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

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>In this study we show that the sequence prediction methods have accuracies nearly comparable to those of spectroscopic methods. However, we also demonstrate that combining the spectroscopic and sequences techniques produces significant overall improvements in secondary structure determinations. In addition, combining the extra information content available from synchrotron radiation circular dichroism data with sequence methods also shows improvements.</p> <p>Conclusion</p> <p>Combining sequence prediction with experimentally determined spectroscopic methods for protein secondary structure content significantly enhances the accuracy of the overall results obtained.</p

Biophysical and computational studies of biomacromolecular systems

The binding of mono- and dinuclear platinum(II) complexes with both double-stranded and G-quadruplex DNA (QDNA) was explored using a combination of spectroscopic and computational techniques. The stabilising effects on G-quadruplex DNA were assessed and structure-activity relationships developed to guide the future development of QDNA selective complexes. Additionally, two pieces of software were developed, each able to process spectroscopic information. The first application calculates binding constants from various spectroscopic data including circular dichroism and fluorescence. The second program, SOMSpec, uses a machine learning approach to elucidate biomacromolecular structure from circular dichroism and infrared spectra

High throughput prediction of the long term stability of pharmaceutical macromolecules from short term multi-instrument spectroscopic data

The field of pharmaceutical chemistry is currently struggling with the question of how to relate changes in the physical form of a macromolecular biopharmaceutical, such as a therapeutic protein, to changes in the drug's efficacy, safety, and long term stability (ESS). A great number of experimental methods are typically utilized to investigate the differences between forms of a macromolecule, yet conclusions regarding changes in ESS are frequently tentative. An opportunity exists, however, to relate changes in form to changes in ESS. At least once during the development of a new drug, a study is undertaken (at great expense) of the ESS of the drug upon perturbation by multiple manufacturing, formulation, storage and transportation variables. The data acquired is then used to build a model that relates changes in ESS to manufacturing, formulation, storage and transportation variables. It is not common in the pharmaceutical industry, however, to relate changes in comprehensive ESS data sets to comprehensive measurements of changes in macromolecular form. We bridge the gap between physical measurements of a macromolecule's form and measurements of its long term stability, utilizing two data sets collected in a collaboration between our group at the University of Kansas and a group at the Ludwig Maximilians University in Munich, Germany. The long term stability data, collected by the team in Germany, contains measurements of the chemical and conformation stability of Granulocyte Colony Stimulating Factor (GCSF) over a period of two years in 16 different liquid formulations. The short term physical data, collected in our lab, is comprised of spectroscopic characterization of the response of GCSF to thermal unfolding. The same 16 liquid formulations of GCSF were used in each study, allowing us to fit models predicting the long term stability of GCSF from short term measurements. We first apply a novel data reduction method to the short term data. This method selects data in the neighborhood of thermal unfolding transitions, and automates traditional comparative analyses. We then model the long term stability measurements using a linear technique, least squares fits, and a nonlinear one, radial basis function networks (RBFN). Using a Pearson correlation coefficient permutation test, we find that many of the fitted results have less than a 1 percent probability of occurring by chance

Polymeric microfluidic platform combined with Fourier Transform infrared imaging to explore biomolecular reactions

Diseases such as Alzheimer’s and Parkinson’s are classified as B-amyloid diseases due to the presence of plaques composed of B-amyloid fibrils, aggregations of misfolded proteins, in the affected tissues. Poorly functioning bioenergetics reactions such as those in cytochrome oxidase are linked to cardiomyopathies. Very early reaction intermediates such as misfolding in proteins that arise in less than a millisecond can lead to a cascade that results in diseases. Reaction mechanisms and kinetics of such sub-millisecond events are especially difficult to investigate experimentally due to (i) the lack of suitable methods to rapidly mix reactants, and/or (ii) lack of facile detection methods that are sensitive to molecular structure. Current techniques for such investigations are impractical in many cases or have serious limitations. The most promising method to investigate fast reactions integrates microfluidic continuous-flow reactors (MCFMs) with Fourier Transform infrared (FTIR) imaging to obtain sub-millisecond temporal resolution and molecular-bond structural resolution. My thesis primarily focuses on developing polymeric MCFMs compatible with FTIR imaging and developing robust methods for high-fidelity FTIR imaging and data analysis of sub-millisecond biomolecular reactions. We developed polymeric MCFMs using a low-cost cyclic olefin copolymer (COC) that is physically and spectrally biocompatible, and well suited for microfabrication. We used strong covalent bonding between device layers to enable the high flow rates needed to probe sub-millisecond reactions and developed robust FTIR imaging and analysis algorithms to extract high-quality FTIR spectral data. After validating the ability of the platform to provide both change in structural details of biomolecules and associated kinetics, we applied the platform and showed the ability of dodine as a chemical denaturant to enable FTIR protein dynamic studies by tracing the conformational change of apomyoglobin, and its unfolding kinetics. We successfully showed that the secondary structures of apomyoglobin behave differently during unfolding, and the unfolding kinetics changed depending on the dodine concentration

Binding Studies of Near Infrared Cyanine Dyes with Human Serum Albumin and Poly-L-Lysine Using Optical Spectroscopy Methods

The sensitivity of biological studies performed between 190 and 650 nm is greatly reduced due to the autofluorescence of biomolecules and impurities in this region. Therefore, the enhanced signal-to-noise ratios encountered at longer wavelengths makes biological analysis within the near infrared (NIR) region from 650 nm to 1100 nm far more advantageous. This dissertation describes the noncovalent binding interactions of near-infrared (NIR) carbocyanine dyes with human serum albumin (HSA) and poly-L-lysine (PLL) using UV-Vis/NIR absorption spectroscopy, emission spectroscopy, circular dichroism (CD), and fluorescence detected circular dichroism (FDCD). The optical spectroscopy methods used in this work are described in detail in Chapter 1. The various applications of NIR dyes in protein analysis are introduced in Chapter 2. In general, the sensitivity of cyanines to the polarity of their local environment makes them quite suitable for protein labeling schemes. In aqueous media, cyanines have a high propensity for self-association. Yet in the hydrophobic binding sites of globular proteins, these aggregates often dissipate. Absorption and emission spectroscopy can be utilized to observe the differential spectral properties of monomer, intra-molecular and intermolecular aggregates. In Chapter 3, the photophysical properties of bis(cyanine) NIR dyes containing di-, tri-, and tetraethylene glycol linkers were each examined in the presence of HSA are discussed. Variations in chain length as well as probe flexibility were demonstrated through distinct differences in absorption and emission spectra. The observed changes in the spectral properties of the NIR dyes in the presence and absence of HSA were correlated to the physical parameters of the probes\u27 local environment (i.e., protein binding sites and self-association). All three bis-cyanines examined exhibited enhanced fluorescence in the presence of HSA. The bis-cyanine dye containing the tri(ethylene glycol) spacer allowed for a complete overlap of the benzene rings, to form π-π interactions which were observed as intra-molecular H-aggregate bands. The dye exhibited no fluorescence in buffer, owing to the H-aggregation observed in the absorption data. In the presence of HSA, the intra-molecular dimers were disrupted and fluorescence was then detected. The cut-on fluorescence displayed by the dye in the presence of HSA made it ideal for noncovalent labeling applications. The utility of several NIR dyes for use as secondary structural probes was investigated in Chapter 4. NIR dyes were screened thoroughly using UV-Vis/NIR absorption spectroscopy dyes with spectral properties which were sensitive to protein secondary structure models of such as PLL in basic solution. Two NIR dyes were found to be quite sensitive to the structural features of uncharged α- and β-PLL. The chiral discrimination of these probes for basic protein secondary structures was also evaluated through CD measurements within the NIR probes\u27 absorption bands

Methods for Molecular Modelling of Protein Complexes.

Biological processes are often mediated by complexes formed between proteins and various biomolecules. The 3D structures of such protein-biomolecule complexes provide insights into the molecular mechanism of their action. The structure of these complexes can be predicted by various computational methods. Choosing an appropriate method for modelling depends on the category of biomolecule that a protein interacts with and the availability of structural information about the protein and its interacting partner. We intend for the contents of this chapter to serve as a guide as to what software would be the most appropriate for the type of data at hand and the kind of 3D complex structure required. Particularly, we have dealt with protein-small molecule ligand, protein-peptide, protein-protein, and protein-nucleic acid interactions.Most, if not all, model building protocols perform some sampling and scoring. Typically, several alternate conformations and configurations of the interactors are sampled. Each such sample is then scored for optimization. To boost the confidence in these predicted models, their assessment using other independent scoring schemes besides the inbuilt/default ones would prove to be helpful. This chapter also lists such software and serves as a guide to gauge the fidelity of modelled structures of biomolecular complexes

THERMODYNAMIC PROPERTIES OF THE UNFOLDED ENSEMBLE OF PROTEINS

A random coil, whose size is determined by its excluded volume, and net energetic interactions with its environment, has served as a representation of the unfolded ensemble of proteins. The work in this thesis involves equilibrium, nuclear magnetic resonance and time-resolved kinetics spectroscopic studies on the unfolded ensemble of BBL, a globally downhill folding 40-residue protein involved the Krebs cycle of E. coli, in its acid-denatured state, and on a sequence-randomized version of this protein. The effect of variability in thermodynamic conditions, such as temperature and the presence of added chaotropes or kosmotropes, on the equilibrium properties and reconfiguration dynamics of the unfolded state, have been deduced in the absence of competition with folding events at low pH. The unfolded ensemble experiences expansion and collapse to varying degrees in response to changes in these conditions. Individual interactions of residues of the protein with the solvent and the cosolvent (direct interactions), and the properties of the solution itself (indirect interactions) are together critical to the unfolded chain's properties and have been quantitatively estimated. Unfolded, protonated BBL can be refolded by tuning the properties of the solvent by addition of kosmotropic salts. Electrostatic interactions turn out to be essential for folding cooperativity, while solvent-mediated changes in the hydrophobic effect can promote structure formation but cannot induce long-range thermodynamic connectivity in the protein. The effect of sequence on the properties of heteropolymers is also tested with a randomized version of BBL's sequence. Chain radii of gyration, and the degree and rate of hydrophobic collapse depend on the composition of the sequence, viz. hydrophilic versus hydrophobic content. However, the ability to maximize stabilizing interactions and adopt compact conformations is more evident in naturally selected protein sequences versus designed heteropolymers. Chain reconfiguration of unfolded BBL takes place in &sim;1/(100 ns), in agreement with theoretical estimates of homopolymer collapse rates. The refolding dynamics of salt-refolded BBL in the range of 1/(6 &mu;s) at 320 K, emerge as being independent of the degree of folding or protonation of the chain, a result in keeping with the description of dynamics in BBL as oscillations in a single, smooth harmonic potential well, which only varies in its position and curvature with varying thermodynamic conditions

Protein Assembly for a Functional Fibrous Product

Natural protein-based materials are exploring their new applications from the traditional uses. Structural proteins provide scaffolds, whereas functional proteins carry essential biological activities through millions of biochemical reactions. The idea of implementing functionalities into natural structures could provide manufactured protein products with a better fit for human desire. The development of synthetic biology and molecular assembly methods illustrates possibilities for the production of functional structures in-situ, which provides better connections between the functional partners with the structural scaffolds. Protein fibres are one of the natural structures which possess a unique shape and superior mechanical properties. Apart from the natural protein fibres, many disease-related peptides self-assembled into amyloid filaments and fibrous structures. Natural globular proteins could also form fibres through the directed assembly by changing their storage conditions or through fusion. Elongated polyglutamine peptides cause many neurodegenerative diseases as they assemble. In this thesis, a polyglutamine peptide (Q77) was fused with functional partners to direct the protein assembly in vitro. The role of the polyglutamine was studied during assembly and after the formation of a self-supportive fibrous product. The extensibility of traditionally size-limited fibrous materials formed by disease-related peptides was tested experimentally for the first time. The resultant fibrous product with embedded functionalities mimics the structure of silk, but the mechanical behaviour of collagen. Two structurally distinct proteins were chosen as the functional partners for Q77: a monomeric red fluorescent protein (mcRFP), which is relatively small in size and possesses a b-barrel structure, and firefly luciferase (Luc), which is a larger protein with a fragile structure consisting of two mobile domains. Both proteins have been widely used as reporters for intracellular activities with either fluorescence or bioluminescent signal. In this work, the functionalities of both proteins were investigated after Q77 fusion and after assembly towards respective fibrous products. The structural variation of these recombinant proteins resulted in the changes of their functionalities. Finally, a self-supportive fibrous ATP sensor was achieved for the first time with this dual functional protein product.Cambridge Trust, China Scholarship Counci