Proteins, the workhorses of living systems, are constructed from chains of amino acids, which are synthesized in the cell based on the instructions of the genetic code and then folded into working proteins. The time for folding varies from microseconds to hours. What controls the folding rate is hotly debated. We postulate here that folding has the same temperature dependence as the ␣-fluctuations in the bulk solvent but is much slower. We call this behavior slaving. Slaving has been observed in folded proteins: Large-scale protein motions follow the solvent fluctuations with rate coefficient k␣ but can be slower by a large factor. Slowing occurs because large-scale motions proceed in many small steps, each determined by k␣. If conformational motions of folded proteins are slaved, so a fortiori must be the motions during folding. The unfolded protein makes a Brownian walk in the conformational space to the folded structure, with each step controlled by k␣. Because the number of conformational substates in the unfolded protein is extremely large, the folding rate coefficient, kf, is much smaller than k␣. The slaving model implies that the activation enthalpy of folding is dominated by the solvent, whereas the number of steps nf ؍ k␣͞kf is controlled by the number of accessible substates in the unfolded protein and the solvent. Proteins, however, undergo not only ␣-but also -fluctuations. These additional fluctuations are local protein motions that are essentially independent of the bulk solvent fluctuations and may be relevant at late stages of folding.folding energy landscape ͉ fractional viscosity dependence ͉ internal viscosity ͉ Maxwell relation ͉ protein-solvent interaction P roteins in cells fold and unfold continuously. Consequently, an understanding of folding rates is key. The distribution and strength of contacts in the native state is one ingredient that influences the rate of folding (1). A second ingredient is the effect of the solvent, because protein motions are intimately linked to the motions of the environment. Our slaving model quantifies the linkage. The model is based on three concepts: Proteins assume a large number of different conformations or substates (2), their organization is described by a hierarchic energy landscape (3), and large-scale protein fluctuations follow the ␣-relaxation (Debye or dielectric relaxation) in the bulk solvent (4-6). Here we propose that these concepts also are valid for folding and that they lead to the model pictured in Fig. 1. Fig. 1a is a cartoon of folding and a 1D cross-section through the high-dimensional energy landscape. Fig. 1b is a 2D cross-section.