Determination of protein backbone structures from residual dipolar couplings.

There are a number of circumstances in which a focus on determination of the backbone structure of a protein, as opposed to a complete all-atom structure, may be appropriate. This is particularly the case for structures determined as a part of a structural genomics initiative in which computational modeling of many sequentially related structures from the backbone of a single family representative is anticipated. It is, however, also the case when the backbone may be a stepping-stone to more targeted studies of ligand interaction or protein-protein interaction. Here an NMR protocol is described that can produce a backbone structure of a protein without the need for extensive experiments directed at side chain resonance assignment or the collection of structural information on side chains. The procedure relies primarily on orientational constraints from residual dipolar couplings as opposed to distance constraints from NOEs. Procedures for sample preparation, data acquisition, and data analysis are described, along with examples from application to small target proteins of a structural genomics project.

Backbone solution structures of proteins using residual dipolar couplings: application to a novel structural genomics target.

Structural genomics (or proteomics) activities are critically dependent on the availability of high-throughput structure determination methodology. Development of such methodology has been a particular challenge for NMR based structure determination because of the demands for isotopic labeling of proteins and the requirements for very long data acquisition times. We present here a methodology that gains efficiency from a focus on determination of backbone structures of proteins as opposed to full structures with all sidechains in place. This focus is appropriate given the presumption that many protein structures in the future will be built using computational methods that start from representative fold family structures and replace as many as 70% of the sidechains in the course of structure determination. The methodology we present is based primarily on residual dipolar couplings (RDCs), readily accessible NMR observables that constrain the orientation of backbone fragments irrespective of separation in space. A new software tool is described for the assembly of backbone fragments under RDC constraints and an application to a structural genomics target is presented. The target is an 8.7 kDa protein from Pyrococcus furiosus, PF1061, that was previously not well annotated, and had a nearest structurally characterized neighbor with only 33% sequence identity. The structure produced shows structural similarity to this sequence homologue, but also shows similarity to other proteins, which suggests a functional role in sulfur transfer. Given the backbone structure and a possible functional link this should be an ideal target for development of modeling methods.

A dipolar coupling based strategy for simultaneous resonance assignment and structure determination of protein backbones.

A new approach for simultaneous protein backbone resonance assignment and structure determination by NMR is introduced. This approach relies on recent advances in high-resolution NMR spectroscopy that allow observation of anisotropic interactions, such as dipolar couplings, from proteins partially aligned in field ordered media. Residual dipolar couplings are used for both geometric information and a filter in the assembly of residues in a sequential manner. Experimental data were collected in less than one week on a small redox protein, rubredoxin, that was 15N enriched but not enriched above 1% natural abundance in 13C. Given the acceleration possible with partial 13C enrichment, the protocol described should provide a very rapid route to protein structure determination. This is critical for the structural genomics initiative where protein expression and structural determination in a high-throughput manner will be needed.

Nuclear magnetic resonance in the era of structural genomics.

Current interests in structural genomics, and the associated need for high through-put structure determination methods, offer an opportunity to examine new nuclear magnetic resonance (NMR) methodology and the impact this methodology can have on structure determination of proteins. The time required for structure determination by traditional NMR methods is currently long, but improved hardware, automation of analysis, and new sources of data such as residual dipolar couplings promise to change this. Greatly improved efficiency, coupled with an ability to characterize proteins that may not produce crystals suitable for investigation by X-ray diffraction, suggests that NMR will play an important role in structural genomics programs.

Variation of molecular alignment as a means of resolving orientational ambiguities in protein structures from dipolar couplings.

Residual dipolar couplings for pairs of proximate magnetic nuclei in macromolecules can easily be measured using high-resolution NMR methods when the molecules are dissolved in dilute liquid crystalline media. The resulting couplings can in principle be used to constrain the relative orientation of molecular fragments in macromolecular systems to build a complete structure. However, determination of relative fragment orientations based on a single set of residual dipolar couplings is inherently hindered by the multi-valued nature of the angular dependence of the dipolar interaction. Even with unlimited dipolar data, this gives rise to a fourfold degeneracy in fragment orientations. In this Communication, we demonstrate a procedure based on an order tensor analysis that completely removes this degeneracy by combining residual dipolar coupling measurements from two alignment media. Application is demonstrated on (15)N-(1)H residual dipolar coupling data acquired on the protein zinc rubredoxin from Clostridium pasteurianum dissolved in two different bicelle media.

Predicting the effectiveness of hydroxyurea in individual sickle cell anemia patients.

The study described in this paper was undertaken to develop the ability to predict the response of sickle-cell patients to hydroxyurea (HU) therapy. We analyzed the effect of HU on the values of 23 parameters of 83 patients. A Student's t-test was used to confirm (Rodgers GP, Dover GJ, Noguchi CT, Schechter AN, Nienhuis AW. Hematologic responses of patients with sickle cell disease to treatment with hydroxyurea, N Engl J Med 1990;322;1037-44) at the 0. 001 level that treatment with HU increases the proportion of fetal hemoglobin (HbF), and the average corpuscular volume (MCV) of the red blood cells. Correlation analysis failed to establish a statistically significant relationship between any of the 23 parameters and the HbF response. Linear regression analysis also failed to predict a patient's response to HU. On the other hand, artificial neural network (ANN) pattern-recognition analysis of the 23 parameters predicts, with 86.6% accuracy, those patients that respond positively to HU and those that do not. Furthermore, we have found that the values of only 10 of the 23 parameters (listed in the body of this paper) are sufficient to train ANNs to predict which patients will respond to HU.

Cryptococcus neoformans chemotyping by quantitative analysis of 1H nuclear magnetic resonance spectra of glucuronoxylomannans with a computer-simulated artificial neural network.

The complete assignment of the proton chemical shifts obtained by nuclear magnetic resonance (NMR) spectroscopy of de-O-acetylated glucuronoxylomannans (GXMs) from Cryptococcus neoformans permitted the high-resolution determination of the total structure of any GXM. Six structural motifs based on an alpha-(1-->3)-mannotriose substituted with variable quantities of 2-O-beta- and 4-O-beta-xylopyranosyl and 2-O-beta-glucopyranosyluronic acid were identified. The chemical shifts of only the anomeric protons of the mannosyl residues served as structure reporter groups (SRG) for the identification and quantitation of the six triads present in any GXM. The assigned protons for the mannosyl residues resonated at clearly distinguishable positions in the spectrum and supplied all the information essential for the assignment of the complete GXM structure. This technique for assigning structure is referred to as the SRG concept. The SRG concept was used to analyze the distribution of the six mannosyl triads of GXMs obtained from 106 isolates of C. neoformans. The six mannosyl triads occurred singularly or in combination with one or more of the other triads. The identification and quantitation of the SRG were simplified by using a computer-simulated artificial neural network (ANN) to automatically analyze the SRG region of the one-dimensional proton NMR spectra. The occurrence and relative distribution of the six mannosyl triads were used to chemotype C. neoformans on the basis of subtle variations in GXM structure determined by analysis of the SRG region of the proton NMR spectrum by the ANN. The data for the distribution of the six SRGs from GXMs of 106 isolates of C. neoformans yielded eight chemotypes, Chem1 through Chem8.