In silico ADME/T and 3D QSAR analysis of KDR inhibitors
Abstract
Tyrosine kinases (KDR) have been considered as a potential targets for the design of new anticancer agents.Recently, a series of N-4-chlorophenylnaphthamides has been reported with KDR inhibitory activity.In order to demonstrate the pharmacokinetics and the relationship between the structures and their inhibition of KDR, 3D-QSAR and in silico ADME/T analysis were performed on a dataset of 13 compounds.Quantum chemical parameters such as LUMO energy, HOMO energy, ionization energy (I), electron affinity (A), chemical potential (μ), hardness (η) and electrophilicity (χ) of the compounds are calculated by using semi-empirical SCF-MO method at PM3 level of theory and various SlogP descriptors from MOE software.In silico ADME/T analysis was performed by using different software's Discovery Studio 2.5, TOPKAT and QikProp 4.3.From in silico ADME and Toxicity studies, it was revealed that selected derivatives have good oral absorption rate and metabolism with no BBB penetration.QSTR (Quantitative Structure Toxicity Relationship) studies by using TOPAK in various computational animal models, showed high LD50 values and the compounds are found to be noncarcenogenic.Moreover, three different QSAR models were generated by Partial Least Squares (PLS) Regression method having correlation coefficient (Q 2 ) of 0.86382, 0.84372, and 0.82629, respectively.These models conclude a significant relationship of KDR inhibition with dipole moment (D), LUMO energy (ELUMO), hardness (η) and…
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
- Stable adiabatic quantum batteries
- A novel self-lipid antigen targets human T cells against CD1c(+) leukemias
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.