T he dark mystery of protein folding has been greatly illuminated by the last decade's work. This enlightenment has come from the simultaneous flowering of new theoretical approaches (1-3), powerful computational studies (4,5), and a fresh wave of experiments using protein engineering (6) and ultrafast kinetics (7,8). How a disordered chain molecule finds its organized, folded state is no longer a paradox, but a scientific problem requiring a close comparison of theories, computation and experiments. A beautiful experimental study of the mechanism of folding of the B domain of streptococcal protein A appears in this issue of PNAS (9). This study joins such landmarks as the elucidation of the folding mechanism of CI2 and barnase by the same group (10). So what's the news? The excitement comes because this protein has been the poster child of computational folders. It is attractive to computationalists because of its small size, 60 residues, at the extreme limit exhibiting cooperative protein-like thermodynamics. The protein also folds fast, so computer studies have the best chance of success. Numerous simulations were carried out (11-23) without extensive laboratory kinetic studies at the residue level to influence the work. It is thus interesting to see how well the computationalists have been able to predict the folding mechanism without much biasing data. Sato et al. (9) liken the comparison of simulations with their kinetic experiment to the biennial exercise Critical Assessment of Structure Prediction (CASP) (24). They, like most participants in CASP, refer to it as a competition, although the organizers decry that appellation. As the leader of a participating group, I can testify to CASP's painfulness, but, despite its undignified similarity to a sporting event, good science comes from CASP. Likewise, the present results do indeed provoke serious thought.When compared with the old view of a single obligate folding pathway (25), the computational studies are in remarkable agreement with each other and with experiment. All these studies show a diffuse folding mechanism in which a fairly diverse ensemble of structures is guided to the native structure by trading stabilization free energy for configurational entropy (1). The energy landscape resembles a funnel in which more native-like structures are stabilized over kinetic traps that could arise from conflicting energetic signals (''frustration''). In a funnel landscape, although trapping is not a problem, a kinetic bottleneck arises because stabilization energy and entropy do not smoothly compensate each other as the protein descends in the funnel. The ensemble of structures at the bottleneck, called the transition state ensemble (TSE), is probed by examining the effect of changing individual amino acids on folding rates. In a funnel-like landscape, these changes can be converted to values that measure how much more structures in the TSE resemble the native structure or the denatured ensemble. If ϭ 1 for a given residue, in the TSE that residue will be in a ...