The family of homodimeric nitric oxide synthases (NOS I-III) catalyzes the generation of the cellular messenger nitric oxide (NO) by oxidation of the substrate L-arginine. The rational design of specific NOS inhibitors is of therapeutic interest in regulating pathological NO levels associated with sepsis, inflammatory, and neurodegenerative diseases. The cofactor (6R)-5,6,7,8-tetrahydrobiopterin (H(4)Bip) maximally activates all NOSs and stabilizes enzyme quaternary structure by promoting and stabilizing dimerization. Here, we describe the synthesis and three-dimensional (3D) quantitative structure-activity relationship (QSAR) analysis of 65 novel 4-amino- and 4-oxo-pteridines (antipterins) as inhibitors targeting the H(4)Bip binding site of the neuronal NOS isoform (NOS-I). The experimental binding modes for two inhibitors complexed with the related endothelial NO synthase (NOS-III) reveal requirements of biological affinity and form the basis for ligand alignment. Different alignment rules were derived by building other compounds accordingly using manual superposition or a genetic algorithm for flexible superposition. Those alignments led to 3D-QSAR models (comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA)), which were validated using leave-one-out cross-validation, multiple analyses with two and five randomly chosen cross-validation groups, perturbation of biological activities by randomization or progressive scrambling, and external prediction. An iterative realignment procedure based on rigid field fit was used to improve the consistency of the resulting partial least squares models. This led to consistent and highly predictive 3D-QSAR models with good correlation coefficients for both CoMFA and CoMSIA, which correspond to experimentally determined NOS-II and -III H(4)Bip binding site topologies as well as to the NOS-I homology model binding site in terms of steric, electrostatic, and hydrophobic complementarity. These models provide clear guidelines and accurate activity predictions for novel NOS-I inhibitors.