Determination of the secondary structure of proteins in different environments by FTIR-ATR spectroscopy and PLS regression

Optimizing the Metal Bioreduction Process in Recombinant Shewanella azerbaijanica Bacteria: A Novel Approach via mtrC Gene Cloning and Nitrate-Reducing Pathway Destruction

Environmental pollution is growing every day in terms of the increase in population, industrialization, and urbanization. Shewanella azerbaijanica is introduced as a highly potent bacterium in metal bioremediation. The mtrC gene was selected as a cloning target to improve electron flux chains in the EET (extracellular electron transfer) pathway. Using the SDM (site-directed mutagenesis) technique, the unique gene assembly featured the mtrC gene sandwiched between two napD/B genes to disrupt the nitrate reduction pathway, which serves as the primary metal reduction competitor. Shew-mtrC gene construction was transferred to expression plasmid pET28a (+) in the expression host bacteria (E. coli BL21 and S. azerbaijanica), in pUC57, cloning plasmid, which was transferred to the cloning host bacteria E. coli Top10 and S. azerbaijanica. All cloning procedures (i.e., synthesis, insertion, transformation, cloning, and protein expression) were verified and confirmed by precise tests. ATR-FTIR analysis, CD, western blotting, affinity chromatography, SDS-PAGE, and other techniques were used to confirm the expression and structure of the MtrC protein. The genome sequence and primers were designed according to the submitted Shewanella oneidensis MR-1 genome, the most similar bacteria to this native species. The performance of recombinant S. azerbaijanica bacterium in metal bioremediation, as sustainable strategy, has to be verified by more research.

Protein Microarrays for High Throughput Hydrogen/Deuterium Exchange Monitored by FTIR Imaging

Proteins form the fastest-growing therapeutic class. Due to their intrinsic instability, loss of native structure is common. Structure alteration must be carefully evaluated as structural changes may jeopardize the efficiency and safety of the protein-based drugs. Hydrogen deuterium exchange (HDX) has long been used to evaluate protein structure and dynamics. The rate of exchange constitutes a sensitive marker of the conformational state of the protein and of its stability. It is often monitored by mass spectrometry. Fourier transform infrared (FTIR) spectroscopy is another method with very promising capabilities. Combining protein microarrays with FTIR imaging resulted in high throughput HDX FTIR measurements. BaF2 slides bearing the protein microarrays were covered by another slide separated by a spacer, allowing us to flush the cell continuously with a flow of N2 gas saturated with 2H2O. Exchange occurred simultaneously for all proteins and single images covering ca. 96 spots of proteins that could be recorded on-line at selected time points. Each protein spot contained ca. 5 ng protein, and the entire array covered 2.5 × 2.5 mm2. Furthermore, HDX could be monitored in real time, and the experiment was therefore not subject to back-exchange problems. Analysis of HDX curves by inverse Laplace transform and by fitting exponential curves indicated that quantitative comparison of the samples is feasible. The paper also demonstrates how the whole process of analysis can be automatized to yield fast analyses.

Probing the effect of microenvironment on the enzyme-like behavior of catalytic peptide assemblies

As bridging species between short peptides and macromolecular proteins, peptide assemblies not only provide a supramolecular approach for the fabrication of controllable molecular machines with enzyme-like functions, but also a simplified model for understanding the catalytic mechanism of natural enzymes. In this study, we focused on probing the effect of microenvironment on the catalytic behavior of peptide assemblies. Upon simply replacing the X residue in Fmoc-FFXAH-CONH2, we realized the modulation of the microenvironment of the amyloid assemblies, which thus appeared esterase-like function with different catalytic abilities. The chemistry, structure and activity were analyzed to explore the principles that how the hydrophobic, charged, polar and chiral microenvironment deciding the catalytic behavior of the esterase mimic. In addition, we also presented the potential of the catalytic assemblies in the encapsulation, delivery and enzymatic metabolization of a mutual prodrug. This work sheds new insights for understanding the structure-function relationship of catalytic peptide assemblies and natural enzymes, and also provides a new avenue for the designing of artificial enzymes with better functions.

ATR-FTIR Biosensors for Antibody Detection and Analysis

Quality control of drug products is of paramount importance in the pharmaceutical world. It ensures product safety, efficiency, and consistency. In the case of complex biomolecules such as therapeutic proteins, small variations in bioprocess parameters can induce substantial variations in terms of structure, impacting the drug product quality. Conditions for obtaining highly reproducible grafting of 11-mercaptoundecanoic acid were determined. On that basis, we developed an easy-to-use, cost effective, and timesaving biosensor based on ATR-FTIR spectroscopy able to detect immunoglobulins during their production. A germanium crystal, used as an internal reflection element (IRE) for FTIR spectroscopy, was covalently coated with immunoglobulin-binding proteins. This thereby functionalized surface could bind only immunoglobulins present in complex media such as culture media or biopharmaceutical products. The potential subsequent analysis of their structure by ATR-FTIR spectroscopy makes this biosensor a powerful tool to monitor the production of biotherapeutics and assess important critical quality attributes (CQAs) such as high-order structure and aggregation level.

Attenuated Total Reflection Far-Ultraviolet (ATR-FUV) Spectroscopy is a Sensitive Tool for Investigation of Protein Adsorption

Attenuated total reflection far-ultraviolet (ATR-FUV) spectra in the 145-250 nm region were studied for four kinds of proteins (two α-helix-rich proteins: bovine serum albumin (BSA) and lysozyme and two β-sheet rich proteins: concanavalin A and γ-globulin) in different solutions (pure water and phosphate buffered saline, or PBS) with different concentrations. All the spectra show a band at 191 nm due to the π-π^* transition of amide bonds of the proteins. The wavelength of the band does not change with their second structures, suggesting that the corresponding electronic transition mode is localized and polarized in the direction that is not affected by the difference in the peptide folding. The intensity of the 191 nm band differs with the concentration of salt in the solution, suggesting that the band intensity reflects the adsorption density of a protein on the internal reflection element (IRE) made of a sapphire glass prism. According to the intensity changes of the band at 191 nm, it is revealed that the properties in adsorption are different from one protein to another. It is assumed that there are two types of forces on the protein adsorption: one is that among the molecules and the other is that between a molecule and a substrate. The origin of force includes localized electrostatic polarity and affinity to water. The ions in the solvent give a marked effect on these forces, resulting in the difference in the response to adsorption density against the salt concentration in the solvent.

Roles of Physicochemical and Structural Properties of RNA-Binding Proteins in Predicting the Activities of Trans-Acting Splicing Factors with Machine Learning

Trans-acting splicing factors play a pivotal role in modulating alternative splicing by specifically binding to cis-elements in pre-mRNAs. There are approximately 1500 RNA-binding proteins (RBPs) in the human genome, but the activities of these RBPs in alternative splicing are unknown. Since determining RBP activities through experimental methods is expensive and time consuming, the development of an efficient computational method for predicting the activities of RBPs in alternative splicing from their sequences is of great practical importance. Recently, a machine learning model for predicting the activities of splicing factors was built based on features of single and dual amino acid compositions. Here, we explored the role of physicochemical and structural properties in predicting their activities in alternative splicing using machine learning approaches and found that the prediction performance is significantly improved by including these properties. By combining the minimum redundancy–maximum relevance (mRMR) method and forward feature searching strategy, a promising feature subset with 24 features was obtained to predict the activities of RBPs. The feature subset consists of 16 dual amino acid compositions, 5 physicochemical features, and 3 structural features. The physicochemical and structural properties were as important as the sequence composition features for an accurate prediction of the activities of splicing factors. The hydrophobicity and distribution of coil are suggested to be the key physicochemical and structural features, respectively.

Unlocking the secret of lignin-enzyme interactions: Recent advances in developing state-of-the-art analytical techniques

Bioconversion of renewable lignocellulosics to produce liquid fuels and chemicals is one of the most effective ways to solve the problem of fossil resource shortage, energy security, and environmental challenges. Among the many biorefinery pathways, hydrolysis of lignocellulosics to fermentable monosaccharides by cellulase is arguably the most critical step of lignocellulose bioconversion. In the process of enzymatic hydrolysis, the direct physical contact between enzymes and cellulose is an essential prerequisite for the hydrolysis to occur. However, lignin is considered one of the most recalcitrant factors hindering the accessibility of cellulose by binding to cellulase unproductively, which reduces the saccharification rate and yield of sugars. This results in high costs for the saccharification of carbohydrates. The various interactions between enzymes and lignin have been explored from different perspectives in literature, and a basic lignin inhibition mechanism has been proposed. However, the exact interaction between lignin and enzyme as well as the recently reported promotion of some types of lignin on enzymatic hydrolysis is still unclear at the molecular level. Multiple analytical techniques have been developed, and fully unlocking the secret of lignin-enzyme interactions would require a continuous improvement of the currently available analytical techniques. This review summarizes the current commonly used advanced research analytical techniques for investigating the interaction between lignin and enzyme, including quartz crystal microbalance with dissipation (QCM-D), surface plasmon resonance (SPR), attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, atomic force microscopy (AFM), nuclear magnetic resonance (NMR) spectroscopy, fluorescence spectroscopy (FLS), and molecular dynamics (MD) simulations. Interdisciplinary integration of these analytical methods is pursued to provide new insight into the interactions between lignin and enzymes. This review will serve as a resource for future research seeking to develop new methodologies for a better understanding of the basic mechanism of lignin-enzyme binding during the critical hydrolysis process.

A simple, rapid, and robust "on-the-go" identity testing of biotherapeutics using FTIR spectroscopy

The stunning rise of biotherapeutics as successful treatments of complex and hard-to-treat diseases, in particular cancer, has necessitated the development of a rapid analytical method capable of differentiating these otherwise significantly similar antibody-based products. The existing methods for product identification pose significant drawbacks in terms of the consumption of time and labor. Here, we present an FTIR spectroscopy-based simple, rapid, and robust method that is capable of differentiating between the biotherapeutics (both innovator products and biosimilars). The proposed approach uses partial least-squares-discriminant analysis to pinpoint subtle differences in the FTIR spectra of the samples, enabling us to not only identify the product but also calculate its concentration. This FTIR-based method can be used to fulfill the identity testing requirement of a pharmaceutical drug in its final packaged form set by the US Food and Drug Administration. Along with this, identity testing can also be deployed at multiple steps in the manufacturing process and can also be used by the appropriate regulatory or government agency for tackling counterfeits of biotherapeutic products.

Process Analytical Technology for Precipitation Process Integration into Biologics Manufacturing towards Autonomous Operation—mAb Case Study

The integration of real time release testing into an advanced process control (APC) concept in combination with digital twins accelerates the process towards autonomous operation. In order to implement this, on the one hand, measurement technology is required that is capable of measuring relevant process data online, and on the other hand, a suitable model must be available to calculate new process parameters from this data, which are then used for process control. Therefore, the feasibility of online measurement techniques including Raman-spectroscopy, attenuated total reflection Fourier transformed infrared spectroscopy (ATR-FTIR), diode array detector (DAD) and fluorescence is demonstrated within the framework of the process analytical technology (PAT) initiative. The best result is achieved by Raman, which reliably detected mAb concentration (R2 of 0.93) and purity (R2 of 0.85) in real time, followed by DAD. Furthermore, the combination of DAD and Raman has been investigated, which provides a promising extension due to the orthogonal measurement methods and higher process robustness. The combination led to a prediction for concentration with a R2 of 0.90 ± 3.9% and for purity of 0.72 ± 4.9%. These data are used to run simulation studies to show the feasibility of process control with a suitable digital twin within the APC concept.

PAT for Continuous Chromatography Integrated into Continuous Manufacturing of Biologics towards Autonomous Operation

This study proposes a reliable inline PAT concept for the simultaneous monitoring of different product components after chromatography. The feed for purification consisted of four main components, IgG monomer, dimer, and two lower molecular weight components of 4.4 kDa and 1 kDa molecular weight. The proposed measurement setup consists of a UV–VIS diode-array detector and a fluorescence detector. Applying this system, a R2 of 0.93 for the target component, a R2 of 0.67 for the dimer, a R2 of 0.91 for the first side component and a R2 of 0.93 for the second side component is achieved. Root mean square error for IgG monomer was 0.027 g/L, for dimer 0.0047 g/L, for side component 1 0.016 g/L and for the side component 2 0.014 g/L. The proposed measurement concept tracked component concentration reliably down to 0.05 g/L. Zero-point fluctuations were kept within a standard deviation of 0.018 g/L for samples with no IgG concentration but with side components present, allowing a reliable detection of the target component. The main reason inline concentration measurements have not been established yet, is the false-positive measurement of target components when side components are present. This problem was eliminated using the combination of fluorescence and UV–VIS data for the test system. The use of this measurement system is simulated for the test system, allowing an automatic fraction cut at 0.05 g/L. In this simulation a consistent yield of >99% was achieved. Process disturbances for processed feed volume, feed purity and feed IgG concentration can be compensated with this setup. Compared to a timed process control, yield can be increased by up to 12.5%, if unexpected process disturbances occur.

FTIR Imaging of Protein Microarrays for High Throughput Secondary Structure Determination

The paper introduces a new method designed for high-throughput protein structure determination. It is based on spotting proteins as microarrays at a density of ca. 2000-4000 samples per cm² and recording Fourier transform infrared (FTIR) spectra by FTIR imaging. It also introduces a new protein library, called cSP92, which contains 92 well-characterized proteins. It has been designed to cover as well as possible the structural space, both in terms of secondary structures and higher level structures. Ascending stepwise linear regression (ASLR), partial least square (PLS) regression, and support vector machine (SVM) have been used to correlate spectral characteristics to secondary structure features. ASLR generally provides better results than PLS and SVM. The observation that secondary structure prediction is as good for protein microarray spectra as for the reference attenuated total reflection spectra recorded on the same samples validates the high throughput microarray approach. Repeated double cross-validation shows that the approach is suitable for the high accuracy determination of the protein secondary structure with root mean square standard error in the cross-validation of 4.9 ± 1.1% for α-helix, 4.6 ± 0.8% for β-sheet, and 6.3 ± 2.2% for the "other" structures when using ASLR.

Amino acid side chain contribution to protein FTIR spectra: impact on secondary structure evaluation

Prediction of protein secondary structure from FTIR spectra usually relies on the absorbance in the amide I–amide II region of the spectrum. It assumes that the absorbance in this spectral region, i.e., roughly 1700–1500 cm⁻¹ is solely arising from amide contributions. Yet, it is accepted that, on the average, about 20% of the absorbance is due to amino acid side chains. The present paper evaluates the contribution of amino acid side chains in this spectral region and the potential to improve secondary structure prediction after correcting for their contribution. We show that the β-sheet content prediction is improved upon subtraction of amino acid side chain contributions in the amide I–amide II spectral range. Improvement is relatively important, for instance, the error of prediction of β-sheet content decreases from 5.42 to 4.97% when evaluated by ascending stepwise regression. Other methods tested such as partial least square regression and support vector machine have also improved accuracy for β-sheet content evaluation. The other structures such as α-helix do not significantly benefit from side chain contribution subtraction, in some cases prediction is even degraded. We show that co-linearity between secondary structure content and amino acid composition is not a main limitation for improving secondary structure prediction. We also show that, even though based on different criteria, secondary structures defined by DSSP and XTLSSTR both arrive at the same conclusion: only the β-sheet structure clearly benefits from side chain subtraction. It must be concluded that side chain contribution subtraction benefit for the evaluation of other secondary structure contents is limited by the very rough description of side chain absorbance which does not take into account the variations related to their environment. The study was performed on a large protein set. To deal with the large number of proteins present, we worked on protein microarrays deposited on BaF₂ slides and FTIR spectra were acquired with an imaging system.

Evaluation of protein secondary structure from FTIR spectra improved after partial deuteration

FTIR spectroscopy has become a major tool to determine protein secondary structure. One of the identified obstacle for reaching better predictions is the strong overlap of bands assigned to different secondary structures. Yet, while for instance disordered structures and α-helical structures absorb almost at the same wavenumber, the absorbance bands are differentially shifted upon deuteration, in part because exchange is much faster for disordered structures. We recorded the FTIR spectra of 85 proteins at different stages of hydrogen/deuterium exchange process using protein microarrays and infrared imaging for high throughput measurements. Several methods were used to relate spectral shape to secondary structure content. While in absolute terms, β-sheet is always better predicted than α-helix content, results consistently indicate an improvement of secondary structure predictions essentially for the α-helix and the category called “Others” (grouping random, turns, bends, etc.) after 15 min of exchange. On the contrary, the β-sheet fraction is better predicted in non-deuterated conditions. Using partial least square regression, the error of prediction for the α-helix content is reduced after 15-min deuteration. Further deuteration degrades the prediction. Error on the prediction for the “Others” structures also decreases after 15-min deuteration. Cross-validation or a single 25-protein test set result in the same overall conclusions.

Searching for a Better Match between Protein Secondary Structure Definitions and Protein FTIR Spectra

Obtaining protein secondary structure content from high-resolution structures requires definitions and thresholds for the various parameters involved, typically hydrogen bond energy or length/angle and backbone φ/ψ angles. Several definitions are currently used and can have a profound impact on secondary structure content. Fourier transform infrared (FTIR) spectroscopy has its own sensitivity to molecular geometry. It is, therefore, important to select a set of definitions that matches this sensitivity. Here, we used a new protein set consisting of 92 proteins designed for the calibration of spectroscopic methods. Spectra have been obtained from protein microarrays in a high throughput process. The potential for improving secondary structure predictions from FTIR spectra has been tested using 71 structures determined according to different definitions. The paper demonstrates that different secondary structure definitions result in large variations in secondary structure content that are not equivalent in view of the protein FTIR spectra. The prediction quality factor ζ can be improved by ca. 20-50% by selecting an adequate definition set. The results also indicate that the dictionary of secondary structure of proteins (DSSP) algorithm, which is currently widely used to evaluate protein secondary structure content, is a good choice when dealing with FTIR spectra.

A convenient protein library for spectroscopic calibrations

While several Raman, CD or FTIR spectral libraries are available for well-characterized proteins of known structure, proteins themselves are usually very difficult to acquire, preventing a convenient calibration of new instruments and new recording methods. The problem is particularly critical in the field of FTIR spectroscopy where numerous new methods are becoming available on the market.

The present papers reports the construction of a protein library (cSP92) including commercially available products, that are well characterized experimentally for their purity and solubility in conditions compatible with the recording of FTIR spectra and whose high-resolution structure is available.

Overall, 92 proteins were selected. These proteins cover well the CATH space at the level of classes and architectures. In terms of secondary structure content, an analysis of their high-resolution structure by DSSP shows that the mean content in the different secondary structures present in cSP92 is very similar to the mean content found in the PDB.

The 92-protein set is analyzed in details for the distribution of helix length, number of strands in β- sheets, length of β-strands and amino acid content, all features that may be important for the interpretation of FTIR spectra.

Platelet-driven formation of interface peptide nano-network biosensor enabling a non-invasive means for early detection of Alzheimer's disease

Soft material fabricated with DNA origami or peptide cross-linking technique may be promising theranostic platforms in the future; however, their naturally occurring counterparts, such as the peptide aggregates in the neurodegenerative diseases, constitute an increasingly burdensome issue of public health. Thus, a design of artificial peptide nano-network biosensor is conceived, in an attempt to combat the natural pathological peptides, by mimicking their pathogenesis process. Specifically, periphery platelet can secrete A-beta and induce its cross-linking & aggregation to form a surface peptide nano-network, resulting in large numbers of poly-tyrosine strands being covalently trapped in the network to serve as an efficient signal amplifier, through the electrochemical oxidation of tyrosine. This method is sensitive and quantitative in the range of normal and pathological periphery platelet distribution and can effectively discriminate Alzheimer's disease (AD) patients based on the detected potential neurodegenerative activity of platelet. These results may point to some future perspective of this method in the early screening of AD.

The mechanisms of humic substances self-assembly with biological molecules: The case study of the prion protein

Humic substances (HS) are the largest constituent of soil organic matter and are considered as a key component of the terrestrial ecosystem. HS may facilitate the transport of organic and inorganic molecules, as well as the sorption interactions with environmentally relevant proteins such as prions. Prions enter the environment through shedding from live hosts, facilitating a sustained incidence of animal prion diseases such as Chronic Wasting Disease and scrapie in cervid and ovine populations, respectively. Changes in prion structure upon environmental exposure may be significant as they can affect prion infectivity and disease pathology. Despite its relevance, the mechanisms of prion interaction with HS are still not completely understood. The goal of this work is to advance a structural-level picture of the encapsulation of recombinant, non-infectious, prion protein (PrP) into different natural HS. We observed that PrP precipitation upon addition of HS is mainly driven by a mechanism of "salting-out" whereby PrP molecules are rapidly removed from the solution and aggregate in insoluble adducts with humic molecules. Importantly, this process does not alter the protein folding since insoluble PrP retains its α-helical content when in complex with HS. The observed ability of HS to promote PrP insolubilization without altering its secondary structure may have potential relevance in the context of "prion ecology". These results suggest that soil organic matter interacts with prions possibly without altering the protein structures. This may facilitate prions preservation from biotic and abiotic degradation leading to their accumulation in the environment.

The amyloid architecture provides a scaffold for enzyme-like catalysts

Natural biological enzymes possess catalytic sites that are generally surrounded by a large three-dimensional scaffold. However, the proportion of the protein molecule that participates in the catalytic reaction is relatively small. The generation of artificial or miniature enzymes has long been a focus of research because enzyme mimetics can be produced with high activity at low cost. These enzymes aim to mimic the active sites without the additional architecture contributed by the protein chain. Previous work has shown that amyloidogenic peptides are able to self-assemble to create an active site that is capable of binding zinc and catalysing an esterase reaction. Here, we describe the structural characterisation of a set of designed peptides that form an amyloid-like architecture and reveal that their capability to mimic carbonic anhydrase and serve as enzyme-like catalysts is related to their ability to self-assemble. These amyloid fibril structures can bind the metal ion Zn²⁺via a three-dimensional arrangement of His residues created by the amyloid architecture. Our results suggest that the catalytic efficiency of amyloid-like assembly is not only zinc-dependent but also depends on an active centre created by the peptides which is, in turn, dependent on the ordered architecture. These fibrils have good esterase activity, and they may serve as good models for the evolution of modern-day enzymes. Furthermore, they may be useful in designing self-assembling fibrils for applications as metal ion catalysts. This study also demonstrates that the ligands surrounding the catalytic site affect the affinity of the zinc-binding site to bind the substrate contributing to the enzymatic activity of the assembled peptides.

Heteropoly acids triggered self-assembly of cationic peptides into photo- and electro-chromic gels

A series of cationic peptides with alternating lysines and hydrophobic residues were designed and synthesized. These kinds of short peptides with protonated lysines can complex with anionic heteropoly acids (HPAs) to form a stable gel in water/ethanol mixed solution. Circular dichroism spectroscopy showed that the short peptides adopted a mixed conformation (β-sheet and random-coil) within the gel matrix. Scanning and transmission electron microscopy revealed that the heteropoly acids, acting as nanosized cross-linkers, first initiated the self-assembly of the cationic peptides into spherical nanostructures. Then these nanospheres accumulated with each other through hydrogen bonds and hydrophobic interactions to form large sheet-like assemblies, which further interconnected with each other forming continuous 3D network structures. Fourier-transform infrared spectroscopy showed that the structural integrity of the HPAs was maintained during the gelation process. The resultant hybrid gels showed reversible photo- and elecrtro-chromic properties. X-ray photoelectron spectroscopy revealed that the hybrid gels, capable of persistent and reversible changes of their colour, are attributed to the intervalence charge-transfer transition of the HPAs. Reversible information writing and erasing were demonstrated through a repeated photo-lithograph or electric stimuli without significant loss of the gel performance.

Clues for divergent, polymorphic amyloidogenesis through dissection of amyloid forming steps of bovine carbonic anhydrase and its critical amyloid forming stretch

Certain amino acid stretches are considered 'critical' to trigger amyloidogenesis in a protein. Synthetic peptides corresponding to these stretches are often used as experimental mimics for studying the amyloidogenesis of their parent protein. Here we provide evidence that such simple extrapolation is misleading. We scrutinized each step of amyloid progression of full length bovine carbonic anhydrase (BCA) and compared it with the amyloidogenic process of its critical peptide stretch 201-227 (PepB). We found that under similar solution conditions amyloidogenesis of BCA followed surface-catalyzed secondary nucleation, whereas, that of PepB followed classical nucleation-dependent pathway. AFM images showed that while BCA formed short, thick and branched fibrils, PepB formed thin, long and unbranched fibrils. Structural information obtained by ATR-FTIR spectroscopy suggested parallel arrangement of intermolecular β-sheet in BCA amyloids in contrast to PepB amyloids which arranged into antiparallel β sheets. Amyloids formed by BCA were unable to seed the fibrillation of PepB and vice versa. Even the intermediates formed during lag phase revealed contrasting FTIR and far UV CD signature, hydrophobicity, morphology and cell cytotoxicity. Thus, we propose that sequences other than critical amyloidogenic stretches may significantly influence the initiation, polymerization and final fibrillar morphology of amyloid forming protein. The results have been discussed in light of primary sequence mediated amyloid polymorphism and its importance in the rational design of amyloid nanomaterials possessing desired physico-chemical properties.

Application of bioflocculating property of Pseudomonas aeruginosa strain IASST201 in treatment of oil-field formation water

A bioflocculating activity of 89.8% was depicted by an activated sludge-borne bacteria Pseudomonas aeruginosa strain IASST201 with a yield of bioflocculant of 2.68 g L(-1) obtained from production media broth after optimization of different parameters. The highest bioflocculation efficiency was found at the pre-stationary phase of the bacterial growth period in the production media broth at 96th hour examined from a growth-flocculation kinetics study. 85.67% of bioflocculation was observed in oil-field formation water, with a separation of 68.7% of aliphatic hydrocarbon contents of the formation water after the application of the bacterial bioflocculant by entrapment mechanism with formation of flocs which was analyzed and examined comparatively through gas-chromatography. Extensive removal of heavy metal contents of the oil-field formation water due to bioflocculation was estimated by Atomic Absorption Spectrophotometer (AAS). The SEM and AFM studies declare the extracellular polymeric nature of the bioflocculant produced by this bacterium clumped within bacterial biofilm supported with FTIR study of the extracted bioflocculant.

Construction and characterization of molecular nonwoven fabrics consisting of cross-linked poly(γ-methyl-L-glutamate)

Molecular nonwoven fabrics in the form of ultrathin layer-by-layer (LbL) helical polymer films with covalent cross-linking were assembled on substrates by an alternate ester-amide exchange reaction between poly(γ-methyl L-glutamate) (PMLG) and cross-linking agent ethylene diamine or 4,4'-diamino azobenzene. The regular growth of helical monolayers without excessive adsorption and the formation of amide bonds were confirmed by ultraviolet-visible (UV-vis) spectrophotometry, quartz crystal microbalance (QCM), ellipsometry, and infrared reflection-absorption spectroscopy (IR-RAS) measurements. Nanostructures with high uniformity and ultrathin films with few defects formed by helical rod segments of PMLG were characterized by atomic force microscopy (AFM) and Kelvin probe force microscopy (KFM).

Light scattering evidence of selective protein fouling on biocompatible block copolymer micelles

Selective protein fouling on block copolymer micelles with well-known potential for tumour-targeting drug delivery was evidenced by using dynamic light scattering measurements. The stability and interaction of block copolymer micelles with model proteins (BSA, IgG, lysozyme and CytC) is reported for systems featuring a hydrophobic (poly[2-(diisopropylamino)-ethyl methacrylate]) (PDPA) core and hydrophilic coronas comprising poly(ethylene oxide)/poly(glycerol monomethacrylate) (PEO-b-PG2MA) or poly[2-(methacryloyloxy)ethyl phosphorylcholine] (PMPC). The results revealed that protein size and hydrophilic chain density play important roles in the observed interactions. The PEO(113)-b-PG2MA(30)-b-PDPA(50) nanoparticles are stable and protein adsorption is prevented at all investigated protein environments. The successful protein-repellent characteristic of these nanoparticles is attributed to a high hydrophilic surface chain density (>0.1 chains per nm(2)) and to the length of the hydrophilic chains. On the other hand, although PMPC also has protein-repellent characteristics, the low surface chain density of the hydrophilic shell is supposed to enable interactions with small proteins. The PMPC(40)-b-PDPA(70) micelles are stable in BSA and IgG environments due to weak repulsion forces between PMPC and the proteins, to the hydration layer, and particularly to a size-effect where the large BSA (R(H) = 4.2 nm) and IgG (R(H) = 7.0 nm) do not easily diffuse within the PMPC shell. Conversely, a clear interaction was observed with the 2.1 nm radius lysozyme. The lysozyme protein can diffuse within the PMPC micellar shell towards the PDPA hydrophobic core in a process favored by its smaller size and the low hydrophilic PMPC surface chain density (∼0.049 chains per nm(2)) as compared to PEO-b-PG2MA (∼0.110 chains per nm(2)). The same behavior was not evidenced with the 2.3 nm radius positively charged CytC, probably due to its higher surface hydrophilicity and the consequent chemical incompatibility with PDPA.

Synchrotron Radiation Spectroscopic Techniques as Tools for the Medicinal Chemist: Microprobe X-Ray Fluorescence Imaging, X-Ray Absorption Spectroscopy, and Infrared Microspectroscopy

This review updates the recent advances and applications of three prominent synchrotron radiation techniques, microprobe X-ray fluorescence spectroscopy/imaging, X-ray absorption spectroscopy, and infrared microspectroscopy, and highlights how these tools are useful to the medicinal chemist. A brief description of the principles of the techniques is given with emphasis on the advantages of using synchrotron radiation-based instrumentation rather than instruments using typical laboratory radiation sources. This review focuses on several recent applications of these techniques to solve inorganic medicinal chemistry problems, focusing on studies of cellular uptake, distribution, and biotransformation of established and potential therapeutic agents. The importance of using these synchrotron-based techniques to assist the development of, or validate the chemistry behind, drug design is discussed.

Vibrational spectroscopy: a clinical tool for cancer diagnostics

Vibrational spectroscopy techniques have demonstrated potential to provide non-destructive, rapid, clinically relevant diagnostic information. Early detection is the most important factor in the prevention of cancer. Raman and infrared spectroscopy enable the biochemical signatures from biological tissues to be extracted and analysed. In conjunction with advanced chemometrics such measurements can contribute to the diagnostic assessment of biological material. This paper also illustrates the complementary advantage of using Raman and FTIR spectroscopy technologies together. Clinical requirements are increasingly met by technological developments which show promise to become a clinical reality. This review summarises recent advances in vibrational spectroscopy and their impact on the diagnosis of cancer.