Homayoun Valafar

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.

Rapid classification of a protein fold family using a statistical analysis of dipolar couplings

MOTIVATION One of the primary aims of the structural genomics initiative is the determination of representative structures from each protein fold family. Given this objective, it is important to rapidly identify proteins that belong to a family that is already well populated (so they can be eliminated from further studies), or more importantly identify proteins that represent new families of fold. RESULTS A method for rapid classification to a fold family by the statistical analyses of unassigned the (15)N-(1)H residual dipolar couplings is presented. The required NMR data can be quickly acquired and analyzed. Using this method, structure determination efforts can be focused on more unique and interesting structures, and the overall efficiency in the construction of an information-rich library can be increased.

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.

REDCRAFT: a tool for simultaneous characterization of protein backbone structure and motion from RDC data.

REDCRAFT, a new open source software tool that accommodates the analysis of RDC data for simultaneous structure and dynamics characterization of proteins is presented in this article. Simultaneous consideration of structure and motion is believed to be necessary for accurate representation of the solution-state of a protein. REDCRAFT is designed to primarily utilize RDC data from multiple alignment media in two stages. During Stage-I, a list of possible torsion angles joining any two neighboring peptide planes is ranked based on their fitness to experimental constraints; in Stage-II, a dipeptide fragment is extended by addition of one peptide plane at a time. The algorithm adopted by REDCRAFT is very efficient and can produce a structure for an 80 residue protein within two hours on a typical desktop computer. REDCRAFT exhibits robustness with respect to noise and missing data. REDCRAFT describes the overall alignment of the molecule in the form of an order tensor matrix and is capable of identifying peptide fragments with internal dynamics. Identification of the location of internal motion will permit a more accurate structural representation. Experimental data from two proteins as well as simulated data are presented to illustrate the capabilities of REDCRAFT in both structure determination and identification of the dynamical regions.

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 Students 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 patients 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.

Phage-induced alignment of membrane proteins enables the measurement and structural analysis of residual dipolar couplings with dipolar waves and lambda-maps.

At pH > 6 added filamentous bacteriophage fd is compatible with many of the detergents used to solubilize membrane proteins for solution NMR studies of membrane proteins and, therefore, serves as an alignment media. In combination with strained polyacrylamide gel alignment, Dipolar Waves can be used to directly assess the secondary structure and a lambda-map extracts the order tensors for de novo structure calculation of membrane proteins without distance restraints.

TALI: LOCAL ALIGNMENT OF PROTEIN STRUCTURES USING BACKBONE TORSION ANGLES

UNLABELLED Torsion angle alignment (TALI) is a novel approach to local structural motif alignment, based on backbone torsion angles (phi, psi) rather than the more traditional atomic distance matrices. Representation of a protein structure in the form of a sequence of torsion angles enables easy integration of sequence and structural information, and adopts mature techniques in sequence alignment to improve performance and alignment quality. We show that TALI is able to match local structural motifs as well as identify global structural similarity. TALI is also compared to other structure alignment methods such as DALI, CE, and SSM, as well as sequence alignment based on PSI-BLAST; TALI is shown to be equally successful as, or more successful than, these other methods when applied to challenging structural alignments. The inference of the evolutionary tree of class II aminoacyl-tRNA synthetase shows the potential for TALI in estimating protein structural evolution and in identifying structural divergence among homologous structures. AVAILABILITY http://redcat.cse.sc.edu/index.php/ PROJECT TALI/.

Estimation of relative order tensors, and reconstruction of vectors in space using unassigned RDC data and its application

Advances in NMR instrumentation and pulse sequence design have resulted in easier acquisition of Residual Dipolar Coupling (RDC) data. However, computational and theoretical analysis of this type of data has continued to challenge the international community of investigators because of their complexity and rich information content. Contemporary use of RDC data has required a-priori assignment, which significantly increases the overall cost of structural analysis. This article introduces a novel algorithm that utilizes unassigned RDC data acquired from multiple alignment media (nD-RDC, n3) for simultaneous extraction of the relative order tensor matrices and reconstruction of the interacting vectors in space. Estimation of the relative order tensors and reconstruction of the interacting vectors can be invaluable in a number of endeavors. An example application has been presented where the reconstructed vectors have been used to quantify the fitness of a template protein structure to the unknown protein structure. This work has other important direct applications such as verification of the novelty of an unknown protein and validation of the accuracy of an available protein structure model in drug design. More importantly, the presented work has the potential to bridge the gap between experimental and computational methods of structure determination.

Efficient and accurate estimation of relative order tensors from λ-maps

The rapid increase in the availability of RDC data from multiple alignment media in recent years has necessitated the development of more sophisticated analyses that extract the RDC datas full information content. This article presents an analysis of the distribution of RDCs from two media (2D-RDC data), using the information obtained from a lambda-map. This article also introduces an efficient algorithm, which leverages these findings to extract the order tensors for each alignment medium using unassigned RDC data in the absence of any structural information. The results of applying this 2D-RDC analysis method to synthetic and experimental data are reported in this article. The relative order tensor estimates obtained from the 2D-RDC analysis are compared to order tensors obtained from the program REDCAT after using assignment and structural information. The final comparisons indicate that the relative order tensors estimated from the unassigned 2D-RDC method very closely match the results from methods that require assignment and structural information. The presented method is successful even in cases with small datasets. The results of analyzing experimental RDC data for the protein 1P7E are presented to demonstrate the potential of the presented work in accurately estimating the principal order parameters from RDC data that incompletely sample the RDC space. In addition to the new algorithm, a discussion of the uniqueness of the solutions is presented; no more than two clusters of distinct solutions have been shown to satisfy each lambda-map.

Multiple structure alignment with msTALI.

BackgroundMultiple structure alignments have received increasing attention in recent years as an alternative to multiple sequence alignments. Although multiple structure alignment algorithms can potentially be applied to a number of problems, they have primarily been used for protein core identification. A method that is capable of solving a variety of problems using structure comparison is still absent. Here we introduce a program msTALI for aligning multiple protein structures. Our algorithm uses several informative features to guide its alignments: torsion angles, backbone Cα atom positions, secondary structure, residue type, surface accessibility, and properties of nearby atoms. The algorithm allows the user to weight the types of information used to generate the alignment, which expands its utility to a wide variety of problems.ResultsmsTALI exhibits competitive results on 824 families from the Homstrad and SABmark databases when compared to Matt and Mustang. We also demonstrate success at building a database of protein cores using 341 randomly selected CATH domains and highlight the contribution of msTALI compared to the CATH classifications. Finally, we present an example applying msTALI to the problem of detecting hinges in a protein undergoing rigid-body motion.ConclusionsmsTALI is an effective algorithm for multiple structure alignment. In addition to its performance on standard comparison databases, it utilizes clear, informative features, allowing further customization for domain-specific applications. The C++ source code for msTALI is available for Linux on the web athttp://ifestos.cse.sc.edu/mstali.