A reference database for circular dichroism spectroscopy covering fold and secondary structure space

MOTIVATION: Circular Dichroism (CD) spectroscopy is a long-established technique for studying protein secondary structures in solution. Empirical analyses of CD data rely on the availability of reference datasets comprised of far-UV CD spectra of proteins whose crystal structures have been determined. This article reports on the creation of a new reference dataset which effectively covers both secondary structure and fold space, and uses the higher information content available in synchrotron radiation circular dichroism (SRCD) spectra to more accurately predict secondary structure than has been possible with existing reference datasets. It also examines the effects of wavelength range, structural redundancy and different means of categorizing secondary structures on the accuracy of the analyses. In addition, it describes a novel use of hierarchical cluster analyses to identify protein relatedness based on spectral properties alone. The databases are shown to be applicable in both conventional CD and SRCD spectroscopic analyses of proteins. Hence, by combining new bioinformatics and biophysical methods, a database has been produced that should have wide applicability as a tool for structural molecular biology.     

Evaluating protein:protein complex formation using synchrotron radiation circular dichroism spectroscopy

Circular dichroism (CD) spectroscopy beamlines at synchrotrons produce dramatically higher light flux than conventional CD instruments. This property of synchrotron radiation circular dichroism (SRCD) results in improved signal-to-noise ratios and allows data collection to lower wavelengths, characteristics that have led to the development of novel SRCD applications. Here we describe the use of SRCD to study protein complex formation, specifically evaluating the complex formed between carboxypeptidase A and its protein inhibitor latexin. Crystal structure analyses of this complex and the individual proteins reveal only minor changes in secondary structure of either protein upon complex formation (i.e., it involves only rigid body interactions). Conventional CD spectroscopy reports on changes in secondary structure and would therefore not be expected to be sensitive to such interactions. However, in this study we have shown that SRCD can identify differences in the vacuum ultraviolet CD spectra that are significant and attributable to complex formation.     

Protein secondary structure analyses from circular dichroism spectroscopy: methods and reference databases

Circular dichroism (CD) spectroscopy has been a valuable method for the analysis of protein secondary structures for many years. With the advent of synchrotron radiation circular dichroism (SRCD) and improvements in instrumentation for conventional CD, lower wavelength data are obtainable and the information content of the spectra increased. In addition, new computation and bioinformatics methods have been developed and new reference databases have been created, which greatly improve and facilitate the analyses of CD spectra. This article discusses recent developments in the analysis of protein secondary structures, including features of the DICHROWEB analysis webserver.     

Combining sequence-based prediction methods and circular dichroism and infrared spectroscopic data to improve protein secondary structure determinations

Background  

A number of sequence-based methods exist for protein secondary structure prediction. Protein secondary structures can also be determined experimentally from circular dichroism, and infrared spectroscopic data using empirical analysis methods. It has been proposed that comparable accuracy can be obtained from sequence-based predictions as from these biophysical measurements. Here we have examined the secondary structure determination accuracies of sequence prediction methods with the empirically determined values from the spectroscopic data on datasets of proteins for which both crystal structures and spectroscopic data are available.     

DICHROWEB: an interactive website for the analysis of protein secondary structure from circular dichroism spectra

A user-friendly website for the analysis of protein secondary structures from Circular Dichroism (CD) and Synchrotron Radiation Circular Dichroism (SRCD) spectra has been created.     

Going deep into protein secondary structure with synchrotron radiation circular dichroism spectroscopy

Circular dichroism (CD) spectroscopy is a fast, powerful, well-established, and widely used analytical technique in the biophysical and structural biology community to study protein secondary structure and to track changes in protein conformation in different environments. The use of the intense light of a synchrotron beam as the light source for collecting CD measurements has emerged as an enhanced method, known as synchrotron radiation circular dichroism (SRCD) spectroscopy, that has several advantages over the conventional CD method, including a significant spectral range extension for data collection, deeper access to the lower limit (cut-off) of conventional CD spectroscopy, an improved signal-to-noise ratio to increase accuracy in the measurements, and the possibility to collect measurements in highly absorbing solutions. In this review, we discuss different applications of the SRCD technique by researchers from Latin America. In this context, we specifically look at the use of this method for examining the secondary structure and conformational behavior of proteins belonging to the four main classes of the hierarchical protein domain classification CATH (Class, Architecture, Topology, Homology) database, focusing on the advantages and improvements associated with SRCD spectroscopy in terms of characterizing proteins composed of different structural elements.     

Tripeptide analysis of protein structures

Background  

An efficient building block for protein structure prediction can be tripeptides. 8000 different tripeptides from a dataset of 1220 high resolution (≤ 2.0°A) structures from the Protein Data Bank (PDB) have been looked at, to determine which are structurally rigid and non-rigid. This data has been statistically analyzed, discussed and summarized. The entire data can be utilized for the building of protein structures.     

Circular dichroism studies of low molecular weight hydrogelators: The use of SRCD and addressing practical issues

Circular dichroism (CD) spectroscopy has been used extensively for the investigation of the conformation and configuration of chiral molecules, but its use for evaluating the mode of self‐assembly in soft materials has been limited. Herein, we report a protocol for the study of such materials by electronic CD spectroscopy using commercial/benchtop instruments and synchrotron radiation (SR) using the B23 beamline available at Diamond Light Source. The use of the B23 beamtime for SRCD was advantageous because of the unique enhanced spatial resolution achieved because of its highly collimated and small beamlight cross section (ca. 250 μm) and higher photon flux in the far UV region (175‐250 nm) enhancing the signal‐to‐noise ratio relative to benchtop CD instruments. A set of low molecular weight (LMW) hydrogelators, comprising two Fmoc‐protected enantiomeric monosaccharides and one Fmoc dipeptide (Fmoc‐FF), were studied. The research focused on the optimization of sample preparation and handling, which then enabled the characterization of sample conformational homogeneity and thermal stability. CD spectroscopy, in combination with other spectroscopic techniques and microscopy, will allow a better insight into the self‐assembly of chiral building blocks into higher order structural architectures.     

Including RNA secondary structures improves accuracy and robustness in reconstruction of phylogenetic trees

Background  

In several studies, secondary structures of ribosomal genes have been used to improve the quality of phylogenetic reconstructions. An extensive evaluation of the benefits of secondary structure, however, is lacking.     

PALSSE: A program to delineate linear secondary structural elements from protein structures

Background  

The majority of residues in protein structures are involved in the formation of α-helices and β-strands. These distinctive secondary structure patterns can be used to represent a protein for visual inspection and in vector-based protein structure comparison. Success of such structural comparison methods depends crucially on the accurate identification and delineation of secondary structure elements.     

PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

Background  

Since the function of a protein is largely dictated by its three dimensional configuration, determining a protein's structure is of fundamental importance to biology. Here we report on a novel approach to determining the one dimensional secondary structure of proteins (distinguishing α-helices, β-strands, and non-regular structures) from primary sequence data which makes use of Parallel Cascade Identification (PCI), a powerful technique from the field of nonlinear system identification.     

Prediction of RNA secondary structure by maximizing pseudo-expected accuracy

Background  

Recent studies have revealed the importance of considering the entire distribution of possible secondary structures in RNA secondary structure predictions; therefore, a new type of estimator is proposed including the maximum expected accuracy (MEA) estimator. The MEA-based estimators have been designed to maximize the expected accuracy of the base-pairs and have achieved the highest level of accuracy. Those methods, however, do not give the single best prediction of the structure, but employ parameters to control the trade-off between the sensitivity and the positive predictive value (PPV). It is unclear what parameter value we should use, and even the well-trained default parameter value does not, in general, give the best result in popular accuracy measures to each RNA sequence.     

Protein structural similarity search by Ramachandran codes

Background  

Protein structural data has increased exponentially, such that fast and accurate tools are necessary to access structure similarity search. To improve the search speed, several methods have been designed to reduce three-dimensional protein structures to one-dimensional text strings that are then analyzed by traditional sequence alignment methods; however, the accuracy is usually sacrificed and the speed is still unable to match sequence similarity search tools. Here, we aimed to improve the linear encoding methodology and develop efficient search tools that can rapidly retrieve structural homologs from large protein databases.     

Large-scale prediction of long disordered regions in proteins using random forests

Background  

Many proteins contain disordered regions that lack fixed three-dimensional (3D) structure under physiological conditions but have important biological functions. Prediction of disordered regions in protein sequences is important for understanding protein function and in high-throughput determination of protein structures. Machine learning techniques, including neural networks and support vector machines have been widely used in such predictions. Predictors designed for long disordered regions are usually less successful in predicting short disordered regions. Combining prediction of short and long disordered regions will dramatically increase the complexity of the prediction algorithm and make the predictor unsuitable for large-scale applications. Efficient batch prediction of long disordered regions alone is of greater interest in large-scale proteome studies.     

Design,implementation and evaluation of a practical pseudoknot folding algorithm based on thermodynamics

Background  

The general problem of RNA secondary structure prediction under the widely used thermodynamic model is known to be NP-complete when the structures considered include arbitrary pseudoknots. For restricted classes of pseudoknots, several polynomial time algorithms have been designed, where the O(n ⁶)time and O(n ⁴) space algorithm by Rivas and Eddy is currently the best available program.     

pi-Turns: types,systematics and the context of their occurrence in protein structures

Background  

For a proper understanding of protein structure and folding it is important to know if a polypeptide segment adopts a conformation inherent in the sequence or it depends on the context of its flanking secondary structures. Turns of various lengths have been studied and characterized starting from three-residue γ-turn to six-residue π-turn. The Schellman motif occurring at the C-terminal end of α-helices is a classical example of hydrogen bonded π-turn involving residues at (i) and (i+5) positions. Hydrogen bonded and non-hydrogen bonded β- and α-turns have been identified previously; likewise, a systematic characterization of π-turns would provide valuable insight into turn structures.     

Residue contact-count potentials are as effective as residue-residue contact-type potentials for ranking protein decoys

Background  

For over 30 years potentials of mean force have been used to evaluate the relative energy of protein structures. The most commonly used potentials define the energy of residue-residue interactions and are derived from the empirical analysis of the known protein structures. However, single-body residue 'environment' potentials, although widely used in protein structure analysis, have not been rigorously compared to these classical two-body residue-residue interaction potentials. Here we do not try to combine the two different types of residue interaction potential, but rather to assess their independent contribution to scoring protein structures.