Corticotropin-releasing factor (CRF) is a neuropeptide that falls into the broad spectrum of having neurotransmitter/neurohormonal/neuromodulator activities. The design and synthesis of low molecular weight non-peptide antagonists for the CRF receptors is a very important area of research as they can be employed in the treatment of a wide variety of disorders. To investigate the ligand-receptor binding mode and design novel CRF1 antagonists, both quantitative and qualitative 3D-QSAR analysis have been performed on a data set of CRF(1) antagonists by using HypoGen and HipHopRefine programs of Catalyst software. The training set of HypoGen study included twenty-five structurally diverse CRF(1) antagonists with Ki values ranging from 0.5 nM to 10 microM. The common feature-based 3D-QSAR study used eight highly potent CRF(1) antagonists and four poor antagonistic ligands to generate 3D-pharmacophore models with excluded volumes. The obtained 3D-pharmacophore models from each study served as queries for virtual screening with a 'focused compound library' for novel CRF(1) antagonist development. Pharmacophore models obtained for antagonist binding are useful for CRF related chemical biology and drug design. Strategies and methods employed in this paper are simple and practical for medicinal chemists in drug R&D.