Selective Compounds Research Articles

Development of dual V1a/V2 antagonists containing triazolobenzazepine scaffold

The development of a dual V1a/V2 antagonist compound is a complex and challenging task. Conivaptan is up to now the only known V1a/V2 antagonist which was approved for the treatment of euvolemic hyponatremia. Previously, we reported RGH-122, a novel selective V1a antagonist compound. Herein, we describe several promising dual antagonist compounds, which are derived from RGH-122 by using modifications in its tail region. These modifications can result in excellent binding affinity on both V1a and V2 receptors.

Cross-pathway integration of cAMP signals through cGMP and calcium-regulated phosphodiesterases in mouse striatal cholinergic interneurons.

Acetylcholine plays a key role in striatal function. Firing properties of striatal cholinergic interneurons depend on intracellular cAMP through the regulation of Ih currents. Yet, the dynamics of cyclic nucleotide signalling in these neurons have remained elusive. We used highly selective FRET biosensors and pharmacological compounds to analyse the functional contribution of phosphodiesterases in striatal cholinergic interneurons in mouse brain slices. PDE1A, PDE3A and PDE4 appear as the main controllers of cAMP levels in striatal cholinergic interneurons. The calcium signal elicited through NMDA or metabotropic glutamate receptors activates PDE1A, which degrades both cAMP and cGMP. Interestingly, the nitric oxide/cGMP pathway amplifies cAMP signalling via PDE3A inhibition-a mechanism hitherto unexplored in a neuronal context. The expression pattern of specific PDE enzymes in striatal cholinergic interneurons, by integrating diverse intracellular pathways, can adjust cAMP responses bidirectionally. These properties eventually allow striatal cholinergic interneurons to dynamically regulate their overall activity and modulate acetylcholine release. Remarkably, this effect is the opposite of the cGMP-induced inhibition of cAMP signals involving PDE2A in striatal medium-sized spiny neurons, which provides important insights for the understanding of signal integration in the striatum.

Carmaphycin B-Based Proteasome Inhibitors to Treat Human African Trypanosomiasis: Structure-Activity Relationship and In Vivo Efficacy.

The proteasome is essential for eukaryotic cell proteostasis, and inhibitors of the 20S proteasome are progressing preclinically and clinically as antiparasitics. We screenedTrypanosoma brucei, the causative agent of human and animal African trypanosomiasis, in vitro with a set of 27 carmaphycin B analogs, irreversible epoxyketone inhibitors that were originally developed to inhibit thePlasmodium falciparum20S (Pf20S). The structure-activity relationship was distinct from that of the human c20S antitarget by the acceptance of d-amino acids at the P3 position of the peptidyl backbone to yield compounds with greatly decreased toxicity to human cells. For the three most selective compounds, binding to the Tb20S β5 catalytic subunit was confirmed by competition with a fluorescent activity-based probe. For one compound, J-80, with its P3 d-configuration, the differential binding to the parasite's β5 subunit was supported by both covalent and noncovalent docking analysis. Further, J-80 was equipotent against both Trypanosoma brucei gambiense and Trypanosoma brucei rhodesiense in vitro. In a mouse model of Stage 1 T. brucei infection, a single intraperitoneal (i.p.) dose of 40 mg/kg J-80 halted the growth of the parasite, and when given at 50 mg/kg i.p. twice daily for 5 days, parasitemia was decreased to below the detectable limit, with parasite recrudescence 48 h after the last dose. The in vivo proof of principle demonstrated by a potent, selective, and irreversible inhibitor of Tb20S reveals an alternative path to the development of kinetoplastid proteasome inhibitors that differs from the current focus on allosteric reversible inhibitors.

An Interdisciplinary Approach Provides Insights into the Pronounced Selectivity of Compound 42 for DPP9.

Dipeptidyl peptidase 8 (DPP8) and 9 (DPP9) are proteases gaining significant attention for their role in health and disease. Distinctive studies of these proteases are hampered by their close homology. Furthermore, designing selective compounds is a major challenge due to the highly conserved catalytic site. Here, we provide mechanistic insights underlying the DPP9-over-DPP8 selectivity of the semi-selective inhibitor "Compound 42". We performed enhanced sampling molecular dynamics simulations to investigate the binding pose of "Compound 42", which enabled the design of various DPP9 mutants that were characterized through a combination of biochemical (Ki determinations) and in silico approaches. Our findings show that DPP9 residue F253 is an important selectivity-determining factor. This work marks the discovery and validation of a structural feature that can be exploited for the design of DPP8 or DPP9 selective inhibitors.

Light up heart-type fatty acid binding protein (FABP3) with a novel fluorine-18 labelled selective FABP3 ligand

BackgroundHeart-type fatty acid binding proteins (FABP3) constitute a family of lipid chaperone proteins. They are found in the cytosol and enhance cellular fatty acid solubilisation, transport, and metabolism. FABP3 is highly expressed in the myocardium and is released from myocytes during myocardial damage. As FABP3 content in the myocardium is closely related to the metabolic state of fatty acids, we hypothesised that targeting of FABP3 with a radiolabelled small organic compound would visualise myocardium.ResultsThe selective FABP3 inhibitor, 4-(4-fluoro-2-(1-phenyl-5-(2-(trifluoromethyl)phenyl)-1H-pyrazol-3-yl)phenoxy)butanoic acid (LUF), was radiolabelled via a two-step reaction comprising copper-mediated 18F-fluorination of an arylboronic precursor followed by alkaline hydrolysis of the ethoxy protecting group. [18F]LUF was successfully synthesised by automated synthesiser with sufficient activity yields (14.0 ± 1.8 GBq) and high quality (molar activity, > 250 GBq/µmol and radiochemical purity, > 99.6%). Biological assessment of [18F]LUF as an in vivo myocardial imaging agent included evaluations of biodistribution, metabolite analysis, and positron emission tomography (PET) imaging of small animals. [18F]LUF clearly visualised the myocardium with high contrast against background tissues such as the lung and liver. [18F]LUF also showed a high absolute myocardial uptake equivalent to that of the promising myocardial perfusion tracer [18F]flurpiridaz and excellent metabolic stability in the body. These properties are ideal for stable and noise-less imaging of the heart. PET imaging of rat surgical permanent myocardial infarction (MI) and experimental autoimmune myocarditis (EAM) was also performed. [18F]LUF successfully visualised lesions of permanent MI and EAM.ConclusionOur results showed for the first time that the 18F-labelled FABP3 selective small organic compound clearly visualised myocardium with good quality. To determine the clinical utility of [18F]LUF for cardiovascular disease in clinical practice, it will be necessary to evaluate a greater variety of cardiovascular disease models and elucidate the accumulation mechanism, particularly in relation to fatty acid metabolism in the myocardium.

High throughput application of the NanoBiT Biochemical Assay for the discovery of selective inhibitors of the interaction of PI3K-p110α with KRAS

The NanoBiT Biochemical Assay (NBBA) was designed as a biochemical format of the NanoBiT cellular assay, aiming to screen weak protein-protein interactions (PPIs) in mammalian cell lysates. Here we present a High Throughput Screening (HTS) application of the NBBA to screen small molecule and fragment libraries to identify compounds that block the interaction of KRAS-G12D with phosphatidylinositol 3-kinase (PI3K) p110α. This interaction promotes PI3K activity, resulting in the promotion of cell growth, proliferation and survival, and is required for tumour initiation and growth in mouse lung cancer models, whilst having little effect on the health of normal adult mice, establishing the significance of the p110α/KRAS interaction as an oncology drug target. Despite the weak binding affinity of the p110α/KRAS interaction (KD = 3 μM), the NBBA proved to be robust and displayed excellent Z’-factor statistics during the HTS primary screening of 726,000 compounds, which led to the identification of 8,000 active compounds. A concentration response screen comparing KRAS/p110α with two closely related PI3K isoforms, p110δ and p110γ, identified selective p110α-specific compounds and enabled derivation of an IC50 for these hits. We identified around 30 compounds showing greater than 20-fold selectivity towards p110α versus p110δ and p110γ with IC50 < 2 μM. By using Differential Scanning Fluorimetry (DSF) we confirmed several compounds that bind directly to purified p110α. The most potent hits will be followed up by co-crystallization with p110α to aid further elucidation of the nature of the interaction and extended optimisation of these compounds.

Copper Phthalocyanine for Designing a Highly Selective and Disposable Electrochemical Volatile Organic Compound (VOC) Sensor

AbstractFormic acid (FA) is one of the very important organic acids that has been widely used in various industries. The highly corrosive FA can have severe adverse effects on the surrounding environment. Here, we developed an electrochemical sensor that utilizes the material properties of multi‐walled carbon nanotubes (MWCNTs), and copper phthalocyanine (CuPc) for the real‐time detection of FA gas. The response of FA has been compared with the responses of 9 common volatile organic compounds (VOCs). The chronoamperometry (CA) results revealed a high selectivity towards FA by showing an increase in the sensor current by about 25 %, in contrast to the decrease of the current in response to the other VOCs. The sensitivity of the CuPc device to FA was calculated to be 38.85 mAM−1. Material characterization (SEM, EDX, FTIR, Raman, and UV‐vis) also strongly suggests a protonation mechanism caused by the carboxylic acid group, which enhances the electrical conductivity.

Transition-Metal-Free Radical Relay Cascade Annulation of Amides: Access to Antitumor Active Benzo[b]azepine and Oxindole Derivatives.

Efficient transition-metal-free synthesis of benzo[b]azepines and oxindoles is achieved via a radical relay cascade strategy employing halogen atom transfer (XAT) for aryl radical generation followed by intramolecular hydrogen atom transfer (HAT). Optimization yielded moderate to substantial yields under visible light irradiation. Preliminary biological assessments revealed promising anti-tumor activity for select compounds. This study underscores the potential of XAT-mediated radical relay cascades in medicinal chemistry and anticancer drug discovery.

Anti-cancer Activity Evaluation of Naphthalenonic and Chromanonic Spiroisoxazoline Derivatives as Selective COX-2 Inhibitors on HT29 Cell Lines

Background: Cyclooxygenase-2 (COX-2) is induced in response to proinflammatory conditions, and it is not only a key enzyme in the inflammatory process, but also seems to be highly expressed in various types of cancer cells. On the other hand, it is well documented that chemical compounds with spiro scaffolds in their structure could be effective chemical agents against cancer types. Objective: In this study, the cytotoxicity effects of spiroisoxazoline derivatives containing naphthalinone and chromanone spiro-bridge were investigated. Methods: The cytotoxicity effects of compounds 7a-7h were evaluated by performing the MTT assay on the HT-29 (colorectal cancer), MCF-7 (breast cancer), and HEK-293 (normal kidney) cell lines. After that, a compound with high yield and remarkable cytotoxic activity was selected to analyze the cell cycle and apoptosis mechanism. Results: The most effective cytotoxic activity was observed on HT-29 and MCF-7 cell lines of compounds 7b (IC50 value: 1.07±0.28 µM) and 7f (IC50 value: 11.92±1.07 µM). None of the compounds had a toxic effect on normal HEK-293 cells, except for compound 7g with an IC50 value of 21.30±16.14 µM, whose effect was much lower than that of cisplatin and doxorubicin, known as anti-cancer agents. Subsequently, compound 7e with significant yield and cytotoxic activity was investigated to evaluate cell cycle and apoptosis. The result showed that compound 7e induced significant G0/G1 cell cycle arrest and apoptosis in HT-29 cells Conclusion: The selective COX-2 inhibitor compounds with spiroisoxazoline core structure could be suitable scaffolds for cytotoxic effects.

Evaluation of STK17B as a cancer immunotherapy target utilizing highly potent and selective small molecule inhibitors.

The serine/threonine kinase 17B (STK17B) is involved in setting the threshold for T cell activation and its absence sensitizes T cells to suboptimal stimuli. Consequently, STK17B represents an attractive potential target for cancer immunotherapy. To assess the potential of STK17B as an immuno-oncology target, we developed potent and selective tool compounds from starting points in Blueprint Medicines Corporation's proprietary kinase inhibitor library. To characterize these molecules, enzyme and cellular assays for STK17A and STK17B were established to drive chemistry optimization. Mass spectrometry-based phosphoproteomics profiling with tool inhibitors led to the identification of Ser19 on myosin light chain 2 as STK17B substrate, which is then developed into a flow cytometry-based pharmacodynamic readout of STK17B inhibition both in vitro and in vivo. In a mouse T cell activation assay, STK17B inhibitors demonstrated the ability to enhance interleukin-2 (IL-2) production. Similarly, treatment with STK17B inhibitors resulted in stronger cytokine secretion in human T cells activated using a T cell bispecific antibody. Subsequent chemistry optimization led to the identification of a highly selective and orally bioavailable tool compound, BLU7482. In vivo, STK17B inhibition led to dose-dependent modulation of myosin light chain 2 phosphorylation and enhanced priming of naïve T cells, as determined by upregulation of CD69, IL-2 and interferon-γ secretion. In line with increased T cell activation, treatment with STK17B inhibitor enhanced antitumor activity of anti-PD-L1 antibody in the MCA205 model. In summary, we successfully identified and optimized STK17B kinase inhibitors which led to increased T cell responses in vitro and in vivo. This allowed us to evaluate the potential of STK17B inhibition as an approach for cancer immunotherapy.

Design, synthesis and biological evaluation of novel benzimidazole-derived p21-activited kinase 4 (PAK4) inhibitors bearing a 4-(4-methylpiperazin-1-yl)phenyl scaffold as potential antitumor agents

A series of novel 6-(4-(4-methylpiperazin-1-yl)phenyl)-1H-benzo[d]imidazole-based p21-activited kinase 4 (PAK4) inhibitors were designed and synthesized based on the structure of lead compound GNE-2861 and that of anticancer inhibitors reported in our previous studies. All target compounds so designed were preliminarily screened in vitro for anti-tumor potency through kinase inhibitory assays and MTT assays, which revealed that most compounds exhibited significant inhibitory effects on PAK4 enzyme as well as prominent antiproliferative activities against four cancer cell models (A549, NCI–H1975, MDA-MB-231 and SK-BR-3) and low damage to healthy cells. In particular, the hit compound 12i was identified as the most effective and rather selective compound both at the enzyme and cellular level. Meanwhile, molecular docking and dynamic studies disclosed that compound 12i could bind to PAK4 stably via multiple interactions applied between the compound and the enzyme. Further mechanism studies indicated that compound 12i could inhibit the proliferation and suppress the migratory potential of MDA-MB-231 cells by inhibiting the phosphorylation of PAK4 and LIMK1, arresting cell cycle in the G0/G1 phase, inducing apoptosis and promoting ROS production. Notably, compound 12i could effectively inhibit triple-negative breast cancer (TNBC) growth with little toxicity in the MDA-MB-231 cell xenograft model. Taken together, in vitro and in vivo results demonstrated that compound 12i possessed high drug potential as an inhibitor of PAK4 to inhibit the growth and metastasis of TNBC.

Design, synthesis, and evaluation of triazoline schiff bases as potential antibacterial agents against methicillin-resistant Staphylococcus aureus (MRSA): A comprehensive computational and experimental study

In this study, a series of novel triazoline Schiff bases are designed and synthesized on a triazole-based AADHR_1 hypothesis pharmacophore model tailored to meet structural requirements for antibacterial activity. FT-IR, 1H NMR, and 13C NMR spectroscopy techniques confirmed molecular structures. Assessment of ADMET properties utilizing the pkCSM online tool unveiled encouraging pharmacokinetic profiles. Detailed Density Functional Theory (DFT) calculations showed significant electronic properties, delineating certain compounds as potent electron donors or acceptors. Docking studies unveil that, the compound 1-((1-(p-tolyl)piperidin-4-yl)methyl)-1H-1,2,3-triazole-4-carboxylic acid (2b) binded into the active site of the Penicillin-binding protein (PBP2a) of Methicillin-resistant Staphylococcus aureus (MRSA) with the docking score of -8.0 kcal/mol. Molecular dynamics simulations further corroborated the stability of the protein-ligand complex, emphasizing the compound 2b is enduring interaction at the MRSA protein's active site. Antibacterial assays against MRSA showed selective compounds exhibiting minimum inhibitory concentrations (MICs) of 20 µg/mL and Zone of inhibition up to 14 mm, highlighting their potential as effective antimicrobial agents against antibiotic-resistant bacteria. These findings collectively suggest the promising therapeutic prospects of the synthesized triazoline Schiff bases in combatting MRSA infections.

Insights into antibacterial design: Computational modeling of eugenol derivatives targeting DNA gyrase

The rise of antibiotic resistance underscores the urgent need for novel antibacterial agents. DNA gyrase, an essential enzyme involved in bacterial DNA replication, is a promising target for antibacterial therapy. Computational approaches offer a cost-effective means to design and screen potential inhibitors, such as eugenol derivatives. This study aims to computationally design eugenol derivatives as potential antibacterial agents targeting DNA gyrase, assess their binding affinities, evaluate physicochemical properties, and toxicity, and select lead compounds for further investigation. Molecular docking simulations were conducted to investigate the binding affinities of eugenol derivatives and controls to DNA gyrase. Physicochemical properties and toxicity assessments of eugenol were evaluated. Lead compounds were selected based on drug likeness, toxicity, and binding affinity. Molecular docking studies revealed varying binding affinities of eugenol derivatives to DNA gyrase, with lead compounds exhibiting superior affinity compared to eugenol. Physicochemical properties indicated moderate lipophilicity and low aqueous solubility for eugenol. Toxicity assessment revealed mutagenicity and tumorigenicity. De novo compound synthesis generated 244 novel compounds, with 44 selected based on drug-likeness, toxicity, and binding affinity as lead candidates. These findings provide valuable insights for the development of novel antibacterial agents targeting DNA gyrase, with implications for combating antibiotic resistance.

A Hybrid Metaheuristic based Feature Selection Framework for In-silico Mutagenicity Prediction

Mutagenicity is both a toxic risk to humans and an indicator of carcinogenicity. Hence, estimating mutagenicity in the early stages of drug design is crucial to minimize last-stage failures and withdrawals in drug discovery. Recently, in-silico methods have started to play critical and essential roles in the drug development process because they are low cost and low effort procedures. This study aims to predict mutagenicity of chemicals using in-silico methods. To achieve this goal, a two-phased flexible framework was proposed: 1) searching the effective and representative descriptors subset with Butterfly Optimization Algorithm (BOA) and Particle Swarm Optimization and 2) predicting mutagenicity of chemicals by the selected descriptor using gradient boosted tree-based ensemble methods. The study used two datasets: one including 8167 compounds for descriptor selection and modelling, and another containing 716 external compounds to validate the efficacy of our models. The datasets comprise 162 descriptors calculated using PaDEL. The results of both the cross-validation and the external data showed that descriptors reduced by nearly one-third by BOA (51 descriptors) yielded similar or slightly better predictive results than results obtained with the entire data set. The accuracy range attained by the proposed approach using BOA is approximately 91.9% to 97.91% for the external set and 83.35% to 86.47% for the test set. This research contributes that using optimization techniques for improving early drug design and minimizing risks in drug discovery can be considered as a valuable insights and advances in the field of drug toxicity prediction, based on the findings.

Sesquiterpene Coumarins, Chromones, and Acetophenone Derivatives with Selective Cytotoxicities from the Roots of Ferula caspica M. Bieb. (Apiaceae).

In search of selective cytotoxic compounds from Ferula species as potential leads for the treatment of various cancer diseases, a bioactivity-guided isolation study was performed on the roots of Ferula caspica M. Bieb. COLO 205 (colon), K-562 (leukemia), and MCF-7 (breast) cancer cell lines were used to monitor the cytotoxic activity of column fractions and determine the IC50 value of the active compounds. In addition to the seven known (5-11) compounds, four previously unknown compounds: kayserin A (1), kayserin B (2), 8'-epi-kayserin B angelate (3), and 3-epi-ferulin D (4) were isolated from the dichloromethane extract of the roots of F. caspica. Structure elucidation of the isolated compounds was carried out by extensive spectroscopic analyses such as 1D- and 2D-NMR spectroscopy, High-Resolution Mass Spectroscopy (HRMS), IR spectroscopy, and UV spectroscopy. Although all of the isolated compounds showed various degrees of cytotoxic activity on COLO 205, K-562, and MCF-7 cancer cell lines, the most potent compounds were identified in the following order: 1-Hydroxy-1-(1'-farnesyl)-4,6-dihydroxyacetophenone (HFDHAP, 11), 3-epi-ferulin D (3EFD, 4), and 7-desmethylferulin D (7DMFD, 6). The cytotoxic activities of all three compounds were more potent than that of the reference compound cisplatin (Cis) against all tested cancer cell lines. Still, only HFDHAP (11) was more potent than the reference compound doxorubicin (Dox) against the MCF-7 cancer cell line. The mechanism of action of these three compounds was investigated on the COLO 205 cell line. The results indicated that compounds 4, 6, and 11 trigger caspase-3/8/9 activation and suppress the anti-apoptotic protein, Bcl-xL. Molecular docking studies confirmed the interactions of the three cytotoxic molecules with the active site of the Bcl-xL protein.

Cognitive and Histopathological Alterations in Rat Models of Early- and Late-Phase Memory Dysfunction: Effects of Sigma-1 Receptor Activation.

Sigma-1 receptors are highly expressed in brain areas related to cognitive function and are a promising target for anti-amnesic treatments. We previously showed that activation of sigma-1 receptors by the selective agonist compound methyl(1 R,2 S/1 S,2 R)-2-[4-hydroxy-4-phenylpiperidin-1-yl)methyl]-1-(4-methylphenyl) cyclopropane carboxylate [(±)-PPCC] promotes a remarkable recovery in rat models of memory loss associated to cholinergic dysfunction. In this study, we sought to assess the role of (±)-PPCC on working memory deficits caused by noradrenergic depletion. Animals with a mild or severe working memory deficits associated to varying degrees of noradrenergic neuronal depletion were treated with the sigma-1 agonist just prior to the beginning of each behavioral testing session. While (±)-PPCC alone at a dose of 1 mg/kg/day failed to affect working memory in lesioned animals, its association with the α2 adrenergic receptor agonist clonidine, completely blocked noradrenaline release, significantly improving rat performance. This effect, distinct from noradrenaline activity, is likely to result from a direct action of the (±)-PPCC compound onto sigma-1 receptors, as pre-treatment with the selective sigma-1 receptor antagonist BD-1047 reversed the improved working memory performance. Despite such clear functional effects, the treatment did not affect noradrenergic neuron survival or terminal fiber proliferation. Future studies are thus necessary to address the effects of long-lasting (±)-PPCC treatment, with or without clonidine, on cognitive abilities and Alzheimer's disease-like histopathology. Considering the already established involvement of sigma-1 receptors in endogenous cell plasticity mechanisms, their activation by selective agonist compounds holds promises as possibly positive contributor to disease-modifying events in neurodegenerative diseases.

Applications of reinforcement learning, machine learning, and virtual screening in SARS-CoV-2-related proteins

Similarly, to all coronaviruses, SARS-CoV-2 uses the S glycoprotein to enter host cells, which contains two functional domains: S1 and S2 receptor binding domain (RBD). Angiotensin-converting enzyme 2 (ACE2) is recognizable by the S proteins on the surface of the SARS-CoV-2 virus. The SARS-CoV-2 virus causes SARS, but some mutations in the RBD of the S protein markedly enhance their binding affinity to ACE2. Searching for new compounds in COVID-19 is an important initial step in drug discovery and materials design. Still, the problem is that this search requires trial-and-error experiments, which are costly and time-consuming. In the automatic molecular design method based on deep reinforcement learning, it is possible to design molecules with optimized physical properties by combining a newly devised coarse-grained representation of molecules with deep reinforcement learning. Also, structured-based virtual screening uses protein 3D structure information to evaluate the binding affinity between proteins and compounds based on physicochemical interactions such as van der Waals forces, Coulomb forces, and hydrogen bonds, and select drug candidate compounds. In addition, AlphaFold can predict 3D protein structures, given the amino acid sequence, and the protein building blocks. Ensemble docking, in which multiple protein structures are generated using the molecular dynamics method and docking calculations are performed for each, is often performed independently of docking calculations. In the future, the AlphaFold algorithm can be used to predict various protein structures related to COVID-19.

Discovery and Preclinical Profile of ALG-055009, a Potent and Selective Thyroid Hormone Receptor Beta (THR-β) Agonist for the Treatment of MASH.

Agonists of thyroid hormone receptor β (THR-β) decreased LDL cholesterol (LDL-C) and triglyceride (TG) levels in human clinical trials for patients with dyslipidemia. The authors present the highly potent and selective compound ALG-055009 (14) as a potential best in class THR-β agonist. The high metabolic stability and good permeability translated well in vivo to afford a long in vivo half-life pharmacokinetic profile with limited liability for DDI, and it overcomes certain drawbacks seen in recent clinical candidates.

In silico Approaches for Exploring the Pharmacological Activities of Benzimidazole Derivatives: A Comprehensive Review.

This article reviews computational research on benzimidazole derivatives. Cytotoxicity for all compounds against cancer cell lines was measured and the results revealed that many compounds exhibited high inhibitions. This research examines the varied pharmacological properties like anticancer, antibacterial, antioxidant, anti-inflammatory and anticonvulsant activities of benzimidazole derivatives. The suggested method summarises In silico research for each activity. This review examines benzimidazole derivative structure-activity relationships and pharmacological effects. In silico investigations can anticipate structural alterations and their effects on these derivative's pharmacological characteristics and efficacy through many computational methods. Molecular docking, molecular dynamics simulations and virtual screening help anticipate pharmacological effects and optimize chemical design. These trials will improve lead optimization, target selection, and ADMET property prediction in drug development. In silico benzimidazole derivative studies will be assessed for gaps and future research. Prospective studies might include empirical verification, pharmacodynamic analysis, and computational methodology improvement. This review discusses benzimidazole derivative In silico research to understand their specific pharmacological effects. This will help scientists design new drugs and guide future research. Latest, authentic and published reports on various benzimidazole derivatives and their activities are being thoroughly studied and analyzed. The overview of benzimidazole derivatives is more comprehensive, highlighting their structural diversity, synthetic strategies, mechanisms of action, and the computational tools used to study them. In silico studies help to understand the structure-activity relationship (SAR) of benzimidazole derivatives. Through meticulous alterations of substituents, ring modifications, and linker groups, this study identified the structural factors influencing the pharmacological activity of benzimidazole derivatives. These findings enable the rational design and optimization of more potent and selective compounds.

Selective Detection of Paraquat in Adulterated and Complex Environmental Samples Using Raman Spectroelectrochemistry.

Growing demand for pesticides has created an environment prone to deceptive activities, where counterfeit or adulterated pesticide products infiltrate the market, often escaping rapid detection. This situation presents a significant challenge for sensor technology, crucial in identifying authentic pesticides and ensuring agricultural safety practices. Raman spectroscopy emerges as a powerful technique for detecting adulterants. Coupling the electrochemical techniques allows a more specific and selective detection and compound identification. In this study, we evaluate the efficacy of spectroelectrochemical measurements by coupling a potentiostat and Raman spectrograph to identify paraquat, a nonselective herbicide banned in several countries. Our findings demonstrate that applying -0.70 V during measurements yields highly selective Raman spectra, highlighting the primary vibrational bands of paraquat. Moreover, the selective Raman signal of paraquat was discernible in complex samples, including tap water, apple, and green cabbage, even in the presence of other pesticides such as diquat, acephate, and glyphosate. These results underscore the potential of this technique for reliable pesticide detection in diverse and complex matrices.