Many functional proteins do not have well defined folded structures. In recent years, both experimental and computational approaches have been developed to study the conformational behaviour of this type of protein. It has been shown previously that experimental RDCs (residual dipolar couplings) can be used to study the backbone sampling of disordered proteins in some detail. In these studies, the backbone structure was modelled using a common geometry for all amino acids. In the present paper, we demonstrate that experimental RDCs are also sensitive to the specific geometry of each amino acid as defined by energy-minimized internal co-ordinates. We have modified the FM (flexible-Meccano) algorithm that constructs conformational ensembles on the basis of a statistical coil model, to account for these differences. The modified algorithm inherits the advantages of the FM algorithm to efficiently sample the potential energy landscape for coil conformations. The specific geometries incorporated in the new algorithm result in a better reproduction of experimental RDCs and are generally applicable for further studies to characterize the conformational properties of intrinsically disordered proteins. In addition, the internal-co-ordinate-based algorithm is an order of magnitude more efficient, and facilitates side-chain construction, surface osmolyte simulation, spin-label distribution sampling and proline cis/trans isomer simulation.

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