Large Biomolecules Research Articles

Electric Field Induced Drift of Bacterial Protein Toxins of Foodborne Pathogens Staphylococcus aureus and Escherichia coli from Water

Bacterial protein toxins secreted by foodborne pathogens, such as Staphylococcus aureus and Shiga toxin-producing Escherichia coli (STEC) strains, may cause severe toxicosis in humans if present in foods or water and constitute an important public health problem. These toxins are large biomolecules with negative and positive ions due to the ionizable groups in the residual amino acids. An innovative theoretical model of purifying aqueous flowing solutions from ionic toxins is proposed in this study. The principle of the model is based on the drift of the ionic toxins, under the application of the external electric field, towards the walls of the duct, leaving the largest part of the duct with reduced levels of toxin. Parameters, such as toxin concentration, potential and electric field intensity distributions, and surface charge densities, are studied analytically for various duct widths and various external electric fields. The proposed model succeeded to reduce toxin levels by more than 99%, for duct widths less than 1cm, making it suitable for small-scale water purification.

Highly porous bio-glass scaffolds fabricated by polyurethane template method with hydrothermal treatment for tissue engineering uses.

Bioglass scaffolds, which contain a significant percentage of porosity for tissue engineering purposes, have low strength. For increasing the strength and efficiency of such structures for use in tissue engineering, fabrication of hierarchical meso/macro-porous bioglass scaffolds, developing their mechanical strength by hydrothermal treatment and adjusting pH method, and achieving the appropriate mesopore size for loading large biomolecules, were considered in this study. Mesoporous bioglass (MBG) powders were synthesized using cetyltrimethylammonium bromide as a surfactant, with different amounts of calcium sources to obtain the appropriate size of the mesoporous scaffolds. Then MBG scaffolds were fabricated by a polyurethane foam templating method, and for increasing scaffold strength hydrothermal treatment (90 °C, for 5 days) and adjustment pH (pH=9) method was used to obtain hierarchical meso/macro-porous structures. The sample characterization was done by Simultaneous thermal analysis, Fourier transform infrared spectroscopy, Field Emission Scanning electron microscopy, small and wide-angle X-ray powder diffractions, transmission electron microscopy, and analysis of nitrogen adsorption-desorption isotherm. The mechanical strength of scaffolds was also determined. The MBG scaffolds based on 80.28 (wt.) % SiO2- 17.89 (wt.) % CaO- 1.81 (wt.) % P2O5 presented interconnected large pores and pores in the range of 100-150 μm and 6-18 nm, respectively and 0.4 MPa compressive strength. The total pore volume and specific surface area were obtained from the Brunauer-Emmett-Teller theory, 0.709 cm3 g-1 and 213.83 m2 g-1, respectively. These findings could be considered in bone-cartilage tissue engineering.

Therapeutic Stimulation of Glycolytic ATP Production for Treating ROS-Mediated Cellular Senescence.

Cellular senescence is conditioned through two interrelated processes, i.e., a reduction in adenosine triphosphate (ATP) and the enhancement of reactive oxygen species (ROS) production levels in mitochondria. ATP shortages primarily influence the energy-intensive synthesis of large biomolecules, such as deoxyribonucleic acid (DNA). In addition, as compared to small biomolecules, large biomolecules are more prone to ROS-mediated damaging effects. Based on the available evidence, we suggest that the stimulation of anaerobic glycolytic ROS-independent ATP production could restrain cellular senescence. Consistent with this notion, non-drug related intermittent hypoxia (IH)-based therapy could be effectively applied in sports medicine, as well as for supporting the physical activity of elderly patients and prophylactics of various age-related disorders. Moreover, drug therapy aiming to achieve the partial blockade of respiratory chain and downstream compensatory glycolysis enhancement could prove to be useful for treating cardiovascular, neurological and hormonal diseases. We maintain that non-drug/drug-related therapeutic interventions applied in combination over the entire lifespan could significantly rejuvenate and prolong a high quality of life for individuals.

Cell-Penetrating Peptides (CPPs) as Therapeutic and Diagnostic Agents for Cancer.

Cell-Penetrating Peptides (CPPs) are short peptides consisting of <30 amino acids. Their ability to translocate through the cell membrane while carrying large cargo biomolecules has been the topic of pre-clinical and clinical trials. The ability to deliver cargo complexes through membranes yields potential for therapeutics and diagnostics for diseases such as cancer. Upon cellular entry, some CPPs have the ability to target specific organelles. CPP-based intracellular targeting strategies hold tremendous potential as they can improve efficacy and reduce toxicities and side effects. Further, recent clinical trials show a significant potential for future CPP-based cancer treatment. In this review, we summarize recent advances in CPPs based on systematic searches in PubMed, Embase, Web of Science, and Scopus databases until 30 September 2022. We highlight targeted delivery and explore the potential uses for CPPs as diagnostics, drug delivery, and intrinsic anti-cancer agents.

Microsphere amplified fluorescence and its application in sensing

The far-field fluorescence amplification, the intense fluorescence emission addresses the great potential in sensitive detection to large biomolecules, was seriously ignored for the failure in amplifying the weak fluorescence excepting the electromagnetic field (EM) induced fluorescence amplification on the metallic surfaces. Here, a microsphere in hundreds of micrometers was adopted to proceed with the fluorescence amplification via building up a local dielectric surrounding for fluorophore. The wide range of contribution-angle fluorescence could be efficiently restricted within the microsphere by facilitating the energy of reflection restraining and declining the energy of refraction decaying and the intense fluorescence emission confined within the microsphere could be directly observed. The proposed microsphere amplified fluorescence was demonstrated to induce about 2600 times of improved sensitivity in the detection of the fluorescent resorufin referring that of the original resorufin solution through the laser induced fluorescence (LIF). Furthermore, the limit of detection (LOD) of human IgA was successfully obtained to 3.25 fM through the microsphere in 47.7 pL when the microsphere amplified fluorescence was utilized in the fluoroimmunoassay. We believe the microsphere amplified fluorescence would be a potential strategy to implement the sensitive fluorescence sensing.

Deciphering the QR Code of the CRISPR-Cas9 System: Synergy between Gln768 (Q) and Arg976 (R).

Markov state models (MSMs) and machine learning (ML) algorithms can extrapolate the long-time-scale behavior of large biomolecules from molecular dynamics (MD) trajectories. In this study, an MD-MSM-ML scheme has been applied to probe the large endonuclease (Cas9) in the bacterial adaptive immunity CRISPR-Cas9 system. CRISPR has become a programmable and state-of-the-art powerful genome editing tool that has already revolutionized life sciences. CRISPR-Cas9 is programmed to process specific DNA sequences in the genome. However, human/biomedical applications are compromised by off-target DNA damage. Characterization of Cas9 at the structural and biophysical levels is a prerequisite for the development of efficient and high-fidelity Cas9 variants. The Cas9 wild type and two variants (R63A-R66A-R70A, R69A-R71A-R74A-R78A) are studied herein. The configurational space of Cas9 is provided with a focus on the conformations of the side chains of two residues (Gln768 and Arg976). A model for the synergy between those two residues is proposed. The results are discussed within the context of experimental literature. The results and methodology can be exploited for the study of large biomolecules in general and for the engineering of more efficient and safer Cas9 variants for applications.

Percolation transition prescribes protein size-specific barrier to passive transport through the nuclear pore complex

Nuclear pore complexes (NPCs) control biomolecular transport in and out of the nucleus. Disordered nucleoporins in the complex’s pore form a permeation barrier, preventing unassisted transport of large biomolecules. Here, we combine coarse-grained simulations of experimentally derived NPC structures with a theoretical model to determine the microscopic mechanism of passive transport. Brute-force simulations of protein transport reveal telegraph-like behavior, where prolonged diffusion on one side of the NPC is interrupted by rapid crossings to the other. We rationalize this behavior using a theoretical model that reproduces the energetics and kinetics of permeation solely from statistics of transient voids within the disordered mesh. As the protein size increases, the mesh transforms from a soft to a hard barrier, enabling orders-of-magnitude reduction in permeation rate for proteins beyond the percolation size threshold. Our model enables exploration of alternative NPC architectures and sets the stage for uncovering molecular mechanisms of facilitated nuclear transport.

Surface Filtration in Mesoporous Au Films Decorated by Ag Nanoparticles for Solving SERS Sensing Small Molecules in Living Cells.

For surface-enhanced Raman spectroscopy (SERS) sensing of small molecules in the presence of living cells, biofouling and blocking of plasmonic centers are key challenges. Here, we have developed a mesoporous Au (AuM) film coated with a Ag nanoparticles (NPs) as a plasmonic sensor (AuM@Ag) to analyze aromatic thiols, which is an example of a small molecule, in the presence of a living cell strain (e.g., MDA-MB-231) as a model living system. The resulting AuM@Ag provides 0.1 nM sensitivity and high reproducibility for thiols sensing. Simultaneously, the AuM@Ag film filters large biomolecules, preventing Raman signals from overlapping produced by large biomolecules. After analysis, the AuM@Ag film undergoes recycling by the full dissolution of the Ag-thiol layer and removal of thiols from AuM. Furthermore, fresh AgNPs are formed for further SERS analysis, which circumvents the Ag oxidation issue. The ease of the AgNPs deposition allows up to 12 cycles of on-demand recycling and sensing even after utilization as a sensor in multicomponent media without enhancement and sensitivity loss. The reported mesoporous film with surface filtering ability and prominent recycling procedure promises to offer a new strategy for the detection of various small molecules in the presence of living cells.

Efficient simulation of resonance Raman spectra with tight-binding approximations to density functional theory.

Resonance Raman spectroscopy has long been established as one of the most sensitive techniques for detection, structure characterization, and probing the excited-state dynamics of biochemical systems. However, the analysis of resonance Raman spectra is much facilitated when measurements are accompanied by Density Functional Theory (DFT) calculations that are expensive for large biomolecules. In this work, resonance Raman spectra are therefore computed with the Density Functional Tight-Binding (DFTB) method in the time-dependent excited-state gradient approximation. To test the accuracy of the tight-binding approximations, this method is first applied to typical resonance Raman benchmark molecules, such as β-carotene, and compared to results obtained with pure and range-separated exchange-correlation functionals. We then demonstrate the efficiency of the approach by considering a computationally challenging heme variation. Overall, we find that the vibrational frequencies and excited-state properties (energies and gradients) that are needed to simulate the spectra are reasonably accurate and suitable for interpretation of experiments. We can therefore recommend DFTB as a fast computational method to interpret resonance Raman spectra.

Gated Organonanoclays for Large Biomolecules: Controlled Release Triggered by Surfactant Stimulus

The low toxicity and high adsorption capacities of clay minerals make them attractive for controlled delivery applications. However, the number of controlled-release studies in the literature using clay minerals is still scarce. In this work, three different clays from the smectite group (Kunipia F, montmorillonite; Sumecton SA, saponite; and Sumecton SWN, hectorite) were successfully loaded with rhodamine B dye and functionalized with oleic acid as a gatekeeper to produce organonanoclays for active and controlled payload-release. Moreover, hematin and cyanocobalamin have also been encapsulated in hectorite gated clay. These organonanoclays were able to confine the entrapped cargos in an aqueous environment, and effectively release them in the presence of surfactants (as bile salts). A controlled delivery of 49 ± 6 μg hematin/mg solid and 32.7 ± 1.5 μg cyanocobalamin/mg solid was reached. The cargo release profiles of all of the organonanoclays were adjusted to three different release-kinetic models, demonstrating the Korsmeyer–Peppas model with release dependence on (i) the organic–inorganic hybrid system, and (ii) the nature of loaded molecules and their interaction with the support. Furthermore, in vitro cell viability assays were carried out with Caco-2 cells, demonstrating that the organonanoclays are well tolerated by cells at particle concentrations of ca. 50 μg/mL.

Modeling of the transient diffusion regime in fully porous particles—Application to the analysis of large biomolecules by ultra-high pressure liquid chromatography

The transient diffusion regime of large biomolecules such as monoclonal antibodies, double-stranded (ds) DNA (base pair number ∼ 100), and virus-like particles is modeled in a single fully porous particle utilized as size exclusion chromatography (SEC) packing materials in ultra-high pressure liquid chromatography (UHPLC). The expression of the time and space dependent concentration profiles is derived for a step concentration change. Four different UHPLC particles were considered in the calculations depending on the size of the analyte : 2.0 μm 125 Å Bridge-Ethylene-Hybrid (BEH) XBridgeTM particles for small molecules (size: 4 Å), 2.0 μm 125 Å and 250 Å BEH particles for monoclonal antibodies (size: 55 Å), 2.0 μm 250 Å and 2.5 μm 450 Å BEH particles for dsDNA (size: 160 Å), and 2.5 μm 900 Å BEH particles for virus-like particles (size: 500 Å). The accessible porosities and the hindrance diffusion factors of these analytes were determined from the physical reconstruction of the internal structure of a 2.0 μm 130 Å BEH particle and from the simulation of the analyte mobility in the reconstructed mesopores. The analysis of the transient diffusion profiles reveals that there is insufficient time for the largest analytes to fully equilibrate the BEH particles in UHPLC. The dynamic capacity of the BEH particles is estimated to decrease from more than 99% for small molecules to 96% for monoclonal antibodies, 74% for 100 base pair dsDNA, and to less than 2% for virus-like particles. A full but reduced column capacity relative to fully porous particles can be recovered for monoclonal antibodies by considering superficially porous particles with a core-to-particle diameter ratio of about 0.8. In contrast, this is not possible for either large dsDNA (base pair number ≥ 100) or virus-like particles because the shell thickness would become smaller than the mesopore size required. The presented results open up two research avenues in order to analyze such large biomolecules by UHPLC: prepare ultra-high pressure-resistant sub-3 μm silica-based particles with pore sizes much larger than 1000 Å and design proper nonporous macrostructures to load, trap, separate, and elute rapidly by gradient UHPLC.

Determination of Amide cis/trans Isomers in N-Acetyl-d-glucosamine: Tailored NMR Analysis of the N-Acetyl Group Conformation.

N‐Acetyl‐d‐glucosamine (GlcNAc) is one of the most common amino sugars in nature, but the conformation of its N‐acetyl group has drawn little attention. We report herein the first identification of NH protons of the amide cis forms of α‐ and β‐GlcNAc by NMR spectroscopy. Relative quantification and thermodynamic analysis of both cis and trans forms was carried out in aqueous solution. The NH protons were further utilized by adapting protein NMR experiments to measure eight J‐couplings within the N‐acetyl group, of which six are sensitive to the H2‐NH conformation and two are sensitive to the amide conformation. For amide cis and trans forms, the orientation between H2 and NH was determined as anti conformation, while a small percentage of syn conformation was predicted for the amide trans form of β‐GlcNAc. This approach holds great promise for the detailed conformational analysis of GlcNAc in larger biomolecules, such as glycoproteins and polysaccharides.

Multifunctional nanomaterials and nanocomposites for sensing and monitoring of environmentally hazardous heavy metal contaminants

The applications of conventional sensors are limited by the long response time, high cost, large detection limit, low sensitivity, complicated usage and low selectivity. These sensors are nowadays replaced by Nanocomposite-based modalities and nanomaterials which are known for their high selectivity and physical and chemical properties. These nanosensors effectively detect heavy metal contaminants in the environment as the discharge of heavy metals into natural water as a result of human activity has become a global epidemic. Exposure to these toxic metals might induce many health-related complications, including kidney failure, brain injury, immune disorders, muscle paleness, cardiac damage, nervous system impairment and limb paralysis. Therefore, designing and developing novel sensing systems for the detection and recognition of these harmful metals in various environmental matrices, particularly water, is of extremely important. Emerging nanotechnological approaches in the past two decades have played a key role in overcoming environmentally-related problems. Nanomaterial-based fabrication of chemical nanosensors has widely been applied as a powerful analytical tool for sensing heavy metals. Portability, high sensitivity, on-site detection capability, better device performance and selectivity are all advantages of these nanosensors. The detection and selectivity have been improved using molecular recognition probes for selective binding on different nanostructures. This study aims to evaluate the sensing properties of various nanomaterials such as metal-organic frameworks, fluorescent materials, metal-based nanoparticles, carbon-based nanomaterials and quantum dots and graphene-based nanomaterials and quantum dots for heavy metal ions recognition. All these nano-architectures are frequently served as effective fluorescence probes to directly (or by modification with some large or small biomolecules) sense heavy metal ions for improved selectivity. However, efforts are still needed for the simultaneous designing of multiple metal ion-based detection systems, exclusively in colorimetric or optical fluorescence nanosensors for heavy metal cations.

A simple mathematical treatment for predicting linear solvent strength behavior in gradient elution: Application to biomolecules.

This paper describes an approach to rapidly and easily calculate the linear solvent strength parameters, namely log k 0 and S, under reversed‐phase liquid chromatography conditions. This approach, which requires two preliminary gradient experiments to determine the retention parameters, was applied to various representative compounds including small molecules, peptides, and proteins. The retention time prediction errors were compared to the ones obtained with a commercial HPLC modeling software, and a good correlation was found between the values. However, two important constraints have to be accounted for to maintain good predictions with this new approach: i) the retention factor at the initial composition of the preliminary gradient series have to be large enough (i.e., log k i above 2.1) and ii) the retention models have to be sufficiently linear. While these two conditions are not always met with small molecules or even peptides, the situation is different with large biomolecules. This is why our simple calculation method should be preferentially applied to calculate the linear solvent strength parameters of protein samples.

Pressure-Enhanced Liquid Chromatography, a Proof of Concept: Tuning Selectivity with Pressure Changes and Gradients.

Many chromatographers have observed that the operating pressure can dramatically change the chromatographic retention of solutes. Small molecules show observables changes, yet even more sizable effects are encountered with large biomolecules. With this work, we have explored the use of pressure as a method development parameter to alter the reversed-phase selectivity of peptide and protein separations. An apparatus for the facile manipulation of column pressure was assembled through a two-pump system and postcolumn flow restriction. The primary pump provided an eluent flow through the column, while the secondary pump provided a pressure-modulating flow at a tee junction after the column but ahead of a flow restrictor. Using this setup, we were able to quickly program various constant pressure changes and even pressure gradients. It was reconfirmed that pressure changes impact the retention of large molecules to a much greater degree than small molecules, making it especially interesting to consider the use of pressure to selectively separate solutes of different sizes. The addition of pressure to bring the column operating pressure beyond 500 bar was enough to change the elution order of insulin (a peptide hormone) and cytochrome C (a small serum protein). Moreover, with the proposed setup, it was possible to combine eluent and pressure gradients in the same analytical run. This advanced technique was applied to improve the separation of insulin from one of its forced degradation impurities. We have referred to this method as pressure-enhanced liquid chromatography and believe that it can offer unseen selectivity, starting with peptide and protein reversed-phase separations.

1,4-bis[β-(2-benzoxazoly1) vinyl] benzene (BBVB) laser dye and sodium salt of meso-tetrakis (4-sulfonatophenyl) porphyrin (TPPS); spectroscopic investigation and DFT, NBO and TD-DFT calculations

Excitation energy transfer (ET) from 1,4-bis[β-(2-benzoxazoly1) vinyl] benzene as a donor to sodium salt of meso-tetrakis (4-sulfonatophenyl) porphyrin (TPPS) as an acceptor was investigated in the absence and presence of metallic silver nanoparticles (Ag NPs). The emission intensities and Stern –Volmer constants (KSV) of the ET processes were calculated in methanol (MeOH) and 40% ethylene glycol (EG) as 5.87 × 104 M−1 and 6.27 × 104 M−1, respectively. KSV value in the presence of Ag NPs was 1.028 × 105 M−1 in methanol, much higher than in absence of NPs. This is attributed to the role of Ag NPs in increasing the strength of the donor–acceptor interactions. These results denote the use of Ag NPs for measuring the proximity of large biomolecules and ET-based assays. Also, the critical ET distance Ro was calculated as 36 Å. This magnitude is higher than the common value of 10 Å for the collisional ET mechanism. This high Ro value indicates the underlying mechanism as long-range dipole–dipole interaction. The BBVB, TPPS, and BBVB/TPPS molecular structures (MSs) were optimized using the DFT/ B3LYP/6-311G (d) method for the quantum calculations. The calculated electronic UV–Vis absorption spectra for BBVB and BBVB/TPPS MSs in MeOH were examined by the time-dependent density functional theory (TD-DFT) at CAM-B3LYP/6-311G++(3d,3p) level. Interestingly, all theoretical results of BBVB and BBVB/TPPS molecules were highly matched with the experimental results. Furthermore, the Natural Bond Orbital (NBO) analyses for BBVB and BBVB/TPPS MSs were obtained using the B3LYP/6-311G(d) level of theory.

METHOD SUPER LEARNING FOR DETERMINATION OF MOLECULAR RELATIONSHIP

This paper uses the Super Learning principle to predict the molecular affinity between the receptor (large biomolecule) and ligands (small organic molecules). Meta-models study the optimal combination of individual basic models in two consecutive ensembles – classification and regression. Each costume contains six models of machine learning, which are combined by stacking. Base models include the reference vector method, random forest, gradient boosting, neural graph networks, direct propagation, and transformers. The first ensemble predicts binding probability and classifies all candidate molecules to the selected receptor into active and inactive. Ligands recognized as involved by the first ensemble are fed to the second ensemble, which assumes the degree of their affinity for the receptor in the form of an inhibition factor (Ki). A feature of the method is the rejection of the use of atomic coordinates of individual molecules and their complexes – thus eliminating experimental errors in sample preparation and measurement of nuclear coordinates and the method to determine the affinity of biomolecules with unknown spatial configurations. It is shown that meta-learning increases the response (Recall) of the classification ensemble by 34.9% and the coefficient of determination (R2) of the regression ensemble by 21% compared to the average values. This paper shows that an ensemble with meta-stacking is an asymptotically optimal system for learning. The feature of Super Learning is to use k-fold cross-validation to form first-level predictions that teach second-level models — or meta-models — that combine first-level models optimally. The ability to predict the molecular affinity of six machine learning models is studied, and the efficiency improvement is due to the combination of models in the ensemble by the stacking method. Models that are combined into two consecutive ensembles are shown.

On the temperature of large biomolecules in ion-storage rings

On the temperature of large biomolecules in ion-storage rings

The Suitability of Latex Particles to Evaluate Critical Process Parameters in Steric Exclusion Chromatography.

The steric exclusion chromatography (SXC) is a rather new method for the purification of large biomolecules and biological nanoparticles based on the principles of precipitation. The mutual steric exclusion of a nonionic organic polymer, i.e., polyethylene glycol (PEG), induces target precipitation and leads to their retention on the chromatographic stationary phase. In this work, we investigated the application of latex particles in the SXC by altering the particle’s surface charge as well as the PEG concentration and correlated both with their aggregation behavior. The parameters of interest were offline precipitation kinetics, the product recovery and yield, and the chromatographic column blockage. Sulfated and hydroxylated polystyrene particles were first characterized concerning their aggregation behavior and charge in the presence of PEG and different pH conditions. Subsequently, the SXC performance was evaluated based on the preliminary tests. The studies showed (1) that the SXC process with latex particles was limited by aggregation and pore blockage, while (2) not the aggregate size itself, but rather the aggregation kinetics dominated the recoveries, and (3) functionalized polystyrene particles were only suitable to a limited extent to represent biological nanoparticles of comparable size and charge.

New physical insights: Formamide discharge decomposition and the role of fragments in the formation of large biomolecules

In this work we present a time-resolved FTIR spectroscopic study on kinetics of atomic and molecular species, specifically CO, CN radical, N2, HCN and CO2 generated in a glow discharge of formamide-nitrogen-water mixture in a helium buffer gas. Radicals such as NH, CH and OH have been proven to be fundamental stones of subsequent chemical reactions having a crucial role in a prebiotic synthesis of large organic molecules.This work contains three main goals. Firstly, we present our time-resolved spectra of formamide decomposition products and discuss the mechanism of collisional excitations between specific species. Secondly, according to our time resolution, we demonstrate and explain the band shape of CO’s first overtone and the energy transfer between excited nitrogen and CO, present in our spectra. Lastly, we present theoretical results for the non-LTE modelling of the spectra using bi-temperature approach and a 1D harmonic Franck-Condon approach for the multi-molecule spectra of the formamide decomposition process in the 1800–5600 cm−1 spectral range.