A strategy for simultaneous study of the structure and internal dynamics of a membrane protein is described using the REDCRAFT algorithm. The membrane-bound form of the Pf1 major coat protein (mbPf1) was used as an example. First, synthetic data is utilized to validate the simultaneous study of structure and dynamics with REDCRAFT using dihedral restraints and backbone N-H RDCs from two different alignments. Subsequently, the validated analysis is applied to experimental data and confirms that REDCRAFT produces meaningful structures from sparse RDC data. Furthermore, simulated data from a two state jump motion is used to illustrate the necessity for simultaneous consideration of structure and dynamics. Disregarding internal dynamics during the course of structure determination is shown to produce an average-state that is not related to the two intermediate states. During the analysis of RDC data from the dynamic model, REDCRAFT appropriately identifies the region separating the static and dynamic domains of the protein. Finally, analysis of experimental data strongly suggests the existence of internal motion between the amphipathic and the transmembrane helices of the membrane-bound form of the protein. The ability to perform fragmented structure determination of each domain without a priori assumption of the order tensors allows an independent determination of the order tensors, which yields a more comprehensive description of protein structure and dynamics and is particularly relevant to the study of membrane proteins.

Within the past two decades, there has been an increase in the acquisition of residual dipolar couplings (RDC) for investigations of biomolecular structures. Their use however is still not as widely adopted as the traditional methods of structure determination by NMR, despite their potential for extending the limits in studies that examine both the structure and dynamics of biomolecules. This is in part due to the difficulties associated with the analysis of this information-rich data type. The software analysis tool REDCRAFT was previously introduced to address some of these challenges. Here we describe and evaluate a number of additional features that have been incorporated in order to extend its computational and analytical capabilities. REDCRAFT's more traditional enhancements integrate a modified steric collision term, as well as structural refinement in the rotamer space. Other, non-traditional improvements include: the filtering of viable structures based on relative order tensor estimates, decimation of the conformational space based on structural similarity, and forward/reverse folding of proteins. Utilizing REDCRAFT's newest features we demonstrate de-novo folding of proteins 1D3Z and 1P7E to within less than 1.6 Å of the corresponding X-ray structures, using as many as four RDCs per residue and as little as two RDCs per residue, in two alignment media. We also show the successful folding of a structure to less than 1.6 Å of the X-ray structure using {C(i-1)-N(i), N(i)-H(i), and C(i-1)-H(i)} RDCs in one alignment medium, and only {N(i)-H(i)} in the second alignment medium (a set of data which can be collected on deuterated samples). The program is available for download from our website at http://ifestos.cse.sc.edu .

An NMR investigation of proteins with known X-ray structures is of interest in a number of endeavors. Performing these studies through nuclear magnetic resonance (NMR) requires the costly step of resonance assignment. The prevalent assignment strategy does not make use of existing structural information and requires uniform isotope labeling. Here we present a rapid and cost-effective method of assigning NMR data to an existing structure—either an X-ray or computationally modeled structure. The presented method, Exhaustively Permuted Assignment of RDCs (EPAR), utilizes unassigned residual dipolar coupling (RDC) data that can easily be obtained by NMR spectroscopy. The algorithm uses only the backbone N–H RDCs from multiple alignment media along with the amino acid type of the RDCs. It is inspired by previous work from Zweckstetter and provides several extensions. We present results on 13 synthetic and experimental datasets from 8 different structures, including two homodimers. Using just two alignment media, EPAR achieves an average assignment accuracy greater than 80%. With three media, the average accuracy is higher than 94%. The algorithm also outputs a prediction of the assignment accuracy, which has a correlation of 0.77 to the true accuracy. This prediction score can be used to establish the needed confidence in assignment accuracy.

Current protein forcefields like the ones seen in CHARMM or Xplor-NIH have many terms that include bonded and non-bonded terms. Yet the forcefields do not take into account the use of hydrogen bonds which are important for secondary structure creation and stabilization of proteins. SCOPE is an open-source program that generates proteins from rotamer space. It then creates a forcefield that uses only non-bonded and hydrogen bond energy terms to create a profile for a given protein. The profiles can then be used in an artificial neural network to create a linear model which is funneled to the true protein conformation.

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