Three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been developed using comparative molecular field analysis (CoMFA) on a large data set (118 compounds) of diverse cyclic urea derivatives as protease inhibitors against the human immunodeficiency virus type 1 (HIV-1). X-ray crystal structures of HIV-1 protease bound with this class of inhibitors were used to derive the most probable bioactive conformations of the inhibitors. The enzyme active site was used as a constraint to limit the number of possible conformations that are sterically accessible. The test sets have been created keeping in mind structural diversity as well as the uniform simple statistical criteria (mean, standard deviation, high and low values) of the protease inhibitory activities of the molecules compared to the training sets. Multiple predictive models have been developed with the training sets (93 compounds in each set) and validated with the corresponding test sets (25 compounds in each set). All the models yielded high predictive correlation coefficients (q2 from 0.699 to 0.727), substantially high fitted correlation coefficients (r2 from 0.965 to 0.973), and reasonably low standard errors of estimates (S from 0. 239 to 0.265). The steric and electrostatic effects have approximately equal contributions, 45% and 55% (approximately), respectively, toward explaining protease inhibitory activities. This analysis yielded models with significant information on steric and electrostatic interactions clearly discerned by the respective coefficient contour plots when overlapped on the X-ray structure of the HIV-1 protease. The HINT CoMFA study revealed significant contribution of hydrophobicity toward protease inhibitory activity. The 3D visualization technique utilizing these contour plots as well as the receptor site geometry may significantly improve our understanding of the inhibitor-protease (HIV-1) interactions and help in designing compounds with improved activity.