Roberto Tejero

Evaluating Protein Structures Determined by Structural Genomics Consortia

Structural genomics projects are providing large quantities of new 3D structural data for proteins. To monitor the quality of these data, we have developed the protein structure validation software suite (PSVS), for assessment of protein structures generated by NMR or X‐ray crystallographic methods. PSVS is broadly applicable for structure quality assessment in structural biology projects. The software integrates under a single interface analyses from several widely‐used structure quality evaluation tools, including PROCHECK (Laskowski et al., J Appl Crystallog 1993;26:283–291), MolProbity (Lovell et al., Proteins 2003;50:437–450), Verify3D (Luthy et al., Nature 1992;356:83–85), ProsaII (Sippl, Proteins 1993;17: 355–362), the PDB validation software, and various structure‐validation tools developed in our own laboratory. PSVS provides standard constraint analyses, statistics on goodness‐of‐fit between structures and experimental data, and knowledge‐based structure quality scores in standardized format suitable for database integration. The analysis provides both global and site‐specific measures of protein structure quality. Global quality measures are reported as Z scores, based on calibration with a set of high‐resolution X‐ray crystal structures. PSVS is particularly useful in assessing protein structures determined by NMR methods, but is also valuable for assessing X‐ray crystal structures or homology models. Using these tools, we assessed protein structures generated by the Northeast Structural Genomics Consortium and other international structural genomics projects, over a 5‐year period. Protein structures produced from structural genomics projects exhibit quality score distributions similar to those of structures produced in traditional structural biology projects during the same time period. However, while some NMR structures have structure quality scores similar to those seen in higher‐resolution X‐ray crystal structures, the majority of NMR structures have lower scores. Potential reasons for this “structure quality score gap” between NMR and X‐ray crystal structures are discussed. Proteins 2007.

An Integrated Platform for Automated Analysis of Protein NMR Structures

Recent developments provide automated analysis of NMR assignments and three-dimensional (3D) structures of proteins. These approaches are generally applicable to proteins ranging from about 50 to 150 amino acids. In this chapter, we summarize progress by the Northeast Structural Genomics Consortium in standardizing the NMR data collection process for protein structure determination and in building an integrated platform for automated protein NMR structure analysis. Our integrated platform includes the following principal steps: (1) standardized NMR data collection, (2) standardized data processing (including spectral referencing and Fourier transformation), (3) automated peak picking and peak list editing, (4) automated analysis of resonance assignments, (5) automated analysis of NOESY data together with 3D structure determination, and (6) methods for protein structure validation. In particular, the software AutoStructure for automated NOESY data analysis is described in this chapter, together with a discussion of practical considerations for its use in high-throughput structure production efforts. The critical area of data quality assessment has evolved significantly over the past few years and involves evaluation of both intermediate and final peak lists, resonance assignments, and structural information derived from the NMR data. Methods for quality control of each of the major automated analysis steps in our platform are also discussed. Despite significant remaining challenges, when good quality data are available, automated analysis of protein NMR assignments and structures with this platform is both fast and reliable.

Assessing model accuracy using the homology modeling automatically software.

Homology modeling is a powerful technique that greatly increases the value of experimental structure determination by using the structural information of one protein to predict the structures of homologous proteins. We have previously described a method of homology modeling by satisfaction of spatial restraints (Li et al., Protein Sci 1997;6:956–970). The Homology Modeling Automatically (HOMA) web site, , is a new tool, using this method to predict 3D structure of a target protein based on the sequence alignment of the target protein to a template protein and the structure coordinates of the template. The user is presented with the resulting models, together with an extensive structure validation report providing critical assessments of the quality of the resulting homology models. The homology modeling method employed by HOMA was assessed and validated using twenty‐four groups of homologous proteins. Using HOMA, homology models were generated for 510 proteins, including 264 proteins modeled with correct folds and 246 modeled with incorrect folds. Accuracies of these models were assessed by superimposition on the corresponding experimentally determined structures. A subset of these results was compared with parallel studies of modeling accuracy using several other automated homology modeling approaches. Overall, HOMA provides prediction accuracies similar to other state‐of‐the‐art homology modeling methods. We also provide an evaluation of several structure quality validation tools in assessing the accuracy of homology models generated with HOMA. This study demonstrates that Verify3D (Luthy et al., Nature 1992;356:83–85) and ProsaII (Sippl, Proteins 1993;17:355–362) are most sensitive in distinguishing between homology models with correct or incorrect folds. For homology models that have the correct fold, the steric conformational energy (including primarily the Van der Waals energy), MolProbity clashscore (Word et al., Protein Sci 2000;9:2251–2259), and the PROCHECK G‐factors (Laskowski et al., J Biomol NMR 1996;8:477–486) provide sensitive and consistent methods for assessing accuracy and can distinguish between homology models of higher and lower accuracy. As demonstrated in the accompanying paper (Bhattacharya et al., accompanying paper), combinations of these scores for models generated with HOMA provide a basis for distinguishing low from high accuracy models. Proteins 2008.

Construct optimization for protein NMR structure analysis using amide hydrogen/deuterium exchange mass spectrometry

Disordered or unstructured regions of proteins, while often very important biologically, can pose significant challenges for resonance assignment and three‐dimensional structure determination of the ordered regions of proteins by NMR methods. In this article, we demonstrate the application of 1H/2H exchange mass spectrometry (DXMS) for the rapid identification of disordered segments of proteins and design of protein constructs that are more suitable for structural analysis by NMR. In this benchmark study, DXMS is applied to five NMR protein targets chosen from the Northeast Structural Genomics project. These data were then used to design optimized constructs for three partially disordered proteins. Truncated proteins obtained by deletion of disordered N‐ and C‐terminal tails were evaluated using 1H‐15N HSQC and 1H‐15N heteronuclear NOE NMR experiments to assess their structural integrity. These constructs provide significantly improved NMR spectra, with minimal structural perturbations to the ordered regions of the protein structure. As a representative example, we compare the solution structures of the full length and DXMS‐based truncated construct for a 77‐residue partially disordered DUF896 family protein YnzC from Bacillus subtilis, where deletion of the disordered residues (ca. 40% of the protein) does not affect the native structure. In addition, we demonstrate that throughput of the DXMS process can be increased by analyzing mixtures of up to four proteins without reducing the sequence coverage for each protein. Our results demonstrate that DXMS can serve as a central component of a process for optimizing protein constructs for NMR structure determination. Proteins 2009.

Protein NMR Structures Refined with Rosetta Have Higher Accuracy Relative to Corresponding X‑ray Crystal Structures

We have found that refinement of protein NMR structures using Rosetta with experimental NMR restraints yields more accurate protein NMR structures than those that have been deposited in the PDB using standard refinement protocols. Using 40 pairs of NMR and X-ray crystal structures determined by the Northeast Structural Genomics Consortium, for proteins ranging in size from 5–22 kDa, restrained Rosetta refined structures fit better to the raw experimental data, are in better agreement with their X-ray counterparts, and have better phasing power compared to conventionally determined NMR structures. For 37 proteins for which NMR ensembles were available and which had similar structures in solution and in the crystal, all of the restrained Rosetta refined NMR structures were sufficiently accurate to be used for solving the corresponding X-ray crystal structures by molecular replacement. The protocol for restrained refinement of protein NMR structures was also compared with restrained CS-Rosetta calculations. For proteins smaller than 10 kDa, restrained CS-Rosetta, starting from extended conformations, provides slightly more accurate structures, while for proteins in the size range of 10–25 kDa the less CPU intensive restrained Rosetta refinement protocols provided equally or more accurate structures. The restrained Rosetta protocols described here can improve the accuracy of protein NMR structures and should find broad and general for studies of protein structure and function.

PDBStat: a universal restraint converter and restraint analysis software package for protein NMR.

The heterogeneous array of software tools used in the process of protein NMR structure determination presents organizational challenges in the structure determination and validation processes, and creates a learning curve that limits the broader use of protein NMR in biology. These challenges, including accurate use of data in different data formats required by software carrying out similar tasks, continue to confound the efforts of novices and experts alike. These important issues need to be addressed robustly in order to standardize protein NMR structure determination and validation. PDBStat is a C/C++ computer program originally developed as a universal coordinate and protein NMR restraint converter. Its primary function is to provide a user-friendly tool for interconverting between protein coordinate and protein NMR restraint data formats. It also provides an integrated set of computational methods for protein NMR restraint analysis and structure quality assessment, relabeling of prochiral atoms with correct IUPAC names, as well as multiple methods for analysis of the consistency of atomic positions indicated by their convergence across a protein NMR ensemble. In this paper we provide a detailed description of the PDBStat software, and highlight some of its valuable computational capabilities. As an example, we demonstrate the use of the PDBStat restraint converter for restrained CS-Rosetta structure generation calculations, and compare the resulting protein NMR structure models with those generated from the same NMR restraint data using more traditional structure determination methods. These results demonstrate the value of a universal restraint converter in allowing the use of multiple structure generation methods with the same restraint data for consensus analysis of protein NMR structures and the underlying restraint data.

Ternary interaction parameters in n-hexane/butanone (MEK)/poly(dimethylsiloxane) (PDMS) and n-heptane/MEK/PDMS systems

Abstract Second virial coefficients, A2, intrinsic viscosities, [η], and solvation preferential coefficients, γ, for the ternary systems n-hexane, HEX, (1)/butanone, MEK, (2)/poly(dimethylsiloxane), PDMS, (3) and n-heptane, HEP, (1)/MEK (2)/PDMS (3) have been determined at 20.0°. Binary interaction parameters, g2, have also been measured by light scattering. Inversion in γ at u 2 ⋍ 0.15 in the HEX system and at u 2 ⋍ 0.22 in the HEP system takes place. The inversion points are accompanied by smooth maxima in A2 and in [η]. Both systems show a weak cosolvent character. Theoretical γs derived, according to Flory-Huggins and Flory-Prigogine-Patterson, are compared with experimental values. The evaluation of the ternary interaction potential, gT, and its dependence on system composition allow evaluation of the binary interaction potentials and their dependence on polymer concentration.

Quality assessment of protein NMR structures.

Biomolecular NMR structures are now routinely used in biology, chemistry, and bioinformatics. Methods and metrics for assessing the accuracy and precision of protein NMR structures are beginning to be standardized across the biological NMR community. These include both knowledge-based assessment metrics, parameterized from the database of protein structures, and model versus data assessment metrics. On line servers are available that provide comprehensive protein structure quality assessment reports, and efforts are in progress by the world-wide Protein Data Bank (wwPDB) to develop a biomolecular NMR structure quality assessment pipeline as part of the structure deposition process. These quality assessment metrics and standards will aid NMR spectroscopists in determining more accurate structures, and increase the value and utility of these structures for the broad scientific community.

Cosolvency in n-alkane-butanone-poly(dimethylsiloxane) systems

Abstract Second virial (A2) and preferential solvation (λ) coefficients, as well as binary interaction potential (g12), as measured by light scattering, for the system n-decane (1)-butanone (MEK) (2)-poly(dimethylsiloxane) (PDMS) (3) have been determined at 20°. The system displays cosolvency, as the inversion in λ and the maximum in A2 at φ 10 ⋍ 0.65 seem to indicate. ΔAmax2, defined as the difference between the “real” and “ideal” A2 values at the solvent mixture composition in which A2 attains its maximum value, is proposed as the most adequate parameter to define quantitatively the cosolvency degree in a ternary system. Theoretical ΔAmax2 values, as calculated through the Flory-Huggins (FH) formalism and the Pouchly generalized formalism (FHP), are compared to experimental values for diverse n-alkane-MEK-PDMS systems. Poor agreement is obtained between the sets of data if ternary interactions are neglected. Moreoever, through ax, the parameter correlating A2 experimental data, excess free energies for the solvent mixtures n-alkane-MEK are evaluated and also compared with fair agreement with the corresponding experimental values.

A model accounting for concentration effects in exclusion chromatography

Abstract A model has been developed that gives a quantitative description for the dependence of the elution volume, Ve, on the concentration of injected solute, c, in exclusion chromatography (SEC). The concentration-dependent shrinkage of coils has been evaluated from the intrinsic viscosity displayed by a polymer in a binary dilute solution formed by itself (at c concentration) and the eluent. In the derived equation, concentration effects are mainly governed by the Huggins coefficient, kH, which includes hydrodynamic as well as thermodynamic interactions. Comparisons of predicted and experimental elution volumes for diverse literature polymer/eluent/gel systems show that the model quantitatively correctly describes the dependences of concentration effects on polymer molecular weight and on thermodynamic quality of eluent.