Molecular modelling of quinoline derivatives as telomerase inhibitors through 3D-QSAR, molecular dynamics simulation, and molecular docking techniques

RETRACTED: In-silico modelling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions

“…The CoMFA and CoMSIA methods were used to generate the 3D-QSAR models of the NA inhibitors using SYBYL-X 2.1.1 software (Tripos Inc) to explain the relationship between the inhibitory activity (pIC 50 ) as the dependent variable and the 3D structure of molecules ( Vishwakarma and Bhatt, 2021 ). The descriptor parameters of the built CoMFA model were electrostatic (E) and steric (S) energy values at a point in space surrounding the molecules while the CoMSIA model was built with more additional field descriptors such as steric(S), electrostatic (E), hydrophobic (H), hydrogen bond donor (HBD) field, hydrogen bond acceptor (HBA) for both training and test set ( Goudzal et al., 2022 ).…”

Molecular docking, 3D-QASR and molecular dynamics simulations of benzimidazole Pin1 inhibitors

“…q 2 is not necessary to evaluate the goodness of 3D-QSAR models. Using the CoMFA and CoMSIA models constructed from the training set to predict the biological activity of the test set and obtaining the external predictive correlation coefficient ( r pred 2 ) to characterize the degree of fit of the constructed models to the compounds of the test set is the most reliable method, and the formula for r pred 2 is given below: 33 where SD denotes the sum of the squares of the differences between the actual pIC 50 values of each compound in the test set and the average of the actual pIC 50 values of the compounds in the training set, and PRESS denotes the sum of the squares of the differences between the actual pIC 50 values and the predicted pIC 50 values of each compound in the test set.…”

Computational modelling studies of some 1,3-thiazine derivatives as anti-influenza inhibitors targeting H1N1 neuraminidase via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions

“…The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used for building the 3D-QSAR models [30]. The descriptor parameters utilized for the CoMFA model building were electrostatic (E) and steric (S) energies at a point in space surrounding the compounds, while the CoMSIA model was utilized for more additional descriptors such as hydrophobic (H), hydrogen bond donor (HBD) field, and hydrogen bond acceptor (HBA) fields [31].…”