We have recently presented a new pharmacophore design method that allows for the incorporation of the inherent flexibility of a target active site. The flexibility of the enzymatic system is described by collecting many conformations of the uncomplexed protein; this ensemble of conformational states can come from a molecular dynamics (MD) simulation, multiple crystal structures, or many NMR structures. Binding sites for functional groups that complement the active site are determined through multiple-copy calculations. These calculations are conducted for each protein conformation, providing a large collection of potential binding sites. The Cartesian coordinates from each protein conformation are overlaid through RMS fitting of essential catalytic residues, and the pharmacophore model is described by binding regions that are conserved over many protein conformations. Previously, we developed a "dynamic" pharmacophore model for HIV-1 integrase using 11 conformations of the protein from an MD simulation; the MUSIC procedure was used to calculate binding positions for methanol molecules in each configuration of the active site. Here we present "static" pharmacophore models developed with a single conformation of the protein from two new crystal structures (standard protocol for multiple-copy methods). The static models do not perform as well as the previous dynamic model in fitting known inhibitors of HIV-1 integrase. To test the applicability of the dynamic pharmacophore method and the assumption that any reliable source of protein conformations is applicable, we have now developed a second dynamic pharmacophore model based on the two crystal structures also used for the development of the static models. Though the dynamic model based on the two crystal structures does not fit as many known inhibitors as the previous dynamic model, it is a significant improvement over the static models. Even better performance is expected with the addition of new crystal structures as they become available. However, it is notable that using only two structures leads to great improvement in the models.