Structure Of Globular Proteins Research Articles

AIUPred: combining energy estimation with deep learning for the enhanced prediction of protein disorder.

Intrinsically disordered proteins and protein regions (IDPs/IDRs) carry out important biological functions without relying on a single well-defined conformation. As these proteins are a challenge to study experimentally, computational methods play important roles in their characterization. One of the commonly used tools is the IUPred web server which provides prediction of disordered regions and their binding sites. IUPred is rooted in a simple biophysical model and uses a limited number of parameters largely derived on globular protein structures only. This enabled an incredibly fast and robust prediction method, however, its limitations have also become apparent in light of recent breakthrough methods using deep learning techniques. Here, we present AIUPred, a novel version of IUPred which incorporates deep learning techniques into the energy estimation framework. It achieves improved performance while keeping the robustness of the original method. Based on the evaluation of recent benchmark datasets, AIUPred scored amongst the top three single sequence based methods. With a new web server we offer fast and reliable visual analysis for users as well as options to analyze whole genomes in mere seconds with the downloadable package. AIUPred is available at https://aiupred.elte.hu.

Controlling spatiotemporal mechanics of globular protein-polymer hydrogel via metal-coordination interactions

Mechanical properties of hydrogels are dependent on their spatial and temporal structural properties. Several attempts have been made to tune the mechanical properties of hydrogels either through controlling spatial or temporal design elements. However, controlling both elements simultaneously still proves to be extremely difficult and elusive. This goal could be achieved by combining the function and structure of globular proteins with the versatility of synthetic polymers to form a hybrid hydrogel. In this study, a physically crosslinked protein-polymer hydrogel (PPH) was synthesized. As a model globular protein, bovine serum albumin (BSA) was used together with poly(methacrylamide) to control hydrogel spatiotemporal mechanics. In order to control the temporal hierarchy (crosslinking kinetics) we used the coordination sites of BSA to create metal-coordination crosslinks, while the folding-unfolding of BSA triggered by specific metal ions was exploited to define the network architecture (spatial hierarchy). Mechanical properties, relaxation times, and microstructure were found to be affected by the nature of metal ions in the PPHs. It is anticipated that understanding of spatiotemporal mechanics will facilitate the development of novel PPHs with fine-tuned mechanical properties.

The refinement of the parameters of β-turns using neutron diffraction data

Beta-bends are a difficult to interpret type of polypeptide chain backbone structure of globular proteins. Beta-bends are usually classified according to the dihedral angles φ and ψ of amino acid residues i + 1 and i + 2. Ramachandran map analysis of amino acid residues i + 1 and i + 2 indicates the resulting conformational stresses in bending. The mechanism of stabilization of their energetically disadvantageous conformations is still unclear. This kind of conformation stresses can only be compensated by additional interactions, such as additional hydrogen bonds, whose geometry and energy compensates for the beta-bending stress. Neutronography is the only available direct method for determining the position of hydrogen atoms in the structures of chemical compounds, including proteins. In this work, beta-bends from 176 protein structures from PDB established by neutronography are studied. In these structures, 3733 beta-bends were found using the i → i + 3 hydrogen bonding criterion. Using clustering by the magnitude of conformational angles, eight types of bends were newly identified. The magnitudes of conformational angles for each type of bend were determined. The hypothesis of additional hydrogen bonding to stabilize the bend was not confirmed, suggesting that the bending stress is compensated by other factors.

Protein intrinsically disordered regions have a non-random, modular architecture.

Protein sequences can be broadly categorized into two classes: those which adopt stable secondary structure and fold into a domain (i.e. globular proteins), and those that do not. The sequences belonging to this latter class are conformationally heterogeneous and are described as being intrinsically disordered. Decades of investigation into the structure and function of globular proteins has resulted in a suite of computational tools that enable their sub-classification by domain type, an approach that has revolutionized how we understand and predict protein functionality. Conversely, it is unknown if sequences of disordered protein regions are subject to broadly generalizable organizational principles that would enable their sub-classification. Here, we report the development of a statistical approach that quantifies linear variance in amino acid composition across a sequence. With multiple examples, we provide evidence that intrinsically disordered regions are organized into statistically non-random modules of unique compositional bias. Modularity is observed for both low and high-complexity sequences and, in some cases, we find that modules are organized in repetitive patterns. These data demonstrate that disordered sequences are non-randomly organized into modular architectures and motivate future experiments to comprehensively classify module types and to determine the degree to which modules constitute functionally separable units analogous to the domains of globular proteins. The source code, documentation, and data to reproduce all figures are freely available at https://github.com/MWPlabUTSW/Chi-Score-Analysis.git. The analysis is also available as a Google Colab Notebook (https://colab.research.google.com/github/MWPlabUTSW/Chi-Score-Analysis/blob/main/ChiScore_Analysis.ipynb).

Small angle X-ray scattering investigation of ionic liquid effect on the aggregation behavior of globular proteins

Globular proteins are well-folded model proteins, where ions can substantially influence their structure and aggregation. Ionic liquids (ILs) are salts in the liquid state with versatile ion combinations. Understanding the IL effect on protein behavior remains a major challenge. Here, we employed small angle X-ray scattering to investigate the effect of aqueous ILs on the structure and aggregation of globular proteins, namely, hen egg white lysozyme (Lys), human lysozyme (HLys), myoglobin (Mb), β-lactoglobulin (βLg), trypsin (Tryp) and superfolder green fluorescent protein (sfGFP). The ILs contain ammonium-based cations paired with the mesylate, acetate or nitrate anion. Results showed that only Lys was monomeric, whereas the other proteins formed small or large aggregates in buffer. Solutions with over 17 mol% IL resulted in significant changes in the protein structure and aggregation. The Lys structure was expanded at 1 mol% but compact at 17 mol% with structural changes in loop regions. HLys formed small aggregates, with the IL effect similar to Lys. Mb and βLg mostly had distinct monomer and dimer distributions depending on IL type and IL concentration. Complex aggregation was noted for Tryp and sfGFP. While the anion had the largest ion effect, changing the cation also induced the structural expansion and protein aggregation.

Point-of-care detection of Japanese encephalitis virus biomarker in clinical samples using a portable smartphone-enabled electrochemical "Sensit" device.

Japanese encephalitis (JE), a neglected tropical zoonotic disease prevalent in south-east Asian and western pacific countries, caused by the flavivirus JE virus (JEV), has a dearth of electrochemical point-of-care (PoC) diagnostic tools available to manage endemic breakouts. To overcome this, we have developed a screen-printed carbon electrode (SPCE) immunosensor for rapid PoC detection of JEV nonstructural 1 (NS1) antigen (Ag), found circulating in serum of infected individuals using a smartphone based portable "Sensit" device. The modification of SPCE surface with JEV NS1 antibody (Ab) was confirmed via observation of globular protein structures via scanning electron microscopy (SEM), increase in electrode surface hydrophilicity via contact angle measurement and decrease in current via differential pulse voltammetry (DPV). The fabrication and testing parameters were optimized based on highest current output obtained using DPV. The SPCE was tested for detection limit of target JEV NS1 Ag ranging from 1fM to 1μM, which was determined as 0.45 fM in spiked serum. The disposable immunosensor was also found to be highly specific in detecting JEV NS1 Ag over other flaviviral NS1 Ag. Finally, the modified SPCE was clinically validated by testing 62 clinical JEV samples using both a portable miniaturized electrochemical "Sensit" device coupled with a smartphone and a laboratory-based potentiostat. The results were corroborated with gold-standard RT-PCR and showed 96.77% accuracy, 96.15% sensitivity, and 97.22% specificity. Hence, this technique may further be developed into a one-step rapid diagnostic tool for JEV, especially in rural areas.

CHARMM-GUI bicelle builder for modeling and simulations of bicelle systems.

Bicelles are a morphology consisting of phospholipids and detergent molecules, which is generally described by q (q = [lipid]/[detergent]). Bicelles are model membranes valuable for structural studies of lipid membranes and protein structures. For example, the membrane proteins can be embedded into bicelles and the size of bicelles can be controlled small enough, and thus one can utilize solid-state or solution-state NMR spectroscopy for their studies. In addition, the magnetically aligned bicelles and isotropic bicelles are respectively useful for studies of globular protein structures and protein-membrane interactions. Despite the importance of understanding the bicelle structures at the atomistic level, computational approach is limited as preparation of such systems is arduous and requires much effort. In this study, we introduce CHARMM-GUI Bicelle Builder, a web-based platform for modeling and simulations of bicelle systems, present its applications by employing various detergents on top of the 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) lipids, and compare our results with experimental observations. CHARMM-GUI Bicelle Builder will help researchers to obtain a better understanding of not only bicelle itself, but also atomistic-level structure of membrane proteins that are not easily accessible from experimental approaches.

Constrained Layer Assignment for the Protein Burial Folding Code Accounting for Chain Connectivity.

The connection between protein sequences and tertiary structures has intrigued investigators for decades. A plausible hypothesis for the coding scheme postulates that atomic burial information obtainable from the sequence could be sufficient for structural determination when combined to sequence-independent constraints. Accordingly, folding simulations using native burial information expressed by atomic central distances, discretized into a small number L of equiprobable burial layers, have indeed been successful in reaching and distinguishing the native structure of several globular proteins. Attempted predictions of layers from sequence, however, turned out to be insufficiently accurate for most proteins. Here we explore the possibility that a nonuniform assignment of layers, which is intended to account for constraints imposed by chain connectivity, might provide a more efficient burial encoding of tertiary structures. We consider the condition that adjacent Cα-atoms along the sequence cannot occupy nonadjacent layers, in which case the information required to specify sequences of burials would be smaller. It is shown that appropriate folding behavior can still be observed in this explicitly more constrained scenario with a structure-dependent assignment intended to produce the thinnest possible layers still compatible with the imposed burial constraint. This thinnest assignment turns out to be sufficiently restrictive for the observed examples and provides appropriately thinner layers or, equivalently, a larger number of layers, for examples previously observed to indeed require more restrictive constraints when compared to counterparts of similar size, as well as the appropriate increase in number of layers for larger proteins. Implications for the general understanding of the protein folding code are discussed.

On the Possible Spatial Structures of the β-Amyloid

Spatial models of the β - structures of protein molecules, forming layers of amino acids, in principle, of unlimited length for both antiparallel and parallel conformation have been constructed. It is shown that the simplified flat Pauling models do not reflect the spatial structure of these layers. Using the recently developed theory of higher-dimensional polytopic prismahedrons, models of the volumetric filling of space with amino acid molecules are constructed. The constructed models for the first time mathematically describe the native structures of globular proteins.

Building blocks of protein structures: Physics meets biology.

The native state structures of globular proteins are stable and well packed indicating that self-interactions are favored over protein-solvent interactions under folding conditions. We use this as a guiding principle to derive the geometry of the building blocks of protein structures-α helices and strands assembled into β sheets-with no adjustable parameters, no amino acid sequence information, and no chemistry. There is an almost perfect fit between the dictates of mathematics and physics and the rules of quantum chemistry. Protein evolution is facilitated by sequence-independent platforms, which can elaborate sequence-dependent functional diversity. Our work highlights the vital role of discreteness in life and may have implications for the creation of artificial life and on the nature of life elsewhere in the cosmos.

Brownian motion, spin diffusion and protein structure determination in solution

This paper presents my recollections on the development of protein structure determination by NMR in solution from 1968 to 1992. The key to success was to identify NMR-accessible parameters that unambiguously determine the spatial arrangement of polypeptide chains. Inspired by work with cyclopeptides, model considerations showed that enforcing short non-bonding interatomic distances imposes «ring closure conditions» on polypeptide chains. Given that distances are scalar parameters, this indicated an avenue for studies of proteins in solution, i.e., under the regime of stochastic rotational and translational motions at frequencies in the nanosecond range (Brownian motion), where sharp pictures could not be obtained by photography-related methods. Later-on, we used distance geometry calculations with sets of inter-atomic distances derived from protein crystal structures to confirm that measurements of short proton—proton distances could provide atomic-resolution structures of globular proteins. During the years 1976–1984 the following four lines of research then led to protein structure determination by NMR in solution. First, the development of NMR experiments enabling the use of the nuclear Overhauser effect (NOE) for measurements of interatomic distances between pairs of hydrogen atoms in proteins. Second, obtaining sequence-specific resonance assignment solved the “phase problem” for protein structure determination by NMR. Third, generating and programming novel distance geometry algorithms enabled the calculation of atomic-resolution protein structures from limited sets of distance constraints measured by NMR. Fourth, the introduction of two-dimensional NMR provided greatly improved spectral resolution of the complex spectra of proteins as well as efficient delineation of scalar and dipole–dipole 1H–1H connectivities, thus making protein structure determination in solution viable and attractive.

Consistent Force Field Captures Homologue-Resolved HP1 Phase Separation.

Many proteins have been shown to function via liquid-liquid phase separation. Computational modeling could offer much needed structural details of protein condensates and reveal the set of molecular interactions that dictate their stability. However, the presence of both ordered and disordered domains in these proteins places a high demand on the model accuracy. Here, we present an algorithm to derive a coarse-grained force field, MOFF, which can model both ordered and disordered proteins with consistent accuracy. It combines maximum entropy biasing, least-squares fitting, and basic principles of energy landscape theory to ensure that MOFF recreates experimental radii of gyration while predicting the folded structures for globular proteins with lower energy. The theta temperature determined from MOFF separates ordered and disordered proteins at 300 K and exhibits a strikingly linear relationship with amino acid sequence composition. We further applied MOFF to study the phase behavior of HP1, an essential protein for post-translational modification and spatial organization of chromatin. The force field successfully resolved the structural difference of two HP1 homologues despite their high sequence similarity. We carried out large-scale simulations with hundreds of proteins to determine the critical temperature of phase separation and uncover multivalent interactions that stabilize higher-order assemblies. In all, our work makes significant methodological strides to connect theories of ordered and disordered proteins and provides a powerful tool for studying liquid-liquid phase separation with near-atomistic details.

Identifying Native and Non-native Membrane Protein Loops by Using Stabilizing Energetic Terms of Three Popular Force Fields

Background: Predicting the three-dimensional structure of globular proteins from their amino acid sequence has reached a fair accuracy, but predicting the structure of membrane proteins, especially loop regions, is still a difficult task in structural bioinformatics. The difficulty in predicting membrane loops is due to various factors like length variation, position, flexibility, and they are easily prone to mutation. Objective: In the present work, we address the problem of identifying and ranking near-native loops from a set of decoys generated by Monte-Carlo simulations. Methods: We systematically analyzed native and generated non-native decoys to develop a scoring function. The scoring function uses four important stabilizing energy terms from three popular force fields, such as FOLDX, OPLS, and AMBER, to identify and rank near-native membrane loops. Results: The results reveal better discrimination of native and non-natives and perform poor prediction in binary classifying native and near-native defined based on Root Mean Square Deviation (RMSD), Global Distance Test (GDT), and Template Modeling (TM) score, respectively. Conclusions: From our observations, we conclude that the important energy features described here may help to improve the loop prediction when the membrane protein database size increases.

Comparative roles of charge, π, and hydrophobic interactions in sequence-dependent phase separation of intrinsically disordered proteins

Endeavoring toward a transferable, predictive coarse-grained explicit-chain model for biomolecular condensates underlain by liquid-liquid phase separation (LLPS) of proteins, we conducted multiple-chain simulations of the N-terminal intrinsically disordered region (IDR) of DEAD-box helicase Ddx4, as a test case, to assess roles of electrostatic, hydrophobic, cation-π, and aromatic interactions in amino acid sequence-dependent LLPS. We evaluated three different residue-residue interaction schemes with a shared electrostatic potential. Neither a common hydrophobicity scheme nor one augmented with arginine/lysine-aromatic cation-π interactions consistently accounted for available experimental LLPS data on the wild-type, a charge-scrambled, a phenylalanine-to-alanine (FtoA), and an arginine-to-lysine (RtoK) mutant of Ddx4 IDR. In contrast, interactions based on contact statistics among folded globular protein structures reproduce the overall experimental trend, including that the RtoK mutant has a much diminished LLPS propensity. Consistency between simulation and experiment was also found for RtoK mutants of P-granule protein LAF-1, underscoring that, to a degree, important LLPS-driving π-related interactions are embodied in classical statistical potentials. Further elucidation is necessary, however, especially of phenylalanine's role in condensate assembly because experiments on FtoA and tyrosine-to-phenylalanine mutants suggest that LLPS-driving phenylalanine interactions are significantly weaker than posited by common statistical potentials. Protein-protein electrostatic interactions are modulated by relative permittivity, which in general depends on aqueous protein concentration. Analytical theory suggests that this dependence entails enhanced interprotein interactions in the condensed phase but more favorable protein-solvent interactions in the dilute phase. The opposing trends lead to only a modest overall impact on LLPS.

Effects of heat treatment and stabilizing salts supplementation on the physicochemical properties, protein structure and salts balance of goat milk

This study investigated the effects of heat treatment and stabilizing salts on the physicochemical properties, protein structure and salt balance of goat milk. Heat treatment altered the quantity of sediment (peak width) and particle concentration (delta backscattering) of goat milk observed in Turbiscan spectrograms. A higher Turbiscan Stability Index, and greater sediment thickness and velocity were observed in UHT goat milk than in UHT cow milk, indicating poorer heat stability of goat milk than cow milk. The poor heat stability of goat milk might be caused by the heat-induced conversion from stretching structure (β-sheet and β-turn) to globurizing structure (random coil and α-helix) of protein, and changes in distributions of proteins (β-CN, αs1-CN, αs2-CN, κ-CN, β-LG and α-LA), calcium and phosphorus between supernatant and sediment. Compared with UHT goat milk without stabilizing salts, the addition of stabilizing salts increased the amounts of calcium and phosphorus in the supernatant and decreased the amounts of sediment, protein particle size, and globular protein structure in UHT goat milk. This demonstrates that stabilizing salts can be used to improve the heat stability of goat milk.

Autonomous aggregation suppression by acidic residues explains why chaperones favour basic residues.

Many chaperones favour binding to hydrophobic sequences that are flanked by basic residues while disfavouring acidic residues. However, the origin of this bias in protein quality control remains poorly understood. Here, we show that while acidic residues are the most efficient aggregation inhibitors, they are also less compatible with globular protein structure than basic amino acids. As a result, while acidic residues allow for chaperone-independent control of aggregation, their use is structurally limited. Conversely, we find that, while being more compatible with globular structure, basic residues are not sufficient to autonomously suppress protein aggregation. Using Hsp70, we show that chaperones with a bias towards basic residues are structurally adapted to prioritize aggregating sequences whose structural context forced the use of the less effective basic residues. The hypothesis that emerges from our analysis is that the bias of many chaperones for basic residues results from fundamental thermodynamic and kinetic constraints of globular structure. This also suggests the co-evolution of basic residues and chaperones allowed for an expansion of structural variety in the protein universe.

Thermodynamic and Evolutionary Coupling between the Native and Amyloid State of Globular Proteins

SummaryThe amyloid-like aggregation propensity present in most globular proteins is generally considered to be a secondary side effect resulting from the requirements of protein stability. Here, we demonstrate, however, that mutations in the globular and amyloid state are thermodynamically correlated rather than simply associated. In addition, we show that the standard genetic code couples this structural correlation into a tight evolutionary relationship. We illustrate the extent of this evolutionary entanglement of amyloid propensity and globular protein stability. Suppressing a 600-Ma-conserved amyloidogenic segment in the p53 core domain fold is structurally feasible but requires 7-bp substitutions to concomitantly introduce two aggregation-suppressing and three stabilizing amino acid mutations. We speculate that, rather than being a corollary of protein evolution, it is equally plausible that positive selection for amyloid structure could have been a driver for the emergence of globular protein structure.

Propensities of Amino Acid Pairings in Secondary Structure of Globular Proteins.

A class of secondary structure prediction algorithms use the information from the statistics of the residue pairs found in secondary structural elements. Because the protein folding process is dominated by backbone hydrogen bonding, an approach based on backbone hydrogen-bonded residue pairings would improve the predicting capabilities of these class algorithms. The reliability of the prediction algorithms depends on the quality of the statistics, therefore, of the data set. In this study, it was aimed to determine the propensities of the backbone hydrogen-bonded residue pairings for secondary structural elements of α-helix and β-sheet in globular proteins using a new and comprehensive data set created from the peptides deposited in Worldwide Protein Data Bank. A master data set including 4882 globular peptide chains with resolution better than 2.5 Å, sequence identity smaller than 25% and length of no shorter than 100 residues were created. Separate data sub sets also were created for helix and sheet structures from master set and each sub set includes 4594 and 4483 chains, respectively. Backbone hydrogen-bonded residue pairings in helices and sheets were detected and the propensities of them were represented as odds ratios (observed/[random or expected]) in matrices. Propensities assigned by this study to the residue pairings in secondary structural elements (as helix, overall strands, parallel strands and antiparallel strands) differ from the previous studies by 19 to 34%. These dissimilarities are important and they would cause further improvements in secondary structure prediction algorithms.

Forecasting the upper bound free energy difference between protein native-like structures

Using a combination of statistical thermodynamics and the Gershgorin theorem we computed, in the thermodynamic limit, a plausible value for the upper bound of the free energy difference between native-like structures of monomeric globular proteins. The validity of our result is discussed herein in terms of both the observed free-energy change between the native and denatured states and the micro stability free-energy values obtained from the observed micro-unfolding tendency of nine monomeric globular proteins.

Characterization of the in situ pellicle ultrastructure formed under the influence of bovine milk and milk protein isolates

ObjectivesThe present study aimed to investigate if bovine milk or milk protein isolates, respectively, alter the ultrastructure of thein situ pellicle and might therefore have an influence on oral health. MethodsIn situ pellicle samples were formed on bovine enamel slabs exposed in the oral cavity of three subjects for 6, 30, 60 or 120 min. After 3 min of pellicle formation, mouthrinses were performed for 3 min with (non-)homogenized UHT- or fresh milk (0.3% or 3.8% fat), 30% UHT-treated cream or different types of casein- or milk protein isolates containing preparations. The specimens were removed after the exposure times and transmission electron microscopy (TEM) was performed. Native pellicle samples served as controls. ResultsTopical ultrastructural pellicle modifications were detected after mouthrinses with all types of homogenized UHT- or fresh milk and after the application of a 3% native casein micelles containing experimental solution. Atypical globular protein structures, identified as casein micelles, were temporarily adsorbed onto the pellicle. They were closely associated with lipid droplets. Furthermore, the mouthrinses occasionally affected the morphology of salivary bacteria. However, no notable ultrastructural alterations remained after 120 min of pellicle formation. ConclusionFor the first time, bovine milk- and micellar casein-induced pellicle modifications were revealed by TEM. The adsorption of micellar casein is possibly due to its molecular interactions. Clinical significanceBovine milk or micellar caseins provide some potential for the development of preventive strategies against bacterial biofilm formation or erosive processes at the tooth surface.