Synthesis of Thiazolidine-2,4‑dione tethered pyrazolyl coumarin hybrids and In-Silico ADMET predictions

The current work describes an efficient synthesis of Morita-Baylis-Hillman adducts (MBHAs) derived heterocycles (4, 5, 6, 7, 10, 11, 12, 13, 16 and 17) with the Michael addition of piperidine and piperazine heterocycles. The comparative studies of mono and di-hydrogen bond acceptors heterocycles, meta and para substituted nitro-phenyl rings and the isolated single diastereomer 16 through molecular docking coupled with invivo bioactivities displayed very important results. The biological significances were observed against urease enzyme (IC50=3.95±0.10 µM). Almost all the compounds displayed different ranges of inhibition potential whereas the di-hydrogen bond donor diastereomers 12 and 13 were found to be highly potent against the targeted enzyme while the remaining had shown comparable inhibitory activity. The diastereomers 12 and 13 were the most active having minimum inhibitory concentration (MIC) IC50=3.95±0.10 µM. All the synthesized compounds were docked and their best poses were explored for enhanced biological properties. The molecular docking studies revealed better binding interactions of the ligand with the target enzyme. Furthermore, ADMET predictions were also observed which revealed drug like properties for all the novel MBHAs based piperidine and piperazine derivatives.

Synthesis, DFT analysis, dyeing potential and evaluation of antibacterial activities of azo dye derivatives combined with in-silico molecular docking and ADMET predictions

Pyridopyrimidine are heterocyclic molecules enclosing fused pyridine and pyrimidine rings. Owing to its fascinating core structure and pharmacological applications a series of 7-([1,1′-biphenyl]-4-yl)-5-arylpyrido[2,3-d]pyrimidine-2,4(1H,3H)-diones were synthesized and characterized using IR, 1H, 13C NMR and Mass spectral techniques. The antibacterial, antioxidant and anticancer activities were investigated for the synthesized compound 5a-5f. Compounds with electron-donating groups showed excellent free radical scavenging activity. Halogen-substituted compounds showed more potent antimicrobial and anticancer activity than other derivatives in comparison with their respective standards. Based on the IC50 value obtained from anticancer activity, 5c was further analyzed for apoptosis by AO/EB staining method. The findings suggested early apoptosis in the MCF-7 cell line. Molecular Docking studies of the synthesized compounds were performed with Kinase 1 inhibitors (PDB id: 2YEX), 5c exposed good docking results with minimum binding energy. Further, these compounds were acknowledged as orally active drug candidates from in-silico ADMET studies. Computational analysis supports biological findings indicating compound 5c as a promising anticancer agent against the human breast cancer MCF-7 cell line.

Background: Quinoline derivatives have evinced their biological importance in targeting bacteria by inhibiting Dihydrofolate reductase. H2SO4 was successfully applied as an acid catalyst for a green, efficient, and one-pot solvent-free synthesis of quinoline derivatives using sonochemistry approach from various aromatic amines and glycerol with affording yield up to 96% within 6-10 min. Objective: In this study, the synthesis, characterization, and biological assessment of fifteen quinoline derivatives (1-15) as potential DHFR inhibitors were carried out. The target compounds were docked to study the molecular interactions and binding affinities with the 1DLS enzyme. Methods: The synthesized molecules were characterized using IR, MASS, and 1H and 13C NMR. The Insilico molecular docking study was carried out through target Human Dihydrofolate Reductase (DHFR) retrieved from a protein data bank having PDB ID: 1DLS and the antimicrobial activity of all synthesized compounds were tested against Human Dihydrofolate Reductase(DHFR) enzyme by using in-vitro DHFR assay kit. Results: The molecular docking results revealed that compounds 2 and 6 have the lowest binding energy and good binding affinity with the DHFR enzyme. In-silico ADMET predictions revealed that all bestscored compounds had good absorption and drug-like properties for potential use as DHFR inhibitors to treat bacterial infection. The in vitro studies revealed that compounds 2 and 6 show potent DFHR inhibitory activity against gram-positive and gram-negative with IC50 = 12.05 ± 1.55 μM and 10.04 ± 0.73 μM, respectively. While compounds 12, 13, and 15 exhibited moderate antimicrobial activity through DHFR inhibition with IC50= 16.33 ± 0.73 μM, 17.02 ± 1.55 μM, and 18.04 ± 1.05 μM, respectively. Conclusion: This environmentally benign sonochemistry-based approach for synthesizing quinoline derivatives could be affordable for large-scale production and become a potential lead candidate for developing a new quinoline-based antimicrobial agent.

This Present research provides valuable insights and implications for the development of quinazoline derivatives as novel EGFR inhibitors. The in-silico ADMET predictions indicate that the quinazoline derivatives possess promising drug-like properties, suggesting their potential for further development as oral drugs. The low risk of toxicity and favorable metabolic and excretion profiles enhance their suitability for therapeutic applications Molecular docking studies revealed strong binding interactions between the quinazoline derivatives and the EGFR kinase domain. These interactions suggest that these compound shave the potential to effectively inhibit EGFR activity, making them promising candidates for anti- cancer drug development to progress from in-silico findings to clinical applications, further research is essential. Future work should encompass in vitro and in vivo experiments to validate the inhibitory potential of these compounds against EGFR. Additionally, pharmacokinetic studies are warranted to confirm their ADMET properties. Structural optimization through medicinal chemistry approaches may further enhance their binding affinities and specificity for EGFR. It represents a pivotal step in the exploration of quinazoline derivatives as novel EGFR inhibitors. The combined efforts in ADMET prediction, structure-based drug design, and molecular docking have provided a strong foundation for the development of innovative anti-cancer therapies. The potential of these compounds to target EGFR, a crucial player in various cancers, holds great promise for improving the treatment options available to patients and advancing the field of oncology.

QSAR, an efficient and successful approach for optimizing lead compounds in drug design, was employed to study a reported series of compounds derived from 2,4,6-trimethoxy chalcone derivatives. The ability of these compounds to inhibit CDK1 was examined, with the help of QSARINS software for model development. The generated QSAR model revealed three significant descriptors, exhibiting strong correlations with impressive statistical values: cross-validation leave-one-out correlation coefficient (Q 2LOO) = 0.6663, coefficient of determination (R 2) = 0.7863, external validation coefficient (R 2 ext) = 0.7854, cross-validation leave-many-out correlation coefficient (Q 2LMO) = 0.6256, Concordance Correlation Coefficient for cross-validation (CCCcv) = 0.8150, CCCtr = 0.8804, and CCCext = 0.8750. From the key structural findings and the insights gained from the descriptors, ETA_dPsi_A, WTPT-5, and GATS7s, new lead molecules were designed. The designed molecules were then evaluated for their CDK1 inhibitory activity using the three-descriptor model developed in this study. To evaluate their drug likeliness, in-silico ADMET predictions were made using Schrodinger’s Software. Molecular docking was carried out to determine the interactions of designed compounds with the target protein. The designed compounds having excellent binding pocket molecular stability and anticancer effectiveness was substantiated by the findings of the molecular dynamics simulation. The results of this work point out important properties and crucial interactions necessary for efficient protein inhibition, suggesting lead candidates for further development as novel anticancer agents.

In-silico design and ADMET predictions of some new imidazo[1,2-a]pyridine-3-carboxamides (IPAs) as anti-tubercular agents

Pyridine-2,6-dicarboxylic acid derivatives of potential antileishmanial activity: synthesis, biological evaluation, and in-silico studies.

Tuberculosis (TB) is one of the emerging infectious diseases in the world. DprE1 (Decaprenylphosphoryl-β-d-ribose 2′-epimerase), an enzyme accountable for mycobacterial cell wall synthesis was the first drug gable target based on discoveries of inhibitors via HTS (high throughput screening). Since then, many literature reports have been published so far enlightening varieties of chemical scaffolds acting as inhibitors of DprE1. Herein, in our present study, we have developed statistically robust GA-MLR (genetic algorithm multiple linear regression), atom-based as well as field based-3D-QSAR models. Both atom-based as well as field based-3D-QSAR models (internally as well as externally validated) were obtained with robust Training set, R2 > 0.69 and Test set, Q2 > 0.50. We have also developed top ranked 5 point hypothesis AAAHR_1 among 14 CPHs (common pharmacophore hypotheses). We found that our dataset molecule had more docking score (XP mode = − 9.068 kcal/mol) than the standards isoniazid and ethambutol; when docked into binding pockets of enzyme 4P8C with Glide module. We further queried our best docked dataset molecule 151 for ligand based virtual screening using “SwissSimilarity” platform. Among 9 identified hits, we found ZINC12196803 had best binding energies and docking score (docking score = − 9.437 kcal/mol, MMGBSA dgBind = − 70.508 kcal/mol). Finally, our molecular dynamics studies for 1.2–100 ns depicts that these complexes are stable. We have also carried out in-silico ADMET predictions, Cardiac toxicity, ‘SwissTargetPredictions’ and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) binding energy calculations for further explorations of dataset as well as hit molecules. Our current studies showed that the hit molecule ZINC12196803 may enlighten the path for future developments of DprE1 inhibitors.

Design, synthesis, and biological evaluation of novel 2,3-Di-O-Aryl/Alkyl sulfonate derivatives of l-ascorbic acid: Efficient access to novel anticancer agents via in vitro screening, tubulin polymerization inhibition, molecular docking study and ADME predictions

This study focuses on the design, synthesis, and comprehensive biological evaluation of novel quinazoline derivatives as potential therapeutic agents. The structures of nine synthesized compounds were confirmed using spectral methods such as infrared (IR), proton nuclear magnetic resonance (1H NMR) spectroscopy, and elemental analysis. These compounds were assessed for antimicrobial, antioxidant, and anticancer activities against human cancer cell lines including hepatocellular carcinoma (HepG-2), breast cancer (MCF-7), and colorectal carcinoma (HCT-116). Among them, Compounds 8 and 9 exhibited remarkable biological activities. Both compounds demonstrated significant antimicrobial and antioxidant effects, alongside potent antiproliferative activity against (HepG-2), breast cancer (MCF-7) and colorectal carcinoma (HCT-116) cell lines. Notably, Compound 8 showed superior cytotoxicity with IC50 values of 30.81, 53.41, and 76.73 µM against HepG-2, MCF-7, and HCT-116 cells, respectively, outperforming Compound 9. Molecular docking studies corroborated these results, revealing strong binding affinities of Compounds 8 and 9 to key protein targets implicated in antimicrobial and anticancer mechanisms, including Escherichia coli DNA gyrase, Staphylococcus aureus dihydropteroate synthase (DHPS), CDK2 and EGFR. Furthermore, in-silico ADMET predictions indicated favorable drug-likeness and low toxicity risks, aligning with Pfizer’s drug design guidelines. Overall, Compounds 8 and 9 emerge as promising leads with broad-spectrum therapeutic potential for pharmaceutical and food industry applications.

Rationally designed Pyrazolo[1,5-a]pyrimidines as dual inhibitors of CA IX/XII and CDK6: A novel approach for NSCLC treatment.

Class B1 metallo-β-lactamases (MBLs) are metalloenzymes found in drug resistant bacteria. The enzyme requires zinc ions, along with conserved amino acid coordination for nucleophilic attack of the lactam ring to induce hydrolysis and inactivation of β-lactam and some carbapenem antibiotics. To this date there are no clinically relevant class B1 MBL inhibitors, however L-captopril has shown significant results against NDM-1, the most difficult MBL to inhibit. Herein, we report the synthesis and evaluation of novel nucleoside analogues modified with polyethylene glycolamino (PEGA) as potential inhibitors for class B1 MBLs. Molecular dynamics simulations, using internal coordinate mechanics (ICM) algorithm, were performed on subclass B1 enzyme complex models screened with twenty-one possible PEGA-nucleosides. Analogue A, 3'-deoxy-3'-(2-(2-hydroxyethoxy)ethanamino)-β-D-xylofuranosyluracil showed superior binding, with high specificity to the conserved zinc ions in the class B1 MBL active site by utilizing key β-lactam mimic points in the uridine nucleobase. The PEGA moiety showed chelating activity with zinc and disrupted the metal-binding amino acid geometry. In all subclass B1 proteins tested, analogue A had the most effective inhibition when compared to penicillin or L-captopril. Chemical synthesis was performed by condensation of the corresponding keto ribonucleoside with PEGA, followed by enantioselective reduction of the formed imine to produce the amino derivative with desired configuration. Pharmacokinetic and pharmacodynamic screenings revealed that PEGA-pyrimidine nucleosides are not toxic, nor violate Lipinski's rules. These results suggested that analogue A can be proposed as a potential metalloenzyme inhibitor against the widespread antibiotic resistant bacteria and is worth further in vitro and in vivo investigations.

Simultaneous Method Development and Validation of Anastrozole Along with Piperine: Degradation Studies and Degradants Characterization Using LC-QTOF-ESI-MS Along with In-silico ADMET Predictions

A key element in the early stages of drug discovery and development is the accurate prediction of Absorption, Distribution, Metabolism, Excretion, and Toxicity properties. Traditional experimental methods for ADMET profiling are costly, time-consuming, and often limited in scalability, leading to high rates of clinical trial failures due to poor toxicological or pharmacokinetic profiles. Machine learning (ML) has emerged as a powerful tool for modeling complex nonlinear relationships between molecular structure and ADMET behavior, due to the increasing availability of chemical and biological data. Looking ahead, integrating explainable AI, transfer learning, and active learning methods offers the potential to address data scarcity and improve model interpretability and regulatory acceptance. As the field progresses, machine learning-based ADMET prediction is expected to become increasingly reliable, helping to streamline drug development pipelines and facilitate the creation of safer, more effective therapies. The purpose of this study is to examine and assess the state-of-the-art machine learning methods for ADMET prediction. Machine learning algorithms, such as support vector machines, gradient boosting algorithms, random forests, graph neural networks, and other software used to forecast all properties, will be examined. To create trustworthy predictive models, we stress the significance of molecular representations, dataset quality, and model evaluation techniques. Recent developments in multi-task learning and data-driven feature building, which improve prediction accuracy across several ADMET endpoints, are given particular emphasis. The web-based tools that we offer in this chapter, together with the hyperlinks that go with them, make it easier to perform In-silico ADMET research on a variety of drug candidates.