Application of the random coil index to studying protein flexibility

Protein flexibility lies at the heart of many protein–ligand binding events and enzymatic activities. However, the experimental measurement of protein motions is often difficult, tedious and error-prone. As a result, there is a considerable interest in developing simpler and faster ways of quantifying protein flexibility. Recently, we described a method, called Random Coil Index (RCI), which appears to be able to quantitatively estimate model-free order parameters and flexibility in protein structural ensembles using only backbone chemical shifts. Because of its potential utility, we have undertaken a more detailed investigation of the RCI method in an attempt to ascertain its underlying principles, its general utility, its sensitivity to chemical shift errors, its sensitivity to data completeness, its applicability to other proteins, and its general strengths and weaknesses. Overall, we find that the RCI method is very robust and that it represents a useful addition to traditional methods of studying protein flexibility. We have implemented many of the findings and refinements reported here into a web server that allows facile, automated predictions of model-free order parameters, MD RMSF and NMR RMSD values directly from backbone ¹H, ¹³C and ¹⁵N chemical shift assignments. The server is available at . Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Comparative analysis of essential collective dynamics and NMR-derived flexibility profiles in evolutionarily diverse prion proteins

Collective motions on ns-µs time scales are known to have a major impact on protein folding, stability, binding and enzymatic efficiency. It is also believed that these motions may have an important role in the early stages of prion protein misfolding and prion disease. In an effort to accurately characterize these motions and their potential influence on the misfolding and prion disease transmissibility we have conducted a combined analysis of molecular dynamic simulations and NMR-derived flexibility measurements over a diverse range of prion proteins. Using a recently developed numerical formalism, we have analyzed the essential collective dynamics (ECD) for prion proteins from eight different species including human, cow, elk, cat, hamster, chicken, turtle and frog. We also compared the numerical results with flexibility profiles generated by the random coil index (RCI) from NMR chemical shifts. Prion protein backbone flexibility derived from experimental NMR data and from theoretical computations show strong agreement with each other, demonstrating that it is possible to predict the observed RCI profiles employing the numerical ECD formalism. Interestingly, flexibility differences in the loop between second b strand (S2) and the second a helix (HB) appear to distinguish prion proteins from species that are susceptible to prion disease and those that are resistant. Our results show that the different levels of flexibility in the S2-HB loop in various species are predictable via the ECD method, indicating that ECD may be used to identify disease resistant variants of prion proteins, as well as the influence of prion proteins mutations on disease susceptibility or misfolding propensity.     

Comparative analysis of essential collective dynamics and NMR-derived flexibility profiles in evolutionarily diverse prion proteins

Collective motions on ns-µs time scales are known to have a major impact on protein folding, stability, binding and enzymatic efficiency. It is also believed that these motions may have an important role in the early stages of prion protein misfolding and prion disease. In an effort to accurately characterize these motions and their potential influence on the misfolding and prion disease transmissibility we have conducted a combined analysis of molecular dynamic simulations and NMR-derived flexibility measurements over a diverse range of prion proteins. Using a recently developed numerical formalism, we have analyzed the essential collective dynamics (ECD) for prion proteins from eight different species including human, cow, elk, cat, hamster, chicken, turtle and frog. We also compared the numerical results with flexibility profiles generated by the random coil index (RCI) from NMR chemical shifts. Prion protein backbone flexibility derived from experimental NMR data and from theoretical computations show strong agreement with each other, demonstrating that it is possible to predict the observed RCI profiles employing the numerical ECD formalism. Interestingly, flexibility differences in the loop between second b strand (S2) and the second a helix (HB) appear to distinguish prion proteins from species that are susceptible to prion disease and those that are resistant. Our results show that the different levels of flexibility in the S2-HB loop in various species are predictable via the ECD method, indicating that ECD may be used to identify disease resistant variants of prion proteins, as well as the influence of prion proteins mutations on disease susceptibility or misfolding propensity.Key words: prion proteins structural stability, molecular dynamics simulation, essential collective dynamics, protein dynamic domains, biomolecular NMR, rigid loop     

De novo protein structure generation from incomplete chemical shift assignments

NMR chemical shifts provide important local structural information for proteins. Consistent structure generation from NMR chemical shift data has recently become feasible for proteins with sizes of up to 130 residues, and such structures are of a quality comparable to those obtained with the standard NMR protocol. This study investigates the influence of the completeness of chemical shift assignments on structures generated from chemical shifts. The Chemical-Shift-Rosetta (CS-Rosetta) protocol was used for de novo protein structure generation with various degrees of completeness of the chemical shift assignment, simulated by omission of entries in the experimental chemical shift data previously used for the initial demonstration of the CS-Rosetta approach. In addition, a new CS-Rosetta protocol is described that improves robustness of the method for proteins with missing or erroneous NMR chemical shift input data. This strategy, which uses traditional Rosetta for pre-filtering of the fragment selection process, is demonstrated for two paramagnetic proteins and also for two proteins with solid-state NMR chemical shift assignments. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A simple and accurate protocol for absolute polar metabolite quantification in cell cultures using quantitative nuclear magnetic resonance

Absolute analyte quantification by nuclear magnetic resonance (NMR) spectroscopy is rarely pursued in metabolomics, even though this would allow researchers to compare results obtained using different techniques. Here we report on a new protocol that permits, after pH-controlled serum protein removal, the sensitive quantification (limit of detection [LOD] = 5−25 μM) of hydrophilic nutrients and metabolites in the extracellular medium of cells in cultures. The method does not require the use of databases and uses PULCON (pulse length-based concentration determination) quantitative NMR to obtain results that are significantly more accurate and reproducible than those obtained by CPMG (Carr–Purcell–Meiboom–Gill) sequence or post-processing filtering approaches. Three practical applications of the method highlight its flexibility under different cell culture conditions. We identified and quantified (i) metabolic differences between genetically engineered human cell lines, (ii) alterations in cellular metabolism induced by differentiation of mouse myoblasts into myotubes, and (iii) metabolic changes caused by activation of neurotransmitter receptors in mouse myoblasts. Thus, the new protocol offers an easily implementable, efficient, and versatile tool for the investigation of cellular metabolism and signal transduction.     

Monte Carlo sampling of near-native structures of proteins with applications

Since a protein's dynamic fluctuation inside cells affects the protein's biological properties, we present a novel method to study the ensemble of near-native structures (NNS) of proteins, namely, the conformations that are very similar to the experimentally determined native structure. We show that this method enables us to (i) quantify the difficulty of predicting a protein's structure, (ii) choose appropriate simplified representations of protein structures, and (iii) assess the effectiveness of knowledge-based potential functions. We found that well-designed simple representations of protein structures are likely as accurate as those more complex ones for certain potential functions. We also found that the widely used contact potential functions stabilize NNS poorly, whereas potential functions incorporating local structure information significantly increase the stability of NNS.     

Resonance assignment of the NMR spectra of disordered proteins using a multi-objective non-dominated sorting genetic algorithm

A multi-objective genetic algorithm is introduced to predict the assignment of protein solid-state NMR (SSNMR) spectra with partial resonance overlap and missing peaks due to broad linewidths, molecular motion, and low sensitivity. This non-dominated sorting genetic algorithm II (NSGA-II) aims to identify all possible assignments that are consistent with the spectra and to compare the relative merit of these assignments. Our approach is modeled after the recently introduced Monte-Carlo simulated-annealing (MC/SA) protocol, with the key difference that NSGA-II simultaneously optimizes multiple assignment objectives instead of searching for possible assignments based on a single composite score. The multiple objectives include maximizing the number of consistently assigned peaks between multiple spectra (“good connections”), maximizing the number of used peaks, minimizing the number of inconsistently assigned peaks between spectra (“bad connections”), and minimizing the number of assigned peaks that have no matching peaks in the other spectra (“edges”). Using six SSNMR protein chemical shift datasets with varying levels of imperfection that was introduced by peak deletion, random chemical shift changes, and manual peak picking of spectra with moderately broad linewidths, we show that the NSGA-II algorithm produces a large number of valid and good assignments rapidly. For high-quality chemical shift peak lists, NSGA-II and MC/SA perform similarly well. However, when the peak lists contain many missing peaks that are uncorrelated between different spectra and have chemical shift deviations between spectra, the modified NSGA-II produces a larger number of valid solutions than MC/SA, and is more effective at distinguishing good from mediocre assignments by avoiding the hazard of suboptimal weighting factors for the various objectives. These two advantages, namely diversity and better evaluation, lead to a higher probability of predicting the correct assignment for a larger number of residues. On the other hand, when there are multiple equally good assignments that are significantly different from each other, the modified NSGA-II is less efficient than MC/SA in finding all the solutions. This problem is solved by a combined NSGA-II/MC algorithm, which appears to have the advantages of both NSGA-II and MC/SA. This combination algorithm is robust for the three most difficult chemical shift datasets examined here and is expected to give the highest-quality de novo assignment of challenging protein NMR spectra.     

Mars - robust automatic backbone assignment of proteins

MARS a program for robust automatic backbone assignment of (13)C/(15)N labeled proteins is presented. MARS does not require tight thresholds for establishing sequential connectivity or detailed adjustment of these thresholds and it can work with a wide variety of NMR experiments. Using only (13)C(alpha)/(13)C(beta) connectivity information, MARS allows automatic, error-free assignment of 96% of the 370-residue maltose-binding protein. MARS can successfully be used when data are missing for a substantial portion of residues or for proteins with very high chemical shift degeneracy such as partially or fully unfolded proteins. Other sources of information, such as residue specific information or known assignments from a homologues protein, can be included into the assignment process. MARS exports its result in SPARKY format. This allows visual validation and integration of automated and manual assignment.     

CAMRA: Chemical shift based computer aided protein NMR assignments

A suite of programs called CAMRA (Computer Aided Magnetic Resonance Assignment) has been developed for computer assisted residue-specific assignments of proteins. CAMRA consists of three units: ORB, CAPTURE and PROCESS. ORB predicts NMR chemical shifts for unassigned proteins using a chemical shift database of previously assigned homologous proteins supplemented by a statistically derived chemical shift database in which the shifts are categorized according to their residue, atom and secondary structure type. CAPTURE generates a list of valid peaks from NMR spectra by filtering out noise peaks and other artifacts and then separating the derived peak list into distinct spin systems. PROCESS combines the chemical shift predictions from ORB with the spin systems identified by CAPTURE to obtain residue specific assignments. PROCESS ranks the top choices for an assignment along with scores and confidence values. In contrast to other auto-assignment programs, CAMRA does not use any connectivity information but instead is based solely on matching predicted shifts with observed spin systems. As such, CAMRA represents a new and unique approach for the assignment of protein NMR spectra. CAMRA will be particularly useful in conjunction with other assignment methods and under special circumstances, such as the assignment of flexible regions in proteins where sufficient NOE information is generally not available. CAMRA was tested on two medium-sized proteins belonging to the chemokine family. It was found to be effective in predicting the assignment providing a database of previously assigned proteins with at least 30% sequence identity is available. CAMRA is versatile and can be used to include and evaluate heteronuclear and three-dimensional experiments.     

A probabilistic approach for validating protein NMR chemical shift assignments

It has been estimated that more than 20% of the proteins in the BMRB are improperly referenced and that about 1% of all chemical shift assignments are mis-assigned. These statistics also reflect the likelihood that any newly assigned protein will have shift assignment or shift referencing errors. The relatively high frequency of these errors continues to be a concern for the biomolecular NMR community. While several programs do exist to detect and/or correct chemical shift mis-referencing or chemical shift mis-assignments, most can only do one, or the other. The one program (SHIFTCOR) that is capable of handling both chemical shift mis-referencing and mis-assignments, requires the 3D structure coordinates of the target protein. Given that chemical shift mis-assignments and chemical shift re-referencing issues should ideally be addressed prior to 3D structure determination, there is a clear need to develop a structure-independent approach. Here, we present a new structure-independent protocol, which is based on using residue-specific and secondary structure-specific chemical shift distributions calculated over small (3–6 residue) fragments to identify mis-assigned resonances. The method is also able to identify and re-reference mis-referenced chemical shift assignments. Comparisons against existing re-referencing or mis-assignment detection programs show that the method is as good or superior to existing approaches. The protocol described here has been implemented into a freely available Java program called “Probabilistic Approach for protein Nmr Assignment Validation (PANAV)” and as a web server () which can be used to validate and/or correct as well as re-reference assigned protein chemical shifts.     

Characterizing the relative orientation and dynamics of RNA A-form helices using NMR residual dipolar couplings

We present a protocol for determining the relative orientation and dynamics of A-form helices in 13C/15N isotopically enriched RNA samples using NMR residual dipolar couplings (RDCs). Non-terminal Watson-Crick base pairs in helical stems are experimentally identified using NOE and trans-hydrogen bond connectivity and modeled using the idealized A-form helix geometry. RDCs measured in the partially aligned RNA are used to compute order tensors describing average alignment of each helix relative to the applied magnetic field. The order tensors are translated into Euler angles defining the average relative orientation of helices and order parameters describing the amplitude and asymmetry of interhelix motions. The protocol does not require complete resonance assignments and therefore can be implemented rapidly to RNAs much larger than those for which complete high-resolution NMR structure determination is feasible. The protocol is particularly valuable for exploring adaptive changes in RNA conformation that occur in response to biologically relevant signals. Following resonance assignments, the procedure is expected to take no more than 2 weeks of acquisition and data analysis time.     

Kaempferol-3-O-glucosyl(1-2)rhamnoside from Ginkgo biloba and a reappraisal of other gluco(1-2, 1-3 and 1-4)rhamnoside structures.

A kaempferol-3-O-glucorhamnoside from Ginkgo biloba is defined as the 3-O-alpha-L-[ beta-D-glucopyranosyl(1-2)rhamnopyranoside] on the basis of 2D NMR evidence. Complete assignments of the 1H and 13C NMR spectra of this compound and of its known p-coumaroyl derivative are presented for the first time. The NMR distinctions of 1-2, 1-3 and 1-4 linked glucopyranosylrhamnopyranosides are discussed and indicate (i) that the 13C NMR assignments for one published gluco(1-3)rhamnoside are in need of modification, (ii) that the published structure of hordenine-O-[6-O-t-cinnamoyl-beta-glucosyl(1-4)-alpha-rhamnoside] from Selaginella doederleinii is not distinguished from the 1-3 linked glucorhamnoside structure, and (iii) that the 8-prenylkaempferol-3-O-[glucosyl(1-4)rhamnoside]-7-O-glucoside and the equivalent 4'-O-methylated xylosyl(1-4)rhamnoside from Epimedium pubescens and E. washanense, respectively, are (1-2)-linked.     

Genetic control of AAF-induced mutagenesis at alternating GC sequences: An additional role for RecA

In a previous study, the forward mutation spectrum induced by the chemical carcinogen N-acetoxy-N-2-acetylaminofluorene was determined (Koffel-Schwartz et al. 1984). It was found that 90% of the induced mutations are frameshift mutations located within specific sequences (mutation hot spots). Two classes of mutation hot spots were found: (i) -1 frameshift mutations occurring within runs of guanines (i.e. GGGG----GGG; (ii) -2 frameshift mutations occurring within the NarI recognition sequence (GGCGCC----GGCC). In the present work, we further investigate the genetic requirements of these frameshift events by using specific reversion assays. Like UV-induced mutagenesis, frameshift mutations occurring within runs of G's (also referred to as the "slippage pathway") require the activated form of the RecA protein (RecA*). On the other hand, frameshift mutations occurring at the NarI site (the "NarI mutation pathway") require a LexA-controlled function(s) that is not UmuDC. The LexA-controlled gene(s) that is (are) involved in this pathway remain to be identified. Moreover, this pathway does not require RecA* for the proteolytic processing of a protein other than LexA (like the cleavage of UmuD in UV-induced mutagenesis). An "additional" role of RecA can be defined as follows: (i) The non-activated form of the RecA protein acts as an inhibitor in the NarI mutation pathway. (ii) This inhibition is relieved upon activation of RecA by UV irradiation of the bacteria. (iii) A recA deletion mutant is totally proficient in the NarI mutation pathway provided the SOS system is derepressed [lexA (Def) allele]. Therefore, RecA does not actively participate in the fixation of the mutation. A molecular model for this "additional" role of RecA is proposed.     

1H, 13C and 15N backbone and side chain resonance assignments of human halo S100A1

As part of our NMR structure determination of the Human S100A1, we report nearly complete NMR chemical shift assignments for the (1)H, (13)C and (15)N nuclei.     

Calculating absolute and relative protein abundance from mass spectrometry-based protein expression data

Mass spectrometry (MS)-based shotgun proteomics allows protein identifications even in complex biological samples. Protein abundances can then be estimated from the counts of tandem MS (MS/MS) spectra attributable to each protein, provided one accounts for differential MS detectability of contributing peptides. We developed a method, APEX, which calculates Absolute Protein EXpression levels based upon learned correction factors, MS/MS spectral counts and each protein's probability of correct identification. This protocol describes APEX-based calculations in three parts. (i) Using training data, peptide sequences and their sequence properties, a model is built to estimate MS detectability (O(i)) for any given protein. (ii) Absolute protein abundances are calculated from spectral counts, identification probabilities and the learned O(i)-values. (iii) Simple statistics allow calculation of differential expression in two distinct biological samples, i.e., measuring relative protein abundances. APEX-based protein abundances span 3-4 orders of magnitude and are applicable to mixtures of 100s to 1,000s of proteins.     

Prospects for resonance assignments in multidimensional solid-state NMR spectra of uniformly labeled proteins

Summary The feasibility of assigning the backbone ¹⁵N and ¹³C NMR chemical shifts in multidimensional magic angle spinning NMR spectra of uniformly isotopically labeled proteins and peptides in unoriented solid samples is assessed by means of numerical simulations. The goal of these simulations is to examine how the upper limit on the size of a peptide for which unique assignments can be made depends on the spectral resolution, i.e., the NMR line widths. Sets of simulated three-dimensional chemical shift correlation spectra for artificial peptides of varying length are constructed from published liquid-state NMR chemical shift data for ubiquitin, a well-characterized soluble protein. Resonance assignments consistent with these spectra to within the assumed spectral resolution are found by a numerical search algorithm. The dependence of the number of consistent assignments on the assumed spectral resolution and on the length of the peptide is reported. If only three-dimensional chemical shift correlation data for backbone ¹⁵N and ¹³C nuclei are used, and no residue-specific chemical shift information, information from amino acid side-chain signals, and proton chemical shift information are available, a spectral resolution of 1 ppm or less is generally required for a unique assignment of backbone chemical shifts for a peptide of 30 amino acid residues.     

Properties of Caulobacter Ribonucleic Acid Bacteriophage φCb5

The ribonucleic acid (RNA) bacteriophage phiCb5, which specifically infects only one form of the dimorphic stalked bacterium Caulobacter crescentus, has been obtained in high yield. Since the phage is extremely salt-sensitive, a purification procedure was devised which avoided contact with solutions of high ionic strength. Phage phiCb5 was studied with respect to the physical and chemical properties of both the phage and its RNA. In an electron microscope, the phage particles appear as small polyhedra, 23 nm in diameter. The phage is similar to the Escherichia coli RNA phages in that it (i) sediments at an S(20, w) of 70.6S, (ii) is composed of a single molecule of single-stranded RNA and a protein coat, (iii) contains two structural proteins, and (iv) apparently contains the genetic capacity to code for a coat protein subunit, a maturation-like protein, and an RNA polymerase. Phage phiCb5 differs from the E. coli RNA phages in (i) host specificity, (ii) salt sensitivity, and (iii) the presence of histidine, but not methionine, in the coat protein.     

A Fast and Accessible Methodology for Micro-Patterning Cells on Standard Culture Substrates Using Parafilm? Inserts

Micropatterning techniques provide direct control over the spatial organization of cells at the sub-mm scale. Regulation of these spatial parameters is important for controlling cell fate and cell function. While micropatterning has proved a powerful technique for understanding the impact of cell organization on cell behaviour, current methods for micropatterning cells require complex, specialized equipment that is not readily accessible in most biological and bioengineering laboratories. In addition, currently available methods require significant protocol optimization to ensure reliable and reproducible patterning. The inaccessibility of current methods has severely limited the widespread use of micropatterning as a tool in both biology and tissue engineering laboratories. Here we present a simple, cheap, and fast method to micropattern mammalian cells into stripes and circular patterns using Parafilm™, a common material found in most biology and bioengineering laboratories. Our method does not require any specialized equipment and does not require significant method optimization to ensure reproducible patterning. Although our method is limited to simple patterns, these geometries are sufficient for addressing a wide range of biological problems. Specifically, we demonstrate i) that using our Parafilm™ insert method we can pattern and co-pattern ARPE-19 and MDCK epithelial cells into circular and stripe micropatterns in tissue culture polystyrene (TCPS) wells and on glass slides, ii) that we can contain cells in the desired patterns for more than one month and iii) that upon removal of the Parafilm™ insert we can release the cells from the containment pattern and allow cell migration outward from the original pattern. We also demonstrate that we can exploit this confinement release feature to conduct an epithelial cell wound healing assay. This novel micropatterning method provides a reliable and accessible tool with the flexibility to address a wide range of biological and engineering problems that require control over the spatial and temporal organization of cells.     

A fast and accessible methodology for micro-patterning cells on standard culture substrates using Parafilm™ inserts

Micropatterning techniques provide direct control over the spatial organization of cells at the sub-mm scale. Regulation of these spatial parameters is important for controlling cell fate and cell function. While micropatterning has proved a powerful technique for understanding the impact of cell organization on cell behaviour, current methods for micropatterning cells require complex, specialized equipment that is not readily accessible in most biological and bioengineering laboratories. In addition, currently available methods require significant protocol optimization to ensure reliable and reproducible patterning. The inaccessibility of current methods has severely limited the widespread use of micropatterning as a tool in both biology and tissue engineering laboratories. Here we present a simple, cheap, and fast method to micropattern mammalian cells into stripes and circular patterns using Parafilm?, a common material found in most biology and bioengineering laboratories. Our method does not require any specialized equipment and does not require significant method optimization to ensure reproducible patterning. Although our method is limited to simple patterns, these geometries are sufficient for addressing a wide range of biological problems. Specifically, we demonstrate i) that using our Parafilm? insert method we can pattern and co-pattern ARPE-19 and MDCK epithelial cells into circular and stripe micropatterns in tissue culture polystyrene (TCPS) wells and on glass slides, ii) that we can contain cells in the desired patterns for more than one month and iii) that upon removal of the Parafilm? insert we can release the cells from the containment pattern and allow cell migration outward from the original pattern. We also demonstrate that we can exploit this confinement release feature to conduct an epithelial cell wound healing assay. This novel micropatterning method provides a reliable and accessible tool with the flexibility to address a wide range of biological and engineering problems that require control over the spatial and temporal organization of cells.