Design of novel isoxazole derivatives as tubulin inhibitors using computer-aided techniques: QSAR modeling, in silico ADMETox, molecular docking, molecular dynamics, biological efficacy, and retrosynthesis.

In the current work, computational methods were used to investigate new isoxazole derivatives that could be used as tubulin inhibitors. The study aims to develop a reliable quantitative structure-activity relationship (QSAR) model, following the criteria set by Golbraikh, Tropsha, and Roy. As a result, seven candidate compounds were developed, all having higher activity than the well-established anticancer agent Cisplatin (Cisp). According to the ADMETox in silico test, the candidates Pr4, Pr5, and P6 can be toxic. As a result, we have chosen to focus our study on compounds Pr1, Pr2, and Pr3. Molecular docking analysis revealed that drug candidate Pr2 exhibits the highest stability within the oxidized quinone reductase 2 (PDB ID: 4zvm), target receptor (ΔG(Pr2) = ΔG(Pr3) = -10.4 < ΔG(Pr1) = -10.0 < ΔG(Cisp) = -7.3 kcal/mol). This finding aligns with the activity predictions made by the QSAR model. Furthermore, molecular dynamics simulations of the Pr2-4zvm complex over 100 ns confirm the ligand's robust stability within the receptor's active site, supporting the results obtained from molecular docking and the QSAR model predictions. The CaverDock software was utilized to identify the tunnels likely to be followed by ligands moving from the active site to the receptor surface. This analysis also helped in determining the biological efficacy of the target compounds. The results indicated that the Pr2 compound is more effective than the others. Finally, the computer-assisted retrosynthesis process of two high confidence sequences was used to synthesize drug candidates.Communicated by Ramaswamy H. Sarma.

3D-QSAR methods were used to design eight new compounds and anti-tubulin agents.3D-QSAR models were validated by Golbraikh­Tropsha and Roy methods.The toxicity and pharmacokinetics of the proposed compounds were identified by the Lipinski rule of five, Veber rules, and ADMETox.Pr2 and Pr3 had a reasonable affinity to the receptor protein (ID PDB: 4zvm) based on molecular docking, reactivity indices, and molecular dynamics simulation.Metadynamics was used to study ligand transport in the receptor (ID PDB:3zvm).

3D-QSAR, molecular docking, simulation dynamic and ADMET studies on new quinolines derivatives against colorectal carcinoma activity.

Cancer is the uncontrolled spread of abnormal cells that results in abnormal tissue growth in the affected organ. One of the most important organs is exposed to the growth of colon cancer cells, which start in the large intestine (colon) or the rectum. Several therapeutic protocols were used to treat different kinds of cancer. Recently, several studies have targeted tubulin and microtubules due to their remarkable prefoliation. Also, recent research shows that quinoline compounds have significant efficacy against human colorectal cancer. So, the present work investigated the potential of thirty quinoline compounds as tubulin inhibitors using computational methods. A 3D-QSAR approach using two contours (CoMFA and CoMSIA), molecular docking simulation to determine the binding type of the complexes (ligand-receptor), molecular dynamics simulation and identifying pharmacokinetic characteristics were used to design molecules. For all compounds designed (T1-5), molecular docking was used to compare the stability by type of binding. The ADMET has been utilized for molecules with good stability in molecular docking (T1-3); these compounds have good medicinal characteristics. Furthermore, a molecular dynamics simulation (MD) at 100 ns was performed to confirm the stability of the T1-3 compounds; the molecules (T1-3) remained the most stable throughout the simulation. The compounds T1, T2 and T3 are the best-designed drugs for colorectal carcinoma treatments.Communicated by Ramaswamy H. Sarma.

Identification of novel curcumin derivatives against pancreatic cancer: a comprehensive approach integrating 3D-QSAR pharmacophore modeling, virtual screening, and molecular dynamics simulations.

Pancreatic cancer, known as the "silent killer," poses a daunting challenge in cancer therapy. The dysregulation of the PI3Kα signaling pathway in pancreatic cancer has attracted considerable interest as a promising target for therapeutic intervention. In this regard, the use of curcumin derivatives as inhibitors of PI3Kα has emerged, providing a novel and promising avenue for developing effective treatments for this devastating disease. Computational approaches were employed to explore this potential and investigate 58 curcumin derivatives with cytotoxic activity against the Panc-1 cell line. Our approach involved ligand-based pharmacophore modeling and atom-based 3D-QSAR analysis. The resulting QSAR model derived from the best-fitted pharmacophore hypothesis (AAHRR_1) demonstrated remarkable performance with high correlation coefficients (R2) of 0.990 for the training set and 0.977 for the test set. The cross-validation coefficient (Q2) of 0.971 also validated the model's predictive power. Tropsha's recommended criteria, including the Y-randomization test, were employed to ensure its reliability. Furthermore, an enrichment study was conducted to evaluate the model's performance in identifying active compounds. AAHRR_1 was used to screen a curated PubChem database of curcumin-related compounds. Two molecules (CID156189304 and CID154728220) exhibited promising pharmacokinetic properties and higher docking scores than Alpelisib, warranting further investigation. Extensive molecular dynamics simulations provided crucial insights into the conformational dynamics within the binding site, validating their stability and behavior. These findings contribute to our understanding of the potential therapeutic effectiveness of these compounds as PI3Kα inhibitors in pancreatic cancer.Communicated by Ramaswamy H. Sarma.

Computational investigation of imidazo[2,1-b]oxazole derivatives as potential mutant BRAF kinase inhibitors: 3D-QSAR, molecular docking, molecular dynamics simulation, and ADMETox studies.

BRAF inhibitors are known to be an effective therapeutic target for treating melanoma and other types of cancer. Using 3D-QSAR, molecular docking, and MD simulations, this study evaluated various imidazo[2,1-b]oxazole derivatives that function as mutant BRAF kinase inhibitors. Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were used to create the 3D-QSAR models. CoMSIA/SEHA model has solid predictive power across several models (Q2 = 0.578; R2 = 0.828; R2pred = 0.74) and is the best model according to the numerous field models generated. The created model's predictive power was evaluated through external validation using a test set. CoMSIA/SEHA contour maps collect information that can be used to identify critical regions with solid anticancer activity. We developed four inhibitors with high predicted activity due to these observations. ADMET prediction was used to assess the toxicity of the proposed imidazo[2,1-b]oxazole compounds. The predictive molecules (T1-T4) demonstrated good ADMET properties, excluding the toxic active compounds 11r from the database. Molecular docking was also used to determine the patterns and modes of interactions between imidazo[2,1-b]oxazole ligands and receptors, which revealed that the proposed imidazo[2,1-b]oxazole scaffold was stable in the receptor's active site (PDB code: 4G9C). The suggested compounds (T1-T4) were subjected to molecular dynamics simulations lasting 100 ns to determine their binding free energies. The results showed that T2 had a more favorable binding free energy (-149.552 kJ/mol) than T1 (-112.556 kJ/mol), T3 (-115.503 kJ/mol), and T4 (-102.553 kJ/mol). The results suggest that the imidazo[2,1-b]oxazole compounds investigated in this study have potential as inhibitors of BRAF kinase and could be further developed as anticancer drugs. Highlights22 imidazo[2,1-b]oxazole compounds were subjected to research on three-dimensional quantitative conformational relationships.Using contour maps from 3D-QSAR models as a guide was used to figure out the areas and strategies for structural optimization.Combined molecular docking, molecular dynamics simulations, and binding free energy calculations to verify the inhibitor activity of the proposed 22 imidazo[2,1-b]oxazole compounds.Four potential B-RAF Kinase inhibitors were discovered, providing theoretical clues for developing a highly anticancer agent.Communicated by Ramaswamy H. Sarma.