Background: The accuracy of molecular conformation for Quantitative Structure
Activity Relationship (QSAR) studies is an important criteria, and the most favourable bioactive
conformer selection is a tough task. Correct ligand alignment as input for 3D-QSAR is an important
step that is prone to human biases. Multiple-dimensional QSAR (mQSAR) approach provides
a promising alternative to classic 3D-QSAR for drug discovery purposes.
Objective: Obtaining ligand conformations from multiple receptor conformation docking
(MRCD) will reduce the margin of error by incorporating the receptor based alignment of
ligand conformations. To validate this assumption we performed 6D QSAR studies on reported
HIV-1 protease inhibitors using Quasar 6.0.
Materials & Method: The ensemble of conformation was obtained by MRCD of ligands in thirteen
crystal structures of HIV-1 protease. 6D QSAR model was built using 65 cyclic urea molecules reported
as HIV-1 protease inhibitors. Predictive ability of the model was validated using 35 cyclic urea
molecules as test set. External predictive ability of the model was evaluated using a set of 24 HIV-1
protease inhibitors having varied structural scaffold.
Result: 6D QSAR model obtained showed a reliable cross-validated r2(q2) of 0.899, r2(classic) of
0.908 and yielded a predictive r2 (p2) of 0.527. The ratio of q2/r2 was 0.991 and p2/q2 was 0.586 for
external test set.
Conclusion: The QSAR results invariably suggest that our approach is suitable for the identification of
molecules having HIV-1 protease inhibitory potency. The underlying philosophy combines flexible
docking for the identification of the binding modes and 6D QSAR for their quantification.