Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and docking

2D-SAR and 3D-QSAR analyses for acetylcholinesterase inhibitors

Alzheimer's disease (AD) accounts for almost three quarters of dementia patients and interferes people's normal life. Great progress has been made recently in the study of Acetylcholinesterase (AChE), known as one of AD's biomarkers. In this study, acetylcholinesterase inhibitors (AChEI) were collected to build a two-dimensional structure-activity relationship (2D-SAR) model and three-dimensional quantitative structure-activity relationship (3D-QSAR) model based on feature selection method combined with random forest. After calculation, the prediction accuracy of the 2D-SAR model was 89.63% by using the tenfold cross-validation test and 87.27% for the independent test set. Three cutting ways were employed to build 3D-QSAR models. A model with the highest [Formula: see text] (cross-validated correlation coefficient) and [Formula: see text](non-cross-validated correlation coefficient) was obtained to predict AChEI activity. The mean absolute error (MAE) of the training set and the test set was 0.0689 and 0.5273, respectively. In addition, molecular docking was also employed to reveal that the ionization state of the compounds had an impact upon their interaction with AChE. Molecular docking results indicate that Ser124 might be one of the active site residues.

Computational Studies and Drug Design for HIV-1 Reverse Transcriptase Inhibitors of 3′,4′-di-O-(S)-camphanoyl-(+)-cis-Khellactone (DCK) Analogs

Molecular docking and molecular dynamics simulation were applied to study the binding mode of 3',4'-di-O-(S)-camphanoyl-(+)-cis-khellactone (DCK) analogs anti-HIV inhibitors with HIV-1 RT. The results suggest that there is a strong hydrogen bond between DCK O16 and NH of Lys101, and that DCK analogues might act similarly as other types of HIV-1 RT inhibitors. The investigation about drug resistance for DCK shows no remarkable influence on the most frequently observed mutation K103N of HIV-1 RT. Based on the proposed mechanism, some new structures were designed and predicted by a SVM model. All compounds exhibited potent inhibitory activities against HIV replication in H9 lymphocytes with EC50 values lower than 1.95 microM. The rationality of the method was validated by experimental results.