Interleaved dimers and higher order symmetric oligomers are ubiquitous in biology but present a challenge to de novo structure prediction methodology: The structure adopted by a monomer can be stabilized largely by interactions with other monomers and hence not the lowest energy state of a single chain. Building on the Rosetta framework, we present a general method to simultaneously model the folding and docking of multiple-chain interleaved homo-oligomers. For more than a third of the cases in a benchmark set of interleaved homo-oligomers, the method generates near-native models of large ␣-helical bundles, interlocking ␤ sandwiches, and interleaved ␣/␤ motifs with an accuracy high enough for molecular replacement based phasing. With the incorporation of NMR chemical shift information, accurate models can be obtained consistently for symmetric complexes with as many as 192 total amino acids; a blind prediction was within 1 Å rmsd of the traditionally determined NMR structure, and fit independently collected RDC data equally well. Together, these results show that the Rosetta ''fold-and-dock'' protocol can produce models of homo-oligomeric complexes with nearatomic-level accuracy and should be useful for crystallographic phasing and the rapid determination of the structures of multimers with limited NMR information.homo-oligomers ͉ molecular replacement ͉ NMR structure inference ͉ protein structure prediction ͉ symmetry T he majority of expressed proteins function within symmetrical homomeric complexes (1-3). Although a boon for evolving functional diversity (4), this ubiquity of oligomeric structures poses numerous challenges for modern structural biology. The phasing of crystallographic data by molecular replacement and NMR structural inference are complicated by the increasing number of degrees of freedom and spectral degeneracy, respectively, in multimeric systems. The ability to predict de novo the structures of multiple interacting molecular chains would potentially alleviate these problems, allowing unphased diffraction measurements or ambiguously assigned NMR spectra to be resurrected as constraints or as independent validation for in silico structural inference.Accurate modeling of previously unseen homomeric structures has not been demonstrated at high resolution. Significant progress has occurred in modeling the folds of individual monomeric soluble proteins (5-7) and the docking arrangements of predefined monomers (8, 9). However, as proteins interact with other proteins, nucleic acids, or smaller molecules, their lowest free-energy backbone conformations typically shift in response to their partners. These often dramatic structural changes have been a persistent and unsolved issue in blind prediction trials of recent years (8).In this report, we show how two different methods developed for de novo conformational sampling (for folding and for docking) can be melded into a more general procedure that permits the blind prediction of intertwined complexes of proteins at near-atomic resolution. Some of th...

Protein oligomerization serves an important function in biological processes, yet solving structures of protein oligomers has always been a challenge. For solution NMR, the challenge arises both from the increased size of these systems and, in the case of homo-oligomers, from ambiguities in assignment of intra-as opposed to intersubunit NOEs. In this study, we present a residual dipolar coupling (RDC)-assisted method for constructing models of homo-oligomers with purely rotational symmetry. Utilizing the fact that one of the principal axes of the tensor describing the alignment needed for RDC measurement is always parallel to the oligomer symmetry axis, it is possible to greatly restrict possible models for the oligomer. Here, it is shown that, if the monomer structure is known, all allowed dimer models can be constructed using a grid search algorithm and evaluated based on RDC simulations and the quality of the interface between the subunits. Using the Bacillus subtilis protein YkuJ as an example, it is shown that the evaluation criteria based on just two sets of NH RDCs are very selective and can unambiguously produce a model in good agreement with an existing X-ray structure of YkuJ.

A method of identifying the best structural model for a protein of unknown structure from a list of structural candidates using unassigned 15 N-1 H residual dipolar coupling (RDC) data and probability density profile analysis (PDPA) is described. Ten candidate structures have been obtained for the structural genomics target protein PF2048.1 using ROBETTA. 15 N-1 H residual dipolar couplings have been measured from NMR spectra of the protein in two alignment media and these data have been analyzed using PDPA to rank the models in terms of their ability to represent the actual structure.A number of advantages in using this method to characterize a protein structure become apparent. RDCs can easily and rapidly be acquired, and without the need for assignment, the cost and duration of data acquisition is greatly reduced. The approach is quite robust with respect to imprecise and missing data. In the case of PF2048.1, a 79 residue protein, only 58 and 55 of the total RDC data were observed. The method can accelerate structure determination at higher resolution using traditional NMR spectroscopy by providing a starting point for the addition of NOEs and other NMR structural data.

The traditional NMR-based method for determining oligomeric protein structure usually involves distinguishing and assigning intra-and intersubunit NOEs. This task becomes challenging when determining symmetric homo-dimer structures because NOE cross-peaks from a given pair of protons occur at the same position whether intra-or intersubunit in origin. While there are isotope-filtering strategies for distinguishing intra from intermolecular NOE interactions in these cases, they are laborious and often prove ineffectual in cases of weak dimers, where observation of intermolecular NOEs is rare. Here, we present an efficient procedure for weak dimer structure determination based on residual dipolar couplings (RDCs), chemical shift changes upon dilution, and paramagnetic surface perturbations. This procedure is applied to the Northeast Structural Genomics Consortium protein target, SeR13, a negatively charged Staphylococcus epidermidis dimeric protein (K d 3.4 6 1.4 mM) composed of 86 amino acids. A structure determination for the monomeric form using traditional NMR methods is presented, followed by a dimer structure determination using docking under orientation constraints from RDCs data, and scoring under residue pair potentials and shape-based predictions of RDCs. Validation using paramagnetic surface perturbation and chemical shift perturbation data acquired on sample dilution is also presented. The general utility of the dimer structure determination procedure and the possible relevance of SeR13 dimer formation are discussed.

Current state-of-the-art synthetic strategies produce conducting polymers suffering from low processability and unstable chemical and/or physical properties stifling research and development. Here, we introduce a platform for synthesizing scalable submicron-sized particles of the conducting polymer poly­(3,4-ethylenedioxythiophene) (PEDOT). The synthesis is based on a hybrid approach utilizing an aerosol of aqueous oxidant droplets and monomer vapor to engineer a scalable synthetic scheme. This aerosol vapor polymerization technology results in bulk quantities of discrete solid-state submicron particles (750 nm diameter) with the highest reported particle conductivity (330 ± 70 S/cm) so far. Moreover, particles are dispersible in organics and water, obviating the need for surfactants, and remain electrically conductive and doped over a period of months. This enhanced processability and environmental stability enable their incorporation in thermoplastic and cementitious composites for engineering chemoresistive pH and temperature sensors.