  Proteins fold using a two-state or multi-state kinetic mechanisms, but up to
now there isn't a first-principle model to explain this different behaviour. We
exploit the network properties of protein structures by introducing novel
observables to address the problem of classifying the different types of
folding kinetics. These observables display a plain physical meaning, in terms
of vibrational modes, possible configurations compatible with the native
protein structure, and folding cooperativity. The relevance of these
observables is supported by a classification performance up to 90%, even with
simple classifiers such as disciminant analysis.
