Dataset on Insilico approaches for 3,4-dihydropyrimidin-2(1H)-one urea derivatives as efficient Staphylococcus aureus inhibitor

Abstract

Series of anti- Staphylococcus aureus were studied via quantum chemical method and several molecular descriptors were obtained which were further used to develop QSAR model using back propagation neural network method using MATLAB. More so, the molecular interaction observed between 3,4-dihydropyrimidin-2(1H)-one Urea Derivatives and Staphylococcus aureus Sortase (PDB ID Code: 2kid ) via docking was used as a screening tool for the studied compounds. The observed molecular compounds used in this work was also correlated to Lipinski rule of five and the developed QSAR model using selected descriptors from the optimized compounds was also examined for its predictability. Also, the observed molecular docking revealed the interaction between the studied complex.

Dataset on biochemical inhibiting activities of selected phytochemicals in Azadirachta indica L as potential NS2B–NS3 proteases inhibitors

“…The selected phytochemicals were optimized in solvent (water) so as to mimic the environment of therapeutic agent in human being and the duration for completion of individual compound depends on the content of the compound as well as the chosen basis set. The descriptors obtained from 2D and 3D structures of the selected compounds were subjected to QSAR analysis using material studio software [6] and the predicted binding affinity was reported. Also, the developed QSAR models were validated in order to ascertain the reliability of the models; thus, Adjusted R-squared, cross validation R-squared, significance of regression F-value, critical SOR F-value (95%) and Friedman LOF were considered.…”

Dataset on theoretical bio-evaluation of 1,2,4-thiadiazole-1,2,4-triazole analogues against epidermal growth factor receptor kinase down regulating human lung cancer

“…The optimised compounds were divided into two divisions “training set (80%) (5 compounds) and test set (20%) (3 compounds)” by using Kennard stone algorithm approach via Dataset Division GUI 1.2 software [6 , 7] . The selected 3D descriptors for training set were used for developing reliable QSAR model while the compounds for test set were used to validate the predictability of the developed QSAR model.…”

Synthesis, Biological Evaluation, in silico ADMET and Molecular Docking of new 1,4‐Dihydropyridine Derivatives Bearing Ether Substitution as Calcium Channel Blockers

“…was applied as the positive control. [26] As shown in Table 1, all of the designed compounds illustrated moderate activity compared to nifedipine with IC 50 range of 0.55-5.68 μM. The studied compounds can be classified into two series: 1) 3,5-diethyl carboxylate derivatives (5 a-d) and 2) 3,5-dimethyl carboxylate derivatives (5 e-h).…”