Pyrimidine-based sulfonamides and acetamides as potent antimicrobial Agents: Synthesis, Computational Studies, and biological assessment.

A series of novel sulfonamide and acetamide derivatives of pyrimidine were synthesized and their antimicrobial activities were assessed. Based on the Microbroth dilution method, the minimum inhibitory concentration (MIC) of the synthesized compounds demonstrated moderate to good levels of antifungal and antibacterial activity. Structure-activity relationship analysis suggested that the presence of electron-withdrawing groups, such as halogens, nitrile, and nitro groups, on the pyrimidine ring contributed to the enhanced antimicrobial potency, while electron-donating substituents led to a decrease in activity. Computational studies, including density functional theory (DFT), frontier molecular orbitals (FMO), and molecular electrostatic potential (MEP) analysis, provided insights into the electronic properties and charge distribution of the compounds. Drug-likeness evaluation using ADME/Tox analysis indicated that the synthesized compounds possess favorable physicochemical properties and could be potential drug candidates. Molecular docking against the Mycobacterium TB protein tyrosine phosphatase B (MtbPtpB) revealed that the synthesized compounds exhibited strong binding affinities (-46 kcal/mol to - 61 kcal/mol) and formed stable protein-ligand complexes through hydrogen bonding and π-π stacking interactions with key residues in the active site. The observed interactions from the docking simulations were consistent with the predicted interaction sites identified in the FMO and MEP analyses. These findings suggest that the synthesized pyrimidine derivatives could serve as promising antimicrobial agents and warrant further investigation for drug development.

Efficient Synthesis, Structural Characterization, Antibacterial Assessment, ADME-Tox Analysis, Molecular Docking and Molecular Dynamics Simulations of New Functionalized Isoxazoles.

This work describes the synthesis, characterization, and in vitro and in silico evaluation of the biological activity of new functionalized isoxazole derivatives. The structures of all new compounds were analyzed by IR and NMR spectroscopy. The structures of 4c and 4f were further confirmed by single crystal X-ray and their compositions unambiguously determined by mass spectrometry (MS). The antibacterial effect of the isoxazoles was assessed in vitro against Escherichia coli, Bacillus subtilis, and Staphylococcusaureus bacterial strains. Isoxazole 4a showed significant activity against E. coli and B. subtilis compared to the reference antibiotic drugs while 4d and 4f also exhibited some antibacterial effects. The molecular docking results indicate that the synthesized compounds exhibit strong interactions with the target proteins. Specifically, 4a displayed a better affinity for E. coli, S. aureus, and B. subtilis in comparison to the reference drugs. The molecular dynamics simulations performed on 4a strongly support the stability of the ligand-receptor complex when interacting with the active sites of proteins from E. coli, S. aureus, and B. subtilis. Lastly, the results of the Absorption, Distribution, Metabolism, Excretion and Toxicity Analysis (ADME-Tox) reveal that the molecules have promising pharmacokinetic properties, suggesting favorable druglike properties and potential therapeutic agents.

Inhibition of the Janus kinase protein (JAK1) by the A. Pyrethrum Root Extract for the treatment of Vitiligo pathology. Design, Molecular Docking, ADME-Tox, MD Simulation, and in-silico investigation.

This study delves into the therapeutic efficacy of A. pyrethrum in addressing vitiligo, a chronic inflammatory disorder known for inducing psychological distress and elevating susceptibility to autoimmune diseases. Notably, JAK inhibitors have emerged as promising candidates for treating immune dermatoses, including vitiligo. Our investigation primarily focuses on the anti-vitiligo potential of A. pyrethrum root extract, specifically targeting N-alkyl-amides, utilizing computational methodologies. Density Functional Theory (DFT) is deployed to meticulously scrutinize molecular properties, while comprehensive evaluations of ADME-Tox properties for each molecule contribute to a nuanced understanding of their therapeutic viability, showcasing remarkable drug-like characteristics. Molecular docking analysis probes ligand interactions with pivotal site JAK1, with all compounds demonstrating significant interactions; notably, molecule 6 exhibits the most interactions with crucial inhibition residues. Molecular dynamics simulations over 500ns further validate the importance and sustainability of these interactions observed in molecular docking, favoring energetically both molecules 6 and 1; however, in terms of stability, the complex with molecule 6 outperforms others. DFT analyses elucidate the distribution of electron-rich oxygen atoms and electron-poor regions within heteroatoms-linked hydrogens. Remarkably, N-alkyl-amides extracted from A. pyrethrum roots exhibit similar compositions, yielding comparable DFT and Electrostatic Potential (ESP) results with subtle distinctions. These findings underscore the considerable potential of A. pyrethrum root extracts as a natural remedy for vitiligo.

Discovery of 1,3,4-Oxadiazole Derivatives as Broad-Spectrum Antiparasitic Agents.

Vector-borne parasitic diseases (VBPDs) pose a significant threat to public health on a global scale. Collectively, Human African Trypanosomiasis (HAT), Leishmaniasis, and Malaria threaten millions of people, particularly in developing countries. Climate change might alter the transmission and spread of VBPDs, leading to a global burden of these diseases. Thus, novel agents are urgently needed to expand therapeutic options and limit the spread of drug-resistant parasites. Herein, we report the development of broad-spectrum antiparasitic agents by screening a known library of antileishmanial and antimalarial compounds toward Trypanosoma brucei (T. brucei) and identifying a 1,3,4-oxadiazole derivative (19) as anti-T. brucei hit with predicted blood-brain barrier permeability. Subsequently, extensive structure-activity-relationship studies around the lipophilic tail of 19 led to a potent antitrypanosomal and antimalarial compound (27), with moderate potency also toward Leishmania infantum (L. infantum) and Leishmania tropica. In addition, we discovered a pan-active antiparasitic molecule (24), showing low-micromolar IC50s toward T. brucei and Leishmania spp. promastigotes and amastigotes, and nanomolar IC50 against Plasmodium falciparum, together with high selectivity for the parasites over mammalian cells (THP-1). Early ADME-toxicity assays were used to assess the safety profile of the compounds. Overall, we characterized 24 and 27, bearing the 1,3,4-oxadiazole privileged scaffold, as broad-spectrum low-toxicity agents for the treatment of VBPDs. An alkyne-substituted chemical probe (30) was synthesized and will be utilized in proteomics experiments aimed at deconvoluting the mechanism of action in the T. brucei parasite.

Novel Alaninamide Derivatives with Drug-like Potential for Development as Antiseizure and Antinociceptive Therapies─In Vitro and In Vivo Characterization.

In the present study, a series of original alaninamide derivatives have been designed applying a combinatorial chemistry approach, synthesized, and characterized in the in vivo and in vitro assays. The obtained molecules showed potent and broad-spectrum activity in basic seizure models, namely, the maximal electroshock (MES) test, the 6 Hz (32 mA) seizure model, and notably, the 6 Hz (44 mA) model of pharmacoresistant seizures. Most potent compounds 26 and 28 displayed the following pharmacological values: ED50 = 64.3 mg/kg (MES), ED50 = 15.6 mg/kg (6 Hz, 32 mA), ED50 = 29.9 mg/kg (6 Hz, 44 mA), and ED50 = 34.9 mg/kg (MES), ED50 = 12.1 mg/kg (6 Hz, 32 mA), ED50 = 29.5 mg/kg (6 Hz, 44 mA), respectively. Additionally, 26 and 28 were effective in the ivPTZ seizure threshold test and had no influence on the grip strength. Moreover, lead compound 28 was tested in the PTZ-induced kindling model, and then, its influence on glutamate and GABA levels in the hippocampus and cortex was evaluated by the high-performance liquid chromatography (HPLC) method. In addition, 28 revealed potent efficacy in formalin-induced tonic pain, capsaicin-induced pain, and oxaliplatin- and streptozotocin-induced peripheral neuropathy. Pharmacokinetic studies and in vitro ADME-Tox data proved favorable drug-like properties of 28. The patch-clamp recordings in rat cortical neurons showed that 28 at a concentration of 10 µM significantly inhibited fast sodium currents. Therefore, 28 seems to be an interesting candidate for future preclinical development in epilepsy and pain indications.

Astragaloside IV as a Memory-Enhancing Agent: In Silico Studies with In Vivo Analysis and Post Mortem ADME-Tox Profiling in Mice.

Many people around the world suffer from neurodegenerative diseases associated with cognitive impairment. As life expectancy increases, this number is steadily rising. Therefore, it is extremely important to search for new treatment strategies and to discover new substances with potential neuroprotective and/or cognition-enhancing effects. This study focuses on investigating the potential of astragaloside IV (AIV), a triterpenoid saponin with proven acetylcholinesterase (AChE)-inhibiting activity naturally occurring in the root of Astragalus mongholicus, to attenuate memory impairment. Scopolamine (SCOP), an antagonist of muscarinic cholinergic receptors, and lipopolysaccharide (LPS), a trigger of neuroinflammation, were used to impair memory processes in the passive avoidance (PA) test in mice. This memory impairment in SCOP-treated mice was attenuated by prior intraperitoneal (ip) administration of AIV at a dose of 25 mg/kg. The attenuation of memory impairment by LPS was not observed. It can therefore be assumed that AIV does not reverse memory impairment by anti-inflammatory mechanisms, although this needs to be further verified. All doses of AIV tested did not affect baseline locomotor activity in mice. In the post mortem analysis by mass spectrometry of the body tissue of the mice, the highest content of AIV was found in the kidneys, then in the spleen and liver, and the lowest in the brain.

Ligand-Based Design of Novel Quinoline Derivatives as Potential Anticancer Agents: An In-Silico Virtual Screening Approach.

In this study, using the Comparative Molecular Field Analysis (CoMFA) approach, the structure-activity relationship of 33 small quinoline-based compounds with biological anti-gastric cancer activity in vitro was analyzed in 3D space. Once the 3D geometric and energy structure of the target chemical library has been optimized and their steric and electrostatic molecular field descriptions computed, the ideal 3D-QSAR model is generated and matched using the Partial Least Squares regression (PLS) algorithm. The accuracy, statistical precision, and predictive power of the developed 3D-QSAR model were confirmed by a range of internal and external validations, which were interpreted by robust correlation coefficients (RTrain2=0.931; Qcv2=0.625; RTest2=0.875). After carefully analyzing the contour maps produced by the trained 3D-QSAR model, it was discovered that certain structural characteristics are beneficial for enhancing the anti-gastric cancer properties of Quinoline derivatives. Based on this information, a total of five new quinoline compounds were developed, with their biological activity improved and their drug-like bioavailability measured using POM calculations. To further explore the potential of these compounds, molecular docking and molecular dynamics simulations were performed in an aqueous environment for 100 nanoseconds, specifically targeting serine/threonine protein kinase. Overall, the new findings of this study can serve as a starting point for further experiments with a view to the identification and design of a potential next-generation drug for target therapy against cancer.

Indole-pyridine carbonitriles: multicomponent reaction synthesis and bio-evaluation as potential hits against diabetes mellitus.

Background: Diabetes mellitus is a significant health disorder; therefore, researchers should focus on discovering new drug candidates. Methods: A series of indole-pyridine carbonitrile derivatives, 1-34, were synthesized through a one-pot multicomponent reaction and evaluated for antidiabetic and antioxidant potential. Results: In this library, 12 derivatives - 1, 2, 4, 5, 7, 8, 10-12, 14, 15 and 31 - exhibited potent inhibitory activities against α-glucosidase and α-amylase enzymes, in comparison to acarbose (IC50 = 14.50 ± 0.11 µM). Furthermore, kinetics, absorption, distribution, metabolism, excretion and toxicity and molecular docking studies were used to interpret the type of inhibition, binding energies and interactions of ligands with target enzymes. Conclusion: These results indicate that the compounds may be promising hits for controlling diabetes mellitus and its related complications.

Chromone-isoxazole hybrids molecules: synthesis, spectroscopic, MEDT, ELF, antibacterial, ADME-Tox, molecular docking and MD simulation investigations.

A mechanistic study was performed within the molecular electron density theory at the B3LYP/6-311G (d,p) computational level to explain the regioselectivity observed. An electron localization function analysis was also performed, and the results confirm the zwitterionic-type (zw-type) mechanism of the cycloaddition reactions between nitrile oxide and alkylated 4H-chromene-2-carboxylate derivatives and shed more light on the obtained regioselectivity experimentally. In silico studies on the pharmacokinetics, ADME and toxicity tests of the compounds were also performed, and it was projected that compounds 5a, 5b, 5c and 5d are pharmacokinetic and have favorable ADME profiles. Moreover, docking and molecular dynamics investigations were conducted to evaluate the interactions, orientation and conformation of the target compounds on the active sites of four distinct enzymes. The results of this investigation showed that two compounds, 5a and 5c, interacted effectively with the S. aureus active site while maintaining acceptable binding energy.Communicated by Ramaswamy H. Sarma.

Automation of Drug Discovery through Cutting-edge In-silico Research in Pharmaceuticals: Challenges and Future Scope.

The rapidity and high-throughput nature of in silico technologies make them advantageous for predicting the properties of a large array of substances. In silico approaches can be used for compounds intended for synthesis at the beginning of drug development when there is either no or very little compound available. In silico approaches can be used for impurities or degradation products. Quantifying drugs and related substances (RS) with pharmaceutical drug analysis (PDA) can also improve drug discovery (DD) by providing additional avenues to pursue. Potential future applications of PDA include combining it with other methods to make insilico predictions about drugs and RS. One possible outcome of this is a determination of the drug potential of nontoxic RS. ADME estimation, QSAR research, molecular docking, bioactivity prediction, and toxicity testing all involve impurity profiling. Before committing to DD, RS with minimal toxicity can be utilised in silico. The efficacy of molecular docking in getting a medication to market is still debated despite its refinement and improvement. Biomedical labs and pharmaceutical companies were hesitant to adopt molecular docking algorithms for drug screening despite their decades of development and improvement. Despite the widespread use of "force fields" to represent the energy exerted within and between molecules, it has been impossible to reliably predict or compute the binding affinities between proteins and potential binding medications.

Hierarchical Virtual Screening of Potential New Antibiotics from Polyoxygenated Dibenzofurans against Staphylococcus aureus Strains.

Staphylococcus aureus is a microorganism with high morbidity and mortality due to antibiotic-resistant strains, making the search for new therapeutic options urgent. In this context, computational drug design can facilitate the drug discovery process, optimizing time and resources. In this work, computational methods involving ligand- and structure-based virtual screening were employed to identify potential antibacterial agents against the S. aureus MRSA and VRSA strains. To achieve this goal, tetrahydroxybenzofuran, a promising antibacterial agent according to in vitro tests described in the literature, was adopted as the pivotal molecule and derivative molecules were considered to generate a pharmacophore model, which was used to perform virtual screening on the Pharmit platform. Through this result, twenty-four molecules were selected from the MolPort® database. Using the Tanimoto Index on the BindingDB web server, it was possible to select eighteen molecules with greater structural similarity in relation to commercial antibiotics (methicillin and oxacillin). Predictions of toxicological and pharmacokinetic properties (ADME/Tox) using the eighteen most similar molecules, showed that only three exhibited desired properties (LB255, LB320 and LB415). In the molecular docking study, the promising molecules LB255, LB320 and LB415 showed significant values in both molecular targets. LB320 presented better binding affinity to MRSA (-8.18 kcal/mol) and VRSA (-8.01 kcal/mol) targets. Through PASS web server, the three molecules, specially LB320, showed potential for antibacterial activity. Synthetic accessibility (SA) analysis performed on AMBIT and SwissADME web servers showed that LB255 and LB415 can be considered difficult to synthesize and LB320 is considered easy. In conclusion, the results suggest that these ligands, particularly LB320, may bind strongly to the studied targets and may have appropriate ADME/Tox properties in experimental studies.

Herbal concoction Unveiled: A computational analysis of phytochemicals' pharmacokinetic and toxicological profiles using novel approach methodologies (NAMs).

Herbal medications have an extensive history of use in treating various diseases, attributed to their perceived efficacy and safety. Traditional medicine practitioners and contemporary healthcare providers have shown particular interest in herbal syrups, especially for respiratory illnesses associated with the SARS-CoV-2 virus. However, the current understanding of the pharmacokinetic and toxicological properties of phytochemicals in these herbal mixtures is limited. This study presents a comprehensive computational analysis utilizing novel approach methodologies (NAMs) to investigate the pharmacokinetic and toxicological profiles of phytochemicals in herbal syrup, leveraging in-silico techniques and prediction tools such as PubChem, SwissADME, and Molsoft's database. Although molecular dynamics, docking, and broader system-wide analyses were not considered, future studies hold potential for further investigation in these areas. By combining drug-likeness with molecular simulation, researchers identify diverse phytochemicals suitable for complex medication development examining their pharmacokinetic-toxicological profiles in phytopharmaceutical syrup. The study focuses on herbal solutions for respiratory infections, with the goal of adding to the pool of all-natural treatments for such ailments. This research has the potential to revolutionize environmental and alternative medicine by leveraging in-silico models and innovative analytical techniques to identify novel phytochemicals with enhanced therapeutic benefits and explore network-based and systems biology approaches for a deeper understanding of their interactions with biological systems. Overall, our study offers valuable insights into the computational analysis of the pharmacokinetic and toxicological profiles of herbal concoction. This paves the way for advancements in environmental and alternative medicine. However, we acknowledge the need for future studies to address the aforementioned topics that were not adequately covered in this research.

In silico ADME/tox comes of age: twenty years later.

In the early 2000s pharmaceutical drug discovery was beginning to use computational approaches for absorption, distribution, metabolism, excretion and toxicity (ADME/Tox, also known as ADMET) prediction. This emphasis on prediction was an effort to reduce the risk of later stage failures from ADME/Tox.Much has been written in the intervening twenty plus years and significant expenditure has occurred in companies developing these in silico capabilities which can be gleaned from publications. It is therefore an appropriate time to briefly reflect on what was proposed then and what the reality is today.20 years ago, we tended to optimise bioactivity and perhaps one ADME/Tox property at a time. Previously pharmaceutical companies needed a whole infrastructure for models - in silico and in vitro experts, IT, champions on a project team, educators and management support. Now we are in the age of generative de novo design where bioactivity and many ADME/Tox properties can be optimised and large language model technologies are available.There are also some challenges such as the focus on very large molecules which may be outside of current ADME/Tox models.We provide an opportunity to look forward with the increasing public data for ADME/Tox as well as expanded types of algorithms available.

Synthesis, computational and experimental pharmacological studies for (thio)ether-triazine 5-HT6R ligands with noticeable action on AChE/BChE and chalcogen-dependent intrinsic activity in search for new class of drugs against Alzheimer's disease.

Alzheimer's disease is becoming a growing problem increasing at a tremendous rate. Serotonin 5-HT6 receptors appear to be a particularly attractive target from a therapeutic perspective, due to their involvement not only in cognitive processes, but also in depression and psychosis. In this work, we present the synthesis and broad biological characterization of a new series of 18 compounds with a unique 1,3,5-triazine backbone, as potent 5-HT6 receptor ligands. The main aim of this research is to compare the biological activity of the newly synthesized sulfur derivatives with their oxygen analogues and their N-demethylated O- and S-metabolites obtained for the first time. Most of the new triazines displayed high affinity (Ki < 200 nM) and selectivity towards 5-HT6R, with respect to 5-HT2AR, 5-HT7R, and D2R, in the radioligand binding assays. For selected, active compounds crystallographic studies, functional bioassays, and ADME-Tox profile in vitro were performed. The exciting novelty is that the sulfur derivatives exhibit an agonistic mode of action contrary to all other compounds obtained to date in this chemical class herein and previously reported. Advanced computational studies indicated that this intriguing functional shift might be caused by presence of chalcogen bonds formed only by the sulfur atom. In addition, the N-demethylated derivatives have emerged highly potent antioxidants and, moreover, show a significant improvement in metabolic stability compared to the parent structures. The cholinesterase study present micromolar inhibitory AChE and BChE activity for both 5-HT6 agonist 19 and potent antagonist 5. Finally, the behavioral experiments of compound 19 demonstrated its antidepressant-like properties and slight ability to improve cognitive deficits, without inducing memory impairments by itself. Described pharmacological properties of both compounds (5 and 19) allow to give a design clue for the development of multitarget compounds with 5-HT6 (both agonist and antagonist)/AChE and/or BChE mechanism in the group of 1,3,5-triazine derivatives.

High-throughput virtual screening of phenylpyrimidine derivatives as selective JAK3 antagonists using computational methods.

In this study, we used phenylpyrimidine derivatives with known biological activity against JAK3, a critical tyrosine kinase enzyme involved in signaling pathways, to find similar compounds as potential treatments for rheumatoid arthritis. These inhibitors inhibited JAK3 activity by forming a covalent bond with the Cys909 residue, which resulted in a strong inhibitory effect. Phenylpyrimidine is considered a promising therapeutic target. For pharmacophore modeling, 39 phenylpyrimidine derivatives with high pIC50 (Exp) values were chosen. The best pharmacophore model produced 28 molecules, and the five-point common pharmacophore hypothesis from P HASE (DHRRR_1) revealed the requirement for a hydrogen bond donor feature, a hydrophobic group feature, and three aromatic ring features for further design. The validation of the pharmacophore model phase was performed through 3D-QSAR using partial least squares (P LS). The 3D-QSAR study produced two successful models, an atom-based model (R2 = 0.95; Q2 = 0.67) and a field-based model (R2 = 0.93; Q2 = 0.76), which were used to predict the biological activity of new compounds. The pharmacophore model successfully distinguished between active and inactive medications, discovered potential JAK3 inhibitors, and demonstrated validity with a ROC of 0. 77. ADME-Tox was used to eliminate compounds that might have adverse effects. The best pharmacokinetics and affinity derivatives were selected for covalent docking. A molecular dynamics simulation of the selected molecules and the protein complex was performed to confirm the stability of the interaction with JAK3, whereas MM/GBSA simulations further confirmed their binding affinity. By using the principle of retrosynthesis, we were able to map out a pathway for synthesizing these potential drug candidates. This study has the potential to offer valuable and practical insights for optimizing novel derivatives of phenylpyrimidine.Communicated by Ramaswamy H. Sarma.

A Robust Machine Learning Framework Built Upon Molecular Representations Predicts CYP450 Inhibition: Toward Precision in Drug Repurposing.

Human cytochrome P450 (CYP450) enzymes play a crucial role in drug metabolism and pharmacokinetics. CYP450 inhibition can lead to toxicity, in particular when drugs are co-administered with other drugs and xenobiotics or in the case of polypharmacy. Predicting CYP450 inhibition is also important for rational drug discovery and development, and precision in drug repurposing. In this overarching context, digital transformation of drug discovery and development, for example, using machine and deep learning approaches, offers prospects for prediction of CYP450 inhibition through computational models. We report here the development of a majority-voting machine learning framework to classify inhibitors and noninhibitors for seven major human liver CYP450 isoforms (CYP1A2, CYP2A6, CYP2B6, CYP2C9, CYP2C19, CYP2D6, and CYP3A4). For the machine learning models reported herein, we employed interaction fingerprints that were derived from molecular docking simulations, thus adding an additional layer of information for protein-ligand interactions. The proposed machine learning framework is based on the structure of the binding site of isoforms to produce predictions beyond previously reported approaches. Also, we carried out a comparative analysis so as to identify which representation of test compounds (molecular descriptors, molecular fingerprints, or protein-ligand interaction fingerprints) affects the predictive performance of the models. This work underlines the ways in which the structure of the enzyme catalytic site influences machine learning predictions and the need for robust frameworks toward better-informed predictions.

Spectroscopic, theoretical and computational investigations of novel benzo[b]thiophene based ligand and its M(II) complexes: As high portentous antimicrobial and antioxidant agents.

The reaction of 3-chlorobenzo[b]thiophene-2-carbohydrazide with 4-(diethylamino) salicylaldehyde gave the new ligand; 3-chloro-N'-(4-(diethylamino)-2-hydroxybenzylidene)-benzo[b]thiophene-2-carbohydrazide. The Cu(II), Co(II), Ni(II), and Zn(II) complexes have been successfully prepared. The ligand and the complexes were characterized by analytical, FT-IR, 1H NMR, mass, UV-visible spectroscopy, molar conductivity, and magnetic susceptibility measurements. The FT-IR spectral data showed that the ligand adopted a tridentate fashion when binding with the metal ions via the nitrogen atoms of the imine (C = N), carboxyl (C = O), and phenolic oxygen (O-H) donor atoms. Density Functional Theory (DFT) estimations for the ligand at the DFT/B3LYP level via 6-31G++ (d, p) replicate the structure and geometry. Finally, HOMO and LUMO analyses were used for the charge transfer interface of the structure. Furthermore, molecular docking and ADME calculations were also performed to correlate and interpret the experimental results. The antimicrobial activity study illustrated enhancement in the activity of the free ligand upon complex formation, and the Cu(II) complex (MIC 25 µg mL-1) may be considered a promising antibacterial agent, and the Ni(II) and Zn(II) complexes (MIC 25 µg mL-1) as promising antifungal agents. Also, synthesized Cu(II) and Zn(II) metal complexes (MIC 3.125 µg mL-1) showed promising anti-TB activity against M. tuberculosis. Further, benzo[b]thiophene-based ligand and its metal complexes were evaluated for in vitro antioxidant activity, and in silico docking studies were carried out against Cytochrome c Peroxidase (PDB ID: 2X08).

Butein, a potential drug for the treatment of bone cancer pain through bioinformatic and network pharmacology.

Bone cancer pain is a difficult-to-treat pathologic condition that impairs the patient's quality of life. The effective therapy options for BCP are restricted due to the unknown pathophysiology. Transcriptome data were obtained from the Gene Expression Omnibus database and differentially expressed gene extraction was performed. DEGs integrated with pathological targets found 68 genes in the study. Butein was discovered as a possible medication for BCP after the 68 genes were submitted to the Connectivity Map 2.0 database for drug prediction. Moreover, butein has good drug-likeness properties. To collect the butein targets, we used the CTD, SEA, TargetNet, and Super-PRED databases. Furthermore, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed butein's pharmacological effects, indicating that butein may aid in treating BCP by altering the hypoxia-inducible factor, NF-kappa B, angiogenesis, and sphingolipid signaling pathways. Moreover, the pathological targets integrated with drug targets were obtained as the shared gene set A, which was analyzed by ClueGO and MCODE. Biological process analysis and MCODE algorithm further analyzed that BCP related targets were mainly involved in signal transduction process and ion channel-related pathways. Next, we integrated targets related to network topology parameters and targets of core pathways, identified PTGS2, EGFR, JUN, ESR1, TRPV1, AKT1 and VEGFA as butein regulated hub genes by molecular docking, which play a critical role in its analgesic effect. This study lays the scientific groundwork for elucidating the mechanism underlying butein's success in the treatment of BCP.

Design and Synthesis of New 4-(3,4,5-Trimethoxyphenyl)Thiazole-Pyrimidine Derivatives as Potential Antiproliferative Agents.

A new series of 3,4,5-trimethoxyphenyl thiazole pyrimidines has been synthesized and biologically evaluated for its in vitro anticancer activity. Compounds 4a, 4b, and 4h with substituted piperazine showed the best antiproliferative activity. In the NCI-60 cell line screening, compound 4b showed promising cytostatic activity against multiple cell lines. Notably, it elicited a GI value of 86.28% against the NSCL cancer cell line HOP-92 at a 10 µM dose. Compounds 4a and 4h at 10 µM showed promising GI values of 40.87% and 46.14% against HCT-116 colorectal carcinoma and SK-BR-3 breast cancer cell lines, respectively. ADME-Tox prediction of compounds 4a, 4b, and 4h revealed their acceptable drug-likeness properties. In addition, compounds 4a, 4b, and 4h showed a high probability of targeting kinase receptors via Molinspiration and Swiss TargetPrediction.