As one of the three viral encoded enzymes of HIV-1 infection, HIV-1 integrase has become an attractive drug target for the treatment. Diketoacid compounds (DKAs) are one kind of potent and selective inhibitors of HIV-1 IN. In the present work, two three-dimensional QSAR techniques (CoMFA and CoMSIA) were employed to correlate the molecular structure with the activity of inhibiting the strand transfer for 147 DKAs. The all-oritation search (AOS) and all-placement search (APS) were used to optimize the CoMFA model. The diketo and keto-enol tautomers of DKAs were also used to establish the CoMFA models. The results indicated that the enol was the dominant conformation in the HIV-1 IN and DKAs complexes. It can provide a new method and reference to identify the bioactive conformation of drugs by using QSAR analysis. The best CoMSIA model, with five fields combined, implied that the hydrophobic field is very important as well as the steric and electrostatic fields. All models indicated favorable internal validation. A comparative analysis with the three models demonstrated that the CoMFA model seems to be more predictive. The contour maps could afford steric, electrostatic, hydrophobic and H-bond information about the interaction of ligand-receptor complex visually. The models would give some useful guidelines for designing novel and potent HIV-1 integrase inhibitors. As one of the three viral encoded enzymes of HIV-1 infection, HIV-1 integrase has become an attractive drug target for the treatment. Diketoacid compounds (DKAs) are one kind of potent and selective inhibitors of HIV-1 IN. In the present The three-dimensional QSAR techniques (CoMFA and CoMSIA) were employed to correlate the molecular structure with the activity of inhibiting the strand transfer for 147 DKAs. The all-oritation search (AOS) and all-placement search (APS) were used The results indicated that the enol was the dominant conformation in the HIV-1 IN and DKAs complexes. It can provide a new method and reference to identify the bioactive conformation of drugs by using QSAR analysis. The best CoMSIA model, with five fields combined, implied that the hydrophobic field is very important as well as the steric and electrostatic fields. All models indicated favo A comparative analysis with the three models that that the CoMFA model seems to be more predictive. The contour maps could afford steric, electrostatic, hydrophobic and H-bond information about the interaction of ligand-receptor complex visually. The models give some useful guidelines for designing novel and potent HIV-1 integrase inhibitors.