Secondary Structure Determination Research Articles

Isolation and characterization of rabies monoclonal antibody charge variants.

Current postexposure prophylaxis of rabies includes vaccines, human rabies immunoglobulin (RIG), equine RIG, and recombinant monoclonal antibodies (mAb). In the manufacturing of rabies recombinant mAb, charge variants are the most common source of heterogeneity. Charge variants of rabies mAb were isolated by salt gradient cation exchange chromatography (CEX) to separate acidic and basic and main charge variants. Separated variants were further extensively characterized using orthogonal analytical techniques, which include secondary and tertiary structure determination by far and near ultraviolet circular dichroism spectroscopy. Charge and size heterogeneity were evaluated using CEX, isoelectric focusing (IEF), capillary-IEF, size exclusion chromatography, sodium dodecyl sulfate polyacrylamide gel electrophoresis, and western blotting. Antigen binding affinity was assessed by enzyme linked immuno-sorbent assay and rapid florescence foci inhibition test. Results from structural and physicochemical characterizations concluded that charge variants are formed due to posttranslational modification demonstrating that the charge heterogeneity, these charge variants did neither show any considerable physicochemical change nor affect its biological function. This study shows that charge variants are effective components of mAb and there is no need of deliberate removal, until biological functions of rabies mAb will get affected.

1H, 15N and 13C resonance backbone and side-chain assignments and secondary structure determination of the BRCT domain of Mtb LigA.

The BRCA1 carboxyl-terminal (BRCT) domain, an evolutionarily conserved structural motif, is ubiquitous in a multitude of proteins spanning prokaryotic and eukaryotic organisms. In Mycobacterium tuberculosis (Mtb), BRCT domain plays a pivotal role in the catalytic activity of the NAD+-dependent DNA ligase (LigA). LigA is pivotal in DNA replication, catalyzing the formation of phosphodiester bonds in Okazaki fragments and repairing single-strand breaks in damaged DNA, essential for the survival of Mtb. Structural and functional aspects of LigA unveil its character as a highly modular protein, undergoing substantial conformational changes during its catalytic cycle. Although the BRCT domain of Mtb LigA plays an essential role in DNA binding and protein-protein interactions, the precise mechanism of action remains poorly understood. Unravelling the structure of the BRCT domain holds the promise of advancing our understanding of this pivotal domain. Additionally, it will facilitate further exploration of the protein-protein interactions and enhance our understanding of inter domain interactions within LigA, specifically between BRCT and the Adenylation domain. In this study, we demonstrate the overexpression of the BRCT domain of Mtb LigA and conduct its analysis using solution NMR spectroscopy, revealing a well-folded structure and we present the nearly complete chemical shift assignments of both backbone and sidechains. In addition, a secondary structure prediction by TALOS N predicts BRCT consisting of 3 α-helices and 4 β-sheets, closely resembling the typical structural topology of most BRCT domains.

DSSP in GROMACS: Tool for Defining Secondary Structures of Proteins in Trajectories.

This work describes a fast implementation of a software algorithm associated with determination of protein secondary structure based on the Define Secondary Structure of Proteins (DSSP) algorithm. This implementation is fully compatible with the DSSP v.4 and DSSP v.2 algorithms and implemented as a native GROMACS trajectory analysis module, which allows us to analyze molecular dynamics trajectories without any restrictions of the original DSSP implementation. This implementation works much faster than the original DSSP v.4 and DSSP v.2 algorithms.

Identification and prioritisation of potential vaccine candidates using subtractive proteomics and designing of a multi-epitope vaccine against Wuchereria bancrofti

This study employed subtractive proteomics and immunoinformatics to analyze the Wuchereria bancrofti proteome and identify potential therapeutic targets, with a focus on designing a vaccine against the parasite species. A comprehensive bioinformatics analysis of the parasite's proteome identified 51 probable therapeutic targets, among which "Kunitz/bovine pancreatic trypsin inhibitor domain-containing protein" was identified as the most promising vaccine candidate. The candidate protein was used to design a multi-epitope vaccine, incorporating B-cell and T-cell epitopes identified through various tools. The vaccine construct underwent extensive analysis of its antigenic, physical, and chemical features, including the determination of secondary and tertiary structures. Docking and molecular dynamics simulations were performed with HLA alleles, Toll-like receptor 4 (TLR4), and TLR3 to assess its potential to elicit the human immune response. Immune simulation analysis confirmed the predicted vaccine’s strong binding affinity with immunoglobulins, indicating its potential efficacy in generating an immune response. However, experimental validation and testing of this multi-epitope vaccine construct would be needed to assess its potential against W. bancrofti and even for a broader range of lymphatic filarial infections given the similarities between W. bancrofti and Brugia.

RNA structure profiling at single-cell resolution reveals new determinants of cell identity.

RNA structure is critical for multiple steps in gene regulation. However, how the structures of transcripts differ both within and between individual cells is unknown. Here we develop a SHAPE-inspired method called single-cell structure probing of RNA transcripts that enables simultaneous determination of transcript secondary structure and abundance at single-cell resolution. We apply single-cell structure probing of RNA transcripts to human embryonic stem cells and differentiating neurons. Remarkably, RNA structure is more homogeneous in human embryonic stem cells compared with neurons, with the greatest homogeneity found in coding regions. More extensive heterogeneity is found within 3' untranslated regions and is determined by specific RNA-binding proteins. Overall RNA structure profiles better discriminate cell type identity and differentiation stage than gene expression profiles alone. We further discover a cell-type variable region of 18S ribosomal RNA that is associated with cell cycle and translation control. Our method opens the door to the systematic characterization of RNA structure-function relationships at single-cell resolution.

DichroIDP: a method for analyses of intrinsically disordered proteins using circular dichroism spectroscopy

Intrinsically disordered proteins (IDPs) are comprised of significant numbers of residues that form neither helix, sheet, nor any other canonical type of secondary structure. They play important roles in a broad range of biological processes, such as molecular recognition and signalling, largely due to their chameleon-like ability to change structure from unordered when free in solution to ordered when bound to partner molecules. Circular dichroism (CD) spectroscopy is a widely-used method for characterising protein secondary structures, but analyses of IDPs using CD spectroscopy have suffered because the methods and reference datasets used for the empirical determination of secondary structures do not contain adequate representations of unordered structures. This work describes the creation, validation and testing of a standalone Windows-based application, DichroIDP, and a new reference dataset, IDP175, which is suitable for analyses of proteins containing significant amounts of disordered structure. DichroIDP enables secondary structure determinations of IDPs and proteins containing intrinsically disordered regions.

Roadmap for Postnatal Brain Maturation: Changes in Gray and White Matter Composition during Development Measured by Fourier Transformed Infrared Microspectroscopy.

Key events in postnatal brain development, such as neuronal migration, synaptogenesis, and myelination, shape the adult brain. These events are reflected in changes in gray and white matter (GM and WM) occurring during this period. Therefore, precise knowledge of GM and WM composition in perinatal brain development is crucial to characterizing brain formation as well as the neurodevelopmental disruption observed in diseases such as autism and schizophrenia. In this study, we combined histochemical and immunohistochemical staining with biochemical and biophysical analyses using Fourier transform infrared (IR) microspectroscopy (μFTIR) to better understand the chemical changes during postnatal developmental myelination. For this purpose, we analyzed the GM and WM in the mouse brain and cerebellum (strain C57BL/6) from postnatal day 0 (P0) to day P28 and established presumed correlations between staining and IR data. IR spectra allowed the (i) quantification of lipid and protein content through the CH2/amide I ratio, (ii) determination of chemical characteristics of lipids, such as the presence of unsaturated bonds in the carbonate chain or carbonyls from ester groups in the polar head, and (iii) determination of the protein secondary structure (α-helix and intramolecular β-sheets). The results indicate that the increase in the CH2/amide I ratio calculated from the μFTIR data correlates well with lipid histochemical staining. IR data indicated a change in the lipid composition in WM since carbonyl and unsaturated olefinic groups do not increase when lipids accumulate during myelination. Our correlation analysis between IR data and immunohistochemical staining of myelin-associated proteins revealed that myelin oligodendrocyte protein correlated well with lipid accumulation, while myelin basic protein appeared before lipid modifications, which indicated that myelin-associated proteins and lipid deposition were not synchronic. These events were related to a decrease in the intramolecular β/α protein ratio. Our results indicate that lipids and proteins in WM substantially change their composition due to primary myelination, and according to results obtained from staining, these modifications are better described by lipid histochemical staining than by immunohistochemistry against myelin-related proteins. In conclusion, μFTIR can be a useful technique to study WM during perinatal development and provide detailed information about alterations in the chemical composition related to neurodevelopmental diseases.

Structure Elucidation of Secondary Metabolites: Current Frontiers and Lingering Pitfalls.

Analytical methods allow for the structure determination of submilligram quantities of complex secondary metabolites. This has been driven in large part by advances in NMR spectroscopic capabilities, including access to high-field magnets equipped with cryogenic probes. Experimental NMR spectroscopy may now be complemented by remarkably accurate carbon-13 NMR calculations using state-of-the-art DFT software packages. Additionally, microED analysis stands to have a profound effect on structure elucidation by providing X-ray-like images of microcrystalline samples of analytes. Nonetheless, lingering pitfalls in structure elucidation remain, particularly for isolates that are unstable or highly oxidized. In this Account, we discuss three projects from our laboratory that highlight nonoverlapping challenges to the field, with implications for chemical, synthetic, and mechanism of action studies. We first discuss the lomaiviticins, complex unsaturated polyketide natural products disclosed in 2001. The original structures were derived from NMR, HRMS, UV-vis, and IR analysis. Owing to the synthetic challenges presented by their structures and the absence of X-ray crystallographic data, the structure assignments remained untested for nearly two decades. In 2021, the Nelson group at Caltech carried out microED analysis of (-)-lomaiviticin C, leading to the startling discovery that the original structure assignment of the lomaiviticins was incorrect. Acquisition of higher-field (800 MHz 1H, cold probe) NMR data as well as DFT calculations provided insights into the basis for the original misassignment and lent further support to the new structure identified by microED. Reanalysis of the 2001 data set reveals that the two structure assignments are nearly indistinguishable, underscoring the limitations of NMR-based characterization. We then discuss the structure elucidation of colibactin, a complex, nonisolable microbiome metabolite implicated in colorectal cancer. The colibactin biosynthetic gene cluster was detected in 2006, but owing to colibactin's instability and low levels of production, it could not be isolated or characterized. We used a combination of chemical synthesis, mechanism of action studies, and biosynthetic analysis to identify the substructures in colibactin. These studies, coupled with isotope labeling and tandem MS analysis of colibactin-derived DNA interstrand cross-links, ultimately led to a structure assignment for the metabolite. We then discuss the ocimicides, plant secondary metabolites that were studied as agents against drug-resistant P. falciparum. We synthesized the core structure of the ocimicides and found significant discrepancies between our experimental NMR spectroscopic data and that reported for the natural products. We determined the theoretical carbon-13 NMR shifts for 32 diastereomers of the ocimicides. These studies indicated that a revision of the connectivity of the metabolites is likely needed. We end with some thoughts on the frontiers of secondary metabolite structure determination. As modern NMR computational methods are straightforward to execute, we advocate for their systematic use in validating the assignments of novel secondary metabolites.

Determination of Secondary Structure of Proteins by Nanoinfrared Spectroscopy.

Nanoscale infrared spectroscopy (AFMIR) is becoming an important tool for the analysis of biological sample, in particular protein assemblies, at the nanoscale level. While the amide I band is usually used to determine the secondary structure of proteins in Fourier transform infrared spectroscopy, no tool has been developed so far for AFMIR. The paper introduces a method for the study of secondary structure of protein based on a protein library of 38 well-characterized proteins. Ascending stepwise linear regression (ASLR) and partial least square (PLS) regression were used to correlate spectrum characteristic bands with the major secondary structures (α-helixes and β-sheets). ASLR appears to provide better results than PLS. The secondary structure predictions are characterized by a root mean square standard error in a cross validation of 6.39% for α-helixes and 6.23% for β-sheets.

The influence of random-coil chemical shifts on the assessment of structural propensities in folded proteins and IDPs.

In studying secondary structural propensities of proteins by nuclear magnetic resonance (NMR) spectroscopy, secondary chemical shifts (SCSs) serve as the primary atomic scale observables. For SCS calculation, the selection of an appropriate random coil chemical shift (RCCS) dataset is a crucial step, especially when investigating intrinsically disordered proteins (IDPs). The scientific literature is abundant in such datasets, however, the effect of choosing one over all the others in a concrete application has not yet been studied thoroughly and systematically. Hereby, we review the available RCCS prediction methods and to compare them, we conduct statistical inference by means of the nonparametric sum of ranking differences and comparison of ranks to random numbers (SRD-CRRN) method. We try to find the RCCS predictors best representing the general consensus regarding secondary structural propensities. The existence and the magnitude of resulting differences on secondary structure determination under varying sample conditions (temperature, pH) are demonstrated and discussed for globular proteins and especially IDPs.

Comparative In Silico Analysis and Functional Characterization of TANK-Binding Kinase 1-Binding Protein 1.

Protein modelling plays a vital role in the drug discovery process. TANK-binding kinase 1-binding protein 1 is also called an adapter protein, which is encoded by gene TBK1 present in Homo sapiens. It is found in lungs, small intestine, leukocytes, heart, placenta, muscle, kidney, lower level of thymus, and brain. It has a number of protein-binding sites, to which TBK1 and IKBKE bind and perform different functions as immunomodulatory, antiproliferative, and antiviral innate immunity which release different types of interferons. Our study predicts the comparative model of 3-dimensional (3D) structure through different bioinformatics tools that will be helpful for further studies in future. The reactivity and stability of these proteins were evaluated physicochemically and through domain determination and prediction of secondary structure using bioinformatics methods such as ProtParam, Pfam, and SOPMA, respectively. Robetta, an ab initio approach, I-TASSER, and AlphaFold was used for 3D structure prediction, and the models were validated using the SAVESv6.0 (PROCHECK) server. Conclusively, the best 3D structure of TBK1-binding protein 1 was predicted using Robetta software. After unveiling the 3D structure of the novel protein, we concluded that this structure will help us to find out its role other than in antiviral innate immunity and by producing torsion in its 3D structure researchers will be able to detect either this protein is involved in any disease or not because according to previous studies it was not associated with any disease.

Forbidden Secondary Structures Found in Gel-Forming Fibrils of Glycylphenylalanylglycine.

The zwitterionic l-tripeptide glycylphenylalanylglycine self-assembles into very long crystalline fibrils in an aqueous solution, which causes the formation of an exceptionally strong gel phase (G' ∼ 5 × 106 Pa). The Rietveld refinement analysis of its powder X-ray diffraction (PXRD) pattern reveals a unit cell with four peptides forming a P212121 space group and adopting an inverse polyproline II conformation, that is, a right-handed helical structure that occupies the "forbidden" region of the Ramachandran plot. This unusual structure is stabilized by a plethora of intermolecular interactions facilitated by the large number of different functional groups of the unblocked tripeptide. Comparisons of simulated and experimental Fourier transform infrared and vibrational circular dichroism (VCD) amide I' profiles corroborate the PXRD structure. Our experimental setup reduces the sample to a quasi-two-dimensional network of fibrils. We exploited the influence of this reduced dimensionality on the amide I VCD to identify the main fibril axis. We demonstrate that PXRD, vibrational spectroscopy, and amide I simulations provide a powerful toolset for secondary structure and fibril axis determination.

1H, 13C, 15 N backbone and side-chain NMR assignments for three MAX effectors from Magnaporthe oryzae

Effectors are small and very diverse proteins secreted by fungi and translocated in plant cells during infection. Among them, MAX effectors (for Magnaporthe Avrs and ToxB) were identified as a family of effectors that share an identical fold topology despite having highly divergent sequences. They are mostly secreted by ascomycetes from the Magnaporthe genus, a fungus that causes the rice blast, a plant disease leading to huge crop losses. As rice is the first source of calories in many countries, especially in Asia and Africa, this constitutes a threat for world food security. Hence, a better understanding of these effectors, including structural and functional characterization, constitutes a strategic milestone in the fight against phytopathogen fungi and may give clues for the development of resistant varieties of rice. We report here the near complete 1H, 15N and 13C NMR resonance assignment of three new putative MAX effectors (MAX47, MAX60 and MAX67). Secondary structure determination using TALOS-N and CSI.3 demonstrates a high content of β-strands in all the three proteins, in agreement with the canonic ß-sandwich structure of MAX effectors. This preliminary study provides foundations for further structural characterization, that will help in turn to improve sequence predictions of other MAX effectors through data mining.

BeStSel: webserver for secondary structure and fold prediction for protein CD spectroscopy.

Circular dichroism (CD) spectroscopy is widely used to characterize the secondary structure composition of proteins. To derive accurate and detailed structural information from the CD spectra, we have developed the Beta Structure Selection (BeStSel) method (PNAS, 112, E3095), which can handle the spectral diversity of β-structured proteins. The BeStSel webserver provides this method with useful accessories to the community with the main goal to analyze single or multiple protein CD spectra. Uniquely, BeStSel provides information on eight secondary structure components including parallel β-structure and antiparallel β-sheets with three different groups of twist. It overperforms any available method in accuracy and information content, moreover, it is capable of predicting the protein fold down to the topology/homology level of the CATH classification. A new module of the webserver helps to distinguish intrinsically disordered proteins by their CD spectrum. Secondary structure calculation for uploaded PDB files will help the experimental verification of protein MD and in silico modelling using CD spectroscopy. The server also calculates extinction coefficients from the primary sequence for CD users to determine the accurate protein concentrations which is a prerequisite for reliable secondary structure determination. The BeStSel server can be freely accessed at https://bestsel.elte.hu.

Machine learning recognition of protein secondary structures based on two-dimensional spectroscopic descriptors

Protein secondary structure discrimination is crucial for understanding their biological function. It is not generally possible to invert spectroscopic data to yield the structure. We present a machine learning protocol which uses two-dimensional UV (2DUV) spectra as pattern recognition descriptors, aiming at automated protein secondary structure determination from spectroscopic features. Accurate secondary structure recognition is obtained for homologous (97%) and nonhomologous (91%) protein segments, randomly selected from simulated model datasets. The advantage of 2DUV descriptors over one-dimensional linear absorption and circular dichroism spectra lies in the cross-peak information that reflects interactions between local regions of the protein. Thanks to their ultrafast (∼200 fs) nature, 2DUV measurements can be used in the future to probe conformational variations in the course of protein dynamics.

Development of Pyrazole Harbouring Novel Leads Against β-Amyloid Protein Fibrillation by in silico Drug Design

Amyloid [Formula: see text] (A[Formula: see text]) peptide monomers polymerize to form insoluble amyloid fibril aggregates and accumulate as senile plaques which eventually leads to cognitive impairment. Modulating abnormal amyloid aggregation can be considered a therapeutic target for Alzheimer’s disease. Recent studies support that Curcumin interferes with larger protein aggregate formation by destabilizing the salt bridge (Asp 23-Lys 28) of A[Formula: see text] protein. The chemical library of curcumin derivative with pyrazole, isoxazole, and isothiazole showed considerable binding affinity comparable to that of curcumin. In silico docking studies of the library of the compound, revealed strong binding affinity with A[Formula: see text] protein and [Formula: see text]-secretase enzyme (BACE1). De novo ligand design coupled with manual pharmacophore mapping of our best-fitting lead revealed another ligand having a potential binding affinity with both A[Formula: see text] protein and BACE-1. Both the compounds passed Lipinski’s Rule of Five, in silico toxicity testing by admetSAR, and pharmacophore overlaps with Verubecestat, a compound under clinical trial against Alzheimer’s disease. MD dynamic simulation study revealed the stability of protein after it binds to our ligand. Secondary structure determination was also done to observe the changes in [Formula: see text] and [Formula: see text] sheets of the protein with and without ligand binding. Ligand-based drug design was also carried out via pharmacophore mapping and searching the molecules via zinc database.

QCL-IR Spectroscopy for In-Line Monitoring of Proteins from Preparative Ion-Exchange Chromatography.

In this study, an external cavity-quantum cascade laser-based mid-infrared (IR) spectrometer was applied for in-line monitoring of proteins from preparative ion-exchange chromatography. The large optical path length of 25 μm allowed for robust spectra acquisition in the broad tuning range between 1350 and 1750 cm–1, covering the most important spectral region for protein secondary structure determination. A significant challenge was caused by the overlapping mid-IR bands of proteins and changes in the background absorption of water due to the NaCl gradient. Implementation of advanced background compensation strategies resulted in high-quality protein spectra in three different model case studies. In Case I, a reference blank run was directly subtracted from a sample run with the same NaCl gradient. Case II and III included sample runs with different gradient profiles than the one from the reference run. Here, a novel compensation approach based on a reference spectra matrix was introduced, where the signal from the conductivity detector was employed for correlating suitable reference spectra for correction of the sample run spectra. With this method, a single blank run was sufficient to correct various gradient profiles. The obtained IR spectra of hemoglobin and β-lactoglobulin were compared to off-line reference measurements, showing excellent agreement for all case studies. Moreover, the concentration values obtained from the mid-IR spectrometer agreed well with conventional UV detectors and high-performance liquid chromatography off-line measurements. LC–QCL–IR coupling thus holds high potential for replacing laborious and time-consuming off-line methods for protein monitoring in complex downstream processes.

The Extended Hadamard Transform: Sensitivity-Enhanced NMR Experiments Among Labile and Non-Labile 1 Hs of SARS-CoV-2-derived RNAs.

Hadamard encoded saturation transfer can significantly improve the efficiency of NOE‐based NMR correlations from labile protons in proteins, glycans and RNAs, increasing the sensitivity of cross‐peaks by an order of magnitude and shortening experimental times by ≥100‐fold. These schemes, however, fail when tackling correlations within a pool of labile protons – for instance imino‐imino correlations in RNAs or amide‐amide correlations in proteins. Here we analyze the origin of the artifacts appearing in these experiments and propose a way to obtain artifact‐free correlations both within the labile pool as well as between labile and non‐labile 1Hs, while still enjoying the gains arising from Hadamard encoding and solvent repolarizations. The principles required for implementing what we define as the extended Hadamard scheme are derived, and its clean, artifact‐free, sensitivity‐enhancing performance is demonstrated on RNA fragments derived from the SARS‐CoV‐2 genome. Sensitivity gains per unit time approaching an order of magnitude are then achieved in both imino‐imino and imino‐amino/aromatic protons 2D correlations; similar artifact‐free sensitivity gains can be observed when carrying out extended Hadamard encodings of 3D NOESY/HSQC‐type experiments. The resulting spectra reveal significantly more correlations than their conventionally acquired counterparts, which can support the spectral assignment and secondary structure determination of structured RNA elements.

Curcumin Analogues as a Potential Drug against Antibiotic Resistant Protein, β-Lactamases and L, D-Transpeptidases Involved in Toxin Secretion in Salmonella typhi: A Computational Approach

Typhoid fever caused by the bacteria Salmonella typhi gained resistance through multidrug-resistant S. typhi strains. One of the reasons behind β-lactam antibiotic resistance is -lactamase. L, D-Transpeptidases is responsible for typhoid fever as it is involved in toxin release that results in typhoid fever in humans. A molecular modeling study of these targeted proteins was carried out by various methods, such as homology modeling, active site prediction, prediction of disease-causing regions, and by analyzing the potential inhibitory activities of curcumin analogs by targeting these proteins to overcome the antibiotic resistance. The five potent drug candidate compounds were identified to be natural ligands that can inhibit those enzymes compared to controls in our research. The binding affinity of both the Go-Y032 and NSC-43319 were found against β-lactamase was −7.8 Kcal/mol in AutoDock, whereas, in SwissDock, the binding energy was −8.15 and −8.04 Kcal/mol, respectively. On the other hand, the Cyclovalone and NSC-43319 had an equal energy of −7.60 Kcal/mol in AutoDock, whereas −7.90 and −8.01 Kcal/mol in SwissDock against L, D-Transpeptidases. After the identification of proteins, the determination of primary and secondary structures, as well as the gene producing area and homology modeling, was accomplished. The screened drug candidates were further evaluated in ADMET, and pharmacological properties along with positive drug-likeness properties were observed for these ligand molecules. However, further in vitro and in vivo experiments are required to validate these in silico data to develop novel therapeutics against antibiotic resistance.

NMR signal assignments afnd secondary structure determination of the N-terminal domain of the ribosome maturation factor M from Staphylococcus aureus

NMR signal assignments afnd secondary structure determination of the N-terminal domain of the ribosome maturation factor M from Staphylococcus aureus