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We discuss a stochastic approach for reconstructing the native structures ofproteins from the knowledge of the "effective connectivity", which is aone-dimensional structural profile constructed as a linear combination of theeigenvectors of the contact map of the target structure. The structural profileis used to bias a search of the conformational space towards the targetstructure in a Monte Carlo scheme operating on a C_alpha-chain of uniform,finite thickness. Structure information thus enters the folding dynamics viathe effective connectivity, but the interaction is not restricted to pairs ofamino acids that form native contacts, resulting in a free energy landscapewhich does not rely on the assumption of minimal frustration. Moreover,effective connectivity vectors can be predicted more readily from the aminoacid sequence of proteins than the corresponding contact maps, thus suggestingthat the stochastic protocol presented here could be effectively combined withother current methods for predicting native structures.

Stochastic reconstruction of protein structures from effective connectivity profiles