Proteins have a complex free-energy landscape because of their rich topol. and the nature of their nonbonded interaction potential. This has important consequences because the roughness of the landscape affects the ease with which a chain folds and also dets. the dynamic behavior of the folded structure, thus influencing its functional and stability properties. A detailed description of the free-energy landscape is therefore of paramount importance for a quant. understanding of the relationships between structure, dynamics, stability, and functional behavior of proteins. The free-energy landscape of a protein is a high-dimensional hypersurface, difficult to rationalize. Therefore, achieving its detailed graphical representation in a way that goes beyond the familiar funnel-like free-energy model is still a big challenge. We describe here an approach based on global structural parameters that allows a two-dimensional representation of the free-energy landscape from simulated at. trajectories. As shown in this and in the accompanying article, our representation of the landscape, combined with other conformational analyses, provides valuable information on its roughness and on how at. trajectories evolve with time. [on SciFinder (R)]