Two dynamic techniques recently developed to account for conformational flexibility of chemicals in three-dimensional (3D) quantitative structure-activity relationships (QSARs) are presented. A basic assumption underlying both methods is that chemical behavior in complex biological systems is context-dependent. A molecule can exist and interact in a variety of conformations. Selection of the appropriate 'active' conformer(s) in QSAR studies is a task as important as the selection of appropriate molecular parameters because multiple conformers of one chemical can differ significantly in the value of their calculated molecular descriptors. In the dynamic approaches for selection of active conformers in correlative QSAR studies, biological activity is modeled as a function of molecular descriptors derived from specifically selected active conformers, rather than as a property derived from the lowest-energy gas-phase conformer. In a recent pattern recognition approach all energetically reasonable conformers are taken into account to derive the common reactivity pattern (COREPA) of structurally diverse but biologically similar chemicals (and ultimately conformers). The COREPA method is based on the assumption that chemicals which elicit similar biological behavior through a common mechanism of interaction with the biological 'receptor' of interest, should possess a commonality in the values of their steric and/or electronic parameters, thus yielding a COREPA. Applicability of these techniques, based on the same underlying principles, is illustrated. In addition to the impact of conformational flexibility of chemicals in 3D QSAR models, the applicability of various molecular descriptors is discussed. The proposed classification could be useful as guidance for selection of appropriate molecular parameters for modeling a variety of toxicity endpoints according to the specificity of the underlying interactions.