase inhibitory activity as the case study. We developed an ensemble classification model based on the two-dimensional (2D) DFT MIA-QSAR descriptors, with which we screened the NCI Diversity Set V (1593 compounds) and obtained 34 chemical compounds with possible aromatase inhibitory activity. These compounds were docked into the aromatase active site, and the 10 most promising compounds were selected for in vitro experimental validation. Of these compounds, 7419 (nonsteroidal) and 89 201 (steroidal) demonstrated satisfactory antiproliferative and aromatase inhibitory activities. The obtained results suggest that the 2D-DFT MIA-QSAR method may be useful in ligand-based virtual screening of new molecular entities of therapeutic utility.

Structural refinement and prediction of potential CCR2 antagonists through validated multi-QSAR modeling studies

Chemokines trigger numerous inflammatory responses and modulate the immune system. The interaction between monocyte chemoattractant protein-1 and chemokine receptor 2 (CCR2) may be the cause of atherosclerosis, obesity, and insulin resistance. However, CCR2 is also implicated in other inflammatory diseases such as rheumatoid arthritis, multiple sclerosis, asthma, and neuropathic pain. Therefore, there is a paramount importance of designing potent and selective CCR2 antagonists despite a number of drug candidates failed in clinical trials. In this article, 83 CCR2 antagonists by Jhonson and Jhonson Pharmaceuticals have been considered for robust validated multi-QSAR modeling studies to get an idea about the structural and pharmacophoric requirements for designing more potent CCR2 antagonists. All these QSAR models were validated and statistically reliable. Observations resulted from different modeling studies correlated and validated results of other ones. Finally, depending on these QSAR observations, some new molecules were proposed that may exhibit higher activity against CCR2.

Cognitive Effects of Aromatase and Possible Role in Memory Disorders

Diverse cognitive functions in many vertebrate species are influenced by local conversion of androgens to 17β-estradiol (E2) by aromatase. This enzyme is highly expressed in various brain regions across species, with some inter-species variation in terms of regional brain expression. Since women with breast cancer and men and women with other disorders are often treated with aromatase inhibitors (AI), these populations might be especially vulnerable to cognitive deficits due to low neuroE2 synthesis, i.e., synthesis of E2 directly within the brain. Animal models have been useful in deciphering aromatase effects on cognitive functions. Consequences of AI administration at various life cycle stages have been assessed on auditory, song processing, and spatial memory in birds and various aspects of cognition in rodent models. Additionally, cognitive deficits have been described in aromatase knockout (ArKO) mice that systemically lack this gene throughout their lifespan. This review will consider evidence to date that AI treatment in male and female rodent models, birds, and humans results in cognitive impairments. How brain aromatase regulates cognitive function throughout the lifespan, and gaps in current knowledge will be considered, along with future directions to better define how aromatase might guide learning and memory from early development through the geriatric period. Better understanding the importance of E2 synthesis on neurobehavioral responses at various ages will likely aid in the discovery of therapeutic strategies to prevent potential cognitive deficits, including Alzheimer's Disease, in individuals treated with AI or those possessing CYP19 gene polymorphisms, as well as cognitive effects of normal aging that may be related to changes in brain aromatase activity.

Structure-activity relationships and docking studies of synthetic 2-arylindole derivatives determined with aromatase and quinone reductase 1

In our ongoing effort of discovering anticancer and chemopreventive agents, a series of 2-arylindole derivatives were synthesized and evaluated toward aromatase and quinone reductase 1 (QR1). Biological evaluation revealed that several compounds (e.g., 2d, IC50 = 1.61 μM; 21, IC50 = 3.05 μM; and 27, IC50 = 3.34 μM) showed aromatase inhibitory activity with half maximal inhibitory concentration (IC50) values in the low micromolar concentrations. With regard to the QR1 induction activity, 11 exhibited the highest QR1 induction ratio (IR) with a low concentration to double activity (CD) value (IR = 8.34, CD = 2.75 μM), while 7 showed the most potent CD value of 1.12 μM. A dual acting compound 24 showed aromatase inhibition (IC50 = 9.00 μM) as well as QR1 induction (CD = 5.76 μM) activities. Computational docking studies using CDOCKER (Discovery Studio 3.5) provided insight in regard to the potential binding modes of 2-arylindoles within the aromatase active site. Predominantly, the 2-arylindoles preferred binding with the 2-aryl group toward a small hydrophobic pocket within the active site. The C-5 electron withdrawing group on indole was predicted to have an important role and formed a hydrogen bond with Ser478 (OH). Alternatively, meta-pyridyl analogs may orient with the pyridyl 3'-nitrogen coordinating with the heme group.

Integrating regression and classification-based QSARs with molecular docking analyses to explore the structure-antiaromatase activity relationships of letrozole-based analogs

Aromatase is a multienzyme complex responsible for the biosynthesis of estrogen and its level has been found higher in breast cancer. Although the designing strategy of aromatase inhibitors (AIs) has continued for more than four decades, it may still be in demand to design highly effective and less toxic AIs. In this study, several chemometric approaches have been used to explore the important structural features of a series of letrozole-based analogs for their promising aromatase inhibitory activity. All techniques are statistically validated individually and in turn, validated with each other along with the structure–activity relationship (SAR) observations. The imidazole ring has been found to interact with the heme iron, whereas the triazole ring system has not shown any interaction. Moreover, imidazole function is better than 1,2,3-triazole, whereas 1,2,3-triazole is better than the 1,2,5-triazole ring system. Additionally, a bulky aryl substitution in the azole ring along with the orientation of the azole nitrogens and the cyanophenyl function has an essential role in the inhibition of aromatase. Furthermore, a cyano group substituted at the phenyl moiety interacts with Arg115, Met374, and Ser478 at the enzyme active site to form hydrogen bonding interactions. These observations are useful for designing potential AIs in the future.