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 ($R_{Train}^2=0.931$; $Q_{cv}^2=0.625$; $R_{Test}^2=0.875$). 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.

In the present work, the synthesis of new ethacrynic acid (EA) derivatives containing nitrogen heterocyclic, urea, or thiourea moieties via efficient and practical synthetic procedures was reported. The synthesised compounds were screened for their anti-proliferative activity against two different cancer cell lines, namely, HL60 (promyelocytic leukaemia) and HCT116 (human colon carcinoma). The results of the in vitro tests reveal that compounds 1–3, 10, 16(a–c), and 17 exhibit potent anti-proliferative activity against the HL60 cell line, with values of the percentage of cell viability ranging from 20 to 35% at 1 μM of the drug and IC₅₀ values between 2.37 μM and 0.86 μM. Compounds 2 and 10 showed a very interesting anti-proliferative activity of 28 and 48% at 1 μM, respectively, against HCT116. Two PyTAP-based fluorescent EA analogues were also synthesised and tested, showing good anti-proliferative activity. A test on the drug-likeness properties in silico of all the synthetised compounds was performed in order to understand the mechanism of action of the most active compounds. A molecular docking study was conducted on two human proteins, namely, glutathione S-transferase P1-1 (pdb:2GSS) and caspase-3 (pdb:4AU8) as target enzymes. The docking results show that compounds 2 and 3 exhibit significant binding modes with these enzymes. This finding provides a potential strategy towards developing anticancer agents, and most of the synthesised and newly designed compounds show good drug-like properties.

Erythropoietin-producing hepatocellular carcinoma B4 (EphB4) belongs to the Eph family of receptor tyrosine kinases (RTKs) and plays a significant role in the amplification of many kinds of cancers such as lung cancer, head and neck cancer, and mesothelioma. In this work, we applied a fragment-based drug design strategy to find novel Ephb4 receptor inhibitors as potential therapeutic candidates. A screening of over 269,000 fragments from various libraries has been conducted to determine their affinity for binding EphB4. Using Schrödinger software, 1,000 fragments with the highest docking scores underwent fragment linking to generate 100 new molecules. The EphB4 binding affinity and ADMET characteristics of the top 20 docking score molecules were then examined in more detail. After the best compounds were selected, a molecular dynamics study was conducted to determine the stability of the ligand-receptor complex in the top three molecules. The resultant compound may be investigated further in the context of tyrosine kinase inhibitor drug development.

The problem with sleep disorders is that they are frequent, often severe, and obstruct the patient's recovery and quality of life. Therefore, it is extremely important to identify new anti-Sleep Disorders agents. The objective of this research was to identify potent anti-sleep disorders agents using screening that combined molecular docking, dynamics. As part of this study, we have screened 20 compounds of Cannabis sativa L plants against orexin. Drug-like filters and ADMET analysis were used to refine the selected molecules. Based on the results of drug like and ADMET, we use the docking tools aids to visualizing and analysing protein-ligand complexes at the atomic level. In the end, two hits were chosen for molecular dynamics simulation. Results showed that two hits had potent inhibitory activity and excellent ADMET characteristics, and they might be used as new leads for the development of potent anti-sleep drugs. MD simulation study is applied for these two hits during 50 ns. As a result of these in-silico experiments, there is a strong basis for further investigation into their anti-Sleep properties.

In this work, we investigated the quantitative relationship between biological activity against non-small cell lung cancer (NSCLC) and the molecular structure of a series of 38 cyclohexane-1,3-dione-dimidone derivatives. For this purpose, molecular descriptors calculated by DFT-B3LYP/6-31G, topological, and physicochemical analysis were used. The results of the evaluations of the quantitative activity structure relationship (QSAR) models developed in this work via Multiple Linear Regression and via Multiple Non-Linear Regression (MLR and MNLR) techniques indicate the high predictive power of these models, (R² = 0.913; R²_CV = 0.85, R²_test = 0.934) for the linear model and (R² = 0.991; R²_CV = 0.82; R²_test = 0.997) for the nonlinear model. Using predictions from the QSAR model, new molecular structures were designed, their activity against NSCLC was evaluated, and the most important interactions between these molecules and the human c-Met protein were predicted. The predictions from QSAR models, molecular docking, and an evaluation of the in silico ADMET properties suggested that 1 of the 16 newly designed molecules is a candidate that may be a drug for NSCLC.