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.     

Virtual screening for anti-HIV-1 RT and anti-HIV-1 PR inhibitors from the Thai medicinal plants database: a combined docking with neural networks approach

The virtual screening approach for docking small molecules into a known protein structure is a powerful tool for drug design. In this work, a combined docking and neural network approach, using a self-organizing map, has been developed and applied to screen anti-HIV-1 inhibitors for two targets, HIV-1 RT and HIV-1 PR, from active compounds available in the Thai Medicinal Plants Database. Based on nevirapine and calanolide A as reference structures in the HIV-1 RT binding site and XK-263 in the HIV-1 PR binding site, 2,684 compounds in the database were docked into the target enzymes. Self-organizing maps were then generated with respect to three types of pharmacophoric groups. The map of the reference structures were then superimposed on the feature maps of all screened compounds. Only the structures having similar features to the reference compounds were accepted. By using the SOMs, the number of candidates for HIV-1 RT was reduced to six and nine compounds consistent with nevirapine and calanolide A, respectively, as references. For the HIV-1 PR target, there are 135 screened compounds showed good agreement with the XK-263 feature map. These screened compounds will be further tested for their HIV-1 inhibitory affinities. The obtained results indicate that this combined method is clearly helpful to perform the successive screening and to reduce the analyzing step from AutoDock and scoring procedure.     

Screening of new non-nucleoside reverse transcriptase inhibitors of HIV-1 based on traditional Chinese medicines database

HIV-1 RT is an important target for the treatment of AIDS.There are two major classes of antiviral agents that inhibit HIV-1 RT have been identified,nucleoside RT inhibitors(NRTIs) and non-nucleoside RT inhibitors(NNRTIs).In this report,a noval class of non-nucleoside compound with potential RT inhibitory activity were found from the traditional Chinese medicines database (TCMD) using a combination of virtual screening,docking,molecular dynamic simulations,where results were ranked by scoring function of...     

CoMFA 3D-QSAR analysis of HIV-1 RT nonnucleoside inhibitors, TIBO derivatives based on docking conformation and alignment

HIV-1 RT is one of the key enzymes in the duplication of HIV-1. Inhibitors of HIV-1 RT are classified as nonnucleoside RT inhibitors (NNRTIs) and nucleoside analogues. NNRTIs bind in a region not associated with the active site of the enzyme. Within the NNRTI category, there is a set of inhibitors commonly referred to as TIBO inhibitors. Fifty TIBO inhibitors were used in the work to build 3-D QSAR models. The two known crystal structures of complexes are used to investigate and validate the docking protocol. The results show that the docking simulations reproduce the crystal complexes very well with RMSDs of approximately 1 A and approximately 0.6 A for 1REV and 1COU, respectively. The alignment of molecules and "active" conformation selection are the key to a successful 3D-QSAR model by CoMFA. The flexible docking (Autodock3) was used on determination of "active" conformation and molecular alignment, and CoMFA and CoMSIA were used to develop 3D-QSAR models of 50 TIBOs in the work. The 3D-QSAR models demonstrate a good ability to predict the activity of studied compounds (r2 = 0.972, 0.944, q2 = 0.704, 0.776). It is shown that the steric and electrostatic properties predicted by CoMFA contours can be related to the binding structure of the complex. The results demonstrate that the combination of ligand-based and receptor-based modeling is a powerful approach to build 3D-QSAR models.