Docking, molecular dynamics and quantitative structure-activity relationship studies for HEPTs and DABOs as HIV-1 reverse transcriptase inhibitors.

As a key component in combination therapy for acquired immunodeficiency syndrome (AIDS), non-nucleoside reverse transcriptase inhibitors (NNRTIs) have been proven to be an essential way in stopping HIV-1 replication. In the present work, in silico studies were conducted on a series of 119 NNRTIs, including 1-(2-hydroxyethoxymethyl)-6-(phenylthio)thymine (HEPT) and dihydroalkoxybenzyloxopyrimidine (DABO) derivatives by using the comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), docking simulations and molecular dynamics (MD). The statistical results of the optimal model, the ligand-based CoMSIA one (Q(2) = 0.48, R(ncv)(2) =0.847, R(pre)(2) = 0.745) validates its satisfactory predictive capacity both internally and externally. The contour maps, docking and MD results correlate well with each other, drawing conclusions as follows: 1) Compounds with bulky substituents in position-6 of ring A, hydrophobic groups around position- 1, 2, 6 are preferable to the biological activities; 2) Two hydrogen bonds between RT inhibitor and the Tyr 318, Lys 101 residues, respectively, and a π-π bond between the inhibitor and Trp 188 are formed and crucial to the orientation of the active conformation of the molecules; 3) The binding pocket is essentially hydrophobic, which are determined by residues such as Trp 229, Tyr 318, Val 179, Tyr 188 and Val 108, and hydrophobic substituents may bring an improvement to the biological activity; 4) DABO and HEPT derivatives have different structures but take a similar mechanism to inhibit RT. The potency difference between two isomers in HEPTs can be explained by the distinct locations of the 6-naphthylmethyl substituent and the reasons are explained in details. All these results could be employed to alter the structural scaffold in order to develop new HIV-1 RT inhibitors that have an improved biological property. To the best of our knowledge, this is the first report on 3D-QSAR modeling of this series of HEPT and DABO NNRTs. The QSAR model and the information derived, we hope, will be of great help in presenting clear guidelines and accurate activity predictions for newly designed HIV-1 reverse transcriptase (RT) inhibitor.