Drug discovery is mostly guided by innovative and knowledge by the application of experimental and computational approaches. Quantitative structure-activity relationships (QSAR) have a critical task in the discovery and optimization of lead compounds, thereby contributing to the development of new chemical entities. 3D-QSAR methods use the information of the tridimensional molecular structure of ligands and can be applied to elucidate the relationships between 3D molecular interactions and their measured biological property, therefore, providing a rational approach for the development of new potential compounds. The purpose of this review is to provide a perspective of the utility of 3DQSAR approaches in drug design, focusing on progress, challenges and future orientations. The essential steps involved to generate reliable and predictive CoMFA models are discussed. Moreover, we present an example of application of a CoMFA study to derive 3D-QSAR models for a series of oxadiazoles inhibitors of Schistosoma mansoni Thioredoxin Glutathione Reductase (SmTGR).