Urea-aromatic interactions in biology

Investigation of Antibody Tolerance in Methanol for Analytical Purposes: Methanol Effect Patterns and Molecular Mechanisms

The extraction of targets from biological samples for immunoassays using organic solvents, such as methanol, is often necessary. However, high concentrations of organic solvents in extracts invariably lead to instability of the employed antibody, resulting in poor performance of the immunoassay. Evaluating the tolerance ability and exploring the molecular mechanisms of antibody tolerance in organic solvents are essential for the development of robust immunoassays. In this work, 25 monoclonal antibodies and methanol are utilized as models to address these questions. A novel protocol is initially established to precisely and rapidly determine antibody tolerance in methanol, identifying two distinct methanol effect patterns. Through a detailed investigation of the structural basis, a novel hypothesis regarding methanol effect patterns is proposed, termed "folding-aggregation," which is subsequently validated through molecular dynamics simulations. Furthermore, the investigation of sequence basis reveals significant differences in residue types within the complementarity-determining regions and ligand-binding residues, distinguishing the two antibody methanol effect patterns. Moreover, the methanol effect patterns of the antibodies are defined by germline antibodies. This work represents the first exploration of antibody methanol effect patterns and associated molecular mechanisms, with potential implications for the discovery and engineering of tolerant antibodies for the development of robust immunoassays.

Development of an Aptamer-Based QCM-D Biosensor for the Detection of Thrombin Using Supported Lipid Bilayers as Surface Functionalization

Biosensors play an important role in numerous research fields. Quartz crystal microbalances with dissipation monitoring (QCM-Ds) are sensitive devices, and binding events can be observed in real-time. In combination with aptamers, they have great potential for selective and label-free detection of various targets. In this study, an alternative surface functionalization for a QCM-D-based aptasensor was developed, which mimics an artificial cell membrane and thus creates a physiologically close environment for the binding of the target to the sensor. Vesicle spreading was used to form a supported lipid bilayer (SLB) of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC) and 1,2-dipalmitoyl-sn-glycero-3-phosphethanolamine-N-(cap biotinyl) (biotin-PE). The SLB was then coated with streptavidin followed by applying a biotinylated aptamer against thrombin. SLB formation was investigated in terms of temperature and composition. Temperatures of 25 °C and below led to incomplete SLB formation, whereas a full bilayer was built at higher temperatures. We observed only a small influence of the content of biotinylated lipids in the mixture on the further binding of streptavidin. The functionalization of the sensor surface with the thrombin aptamer and the subsequent thrombin binding were investigated at different concentrations. The sensor could be reconstituted by incubation with a 5 M urea solution, which resulted in the release of the thrombin from the sensor surface. Thereafter, it was possible to rebind thrombin. Thrombin in spiked samples of human serum was successfully detected. The developed system can be easily applied to other target analytes using the desired aptamers.

BioProtIS: Streamlining protein-ligand interaction pipeline for analysis in genomic and transcriptomic exploration

The identification of protein-ligand interactions plays a pivotal role in elucidating biological processes and discovering potential bioproducts. Harnessing the capabilities of computational methods in drug discovery, we introduce an innovative Inverted Virtual Screening (IVS) pipeline. This pipeline Integrated molecular dynamics and docking analyses to ensure that protein structures are not only energetically favorable but also representative of stable conformations. The primary objective of this pipeline is to automate and streamline the analysis of protein-ligand interactions at both genomic and transcriptomic scales. In the contemporary post-genomic era, high-throughput computational screening for bioproducts, biological systems, and therapeutic drugs has become a cornerstone practice. This approach offers the promise of cost-effectiveness, time efficiency, and optimization of laboratory work. Nevertheless, a notable deficiency persists in the availability of efficient pipelines capable of automating the virtual screening process, seamlessly integrating input and output, and leveraging the full potential of open-source tools. To bridge this critical gap, we have developed a versatile pipeline known as BioProtIS. This tool seamlessly integrates a suite of state-of-the-art tools, including Modeller, AlphaFold, Gromacs, FPOCKET, and AutoDock Vina, thus facilitating the streamlined docking of ligands with an expansive repertoire of proteins sourced from genomes and transcriptomes, and substrates. To assess the pipeline's performance, we employed the transcriptomes of Cereus jamacaru (a cactus species) and Aspisoma lineatum (firefly), along with the genome of Homo sapiens. This integration not only improves the accuracy of ligand-protein interactions by minimizing replicability deviations but also optimizes the discovery process by enabling the simultaneous evaluation of multiple substrates. Furthermore, our pipeline accommodates distinct testing scenarios, such as blind docking or site-specific targeting, which are invaluable in applications ranging from drug repositioning to the exploration of new allosteric binding sites and toxicity assessments. BioProtIS has been designed with modularity at its core. This inherent flexibility empowers users to make custom modifications directly within the source code, tailoring the pipeline to their specific research needs. Moreover, it lays the foundation for seamless integration of diverse docking algorithms in future iterations, promising ongoing advancements in the field of computational biology. This pipeline is available for free distribution and can be download at: https://github.com/BBMDO/BioProtIS.

Disassembly and reassembly of the non-conventional thermophilic C-phycocyanin

C-phycocyanin (CPC), which contains open-chain tetrapyrroles, is a major light-harvesting red-fluorescent protein with an important role in aquatic photosynthesis. Recently, we reported a non-conventional CPC from Thermoleptolyngbya sp. O-77 (CPCO77) that contains two different structures, i.e., a hexameric structure and a non-conventional octameric structure. However, the assembly and disassembly mechanisms of the non-conventional octameric form of CPC remain unclear. To understand this assembly mechanism, we performed an in vitro experiment to study the disassembly and reassembly behaviors of CPC using isolated CPC subunits. The dissociation of the CPCO77 subunit was performed using a Phenyl-Sepharose column in 20 mM potassium phosphate buffer (pH 6.0) containing 7.0 M urea. For the first time, crystals of isolated CPC subunits were obtained and analyzed after separation. After the removal of urea from the purified α and β subunits, we performed an in vitro reassembly experiment for CPC and analyzed the reconstructed CPC using spectrophotometric and X-ray crystal structure analyses. The crystal structure of the reassembled CPC was nearly identical to that of the original CPCO77. The findings of this study indicate that the octameric CPCO77 is a naturally occurring form in the thermophilic cyanobacterium Thermoleptolyngbya sp. O-77.

Smart Polymers for Soft Materials: From Solution Processing to Organic Solids

Polymeric materials are ubiquitous in our everyday life, where they find a broad range of uses-spanning across common household items to advanced materials for modern technologies. In the context of the latter, so called "smart polymers" have received a lot of attention. These systems are soluble in water below their lower critical solution temperature Tℓ and often exhibit counterintuitive solvation behavior in mixed solvents. A polymer is known as smart-responsive when a slight change in external stimuli can significantly change its structure, functionm and stability. The interplay of different interactions, especially hydrogen bonds, can also be used for the design of lightweight high-performance organic solids with tunable properties. Here, a general scheme for establishing a structure-property relationship is a challenge using the conventional simulation techniques and also in standard experiments. From the theoretical side, a broad range of all-atom, multiscale, generic, and analytical techniques have been developed linking monomer level interaction details with macroscopic material properties. In this review, we briefly summarize the recent developments in the field of smart polymers, together with complementary experiments. For this purpose, we will specifically discuss the following: (1) the solution processing of responsive polymers and (2) their use in organic solids, with a goal to provide a microscopic understanding that may be used as a guiding tool for future experiments and/or simulations regarding designing advanced functional materials.

Urea induced unfolding of rai seed cystatin: Influence of glycerol as a chemical chaperone

Cystatin superfamily members, by virtue of their thiol protease regulatory properties, show involvement in myriad physiological processes important for survival and well-being. The current study involves urea-induced denaturation of a novel variant of the cystatin superfamily, rai seed cystatin (RSC), employing a variety of biophysical assays in order to characterize different folding intermediates generated on unfolding. Urea as a denaturant presented the passage of RSC through a series of events resulting in the loss of RSC functional capability, accompanied by changes in the archetype at secondary and tertiary structural levels, as evident from protease inhibitory, UV absorption, and intrinsic fluorescence assays, respectively. ANS fluorescence also revealed routing of RSC through discrete multiple sub-states thus presenting the generation of intermediate states somewhat close to the pre-molten globule and/or molten globule forms of RSC. Furthermore, far-UV circular dichroism analysis revealed a concentration-dependent gradual loss in typical -helical RSC peaks, indicating a nearly 50 % loss in secondary structural elements around 5 M urea treatment. The study also reports the possible role of glycerol in the refolding and/or reactivation of the urea unfolded RSC form. Glycerol presented itself as a potent structural stabilizer as it assisted in the refolding and reactivation of the unfolded RSC in a dosage-dependent manner, concomitantly paving the way for unravelling the mechanistic approach involved in the phenomenon, which can facilitate future studies.

Kinetics of elementary steps in loop-mediated isothermal amplification (LAMP) show that strand invasion during initiation is rate-limiting

Loop-mediated isothermal amplification (LAMP) has proven to be easier to implement than PCR for point-of-care diagnostic tests. However, the underlying mechanism of LAMP is complicated and the kinetics of the major steps in LAMP have not been fully elucidated, which prevents rational improvements in assay development. Here we present our work to characterize the kinetics of the elementary steps in LAMP and show that: (i) strand invasion / initiation is the rate-limiting step in the LAMP reaction; (ii) the loop primer plays an important role in accelerating the rate of initiation and does not function solely during the exponential amplification phase and (iii) strand displacement synthesis by Bst-LF polymerase is relatively fast (125 nt/s) and processive on both linear and hairpin templates, although with some interruptions on high GC content templates. Building on these data, we were able to develop a kinetic model that relates the individual kinetic experiments to the bulk LAMP reaction. The assays developed here provide important insights into the mechanism of LAMP, and the overall model should be crucial in engineering more sensitive and faster LAMP reactions. The kinetic methods we employ should likely prove useful with other isothermal DNA amplification methods.

Urea-Modified Self-Assembling Peptide Amphiphiles That Form Well-Defined Nanostructures and Hydrogels for Biomedical Applications

Hydrogen bonding plays a critical role in the self-assembly of peptide amphiphiles (PAs). Herein, we studied the effect of replacing the amide linkage between the peptide and lipid portions of the PA with a urea group, which possesses an additional hydrogen bond donor. We prepared three PAs with the peptide sequence Phe-Phe-Glu-Glu (FFEE): two are amide-linked with hydrophobic tails of different lengths and the other possesses an alkylated urea group. The differences in the self-assembled structures formed by these PAs were assessed using diverse microscopies, nuclear magnetic resonance (NMR), and dichroism techniques. We found that the urea group influences the morphology and internal arrangement of the assemblies. Molecular dynamics simulations suggest that there are about 50% more hydrogen bonds in nanostructures assembled from the urea-PA than those assembled from the other PAs. Furthermore, in silico studies suggest the presence of urea-π stacking interactions with the phenyl group of Phe, which results in distinct peptide conformations in comparison to the amide-linked PAs. We then studied the effect of the urea modification on the mechanical properties of PA hydrogels. We found that the hydrogel made of the urea-PA exhibits increased stability and self-healing ability. In addition, it allows cell adhesion, spreading, and growth as a matrix. This study reveals that the inclusion of urea bonds might be useful in controlling the morphology, mechanical, and biological properties of self-assembled nanostructures and hydrogels formed by the PAs.

Significantly improved detection performances of immunoassay for ractopamine in urine based on highly urea-tolerant rabbit monoclonal antibody

Highly sensitive and accurate screening of ractopamine (RAC) residue in animal urine is greatly needed to ensure food security. The detection performance of immunoassay for RAC was always seriously harmed by the antibody inactivation derived from urea. Here, we first discovered one rabbit monoclonal antibody (RmAb) to RAC with a high affinity of 0.007 ng mL^-1 and a surprising urea tolerance of 3 M urea, which is beneficial for developing robustly developed immunoassay in urine without sample pretreatment. The limits of detection of developed indirect competitive enzyme-linked immunosorbent assay based on RmAb1 for RAC were 0.0042-0.014 μg L^-1 with the coefficient of variation below 11.7% in swine, sheep, and cow urine, significantly improved 10-100-fold in sensitivity. Moreover, the urea-tolerant mechanism of RmAb1 showed that more non-polar amino acids, more hydrogen bond donors on the surface, and preponderant Pi interaction of antibody-RAC all contributed to the stability of the RmAb1 in a high concentration of urea.

Probing the Interactions Responsible for the Structural Stability of Trypanothione Reductase Through Computer Simulation and Biophysical Characterization

With the necessity to develop antileishmanial drugs with substrate specificity, trypanothione reductase (TryR) has gained popularity in parasitology. TryR is unique to be present only in trypanosomatids and is functionally similar to glutathione in mammals. It protects against oxidative stress exerted by the host defense mechanism. The TryR enzyme is essential for the survival of Leishmania parasites in the host as it reduces trypanothione and aids in neutralizing hydrogen peroxide produced by the host macrophages during infection. Henceforth, it becomes vital to decipher their functional stability and behaviour in the presence of denaturants. Our study is focused on structural, functional and behavioural stability aspects of TryR with different concentrations of Urea, Guanidinium chloride, alcohol based compounds followed by extensive molecular dynamics simulations in a lipid bilayer system. The results obtained from the study reveal an interesting insight into the possible mechanisms of modulation of the structure, function and stability of the TryR protein.

Accessing Organonitrogen Compounds via C-N Coupling in Electrocatalytic CO2 Reduction

Given the limited product variety of electrocatalytic CO₂ reduction reactions solely from CO₂ and H₂O as the reactants, it is desirable to expand the product scope by introducing additional reactants that provide elemental diversity. The integration of inorganic heteroatom-containing reactants into electrocatalytic CO₂ reduction could, in principle, enable the sustainable synthesis of valuable products, such as organonitrogen compounds, which have widespread applications but typically rely on NH₃ derived from the energy-intensive and fossil-fuel-dependent Haber-Bosch process for their industrial-scale production. In this Perspective, research progress toward building C-N bonds in N-integrated electrocatalytic CO₂ reduction is highlighted, and the electrosyntheses of urea, acetamides, and amines are examined from the standpoints of reactivity, catalyst structure, and, most fundamentally, mechanism. Mechanistic discussions of C-N coupling in these advances are emphasized and critically evaluated, with the aim of directing future investigations on improving the product yield and broadening the product scope of N-integrated electrocatalytic CO₂ reduction.

SCONES: Self-Consistent Neural Network for Protein Stability Prediction Upon Mutation

Engineering proteins to have desired properties by mutating amino acids at specific sites is commonplace. Such engineered proteins must be stable to function. Experimental methods used to determine stability at throughputs required to scan the protein sequence space thoroughly are laborious. To this end, many machine learning based methods have been developed to predict thermodynamic stability changes upon mutation. These methods have been evaluated for symmetric consistency by testing with hypothetical reverse mutations. In this work, we propose transitive data augmentation, evaluating transitive consistency with our new S^transitive data set, and a new machine learning based method, the first of its kind, that incorporates both symmetric and transitive properties into the architecture. Our method, called SCONES, is an interpretable neural network that predicts small relative protein stability changes for missense mutations that do not significantly alter the structure. It estimates a residue's contributions toward protein stability (ΔG) in its local structural environment, and the difference between independently predicted contributions of the reference and mutant residues is reported as ΔΔG. We show that this self-consistent machine learning architecture is immune to many common biases in data sets, relies less on data than existing methods, is robust to overfitting, and can explain a substantial portion of the variance in experimental data.

Biophysical Reviews: 2020-looking back, going forward

After first describing the issue contents (Biophysical Reviews-Volume 12 Issue 6), this Editorial goes on to provide a short round-up of the activities of the journal in 2020. Directly following this Editorial are two obituaries marking the recent deaths of Prof. Fumio Oosawa (Japan) and Dr. Herbert Tabor (USA)-two major figures in Biophysical/Biochemical science from the last 100 years.

A new decade for Biophysical Reviews and a look into the future of biophysics

This Editorial for Volume 12 Issue 1 first describes the contents of the current issue before informing on a few of the developments occurring in Biophysical Reviews during 2020. Notable items include the announcement of the (i) inaugural winner of the Michèle Auger Award for Young Scientists' Independent Research and (ii) lineup of Special Issue topics for 2020. This Editorial concludes with a short forward-looking discussion piece on the future of biophysics as an increasingly important and vital sub-discipline of modern scientific research.