A computational chemistry study has been performed on a series of tetrahydropyrimidine-2-ones (THPs) as HIV-1 protease (HIV-1 PR) inhibitors. The present investigation focuses on the correlation of inhibitor-enzyme complexation energies (E(compl)), inhibitor solvation energies E(solv)[I], and both polar and nonpolar buried surface areas (BSAs) with the observed values of the binding affinity (pK(I)). Various combinations of these specific inhibitor- and receptor-based properties were also evaluated as additional descriptors to three-dimensional quantitative structure-activity relationship (3D-QSAR) models constructed using comparative molecular field analysis (CoMFA). Linear regression of the observed pK(I) values with E(compl), E(solv)[I], and the BSAs yielded a strong correlation in terms of both self-consistency (r(2) approximately equal to 0.90) and internal predictive ability (r(cv)(2) > 0.50). The 3D-QSAR models obtained from CoMFA using standard partial least-squares (PLS) analysis also yielded a strong correlation between the CoMFA fields and the experimental pK(i) (r(2) = 0.96; r(cv)(2) = 0.58). Various "enhanced" 3D-QSAR models were constructed in which different combinations of the E(compl), E(solv)[I], and BSAs were added as additional descriptors to the default steric-electrostatic CoMFA fields. Inclusion of E(solv)[I] in particular yielded significant improvement in the predictive ability (r(cv)(2) approximately equal to 0.80) of the resultant 3D-QSAR model.