Bayesian inference assessment of protein secondary structure analysis using circular dichroism data - how much structural information is contained in protein circular dichroism spectra?

An Improved Diabatization Scheme for Computing the Electronic Circular Dichroism of Proteins

We advance the quality of first-principles calculations of protein electronic circular dichroism (CD) through an amelioration of a key deficiency of a previous procedure that involved diabatization of electronic states on the amide chromophore (to obtain interamide couplings) in a β-strand conformation of a diamide. This yields substantially improved calculated far-ultraviolet (far-UV) electronic circular dichroism (CD) spectra for β-sheet conformations. The interamide couplings from the diabatization procedure for 13 secondary structural elements (13 diamide structures) are applied to compute the CD spectra for seven example proteins: myoglobin (α helix), jacalin (β strand), concanavalin A (β type I), elastase (β type II), papain (α + β), 310-helix bundle (310-helix) and snow flea antifreeze protein (polyproline). In all cases, except concanavalin A and papain, the CD spectra computed using the interamide couplings from the diabatization procedure yield improved agreement with experiment with respect to previous first-principles calculations.

Impact of imperfect data on protein secondary structure estimates from Far-UV circular dichroism spectra

Circular dichroism [CD] is widely used to rapidly assess protein structure. Deconvolution of the far-UV CD spectrum is widely used to quantify the secondary structural elements [SSEs]. Multiple algorithms are available for this. Imperfections in the experimental CD spectra arising from spectral noise, instrument miscalibration, spectral offsets and non-linearity will impact on the accuracy and precision of derived secondary structure estimates. Analytical validation for use in regulated environments, such as biopharmaceuticals, requires that the impact of imperfect data on these estimates be understood. Limited information on the impact of poor data were available. A series of noise-free simulated spectral datasets with modified intensity, wavelength, noise and intensity linearity and offsets were created from entries in the Protein Circular Dichroism Data Bank. These datasets were analysed using the BeStSel, on-line resource to estimate secondary structure. Data imperfections caused significant change in SSEs, but the spectral range is also important. This study emphasises the importance of analytical method validation and justifiable estimates of uncertainty when reporting results. The datasets created are made available as a resource to validate other secondary structure estimation programs.

Study on antimicrobial activity of sturgeon skin mucus polypeptides (Rational Design, Self-Assembly and Application)

Despite the favorable biocompatibility of natural antimicrobial peptides (AMPs), their scarcity limits their practical application. Through rational design, the activity of AMPs can be enhanced to expand their application. In this study, we selected a natural sturgeon epidermal mucus peptide, AP-16 (APATPAAPALLPLWLL), as the model molecule and studied its conformational regulation and antimicrobial activity through amino acid substitutions and N-terminal lipidation. The structural and morphological transitions of the peptide self-assemblies were investigated using circular dichroism and transmission electron microscopy. Following amino acid substitution, the conformation of AL-16 (AKATKAAKALLKLWLL) did not change. Following N-terminal alkylation, the C8-AL-16 and C12-AL-16 conformations changed from random coil to β-sheet or α-helix, and the self-assembly changed from nanofibers to nanospheres. AL-16, C8-AL-16, and C8-AL-16 presented significant antimicrobial activity against Pseudomonas and Shewanella at low concentrations. N-terminal alkylation effectively extended the shelf life of Litopenaeus vannamei. These results support the application of natural AMPs.

SOMSpec as a General Purpose Validated Self-Organising Map Tool for Rapid Protein Secondary Structure Prediction From Infrared Absorbance Data

A protein's structure is the key to its function. As protein structure can vary with environment, it is important to be able to determine it over a wide range of concentrations, temperatures, formulation vehicles, and states. Robust reproducible validated methods are required for applications including batch-batch comparisons of biopharmaceutical products. Circular dichroism is widely used for this purpose, but an alternative is required for concentrations above 10 mg/mL or for solutions with chiral buffer components that absorb far UV light. Infrared (IR) protein absorbance spectra of the Amide I region (1,600-1700 cm-1) contain information about secondary structure and require higher concentrations than circular dichroism often with complementary spectral windows. In this paper, we consider a number of approaches to extract structural information from a protein infrared spectrum and determine their reliability for regulatory and research purpose. In particular, we compare direct and second derivative band-fitting with a self-organising map (SOM) approach applied to a number of different reference sets. The self-organising map (SOM) approach proved significantly more accurate than the band-fitting approaches for solution spectra. As there is no validated benchmark method available for infrared structure fitting, SOMSpec was implemented in a leave-one-out validation (LOOV) approach for solid-state transmission and thin-film attenuated total reflectance (ATR) reference sets. We then tested SOMSpec and the thin-film ATR reference set against 68 solution spectra and found the average prediction error for helix (α + 310) and β-sheet was less than 6% for proteins with less than 40% helix. This is quantitatively better than other available approaches. The visual output format of SOMSpec aids identification of poor predictions. We also demonstrated how to convert aqueous ATR spectra to and from transmission spectra for structure fitting. Fourier self-deconvolution did not improve the average structure predictions.

The PCDDB (Protein Circular Dichroism Data Bank): A Bioinformatics Resource for Protein Characterisations and Methods Development

The Protein Circular Dichroism Data Bank (PCDDB) [https://pcddb.cryst.bbk.ac.uk] is an established resource for the biological, biophysical, chemical, bioinformatics, and molecular biology communities. It is a freely-accessible repository of validated protein circular dichroism (CD) spectra and associated sample and other metadata, with entries having links to other bioinformatics resources including, amongst others, structure (PDB) and sequence (UniProt) databases, as well as to published papers which produced the data and cite the database entries. It includes primary (unprocessed) and final (processed) spectral data, which are available in both text and pictorial formats, as well as detailed sample and validation information produced for each of the entries. Recently the metadata content associated with each of the entries, as well as the number and structural breadth of the protein components included, have been expanded. The PCDDB includes data on both wild-type and mutant proteins, and because CD studies primarily examine proteins in solution, it also contains examples of the effects of different environments on their structures, plus thermal unfolding/folding series. Methods for both sequence and spectral comparisons are included. The data included in the PCDDB complement results from crystal, cryo-electron microscopy, NMR spectroscopy, bioinformatics characterisations and classifications, and other structural information available for the proteins via links to other databases. The entries in the PCDDB have been used for the development of new analytical methodologies, for interpreting spectral and other biophysical data, and for providing insight into structures and functions of individual soluble and membrane proteins and protein complexes.

Circular dichroism for secondary structure determination of proteins with unfolded domains using a self-organising map algorithm SOMSpec

Many proteins and peptides are increasingly being recognised to contain unfolded domains or populations that are key to their function, whether it is in ligand binding or material assembly. We report an approach to determine the secondary structure for proteins with suspected significant unfolded domains or populations using our neural network approach SOMSpec. We proceed by derandomizing spectra by removing fractions of random coil (RC) spectra prior to secondary structure fitting and then regenerating α-helical and β-sheet contents for the experimental proteins. Application to bovine serum albumin spectra as a function of temperature proved to be straightforward, whereas lysozyme and insulin have hidden challenges. The importance of being able to interrogate the SOMSpec output to understand the best matching units used in the predictions is illustrated with lysozyme and insulin whose partially melted proteins proved to have significant β_II content and their CD spectrum looks the same as that for a random coil.

Spectroscopy of model-membrane liposome-protein systems: complementarity of linear dichroism, circular dichroism, fluorescence and SERS

A range of membrane models have been developed to study components of cellular systems. Lipid vesicles or liposomes are one such artificial membrane model which mimics many properties of the biological system: they are lipid bilayers composed of one or more lipids to which other molecules can associate. Liposomes are thus ideal to study the roles of cellular lipids and their interactions with other membrane components to understand a wide range of cellular processes including membrane disruption, membrane transport and catalytic activity. Although liposomes are much simpler than cellular membranes, they are still challenging to study and a variety of complementary techniques are needed. In this review article, we consider several currently used analytical methods for spectroscopic measurements of unilamellar liposomes and their interaction with proteins and peptides. Among the variety of spectroscopic techniques seeing increasing application, we have chosen to discuss: fluorescence based techniques such as FRET (fluorescence resonance energy transfer) and FRAP (fluorescence recovery after photobleaching), that are used to identify localisation and dynamics of molecules in the membrane; circular dichroism (CD) and linear dichroism (LD) for conformational and orientation changes of proteins on membrane binding; and SERS (Surface Enhanced Raman Spectroscopy) as a rapidly developing ultrasensitive technique for site-selective molecular characterisation. The review contains brief theoretical basics of the listed techniques and recent examples of their successful applications for membrane studies.