Computational evaluation of 1,2,3-triazole-based VEGFR-2 inhibitors: anti-angiogenesis potential and pharmacokinetic assessment.

The vascular endothelial growth factor (VEGF) and its cell surface receptor, as well as the human VEGFR-2 domain kinase, are some of the signaling pathways that have received the most attention in this field. This study aimed to identify novel molecules as VEGFR-2 inhibitors using 3D-QSAR modeling based on 1,2,3-triazole. Docking studies and dynamic simulations were performed to analyze novel interactions with the inhibitors and validate the molecular docking, dynamic simulations, and ADMET analyses. The optimized CoMSIA/SEH model showed good statistical results, and molecular docking and molecular dynamics simulations demonstrated stability of M3 ligand with the receptor and provided insight into ligand-receptor interactions. The newly developed compounds performed well in ADMET evaluations and showed promising results using Lipinski's rule of five, suggesting that the molecule M3 could be a useful anti-angiogenesis agent. In conclusion, this study provides insights into the structure-activity relationship of VEGFR-2 inhibitors and identifies M3 as a potential new anti-angiogenesis drug. The methodology used in this study can be applied to other similar drug targets to discover new and potent inhibitors.Communicated by Ramaswamy H. Sarma.

Computational Prediction of 3,5-Diaryl-1H-Pyrazole and spiropyrazolines derivatives as potential acetylcholinesterase inhibitors for alzheimer disease treatment by 3D-QSAR, molecular docking, molecular dynamics simulation, and ADME-Tox.

The efficacy of 40 synthesized variants of 3,5-diaryl-1H-pyrazole and spiropyrazoline' derivatives as acetylcholinesterase inhibitors is verified using a quantitative three-dimensional structure-activity relationship (3D-QSAR) by comparative molecular field analysis (CoMFA) and molecular similarity index analysis (CoMSIA) models. In this research, different field models proved that CoMSIA/SE model is the best model with high predictive power compared to several models (Qved2 = O.65; R2 = 0.980; R2test = 0.727). Also, contour maps produced by CoMSIA/SE model have been employed to prove the key structural needs of the activity. Consequently, six new compounds have been generated. Among these compounds, M4 and M5 were the most active but remained toxic and had poor absorption capacities. While the M1, M2, M3 and M6 remained highly active while respecting ADMET's characteristics. Molecular docking results showed compound M2 better with acetylcholinesterase than compound 22. The interactions are classical hydrogen bonding with residues TYR:124, TYR:72, and SER:293, which play a critical role in the biological activity as AChE inhibitors. MD results confirmed the docking results and showed that compound M2 had satisfactory stability with (ΔGbinding = -151.225 KJ/mol) in the active site of AChE receptor compared with compound 22 (ΔGbinding = -133.375 KJ/mol). In addition, both compounds had good stability regarding RMSD, Rg, and RMSF. The previous results show that the newly designed compound M2 is more active in the active site of AChE receptor than compound 22.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.