Novel 2-(2-alkylthiobenzenesulfonyl)-3-(phenylprop-2-ynylideneamino)guanidine derivatives as potent anticancer agents – Synthesis, molecular structure, QSAR studies and metabolic stability

Synthetic and natural guanidine derivatives as antitumor and antimicrobial agents: A review

Guanidines are fascinating small nitrogen-rich organic compounds, which have been frequently associated with a wide range of biological activities. This is mainly due to their interesting chemical features. For these reasons, for the past decades, researchers have been synthesizing and evaluating guanidine derivatives. In fact, there are currently on the market several guanidine-bearing drugs. Given the broad panoply of pharmacological activities displayed by guanidine compounds, in this review, we chose to focus on antitumor, antibacterial, antiviral, antifungal, and antiprotozoal activities presented by several natural and synthetic guanidine derivatives, which are undergoing preclinical and clinical studies from January 2010 to January 2023. Moreover, we also present guanidine-containing drugs currently in the market for the treatment of cancer and several infectious diseases. In the preclinical and clinical setting, most of the synthesized and natural guanidine derivatives are being evaluated as antitumor and antibacterial agents. Even though DNA is the most known target of this type of compounds, their cytotoxicity also involves several other different mechanisms, such as interference with bacterial cell membranes, reactive oxygen species (ROS) formation, mitochondrial-mediated apoptosis, mediated-Rac1 inhibition, among others. As for the compounds already used as pharmacological drugs, their main application is in the treatment of different types of cancer, such as breast, lung, prostate, and leukemia. Guanidine-containing drugs are also being used for the treatment of bacterial, antiprotozoal, antiviral infections and, recently, have been proposed for the treatment of COVID-19. To conclude, the guanidine group is a privileged scaffold in drug design. Its remarkable cytotoxic activities, especially in the field of oncology, still make it suitable for a deeper investigation to afford more efficient and target-specific drugs.

New ferrocene integrated amphiphilic guanidines: Synthesis, spectroscopic elucidation, DFT calculation and in vitro α-amylase and α-glucosidase inhibition combined with molecular docking approach

Three N, N', N″-trisubstituted ferrocenyl guanidines (MG-10, MG-12 and MG-14) were synthesized, characterized by several analytical methods such as FT-IR, ¹H and ¹³C NMR, elemental analysis and UV-visible spectroscopy. These compounds have long chain aliphatic groups therefore their aliphatic nature has been evaluated by determining their critical micelle concentration (CMC). CMC point decreases from 0.036 mM to 0.013 mM with increase in the aliphatic chain length. The quantum mechanical parameters such as the energy of frontier molecular orbitals (E_HOMO and E_LUMO) and the Mulliken charge distribution on the optimized structures were determined using a DFT/B3LYP method combined with the 6-31G (d,p) basis set in the gas phase. The in vitro antidiabetic activity of synthesized compounds showed that MG-12 has IC₅₀value 23.10 μg/mL against α-amylase while MG-10 has IC₅₀value 27.32 μg/mL against α-glucosidase with the respective standard Acarbose (IC₅₀value 20.12 μg/mL). Theoretical docking analysis demonstrated that MG-10 and MG-12 interacted with α-amylase by 3 types of interaction, including hydrogen bonds, hydrophobic interactions and electrostatic interactions.

Synthesis of 3-(2-Alkylthio-4-chloro-5-methylbenzenesulfonyl)-2-(1-phenyl-3-arylprop-2-enylideneamino)guanidine Derivatives with Pro-Apoptotic Activity against Cancer Cells

The untypical course of reaction between chalcones and benzenesulfonylaminoguanidines led to the new 3-(2-alkylthio-4-chloro-5-methylbenzenesulfonyl)-2-(1-phenyl-3-arylprop-2-enylideneamino)guanidine derivatives 8-33. The new compounds were tested in vitro for their impact on the growth of breast cancer cells MCF-7, cervical cancer cells HeLa and colon cancer cells HCT-116 by MTT assay. The results revealed that the activity of derivatives is strongly related to the presence of hydroxy group in the benzene ring at the 3-arylpropylidene fragment. The most cytotoxic compounds 20 and 24 displayed mean IC₅₀ values of 12.8 and 12.7 μM, respectively, against three tested cell lines and were almost 3- and 4-fold more active toward MCF-7 and HCT-116 when compared with non-malignant HaCaT cells. Furthermore, compound 24 induced apoptosis in cancer cells and caused a decrease of mitochondrial membrane potential as well as an increase of cells in sub-G1 phase in contrast to its inactive analog 31. The strongest activity against the most sensitive HCT-116 cell line was found for compound 30 (IC₅₀ = 8 μM), which was 11-fold more effective in the growth inhibition of HCT-116 cells than those of HaCaT cells. Based on this fact, the new derivatives may be promising leading structures for the search for agents for the treatment of colon cancer.

G-quadruplex-mediated specific recognition, stabilization and transcriptional repression of bcl-2 by small molecule

The presence of the G-quadruplex (G4) structure in the promoter region of the human bcl-2 oncogenes makes it a promising target for developing anti-cancer therapeutics. Bcl-2 inhibits apoptosis, and its frequent overexpression in cancer cells contributes to tumor initiation, progression, and resistance to therapy. Small molecules that can specifically bind to bcl-2 G4 with high affinity and selectivity are remaining elusive. Here, we report that small molecule 1,3-bis-) furane-2yl-methylidene-amino) guanidine (BiGh) binds to bcl-2 G4 DNA structure with very high affinity and selectivity over other genomic G4 DNA structures and duplex DNA. BiGh stabilizes folded parallel conformation of bcl-2 G4 via non-covalent and electrostatic interactions and increases the thermal stabilization up to 15 °C. The ligand significantly suppresses the bcl-2 transcription in HeLa cells by a G4-dependent mechanism and induces cell cycle arrest which promotes apoptosis. The in silico ADME profiling confirms the potential 'drug-likeness' of BiGh. Our results showed that BiGh stabilizes the bcl-2 G-quadruplex motif, downregulates the bcl-2 gene transcription as well as translation process in cervical cancer cells, and exhibits potential anti-cancer activity. This work provides a potential platform for the development of lead compound(s) as G4 stabilizers with drug-like properties of BiGh for cancer therapeutics.

Discovery of potent Guanidine derivative that selectively binds and stabilizes the human BCL-2 G-quadruplex DNA and downregulates the transcription

Small molecules that interact with quadruplexes offer a wide range of potential applications, including not just as medications but also as sensors for quadruplexes structures. The BCL-2 is a proto-oncogene that often gets mutated in lethal cancer and could be an interesting target for developing an anti-cancer drug. In the present study, we have employed various biophysical techniques such as fluorescence, CD, Isothermal calorimeter, gel retardation, and PCR stop assay, indicating that Guanidine derivatives GD-1 and GD-2 selectively interact with high affinity with BCL-2 G-quadruplex over other G-quadruplex DNA and duplex DNA. The most promising small molecule GD-1 increases the thermostability of the BCL-2 GQ structure by 12°C. Our biological experiments such as ROS generation, qRT-PCR, western blot, TFP based Reporter assay, show that the GD-1 ligand causes a synthetic lethal interaction by suppressing the expression BCL-2 genes via interaction and stabilization of its the promoter G-quadruplexes in HeLa cells and act as a potential anti-cancer agent.

Thioethers: An Overview

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Spreading rapidly in recent years, cancer has become one of the causes of the highest mor-tality rates after cardiovascular diseases. The reason for cancer development is still not clearly under-stood despite enormous research activities in this area. Scientists are now working on the biology of cancer, especially on the root cause of cancer development. The aim is to treat the cancer disease and thus cure the patients. The continuing efforts for the development of novel molecules as potential anti-cancer agents are essential for this purpose. The main aim of this review was to present a survey on the medicinal chemistry of thioethers and provide practical data on their cytotoxicities against various cancer cell lines. The research articles published between 2001-2020 were consulted to pre-pare this review article; however, patent literature has not been included. The thioether-containing heterocyclic compounds may emerge as a new class of potent and effective anti-cancer agents in the future.

Synthesis, Pharmacological, and Biological Evaluation of 2-Furoyl-Based MIF-1 Peptidomimetics and the Development of a General-Purpose Model for Allosteric Modulators (ALLOPTML)

This work describes the synthesis and pharmacological evaluation of 2-furoyl-based Melanostatin (MIF-1) peptidomimetics as dopamine D₂ modulating agents. Eight novel peptidomimetics were tested for their ability to enhance the maximal effect of tritiated N-propylapomorphine ([³H]-NPA) at D₂ receptors (D₂R). In this series, 2-furoyl-l-leucylglycinamide (6a) produced a statistically significant increase in the maximal [³H]-NPA response at 10 pM (11 ± 1%), comparable to the effect of MIF-1 (18 ± 9%) at the same concentration. This result supports previous evidence that the replacement of proline residue by heteroaromatic scaffolds are tolerated at the allosteric binding site of MIF-1. Biological assays performed for peptidomimetic 6a using cortex neurons from 19-day-old Wistar-Kyoto rat embryos suggest that 6a displays no neurotoxicity up to 100 μM. Overall, the pharmacological and toxicological profile and the structural simplicity of 6a makes this peptidomimetic a potential lead compound for further development and optimization, paving the way for the development of novel modulating agents of D₂R suitable for the treatment of CNS-related diseases. Additionally, the pharmacological and biological data herein reported, along with >20 000 outcomes of preclinical assays, was used to seek a general model to predict the allosteric modulatory potential of molecular candidates for a myriad of target receptors, organisms, cell lines, and biological activity parameters based on perturbation theory (PT) ideas and machine learning (ML) techniques, abbreviated as ALLOPTML. By doing so, ALLOPTML shows high specificity Sp = 89.2/89.4%, sensitivity Sn = 71.3/72.2%, and accuracy Ac = 86.1%/86.4% in training/validation series, respectively. To the best of our knowledge, ALLOPTML is the first general-purpose chemoinformatic tool using a PTML-based model for the multioutput and multicondition prediction of allosteric compounds, which is expected to save both time and resources during the early drug discovery of allosteric modulators.

Perturbation-Theory Machine Learning (PTML) Multilabel Model of the ChEMBL Dataset of Preclinical Assays for Antisarcoma Compounds

Sarcomas are a group of malignant neoplasms of connective tissue with a different etiology than carcinomas. The efforts to discover new drugs with antisarcoma activity have generated large datasets of multiple preclinical assays with different experimental conditions. For instance, the ChEMBL database contains outcomes of 37,919 different antisarcoma assays with 34,955 different chemical compounds. Furthermore, the experimental conditions reported in this dataset include 157 types of biological activity parameters, 36 drug targets, 43 cell lines, and 17 assay organisms. Considering this information, we propose combining perturbation theory (PT) principles with machine learning (ML) to develop a PTML model to predict antisarcoma compounds. PTML models use one function of reference that measures the probability of a drug being active under certain conditions (protein, cell line, organism, etc.). In this paper, we used a linear discriminant analysis and neural network to train and compare PT and non-PT models. All the explored models have an accuracy of 89.19-95.25% for training and 89.22-95.46% in validation sets. PTML-based strategies have similar accuracy but generate simplest models. Therefore, they may become a versatile tool for predicting antisarcoma compounds.

Metabolic stability studies of lead compounds supported by separation techniques and chemometrics analysis

With metabolism being one of the main routes of drug elimination from the body (accounting for removal of around 75% of known drugs), it is crucial to understand and study metabolic stability of drug candidates. Metabolically unstable compounds are uncomfortable to administer (requiring repetitive dosage during therapy), while overly stable drugs increase risk of adverse drug reactions. Additionally, biotransformation reactions can lead to formation of toxic or pharmacologically active metabolites (either less-active than parent drug, or even with different action). There were numerous approaches in estimating metabolic stability, including in vitro, in vivo, in silico, and high-throughput screening to name a few. This review aims at describing separation techniques used in in vitro metabolic stability estimation, as well as chemometric techniques allowing for creation of predictive models which enable high-throughput screening approach for estimation of metabolic stability. With a very low rate of drug approval, it is important to understand in silico methods that aim at supporting classical in vitro approach. Predictive models that allow assessment of certain biological properties of drug candidates allow for cutting not only cost, but also time required to synthesize compounds predicted to be unstable or inactive by in silico models.

Synthesis, Anticancer Evaluation and Structure-Activity Analysis of Novel (E)- 5-(2-Arylvinyl)-1,3,4-oxadiazol-2-yl)benzenesulfonamides

To learn more about the structure-activity relationships of (E)-3-(5-styryl-1,3,4-oxadiazol-2-yl)benzenesulfonamide derivatives, which in our previous research displayed promising in vitro anticancer activity, we have synthesized a group of novel (E)-5-[(5-(2-arylvinyl)-1,3,4-oxadiazol-2-yl)]-4-chloro-2-R1-benzenesulfonamides 7-36 as well as (E)-4-[5-styryl1,3,4-oxadiazol-2-yl]benzenesulfonamides 47-50 and (E)-2-(2,4-dichlorophenyl)-5-(2-arylvinyl)-1,3,4-oxadiazols 51-55. All target derivatives were evaluated for their anticancer activity on HeLa, HCT-116, and MCF-7 human tumor cell lines. The obtained results were analyzed in order to explain the influence of a structure of the 2-aryl-vinyl substituent and benzenesulfonamide scaffold on the anti-tumor activity. Compound 31, bearing 5-nitrothiophene moiety, exhibited the most potent anticancer activity against the HCT-116, MCF-7, and HeLa cell lines, with IC50 values of 0.5, 4, and 4.5 µM, respectively. Analysis of structure-activity relationship showed significant differences in activity depending on the substituent in position 3 of the benzenesulfonamide ring and indicated as the optimal meta position of the sulfonamide moiety relative to the oxadizole ring. In the next stage, chemometric analysis was performed basing on a set of computed molecular descriptors. Hierarchical cluster analysis was used to examine the internal structure of the obtained data and the quantitative structure-activity relationship (QSAR) analysis with multiple linear regression (MLR) method allowed for finding statistically significant models for predicting activity towards all three cancer cell lines.

A Guanidine-Based Synthetic Compound Suppresses Angiogenesis via Inhibition of Acid Ceramidase

Angiogenesis generates new blood vessels from pre-existing vessels. Tumors induce the formation of new blood vessels to ensure sufficient oxygen and nutrients for their growth. Normally, angiogenesis is induced by various pro-angiogenesis factors, including vascular endothelial growth factor (VEGF). Inhibition of VEGF is a promising approach to cancer treatment. A guanidine-based synthetic compound, E2, was identified as a potent hit from 68 guanidine-based derivatives by screening for angiogenesis inhibitors showing antiproliferative activity in human umbilical vein endothelial cells (HUVECs). To explore the mode of action of E2, target proteins were investigated using phage display biopanning, and acid ceramidase 1 (ASAH1) was identified as an E2-binding protein. Drug affinity responsive target stability (DARTS) and ASAH1 activity assays revealed the direct binding of E2 to ASAH1. Moreover, siRNA knockdown of ASAH1 demonstrated its role as an angiogenesis factor. Consequently, E2 inhibited chemoinvasion and tube formation of HUVECs in a dose-dependent manner. E2 also potently suppressed neo-vascularization of chorioallantoic membranes in vivo. Collectively, these data suggest that E2 is a novel angiogenesis inhibitor and ASAH1 is proposed to be a new antiangiogenesis target.

PTML Combinatorial Model of ChEMBL Compounds Assays for Multiple Types of Cancer

Determining the target proteins of new anticancer compounds is a very important task in Medicinal Chemistry. In this sense, chemists carry out preclinical assays with a high number of combinations of experimental conditions (c _j). In fact, ChEMBL database contains outcomes of 65 534 different anticancer activity preclinical assays for 35 565 different chemical compounds (1.84 assays per compound). These assays cover different combinations of c _j formed from >70 different biological activity parameters ( c₀), >300 different drug targets ( c₁), >230 cell lines ( c₂), and 5 organisms of assay ( c₃) or organisms of the target ( c₄). It include a total of 45 833 assays in leukemia, 6227 assays in breast cancer, 2499 assays in ovarian cancer, 3499 in colon cancer, 3159 in lung cancer, 2750 in prostate cancer, 601 in melanoma, etc. This is a very complex data set with multiple Big Data features. This data is hard to be rationalized by researchers to extract useful relationships and predict new compounds. In this context, we propose to combine perturbation theory (PT) ideas and machine learning (ML) modeling to solve this combinatorial-like problem. In this work, we report a PTML (PT + ML) model for ChEMBL data set of preclinical assays of anticancer compounds. This is a simple linear model with only three variables. The model presented values of area under receiver operating curve = AUROC = 0.872, specificity = Sp(%) = 90.2, sensitivity = Sn(%) = 70.6, and overall accuracy = Ac(%) = 87.7 in training series. The model also have Sp(%) = 90.1, Sn(%) = 71.4, and Ac(%) = 87.8 in external validation series. The model use PT operators based on multicondition moving averages to capture all the complexity of the data set. We also compared the model with nonlinear artificial neural network (ANN) models obtaining similar results. This confirms the hypothesis of a linear relationship between the PT operators and the classification as anticancer compounds in different combinations of assay conditions. Last, we compared the model with other PTML models reported in the literature concluding that this is the only one PTML model able to predict activity against multiple types of cancer. This model is a simple but versatile tool for the prediction of the targets of anticancer compounds taking into consideration multiple combinations of experimental conditions in preclinical assays.

Synthesis, molecular structure, and metabolic stability of new series of N'-(2-alkylthio-4-chloro-5-methylbenzenesulfonyl)-1-(5-phenyl-1H-pyrazol-1-yl)amidine as potential anti-cancer agents

A series of new N'-(2-alkylthio-4-chloro-5-methylbenzenesulfonyl)-1-(5-phenyl-1H-pyrazol-1-yl)amidine derivatives have been synthesized and evaluated in vitro by MTT assays for their antiproliferative activity against cell lines of colon cancer HCT-116, cervical cancer HeLa and breast cancer MCF-7. The studied compounds display selective activity mainly against HCT-116 and HeLa cells. Thus, five compounds show selective cytotoxic effect against HCT-116 (IC₅₀ = 3-10 μM) and HeLa (IC₅₀ = 7 μM). Importantly, the noticed values of IC₅₀ for four compounds are almost 4-fold lower for HeLa than non-malignant HaCaT cells. More-in-depth biological research revealed that the treatment of HCT-116 and HeLa with active compound resulted in increased numbers of cells in sub-G1 phase in a time dependent manner, while non-active derivative does not influence cell cycle. Metabolic stability assays using liver microsomes and NADPH provide important information on compounds susceptibility to phase 1 biotransformation reactions.

Synthesis and evaluation of antimicrobial, antitubercular and anticancer activities of 2-(1-benzoyl-1H-benzo[d]imidazol-2-ylthio)-N-substituted acetamides

BACKGROUND

The study describes the synthesis, characterization, in vitro antimicrobial and anticancer evaluation of a series of 2-(1-benzoyl-1H-benzo[d]imidazol-2-ylthio)-N-substituted acetamide derivatives. The synthesized derivatives were also assessed for in vitro antitubercular activity against Mycobacterium tuberculosis H37Rv. The compounds found active in in vitro study were assessed for their in vivo antitubercular activity in mice models and for their inhibitory action on vital mycobacterial enzymes viz, isocitrate lyase, pantothenate synthetase and chorismate mutase.

RESULTS

Compounds 8, 9 and 11 emerged out as excellent antimicrobial agents in antimicrobial assays when compared to standard antibacterial and antifungal drugs. The results of anticancer activity displayed that majority of the derivatives were less cytotoxic than standard drugs (tamoxifen and 5-fluorouracil) towards MCF7 and HCT116 cell lines. However, compound 2 (IC₅₀ = 0.0047 µM/ml) and compound 10 (IC₅₀ = 0.0058 µM/ml) showed highest cytotoxicity against MCF7 and HCT116 cell lines, respectively. The results of in vivo antitubercular activity revealed that a dose of 1.34 mg/kg was found to be safe for the synthesized compounds. The toxic dose of the compounds was 5.67 mg/kg while lethal dose varied from 1.81 to 3.17 mg/kg body weight of the mice. Compound 18 inhibited all the three mycobacterial enzymes to the highest level in comparison to the other synthesized derivatives but showed lesser inhibition as compared to streptomycin sulphate.

CONCLUSIONS

A further research on most active synthesized compounds as lead molecules may result in discovery of novel anticancer and antitubercular agents.

Synthesis, Molecular Structure, Anticancer Activity, and QSAR Study of N-(aryl/heteroaryl)-4-(1H-pyrrol-1-yl)Benzenesulfonamide Derivatives

A series of N-(aryl/heteroaryl)-4-(1H-pyrrol-1-yl)benzenesulfonamides were synthesized from 4-amino-N-(aryl/heteroaryl)benzenesulfonamides and 2,5-dimethoxytetrahydrofuran. All the synthesized compounds were evaluated for their anticancer activity on HeLa, HCT-116, and MCF-7 human tumor cell lines. Compound 28, bearing 8-quinolinyl moiety, exhibited the most potent anticancer activity against the HCT-116, MCF-7, and HeLa cell lines, with IC50 values of 3, 5, and 7 µM, respectively. The apoptotic potential of the most active compound (28) was analyzed through various assays: phosphatidylserine translocation, cell cycle distribution, and caspase activation. Compound 28 promoted cell cycle arrest in G2/M phase in cancer cells, induced caspase activity, and increased the population of apoptotic cells. Relationships between structure and biological activity were determined by the QSAR (quantitative structure activity relationships) method. Analysis of quantitative structure activity relationships allowed us to generate OPLS (Orthogonal Projections to Latent Structure) models with verified predictive ability that point out key molecular descriptors influencing benzenosulfonamide's activity.