Protein folding is a classic grand challenge that is relevant to numerous human diseases, such as protein misfolding diseases like Alzheimer's. Solving the folding problem will ultimately require a combination of theory, simulation, and experiment; with theory and simulation providing an atomically-detailed picture of both the thermodynamics and kinetics of folding and experimental tests grounding these models in reality. However, theory and simulation generally fall orders of magnitude short of biologically relevant timescales. Here we report significant progress towards closing this gap: an atomistic model of the folding of an 80-residue fragment of the λ repressor protein with explicit solvent that captures dynamics on 10 millisecond timescales. In addition, we provide a number of predictions that warrant further experimental investigation. For example, our model's native state is a kinetic hub and biexponential kinetics arise from the presence of many free energy basins separated by barriers of different heights rather than a single low barrier along one reaction coordinate (the previously proposed incipient downhill scenario).Understanding protein folding is a long-standing problem with important medical applications, such as elucidating the role of protein misfolding in diseases like Alzheimer's. Solving the folding problem will ultimately require a combination of theory, simulation, and experiment; with theory and simulation providing an atomically-detailed picture of both the thermodynamics and kinetics of folding and experimental tests grounding these models in reality. However, modeling long timescale dynamics (e.g. microseconds, milliseconds, and beyond) with sufficient statistical accuracy and chemical detail to make a quantitative connection with experiments is extremely challenging. Much progress has been made with small, fast-folding proteins (less than 40 residues and one millisecond folding timescales 1 ) but can the methods used scale to larger, slower systems? Here we report significant progress in this direction: an atomistic model of the folding of an 80-residue fragment of the λ repressor protein (λ 6-85 ) with explicit solvent that captures dynamics on a 10 millisecond timescale.This advance builds on a growing body of work on describing molecular kinetics with network models called Markov state models (MSMs). MSMs are discrete time master equation models that essentially serve as maps of a molecule's conformational space. [1][2][3] The states in an MSM come from kinetic clustering of atomistic simulations (i.e. conformations that can interconvert rapidly are grouped together into what is called a metastable state). Thus, these models are an important advance over previous approaches, like diffusion-collision models, 4,5 as an MSM's states are derived from dynamics in detailed pande@stanford.edu. Supporting Information Available: Methods, Figure S1 to S14, To test whether the MSM approach can scale to larger systems, we have built MSMs for the D14A mutant of λ 6-85 ( Figure 1A). 12...