Factors affecting product association as a mechanism of host-cell protein persistence in bioprocessing

Product association of host-cell proteins (HCPs) to monoclonal antibodies (mAbs) is widely regarded as a mechanism that can enable HCP persistence through multiple purification steps and even into the final drug substance. Discussion of this mechanism often implies that the existence or extent of persistence is directly related to the strength of binding but actual measurements of the binding affinity of such interactions remain sparse. Two separate avenues of investigation of HCP-mAb binding are reported here. One is the measurement of the affinity of binding of individual, commonly persistent Chinese hamster ovary (CHO) HCPs to each of a set of mAbs, and the other uses quantitative proteomic measurements to assess binding of HCPs in a null CHO harvested cell culture fluid (HCCF) to mAbs produced in the same cell line. The individual HCP measurements show that the binding affinities of individual HCPs to different mAbs can vary appreciably but are rarely very high, with only weak pH dependence. The measurements on the null HCCF allow estimation of individual HCP-mAb affinities; these are typically weaker than those seen in affinity measurements on isolated HCPs. Instead, the extent of binding appears correlated with the initial abundance of individual HCPs in the HCCF and the forms of the HCPs in the solution, i.e., whether HCPs are present as free molecules or as parts of large aggregates. Separate protein A chromatography experiments performed by feeding different fractions of a mAb-containing HCCF obtained by size-exclusion chromatography (SEC) showed clear differences in the number and identity of HCPs found in the protein A eluate. These results indicate a significant role for HCP-mAb association in determining HCP persistence through protein A chromatography, presumably through binding of HCP-mAb complexes to the resin. Overall, the results illustrate the importance of considering more fully the biophysical context of HCP-product association in assessing the factors that may affect the phenomenon and determine its implications. Knowledge of the abundances and the forms of individual or aggregated HCPs in HCCF are particularly significant, emphasizing the integration of upstream and downstream bioprocessing and the importance of understanding the collective properties of HCPs in addition to just the biophysical properties of individual HCPs.

Role of UDP-N-acetylmuramic acid in the regulation of MurA activity revealed by molecular dynamics simulations

The peptidoglycan biosynthesis pathway plays a vital role in bacterial cells, and facilitates peptidoglycan layer formation, a fundamental structural component of the bacterial cell wall. The enzymes in this pathway are candidates for antibiotic development, as most do not have mammalian homologues. The UDP-N-acetylglucosamine (UNAG) enolpyruvyl transferase enzyme (MurA) in the peptidoglycan pathway cytoplasmic step is responsible for the phosphoenolpyruvate (PEP)-UNAG catalytic reaction, forming UNAG enolpyruvate and inorganic phosphate. Reportedly, UDP-N-acetylmuramic acid (UNAM) binds tightly to MurA forming a dormant UNAM-PEP-MurA complex and acting as a MurA feedback inhibitor. MurA inhibitors are complex, owing to competitive binding interactions with PEP, UNAM, and UNAG at the MurA active site. We used computational methods to explore UNAM and UNAG binding. UNAM showed stronger hydrogen-bond interactions with the Arg120 and Arg91 residues, which help to stabilize the closed conformation of MurA, than UNAG. Binding free energy calculations using end-point computational methods showed that UNAM has a higher binding affinity than UNAG, when PEP is attached to Cys115. The unbinding process, simulated using τ-random acceleration molecular dynamics, showed that UNAM has a longer relative residence time than UNAG, which is related to several complex dissociation pathways, each with multiple intermediate metastable states. This prevents the loop from opening and exposing the Arg120 residue to accommodate UNAG and potential new ligands. Moreover, we demonstrate the importance of Cys115-linked PEP in closed-state loop stabilization. We provide a basis for evaluating novel UNAM analogues as potential MurA inhibitors. PUBLIC SIGNIFICANCE: MurA is a critical enzyme involved in bacterial cell wall biosynthesis and is involved in antibiotic resistance development. UNAM can remain in the target protein's active site for an extended time compared to its natural substrate, UNAG. The prolonged interaction of this highly stable complex known as the 'dormant complex' comprises UNAM-PEP-MurA and offers insights into antibiotic development, providing potential options against drug-resistant bacteria and advancing our understanding of microbial biology.

Quantitative analysis of MBW complex formation in the context of trichome patterning

Trichome patterning in Arabidopsis is regulated by R2R3MYB, bHLH and WDR (MBW) genes. These are considered to form a trimeric MBW protein complex that promotes trichome formation. The MBW proteins are engaged in a regulatory network to select trichome cells among epidermal cells through R3MYB proteins that can move between cells and repress the MBW complex by competitive binding with the R2R3MYB to the bHLHL protein. We use quantitative pull-down assays to determine the relative dissociation constants for the protein-protein interactions of the involved genes. We find similar binding strength between the trichome promoting genes and weaker binding of the R3MYB inhibitors. We used the dissociation constants to calculate the relative percentage of all possible complex combinations and found surprisingly low fractions of those complexes that are typically considered to be relevant for the regulation events. Finally, we predict an increased robustness in patterning as a consequence of higher ordered complexes mediated by GL3 dimerization.

The Mutagenic Plasticity of the Cholera Toxin B-Subunit Surface Residues: Stability and Affinity

Mastering selective molecule trafficking across human cell membranes poses a formidable challenge in healthcare biotechnology while offering the prospect of breakthroughs in drug delivery, gene therapy, and diagnostic imaging. The cholera toxin B-subunit (CTB) has the potential to be a useful cargo transporter for these applications. CTB is a robust protein that is amenable to reengineering for diverse applications; however, protein redesign has mostly focused on modifications of the N- and C-termini of the protein. Exploiting the full power of rational redesign requires a detailed understanding of the contributions of the surface residues to protein stability and binding activity. Here, we employed Rosetta-based computational saturation scans on 58 surface residues of CTB, including the GM1 binding site, to analyze both ligand-bound and ligand-free structures to decipher mutational effects on protein stability and GM1 affinity. Complimentary experimental results from differential scanning fluorimetry and isothermal titration calorimetry provided melting temperatures and GM1 binding affinities for 40 alanine mutants among these positions. The results showed that CTB can accommodate diverse mutations while maintaining its stability and ligand binding affinity. These mutations could potentially allow modification of the oligosaccharide binding specificity to change its cellular targeting, alter the B-subunit intracellular routing, or impact its shelf-life and in vivo half-life through changes to protein stability. We anticipate that the mutational space maps presented here will serve as a cornerstone for future CTB redesigns, paving the way for the development of innovative biotechnological tools.

Correlation of Experimental and Calculated Inhibition Constants of Protease Inhibitor Complexes

Predicting the potency of inhibitors is key to in silico screening of promising synthetic or natural compounds. Here we describe a predictive workflow that provides calculated inhibitory values, which concord well with empirical data. Calculations of the free interaction energy ΔG with the YASARA plugin FoldX were used to derive inhibition constants Ki from PDB coordinates of protease-inhibitor complexes. At the same time, corresponding KD values were obtained from the PRODIGY server. These results correlated well with the experimental values, particularly for serine proteases. In addition, analyses were performed for inhibitory complexes of cysteine and aspartic proteases, as well as of metalloproteases, whereby the PRODIGY data appeared to be more consistent. Based on our analyses, we calculated theoretical Ki values for trypsin with sunflower trypsin inhibitor (SFTI-1) variants, which yielded the more rigid Pro14 variant, with probably higher potency than the wild-type inhibitor. Moreover, a hirudin variant with an Arg1 and Trp3 is a promising basis for novel thrombin inhibitors with high potency. Further examples from antibody interaction and a cancer-related effector-receptor system demonstrate that our approach is applicable to protein interaction studies beyond the protease field.

Measuring Protein-Protein Interactions and Quantifying Their Dissociation Constants with Mass Photometry

Protein-protein interactions underlie most biological processes, and determining the affinity and abundance of binding partners for each interaction is often a challenging task because these interactions often involve multiple ligands and binding sites. Standard methods for determining the affinity of protein interactions often require a large amount of starting material in addition to potentially disruptive labeling or immobilization of the binding partners. Mass photometry is a bioanalytical technique that measures the mass of single biomolecules in solution, quickly and with minimal sample requirements. This article describes how mass photometry can be used to determine the mass distribution of binding partners, the complexes they form, the relative abundance of each species, and, accordingly, the dissociation constant (KD ) of their interactions. © 2024 Refeyn Ltd. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Using mass photometry to measure protein-protein binding and quantify the KD of this interaction.

Microfluidic Diffusion Sizing Applied to the Study of Natural Products and Extracts That Modulate the SARS-CoV-2 Spike RBD/ACE2 Interaction

The interaction between SARS-CoV-2 spike RBD and ACE2 proteins is a crucial step for host cell infection by the virus. Without it, the entire virion entrance mechanism is compromised. The aim of this study was to evaluate the capacity of various natural product classes, including flavonoids, anthraquinones, saponins, ivermectin, chloroquine, and erythromycin, to modulate this interaction. To accomplish this, we applied a recently developed a microfluidic diffusional sizing (MDS) technique that allows us to probe protein-protein interactions via measurements of the hydrodynamic radius (Rh) and dissociation constant (KD); the evolution of Rh is monitored in the presence of increasing concentrations of the partner protein (ACE2); and the KD is determined through a binding curve experimental design. In a second time, with the protein partners present in equimolar amounts, the Rh of the protein complex was measured in the presence of different natural products. Five of the nine natural products/extracts tested were found to modulate the formation of the protein complex. A methanol extract of Chenopodium quinoa Willd bitter seed husks (50 µg/mL; bisdesmoside saponins) and the flavonoid naringenin (1 µM) were particularly effective. This rapid selection of effective modulators will allow us to better understand agents that may prevent SARS-CoV-2 infection.

From methodological limitations to the function of metallothioneins - A guide to approaches for determining weak, moderate, and tight affinity zinc sites

Mammalian metallothioneins (MTs) are small cysteine-rich proteins whose primary role is participation in zinc and copper homeostasis. Ever since their discovery, MTs have been investigated in terms of metal-binding affinity. The initial concept of seven Zn(II) ions (Zn7MT) bound with the same, undifferentiated low picomolar affinity in the α and β domains prevailed for many years and derived from spectroscopic studies. The application of fluorescent zinc probes has changed the perception of MTs, showing that they function in nano- to subnanomolar free zinc concentrations due to the presence of tight, moderate, and weak binding sites. The discovery of Zn(II)-depleted MTs in many tissues and determination of cellular free Zn(II) concentrations with differentiated zinc affinity sites revealed the critical importance of partially saturated Zn4-6MTs species in cellular zinc buffering in a wide pico- to nanomolar range of free Zn(II) concentrations. Until today, there is no clear agreement on the presence of differentiated or only tight zinc sites. Here, we present a series of spectroscopic, mass spectrometry-based, and enzymatic competition experiments which reveal how weak, moderate, or high affinity ligands interact with human MT2, with special attention to the determination of Zn(II) affinities. The results show that the simplification of the stability model is the major reason for determining significantly different stability data that obscured the actual MTs function. Therefore, we emphasize that different metal affinities are the single most reason for their presumed function, which changed over the years from tight binding and, thus, storage to one that is highly dynamic.

Dual functionality of pyrimidine and flavone in targeting genomic variants of EGFR and ER receptors to influence the differential survival rates in breast cancer patients

Breast cancer ranks as one of the most prevalent forms of cancer and stands as the primary global cause of mortality among women. Overexpression of EGFR and ER receptors or their genomic alterations leads to malignant transformation, disease aggression and is linked to poor patient survival outcomes. The clinical breast cancer patient's genomic expression, survival analysis, and computational drug-targeting approaches were used to identify best-hit phytochemicals for therapeutic purposes. Breast cancer patients have genomic alterations in EGFR (4%, n = 5699) and ER (9%, n = 8461), with the highest proportion being missense mutations. No statistically significant difference was observed in the patient survival rates between the altered and unaltered ER groups, unlike EGFR, with the lowest survival rates in the altered group. Computational screening of natural compound libraries (7711) against each EGFR (3POZ) and ER (3ERT) receptor shortlists the best-hit 3 compounds with minimum docking score (ΔG = -7.9 to -10.8), MMGBSA (-40.16 to -51.91 kcal/mol), strong intermolecular H-bonding, drug-like properties with least kd, and ki. MD simulation studies display stable RMSD, RMSF, and good residual correlation of best-hit common compounds (PubChem ID: 5281672 and 5280863) targeting both EGFR and ER receptors. In vitro, studies revealed that these common drugs exhibited a high anti-proliferative effect on MCF-7 and MDA-MB-231 breast cancer cells, with effective IC50 values (15-40 μM) and lower free energy, kd, and ki (5281672 > 5280863 > 5330286) much affecting HEK-293 non-cancerous cells, indicating the safety profile. The experimental and computational correlation studies suggest that the highly expressed EGFR and ER receptors in breast cancer patients having poor survival rates can be effectively targeted with best-hit common potent drugs with a multi-target therapeutic approach. Insight Box: The findings of this study provide valuable insights into the genomic/proteomic data, breast cancer patient's survival analysis, and EGFR and ER receptor variants structural analysis. The genetic alterations analysis of EGFR and ER/ESR1 in breast cancer patients reveals the high frequency of mutation types, which affect patient's survival rate and targeted therapies. The common best-hit compounds affect the cell survival patterns with effective IC50, drug-like properties having lower equilibrium and dissociation constants demonstrating the anti-proliferative effects. This work integrates altered receptor structural analysis, molecular interaction-based simulations, and ADMET properties to illuminate the identified best hits phytochemicals potential efficacy targeting both EGFR and ER receptors, demonstrating a multi-target therapeutic approach.

Establishment of a Sensitive Monoclonal Antibody Against Mouse CCR9 (C9Mab-24) for Flow Cytometry

The CC chemokine receptor 9 (CCR9), also known as CD199, is one of chemokine receptors. The CC chemokine ligand 25 (CCL25) is known to be the only ligand for CCR9. The CCR9-CCL25 interaction plays important roles in chemotaxis of lymphocytes and tumor cell migration. Therefore, CCR9-CCL25 axis is a promising target for tumor therapy and diagnosis. In this study, we established a sensitive and specific monoclonal antibody (mAb) against mouse CCR9 (mCCR9) using N-terminal peptide immunization method. The established anti-mCCR9 mAb, C₉Mab-24 (rat immunoglobulin [IgG]_2a, kappa), reacted with mCCR9-overexpressed Chinese hamster ovary-K1 (CHO/mCCR9) and mCCR9-endogenously expressed cell line, RL2, through flow cytometry. Kinetic analyses using flow cytometry showed that the dissociation constants (K_D) of C₉Mab-24 for CHO/mCCR9 and RL2 cell lines were 6.0 × 10^-9 M and 4.7 × 10^-10 M, respectively. Results indicated that C₉Mab-24 is useful for detecting mCCR9 through flow cytometry, thereby providing a possibility for targeting mCCR9-expressing cells in vivo experiments.

A novel consensus-based computational pipeline for screening of antibody therapeutics for efficacy against SARS-CoV-2 variants of concern including Omicron variant

Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to evolve carrying flexible amino acid substitutions in the spike protein's receptor binding domain (RBD). These substitutions modify the binding of the SARS-CoV-2 to human angiotensin-converting enzyme 2 (hACE2) receptor and have been implicated in altered host fitness, transmissibility, and efficacy against antibody therapeutics and vaccines. Reliably predicting the binding strength of SARS-CoV-2 variants RBD to hACE2 receptor and neutralizing antibodies (NAbs) can help assessing their fitness, and rapid deployment of effective antibody therapeutics, respectively. Here, we introduced a two-step computational framework with 3-fold validation that first identified dissociation constant as a reliable predictor of binding affinity in hetero- dimeric and trimeric protein complexes. The second step implements dissociation constant as descriptor of the binding strengths of SARS-CoV-2 variants RBD to hACE2 and NAbs. Then, we examined several variants of concerns (VOCs) such as Alpha, Beta, Gamma, Delta, and Omicron and demonstrated that these VOCs RBD bind to the hACE2 with enhanced affinity. Furthermore, the binding affinity of Omicron variant's RBD was reduced with majority of the RBD-directed NAbs, which is highly consistent with the experimental neutralization data. By studying the atomic contacts between RBD and NAbs, we revealed the molecular footprints of four NAbs (GH-12, P2B-1A1, Asarnow_3D11, and C118)-that may likely neutralize the recently emerged Omicron variant-facilitating enhanced binding affinity. Finally, our findings suggest a computational pathway that could aid researchers identify a range of current NAbs that may be effective against emerging SARS-CoV-2 variants.

Molecular interaction between small nuclear ribonucleoprotein polypeptide G and heat shock protein 70.14: a microscale thermophoresis exposition towards developing anti-cancer drugs

BACKGROUND

Targeting protein-protein interactions (PPIs) linked to protein quality control (PQC) pathways as potential anti-cancer drug targets have unanimously widened biological insights and the therapeutic potential of PPIs as smart-drug discovery tools in cancer. PPIs between disease-relevant proteins associated with protein homeostasis in PQC pathways have been linked to improved mechanistic understanding associated with conformational abnormalities and impairment, cellular proteotoxicity, induced apoptosis, and pathogenesis in different types of cancers. In this context, PPIs between small nuclear ribonucleoprotein polypeptide G (SNRPG) and heat shock protein 70.14 (Hsp70.14) have attracted attention as potential smart drug discovery tools in cancer diagnostics and therapeutics. Validated evidence of high-quality biological data has shown the presence of the two proteins in different types of cancers including breast cancer. The links between SNRPG and Hsp70.14 in cancer-cell networks remain elusive, overlooked, and uncharacterized.

METHODOLOGY

In this study, we explored the interaction between the two oncogenic proteins using the MST-based assays.

RESULTS

The results revealed a low K_D in the nanomolar concentration range of 2.4673 × 10^-7 demonstrating a great affinity for SNRPG binding to Hsp70.14.

CONCLUSIONS

The results suggest a possible involvement between the two proteins in hostile tumour microenvironments. Furthermore, these findings offer a different therapeutic perspective that could pave the way for the creation of novel small molecule inhibitors as drugs for the treatment of cancer.

An Automated Approach to Assess Relative Galectin-Glycan Affinity Following Glycan Microarray Analysis

Numerous studies have highlighted the utility of glycan microarray analysis for the elucidation of protein-glycan interactions. However, most current glycan microarray studies analyze glycan binding protein (GBP)-glycan interactions at a single protein concentration. While this approach provides useful information related to a GBP's overall binding capabilities, extrapolation of true glycan binding preferences using this method fails to account for printing variations or other factors that may confound relative binding. To overcome this limitation, we examined glycan array binding of three galectins over a range of concentrations to allow for a more complete assessment of binding preferences. This approach produced a richer data set than single concentration analysis and provided more accurate identification of true glycan binding preferences. However, while this approach can be highly informative, currently available data analysis approaches make it impractical to perform binding isotherms for each glycan present on currently available platforms following GBP evaluation. To overcome this limitation, we developed a method to directly optimize the efficiency of assessing association constants following multi-GBP concentration glycan array analysis. To this end, we developed programs that automatically analyze raw array data (kdMining) to generate output graphics (kaPlotting) following array analysis at multiple doses. These automatic programing methods reduced processing time from 32.8 h to 1.67 min. Taken together, these results demonstrate an effective approach to glycan array analysis that provides improved detail and efficiency when compared to previous methods.

Detection of electrostatic molecular binding using the water proton signal

PURPOSE

Saturation transfer MRI has previously been used to probe molecular binding interactions with signal enhancement via the water signal. Here, we detail the relayed nuclear overhauser effect (rNOE) based mechanisms of this signal enhancement, develop a strategy of quantifying molecular binding affinity, i.e., the dissociation constant ( K D $$ {K}_D $$ ), and apply the method to detect electrostatic binding of several charged small biomolecules. Another goal was to estimate the detection limit for transient receptor-substrate binding.

THEORY AND METHODS

The signal enhancement mechanism was quantitatively described by a three-step magnetization transfer model, and numerical simulations were performed to verify this theory. The binding equilibria of arginine, choline, and acetyl-choline to anionic resin were studied as a function of ligand concentration, pH, and salt content. Equilibrium dissociation constants ( K D $$ {K}_D $$ ) were determined by fitting the multiple concentration data.

RESULTS

The numerical simulations indicate that the signal enhancement is sufficient to detect the molecular binding of sub-millimolar (∼100 μM) concentration ligands to low micromolar levels of molecular targets. The measured rNOE signals from arginine, choline, and acetyl-choline binding experiments show that several magnetization transfer pathways (intra-ligand rNOEs and intermolecular rNOEs) can contribute. The rNOEs that arise from molecular ionic binding were influenced by pH and salt concentration. The molecular binding strengths in terms of K D $$ {K}_{\mathrm{D}} $$ ranged from 70-160 mM for the three cations studied.

CONCLUSION

The capability to use MRI to detect the transient binding of small substrates paves a pathway towards the detection of micromolar level receptor-substrate binding in vivo.

PPI-Affinity: A Web Tool for the Prediction and Optimization of Protein-Peptide and Protein-Protein Binding Affinity

Virtual screening of protein–protein and protein–peptide interactions is a challenging task that directly impacts the processes of hit identification and hit-to-lead optimization in drug design projects involving peptide-based pharmaceuticals. Although several screening tools designed to predict the binding affinity of protein–protein complexes have been proposed, methods specifically developed to predict protein–peptide binding affinity are comparatively scarce. Frequently, predictors trained to score the affinity of small molecules are used for peptides indistinctively, despite the larger complexity and heterogeneity of interactions rendered by peptide binders. To address this issue, we introduce PPI-Affinity, a tool that leverages support vector machine (SVM) predictors of binding affinity to screen datasets of protein–protein and protein–peptide complexes, as well as to generate and rank mutants of a given structure. The performance of the SVM models was assessed on four benchmark datasets, which include protein–protein and protein–peptide binding affinity data. In addition, we evaluated our model on a set of mutants of EPI-X4, an endogenous peptide inhibitor of the chemokine receptor CXCR4, and on complexes of the serine proteases HTRA1 and HTRA3 with peptides. PPI-Affinity is freely accessible at https://protdcal.zmb.uni-due.de/PPIAffinity.

Fluorescence Lifetime Phasor Analysis of the Decamer-Dimer Equilibrium of Human Peroxiredoxin 1

Protein self-assembly is a common feature in biology and is often required for a myriad of fundamental processes, such as enzyme activity, signal transduction, and transport of solutes across membranes, among others. There are several techniques to find and assess homo-oligomer formation in proteins. Naturally, all these methods have their limitations, meaning that at least two or more different approaches are needed to characterize a case study. Herein, we present a new method to study protein associations using intrinsic fluorescence lifetime with phasors. In this case, the method is applied to determine the equilibrium dissociation constant (KD) of human peroxiredoxin 1 (hPrx1), an efficient cysteine-dependent peroxidase, that has a quaternary structure comprised of five head-to-tail homodimers non-covalently arranged in a decamer. The hPrx1 oligomeric state not only affects its activity but also its association with other proteins. The excited state lifetime of hPrx1 has distinct values at high and low concentrations, suggesting the presence of two different species. Phasor analysis of hPrx1 emission lifetime allowed for the identification and quantification of hPrx1 decamers, dimers, and their mixture at diverse protein concentrations. Using phasor algebra, we calculated the fraction of hPrx1 decamers at different concentrations and obtained KD (1.1 × 10-24 M4) and C0.5 (1.36 μM) values for the decamer-dimer equilibrium. The results were validated and compared with size exclusion chromatography. In addition, spectral phasors provided similar results despite the small differences in emission spectra as a function of hPrx1 concentration. The phasor approach was shown to be a highly sensitive and quantitative method to assess protein oligomerization and an attractive addition to the biophysicist's toolkit.

Principles and pitfalls of high-throughput analysis of microRNA-binding thermodynamics and kinetics by RNA Bind-n-Seq

RNA Bind-n-Seq (RBNS) is a cost-effective, high-throughput method capable of identifying the sequence preferences of RNA-binding proteins and of qualitatively defining relative dissociation constants. Although RBNS is often described as an unbiased method, several factors may influence the outcome of the analysis. Here, we discuss these biases and present an analytical strategy to estimate absolute binding affinities from RBNS data, extend RBNS to kinetic studies, and develop a framework to compute relative association and dissociation rate constants. As proof of principle, we measured the equilibrium binding properties of mammalian Argonaute2 (AGO2) guided by eight microRNAs (miRNAs) and kinetic parameters for let-7a. The miRNA-binding site repertoires, dissociation constants, and kinetic parameters calculated from RBNS data using our methods correlate well with values measured by traditional ensemble and single-molecule approaches. Our data provide additional quantitative measurements for Argonaute-bound miRNA binding that should facilitate development of quantitative targeting rules for individual miRNAs.

Capillary electrophoresis applied for the determination of acidity constants and limiting electrophoretic mobilities of ionizable herbicides including glyphosate and its metabolites and for their simultaneous separation

Thermodynamic acidity constants and limiting ionic mobilities were determined for polyprotic non-chromophore analytes using capillary electrophoresis with capacitively coupled contactless conductivity detection. It was not necessary to work with buffers of identical ionic strength as ionic strength effects on effective electrophoretic mobilities were corrected by modeling during data evaluation (software AnglerFish). The mobility data from capillary electrophoresis coupled to conductivity detection were determined in the pH range from 1.25 to 12.02 with a high resolution (36 pH steps). With this strategy, thermodynamic acidity constants and limiting ionic mobilities for various acidic herbicides were determined, sometimes for the first time. The model analytes included glyphosate, its metabolites, and its acetylated derivates (aminomethyl phosphonic acid, glyoxylic acid, sarcosine, glycine, N-acetyl glyphosate, N-acetyl aminomethyl phosphonic acid, hydroxymethyl phosphonic acid). The obtained data were used in simulations to optimize separations by capillary electrophoresis. Simulations correlated very well to experimental results. With the new method, the separation of glyphosate from interfering components like phosphate in beer samples was possible.

Systems analysis shows that thermodynamic physiological and pharmacological fundamentals drive COVID-19 and response to treatment

Why a systems analysis view of this pandemic? The current pandemic has inflicted almost unimaginable grief, sorrow, loss, and terror at a global scale. One of the great ironies with the COVID‐19 pandemic, particularly early on, is counter intuitive. The speed at which specialized basic and clinical sciences described the details of the damage to humans in COVID‐19 disease has been impressive. Equally, the development of vaccines in an amazingly short time interval has been extraordinary. However, what has been less well understood has been the fundamental elements that underpin the progression of COVID‐19 in an individual and in populations. We have used systems analysis approaches with human physiology and pharmacology to explore the fundamental underpinnings of COVID‐19 disease. Pharmacology powerfully captures the thermodynamic characteristics of molecular binding with an exogenous entity such as a virus and its consequences on the living processes well described by human physiology. Thus, we have documented the passage of SARS‐CoV‐2 from infection of a single cell to species jump, to tropism, variant emergence and widespread population infection. During the course of this review, the recurrent observation was the efficiency and simplicity of one critical function of this virus. The lethality of SARS‐CoV‐2 is due primarily to its ability to possess and use a variable surface for binding to a specific human target with high affinity. This binding liberates Gibbs free energy (GFE) such that it satisfies the criteria for thermodynamic spontaneity. Its binding is the prelude to human host cellular entry and replication by the appropriation of host cell constituent molecules that have been produced with a prior energy investment by the host cell. It is also a binding that permits viral tropism to lead to high levels of distribution across populations with newly formed virions. This thermodynamic spontaneity is repeated endlessly as infection of a single host cell spreads to bystander cells, to tissues, to humans in close proximity and then to global populations. The principal antagonism of this process comes from SARS‐CoV‐2 itself, with its relentless changing of its viral surface configuration, associated with the inevitable emergence of variants better configured to resist immune sequestration and importantly with a greater affinity for the host target and higher infectivity. The great value of this physiological and pharmacological perspective is that it reveals the fundamental thermodynamic underpinnings of SARS‐CoV‐2 infection.

Properties and Activity of Peptide Derivatives of ACE2 Cellular Receptor and Their Interaction with SARS-CoV-2 S Protein Receptor-Binding Domain

The aim of this work was to design and characterize peptides based on the α-helices h1 and h2 of the ACE2 receptor, forming the interaction interface between the receptor-binding domain (RBD) of the SARS-CoV-2 S protein and the cellular ACE2 receptor. Monomeric and heterodimeric peptides connected by disulfide bonds at different positions were synthesized. Solubility, RBD-binding affinity, and peptide helicity were experimentally measured, and molecular dynamics simulation was performed in various solvents. It was established that the preservation of the helical conformation is a necessary condition for the binding of peptides to RBD. The peptides have a low degree of helicity and low affinity for RBD in water. Dimeric peptides have a higher degree of helicity than monomeric ones, probably due to the mutual influence of helices. The degree of helicity of the peptides in trifluoroethanol is the highest; however, for in vitro studies, the most suitable solvent is a water-ethanol mixture.

[Determination of absolute mobility and dissociation constant of lovastatin using capillary electrophoresis and empirical equation of ion mobility]

作为一种可以预防动脉粥样硬化和冠心病的潜在药物洛伐他汀,其绝对淌度m₀和解离常数pK_a值的测定有助于其性质与应用的研究。在前期相关研究基础上,该文提出了一种基于毛细管区带电泳(CZE)和离子淌度经验公式测定洛伐他汀m₀和pK_a的新方法。首先,根据经验公式由实际淌度(m_act)、有效淌度(m_eff)和m₀之间的关系推导出m₀的计算公式。对于一元酸HA,根据之前m₀的计算公式,以氢离子的浓度为自变量,m_eff的倒数为因变量可得到一条直线。根据这条直线的斜率计算得到pK_a。为了验证该方法的可行性和可靠性,应用该方法测定了巴比妥酸、苯甲酸、苄胺、苯酚、间甲酚等有机酸碱的m₀和pK_a值。同时,对于pH值低于6的缓冲体系,采用反向毛细管电泳技术,测定其pK_a,并将测得的实验结果与理论参考值进行对比,发现两者具有较高的一致性,m₀的标准偏差小于6.0%, pK_a的标准偏差小于6.2%,且由线性回归方程的相关系数(R)可以看出测定pK_a时的线性回归直线拟合度较好,说明该文建立的新方法具有较高的可靠性。最后基于这种CZE与经验公式结合的新方法,采用二甲基亚砜(DMSO)作为电渗流标记物测定了洛伐他汀的m₀和pK_a,得到的值分别为-1.70×10^-8 m²/(V·s)和9.00。该方法适用于酸性和碱性分析物m₀和pK_a等理化参数的测定,在药物分析尤其是新药理化特性研究中具有重要意义。

Analysis of protein-ligand interactions from titrations and nuclear magnetic resonance relaxation dispersions

We present PLIS, a publicly available, open‐source software for the determination of protein–ligand dissociation constants that can be used to characterize biological processes or to shed light on biophysical aspects of interactions. PLIS can analyze data from titration experiments monitored by for instance fluorescence spectroscopy or from nuclear magnetic resonance relaxation dispersion experiments. In addition to analysis of experimental data, PLIS includes functionality for generation of synthetic data, useful for understanding how different parameters effect the data in order to better analyze experiments.

Preliminary Structural Data Revealed That the SARS-CoV-2 B.1.617 Variant's RBD Binds to ACE2 Receptor Stronger Than the Wild Type to Enhance the Infectivity

The evolution of new SARS-CoV-2 variants around the globe has made the COVID-19 pandemic more worrisome, further pressuring the health care system and immunity. Novel variations that are unique to the receptor-binding motif (RBM) of the receptor-binding domain (RBD) spike glycoprotein, i. e. L452R-E484Q, may play a different role in the B.1.617 (also known as G/452R.V3) variant's pathogenicity and better survival compared to the wild type. Therefore, a thorough analysis is needed to understand the impact of these mutations on binding with host receptor (RBD) and to guide new therapeutics development. In this study, we used structural and biomolecular simulation techniques to explore the impact of specific mutations (L452R-E484Q) in the B.1.617 variant on the binding of RBD to the host receptor ACE2. Our analysis revealed that the B.1.617 variant possesses different dynamic behaviours by altering dynamic-stability, residual flexibility and structural compactness. Moreover, the new variant had altered the bonding network and structural-dynamics properties significantly. MM/GBSA technique was used, which further established the binding differences between the wild type and B.1.617 variant. In conclusion, this study provides a strong impetus to develop novel drugs against the new SARS-CoV-2 variants.

Quantitative Chemical Proteomics Reveals Interspecies Variations on Binding Schemes of L-FABP with Perfluorooctanesulfonate

Evaluating interspecies toxicity variation is a long-standing challenge for chemical hazard assessment. This study developed a quantitative interspecies thermal shift assay (QITSA) for in situ, quantitative, and modest-throughput investigation of chemical-protein interactions in cell and tissue samples across species. By using liver fatty acid binding protein (L-FABP) as a case study, the QITSA method was benchmarked with six per- and polyfluoroalkyl substances, and thermal shifts (ΔT_m) were inversely related to their dissociation constants (R² = 0.98). The QITSA can also distinguish binding modes of chemicals exemplified by palmitic acid. The QITSA was applied to determine the interactions between perfluorooctanesulfonate (PFOS) and L-FABP in liver cells or tissues from humans, mice, rats, and zebrafish. The largest thermal stability enhancement by PFOS was observed for human L-FABP followed by the mouse, rat, and zebrafish. While endogenous ligands were revealed to partially contribute to the large interspecies variation, recombinant proteins were employed to confirm the high binding affinity of PFOS to human L-FABP, compared to the rat and mouse. This study implemented an experimental strategy to characterize chemical-protein interactions across species, and future application of QITSA to other chemical contaminants is of great interest.

The Kinetics of Chitosan Degradation in Organic Acid Solutions

This paper presents a comparative study on chitosan degradation in organic acid solutions according to their different dissociation characteristics. More precisely, the aim of the study was to determine the kinetics of the degradation process depending on the different acid dissociation constants (pKa values). The scientists involved in chitosan to date have focused mainly on acetic acid solutions. Solutions of lactic, acetic, malic, and formic acids in concentrations of 3% wt. were used in this research. The progress of degradation was determined based on the intrinsic viscosity measurement, GPC/SEC chromatographic analysis, and their correlation. Changes in the viscosity parameters were performed at a temperature of 20 °C ± 1 °C and a timeframe of up to 168 h (7 days). The chemical structure and DDA of the initial chitosan were analyzed using 1H-NMR spectroscopy analysis. The results of this study can be considered of high importance for the purpose of electrospinning, production of micro- and nano-capsules for drug delivery, and other types of processing. Understanding the influence of the dissociation constant of the solvent on the kinetics of chitosan degradation will allow the selection of an appropriate medium, ensuring an effective and stable spinning process, in which the occurrence of polymer degradation is unfavorable.

Quantifying H+ exchange from muscle cytosolic energy catabolism using metabolite flux and H+ coefficients from multiple competitive cation binding: New evidence for consideration in established theories

The purpose of this investigation was to present calculations of fractional H+ exchange (~H+e ) from the chemical reactions of non-mitochondrial energy catabolism. Data of muscle pH and metabolite accumulation were based on published research for intense exercise to contractile failure within ~3 min, from which capacities and time profiles were modeled. Data were obtained from prior research for multiple competitive cation dissociation constants of metabolites and the chemical reactions of non-mitochondrial energy catabolism, and pH dependent calculations of ~H+e from specific chemical reactions. Data revealed that the 3 min of intense exercise incurred a total ATP turnover of 142.5 mmol L-1 , with a total intramuscular ~H+ exchange (-'ve = release) of -187.9 mmol L-1 . Total ~H+ metabolic consumption was 130.6 mmol L-1 , revealing a net total ~H+e (~H+te ) of -57.3 mmol L-1 . Lactate production had a ~H+te of 44.2 mmol L-1 (for a peak accumulation = 45 mmol L-1 ). The net ~H+te for the sum of the CK, AK, and AMPD reactions was 36.33 mmol L-1 . The ~H+te from ATP turnover equaled -47.5 mmol L-1 . The total ~H+ release to lactate ratio was 4.3 (187.9/44). Muscle ~H+ release during intense exercise is up to ~4-fold larger than previously assumed based on the lactic acid construct.

Principles and practice of determining metal-protein affinities

Metal ions play many critical roles in biology, as structural and catalytic cofactors, and as cell regulatory and signalling elements. The metal–protein affinity, expressed conveniently by the metal dissociation constant, K_D, describes the thermodynamic strength of a metal–protein interaction and is a key parameter that can be used, for example, to understand how proteins may acquire metals in a cell and to identify dynamic elements (e.g. cofactor binding, changing metal availabilities) which regulate protein metalation in vivo. Here, we outline the fundamental principles and practical considerations that are key to the reliable quantification of metal–protein affinities. We review a selection of spectroscopic probes which can be used to determine protein affinities for essential biological transition metals (including Mn(II), Fe(II), Co(II), Ni(II), Cu(I), Cu(II) and Zn(II)) and, using selected examples, demonstrate how rational probe selection combined with prudent experimental design can be applied to determine accurate K_D values.

Contribution to the Understanding of the Interaction between a Polydopamine Molecular Imprint and a Protein Model: Ionic Strength and pH Effect Investigation

Several studies were devoted to the design of molecularly imprinted polymer (MIP)-based sensors for the detection of a given protein. Here, we bring elements that could contribute to the understanding of the interaction mechanism involved in the recognition of a protein by an imprint. For this purpose, a polydopamine (PDA)-MIP was designed for bovine serum albumin (BSA) recognition. Prior to BSA grafting, the gold surfaces were functionalized with mixed self-assembled monolayers of (MUDA)/(MHOH) (1/9, v/v). The MIP was then elaborated by dopamine electropolymerization and further extraction of BSA templates by incubating the electrode in proteinase K solution. Three complementary techniques, electrochemistry, zetametry, and Fourier-transform infrared spectrometry, were used to investigate pH and ionic strength effects on a MIP's design and the further recognition process of the analytes by the imprints. Several MIPs were thus designed in acidic, neutral, and basic media and at various ionic strength values. Results indicate that the most appropriate conditions, to achieve a successful MIPs, were an ionic strength of 167 mM and a pH of 7.4. Sensitivity and dissociation constant of the designed sensor were of order of (3.36 ± 0.13) µA·cm-2·mg-1·mL and (8.56 ± 6.09) × 10-11 mg/mL, respectively.

Understanding the binding interaction between phenyl boronic acid P1 and sugars: determination of association and dissociation constants using S-V plots, steady-state spectroscopic methods and molecular docking

Continuous monitoring of glucose and sugar sensing plays a vital role in diabetes control. The drawbacks of the present enzyme-based sugar sensors have encouraged the investigation into alternate approaches to design new sensors. The popularity of fluorescence sensors is due to their ability to bind reversibly to compounds containing diol. In this study we investigated the binding ability of phenyl boronic acid P1 for monosaccharides and disaccharides (sugars) in aqueous medium at physiological pH 7.4 using steady-state fluorescence and absorbance. P1 fluorescence was quenched due to formation of esters with sugars. Absorbance and fluorescence measurements led to results that indicated that the sugars studied could be ordered in terms of their affinity to P1, as stated: sucrose > lactose > galactose > xylose > ribose > arabinose. In each case, the slope of modified Stern-Volmer plots was nearly 1, indicating the presence of only a single binding site in boronic acids for sugars. Docking studies were carried out using Schrodinger Maestro v.11.2 software. The binding affinity of phenyl boronic acid P1 with periplasmic protein (PDB ID 2IPM and 2IPL) was estimated using GlideScore.

How to measure and evaluate binding affinities

Quantitative measurements of biomolecule associations are central to biological understanding and are needed to build and test predictive and mechanistic models. Given the advances in high-throughput technologies and the projected increase in the availability of binding data, we found it especially timely to evaluate the current standards for performing and reporting binding measurements. A review of 100 studies revealed that in most cases essential controls for establishing the appropriate incubation time and concentration regime were not documented, making it impossible to determine measurement reliability. Moreover, several reported affinities could be concluded to be incorrect, thereby impacting biological interpretations. Given these challenges, we provide a framework for a broad range of researchers to evaluate, teach about, perform, and clearly document high-quality equilibrium binding measurements. We apply this framework and explain underlying fundamental concepts through experimental examples with the RNA-binding protein Puf4.

On the Electrochemical Detection of Alpha-Fetoprotein Using Aptamers: DNA Isothermal Amplification Strategies to Improve the Performance of Weak Aptamers

Affinity characterization is essential to develop reliable aptamers for tumor biomarker detection. For alpha-fetoprotein (AFP), a biomarker of hepatocellular carcinoma (HCC), two DNA aptamers were described with very different affinity. In this work, we estimate the dissociation constant of both of them by means of a direct assay on magnetic beads modified with AFP and electrochemical detection on carbon screen-printed electrodes (SPCE). Unlike previous works, both aptamers showed similar dissociation constant (Kd) values, in the subµM range. In order to improve the performance of these aptamers, we proposed the isothermal amplification of the aptamers by both terminal deoxynucleotidyl transferase (TdT) and rolling circle amplification (RCA). Both DNA amplifications improved the sensitivity and also the apparent binding constants from 713 nM to 189 nM for the short aptamer and from 526 nM to 32 nM for the long aptamer. This improvement depends on the true affinity of the binding pair, which ultimately limits the analytical usefulness.

Analyzing organophosphate pesticide-serum albumin binding interaction: a combined STD NMR and molecular docking study

In Vitro analysis of the interaction of organophosphate pesticides (OP) with bovine serum albumin (BSA) is crucial to understand their potential effects at the molecular level. In this context, we have employed Saturation Transfer Difference (STD) NMR experiments in conjunction with molecular docking studies to unravel the binding interaction of the OP chlorpyrifos (CPF), diazinon (DZN) and parathion (PA) in solution. The relative STD (%) suggested the detailed epitope mapping of these OP with BSA while the concentration-dependent STD NMR studies were performed to obtain the complex dissociation constant (K_D) of the OP-BSA complexes; K_D=1.81 × 10^-4 M, 1.30 × 10^-3 M and 1.11 × 10^-3 M for CPF, DZN and PA were extracted respectively. Similar binding modes were identified for all the three OP using STD site-marker experiment. ITC experiments were performed as a complementary method that revealed a high binding affinity of OP-BSA complexes through non-covalent interaction. Molecular docking confirmed the possible interacting chemical groups of OP-BSA complexes. These significant results furnish valuable information about the toxicity risk of OP to proteins.Communicated by Ramaswamy H. Sarma.

Activity of N-Phenylpiperazine Derivatives Against Bacterial and Fungal Pathogens

BACKGROUND

As the bacterial resistance to antibacterial chemotherapeutics is one of the greatest problems in modern medicine, efforts are made to develop new antimicrobial drugs. Compounds with a piperazine ring have proved to be promising agents against various pathogens.

OBJECTIVE

The aim of the study was to prepare a series of new N-phenylpiperazines and determine their activity against various pathogens.

METHOD

Target compounds were prepared by multi-step synthesis starting from an appropriate substituted acid to an oxirane intermediate reacting with 1-(4-nitrophenyl)piperazine. Lipophilicity and pKa values were experimentally determined. Other molecular parameters were calculated. The inhibitory activity of the target compounds against Staphylococcus aureus, four mycobacteria strains, Bipolaris sorokiniana, and Fusarium avenaceum was tested. In vitro antiproliferative activity was determined on a THP-1 cell line, and toxicity against plant was determined using Nicotiana tabacum.

RESULTS

In general, most compounds demonstrated only moderate effects. 1-(2-Hydroxy-3-{[4-(propan- 2-yloxy)benzoyl]oxy}propyl)-4-(4-nitrophenyl)piperazinediium dichloride and 1-{3-[(4-butoxybenzoyl)- oxy]-2-hydroxypropyl}-4-(4-nitrophenyl)piperazinediium dichloride showed the highest inhibition activity against M. kansasii (MIC = 15.4 and 15.0 µM, respectively) and the latter also against M. marinum (MIC = 15.0 µM). 1-(2-Hydroxy-3-{[4-(2-propoxyethoxy)benzoyl]oxy}propyl)-4-(4-nitrophenyl)piperazinediium dichloride had the highest activity against F. avenaceum (MIC = 14.2 µM). All the compounds showed only insignificant toxic effects on human and plant cells.

CONCLUSION

Ten new 1-(4-nitrophenyl)piperazine derivatives were prepared and analyzed, and their antistaphylococcal, antimycobacterial, and antifungal activities were determined. The activity against M. kansasii was positively influenced by higher lipophilicity, the electron-donor properties of substituent R and a lower dissociation constant. The exact mechanism of action will be investigated in follow-up studies.

A structure-based model for the prediction of protein-RNA binding affinity

Protein-RNA recognition is highly affinity-driven and regulates a wide array of cellular functions. In this study, we have curated a binding affinity data set of 40 protein-RNA complexes, for which at least one unbound partner is available in the docking benchmark. The data set covers a wide affinity range of eight orders of magnitude as well as four different structural classes. On average, we find the complexes with single-stranded RNA have the highest affinity, whereas the complexes with the duplex RNA have the lowest. Nevertheless, free energy gain upon binding is the highest for the complexes with ribosomal proteins and the lowest for the complexes with tRNA with an average of -5.7 cal/mol/Å2 in the entire data set. We train regression models to predict the binding affinity from the structural and physicochemical parameters of protein-RNA interfaces. The best fit model with the lowest maximum error is provided with three interface parameters: relative hydrophobicity, conformational change upon binding and relative hydration pattern. This model has been used for predicting the binding affinity on a test data set, generated using mutated structures of yeast aspartyl-tRNA synthetase, for which experimentally determined ΔG values of 40 mutations are available. The predicted ΔGempirical values highly correlate with the experimental observations. The data set provided in this study should be useful for further development of the binding affinity prediction methods. Moreover, the model developed in this study enhances our understanding on the structural basis of protein-RNA binding affinity and provides a platform to engineer protein-RNA interfaces with desired affinity.

Sub-Micromolar Pulse Dipolar EPR Spectroscopy Reveals Increasing CuII -labelling of Double-Histidine Motifs with Lower Temperature

Electron paramagnetic resonance (EPR) distance measurements are making increasingly important contributions to the studies of biomolecules by providing highly accurate geometric constraints. Combining double‐histidine motifs with Cu^II spin labels can further increase the precision of distance measurements. It is also useful for proteins containing essential cysteines that can interfere with thiol‐specific labelling. However, the non‐covalent Cu^II coordination approach is vulnerable to low binding‐affinity. Herein, dissociation constants (K_D) are investigated directly from the modulation depths of relaxation‐induced dipolar modulation enhancement (RIDME) EPR experiments. This reveals low‐ to sub‐μm Cu^IIK_Ds under EPR distance measurement conditions at cryogenic temperatures. We show the feasibility of exploiting the double‐histidine motif for EPR applications even at sub‐μm protein concentrations in orthogonally labelled Cu^II–nitroxide systems using a commercial Q‐band EPR instrument.

All tubulins are not alike: Heterodimer dissociation differs among different biological sources

Tubulin, the subunit of microtubules, is a noncovalent heterodimer composed of one α- and one β-tubulin monomer. Both tubulins are encoded by multiple genes or composed of different isotypes, which are differentially expressed in different tissues and in development. Tubulin αβ dimers are found throughout the eukaryotes and, although very similar, are known to differ among organisms. We seek to investigate tubulins from different tissues and different organisms for a basic physical characteristic: heterodimer stability and monomer exchange between heterodimers. We previously showed that mammalian brain tubulin heterodimers reversibly dissociate, following the mass action law. Dissociation yields native monomers that can exchange with added tubulin to form new heterodimers. Here, we compared the dissociation of tubulins from multiple sources, including mammalian (rat) brain, cultured human cells (HeLa cells), chicken brain, chicken erythrocytes, and the protozoan Leishmania We used fluorescence-detected analytical ultracentrifugation to measure tubulin dissociation over a >1000-fold range in concentration and found that tubulin heterodimers from different biological sources differ in K_d by as much as 150-fold under the same conditions. Furthermore, when fluorescent tracer tubulins from various sources were titrated with unlabeled tubulin from a single source (rat brain tubulin), heterologous dimerization occurred, exhibiting similar affinities, in some cases binding even more strongly than with autologous tubulin. These results provide additional insight into the regulation of heterodimer formation of tubulin from different biological sources, revealing that monomer exchange appears to contribute to the sorting of α- and β-tubulin monomers that associate following tubulin folding.

Single-cell quantification of the concentrations and dissociation constants of endogenous proteins

Kinetic simulation is a useful approach for elucidating complex cell-signaling systems. The numerical simulations required for kinetic modeling in live cells critically require parameters such as protein concentrations and dissociation constants (K_d ). However, only a limited number of parameters have been measured experimentally in living cells. Here we describe an approach for quantifying the concentration and K_d of endogenous proteins at the single-cell level with CRISPR/Cas9-mediated knock-in and fluorescence cross-correlation spectroscopy. First, the mEGFP gene was knocked in at the end of the mitogen-activated protein kinase 1 (MAPK1) gene, encoding extracellular signal-regulated kinase 2 (ERK2), through homology-directed repair or microhomology-mediated end joining. Next, the HaloTag gene was knocked in at the end of the ribosomal S6 kinase 2 (RSK2) gene. We then used fluorescence correlation spectroscopy to measure the protein concentrations of endogenous ERK2-mEGFP and RSK2-HaloTag fusion constructs in living cells, revealing substantial heterogeneities. Moreover, fluorescence cross-correlation spectroscopy analyses revealed temporal changes in the apparent K_d values of the binding between ERK2-mEGFP and RSK2-HaloTag in response to epidermal growth factor stimulation. Our approach presented here provides a robust and efficient method for quantifying endogenous protein concentrations and dissociation constants in living cells.

Using Fluorescence Anisotropy for Ligand Binding Kinetics of Membrane Proteins

Determining ligand binding kinetics provides an indirect route to probe the functional capabilities of the binding pocket of a membrane protein receptor. Presented in this unit are four ligand-binding protocols that provide data useful for characterizing membrane proteins, including equilibrium binding, thermostability, competitive ligand binding, and kinetic ligand binding. These techniques use fluorescence anisotropy, which is safer, less costly, and simpler to execute than radioactive ligand binding. Each protocol may be used on its own or in combination with others to quantify a number of ligand binding constants. © 2018 by John Wiley & Sons, Inc.

Disruption of the E. coli LptC dimerization interface and characterization of lipopolysaccharide and LptA binding to monomeric LptC

Lipopolysaccharide (LPS) is an essential element of nearly all Gram-negative bacterial outer membranes and serves to protect the cell from adverse environmental stresses. Seven members of the lipopolysaccharide transport (Lpt) protein family function together to transport LPS from the inner membrane (IM) to the outer leaflet of the outer membrane of bacteria such as Escherichia coli. Each of these proteins has a solved crystal structure, including LptC, which is a largely periplasmic protein that is associated with the IM LptB2 FG complex and anchored to the membrane by an N-terminal helix. LptC directly binds LPS and is hypothesized to be involved in the transfer of LPS to another periplasmic protein, LptA. Purified and in solution, LptC forms a dimer. Here, point mutations designed to disrupt formation of the dimer are characterized using site-directed spin labeling double electron electron resonance (DEER) spectroscopy, light scattering, circular dichroism, and computational modeling. The computational studies reveal the molecular interactions that drive dimerization of LptC and elucidate how the disruptive mutations change this interaction, while the DEER and light scattering studies identify which mutants disrupt the dimer. And, using electron paramagnetic resonance spectroscopy and comparing the results to the previous quantitative characterization of the interactions between dimeric LptC and LPS and LptA, the functional consequences of monomeric LptC were also determined. These results indicate that disruption of the dimer does not affect LPS or LptA binding and that monomeric LptC binds LPS and LptA at levels similar to dimeric LptC.

Peptide Probe for Multiwalled Carbon Nanotubes: Electrophoretic Assessment of the Binding Interface and Evaluation of Surface Functionalization

Noncovalent interactions of peptides and proteins with carbon nanotubes play a key role in sensing, dispersion, and biocompatibility. Advances in these areas require that the forces which contribute to physical adsorption are understood in order that the carbon nanotubes present a degree of functionalization appropriate to the desired application. Affinity analyses of peptides are employed to evaluate the role of tryptophan and arginine residues in physical adsorption to carboxylated multiwalled carbon nanotubes. Peptides containing arginine and tryptophan, WR(W) _n, are used with affinity capillary electrophoresis to identify factors that lead to the formation of peptide-carbon nanotube complexes. The effects of changing the amino acid composition and residue length are evaluated by measuring dissociation constants. Electrostatic interactions contribute significantly to complexation, with the strongest interaction observed using the peptide WRWWWW and carboxylated carbon nanotube. Stronger interaction is observed when the tryptophan content is successively increased as follows: WR(W)₄ > WR(W)₃ > WR(W)₂ > WRW > WR. However, as observed with polytryptophan (W₅, W₄, W₃, and W₂), removing the arginine residue significantly reduces the interaction with carbon nanotubes. Increasing the arginine content to WRWWRW does not improve binding, whereas replacing the arginine residue in WRWWWW with lysine (WKWWWW) reveals that lysine also contributes to surface adsorption, but not as effectively as arginine. These observations are used to guide a search of the primary sequence of lysozyme to identify short regions in the peptide that contain a single cationic residue and two aromatic residues. One candidate peptide sequence (WMCLAKW) from this search is analyzed by capillary electrophoresis. The dissociation constant of carboxylated multiwalled carbon nanotubes is measured for the peptide, WMCLAKW, to demonstrate the utility of affinity capillary electrophoresis analysis.

Characterization of and lipopolysaccharide binding to the E. coli LptC protein dimer

Lipopolysaccharide (LPS, endotoxin) is the major component of the outer leaflet of the outer membrane of Gram-negative bacteria such as Escherichia coli and Salmonella typhimurium. LPS is a large lipid containing several acyl chains as its hydrophobic base and numerous sugars as its hydrophilic core and O-antigen domains, and is an essential element of the organisms' natural defenses in adverse environmental conditions. LptC is one of seven members of the lipopolysaccharide transport (Lpt) protein family that functions to transport LPS from the inner membrane (IM) to the outer leaflet of the outer membrane of the bacterium. LptC is anchored to the IM and associated with the IM LptFGB2 complex. It is hypothesized that LPS binds to LptC at the IM, transfers to LptA to cross the periplasm, and is inserted by LptDE into the outer leaflet of the outer membrane. The studies described here comprehensively characterize and quantitate the binding of LPS to LptC. Site-directed spin labeling electron paramagnetic resonance spectroscopy was utilized to characterize the LptC dimer in solution and monitor spin label mobility changes at 10 sites across the protein upon addition of exogenous LPS. The results indicate that soluble LptC forms concentration-independent N-terminal dimers in solution, LptA binding does not change the conformation of the LptC dimer nor appreciably disrupt the LptC dimer in vitro, and LPS binding affects the entire LptC protein, with the center and C-terminal regions showing a greater affinity for LPS than the N-terminal domain, which has similar dissociation constants to LptA.

Use of fluorescence-detected sedimentation velocity to study high-affinity protein interactions

Sedimentation velocity (SV) analytical ultracentrifugation (AUC) is a classic technique for the real-time observation of free macromolecular migration in solution driven by centrifugal force. This enables the analysis of macromolecular mass, shape, size distribution, and interactions. Although traditionally limited to determination of the sedimentation coefficient and binding affinity of proteins in the micromolar range, the implementation of modern detection and data analysis techniques has resulted in marked improvements in detection sensitivity and size resolution during the past decades. Fluorescence optical detection now permits the detection of recombinant proteins with fluorescence excitation at 488 or 561 nm at low picomolar concentrations, allowing for the study of high-affinity protein self-association and hetero-association. Compared with other popular techniques for measuring high-affinity protein-protein interactions, such as biosensing or calorimetry, the high size resolution of complexes at picomolar concentrations obtained with SV offers a distinct advantage in sensitivity and flexibility of the application. Here, we present a basic protocol for carrying out fluorescence-detected SV experiments and the determination of the size distribution and affinity of protein-antibody complexes with picomolar KD values. Using an EGFP-nanobody interaction as a model, this protocol describes sample preparation, ultracentrifugation, data acquisition, and data analysis. A variation of the protocol applying traditional absorbance or an interference optical system can be used for protein-protein interactions in the micromolar KD value range. Sedimentation experiments typically take ∼3 h of preparation and 6-12 h of run time, followed by data analysis (typically taking 1-3 h).

Tripodal Amine Ligands for Accelerating Cu-Catalyzed Azide-Alkyne Cycloaddition: Efficiency and Stability against Oxidation and Dissociation

Ancillary ligands, especially the tripodal ligands such as tris(triazolylmethyl)amines, have been widely used to accelerate the Cu-catalyzed azide-alkyne cycloaddition (CuAAC, a "click" reaction). However, the relationship between the activity of these Cu(I) complexes and their stability against air oxidation and ligand dissociation/exchange was seldom studied, which is critical for the applications of CuAAC in many biological systems. In this work, we synthesized twenty-one Cu(I) tripodal ligands varying in chelate arm length (five to seven atoms), donor groups (triazolyl, pyridyl and phenyl), and steric hindrance. The effects of these variables on the CuAAC reaction, air oxidation, and ligand dissociation were evaluated. Reducing the chelate arm length to five atoms, decreasing steric hindrance, or using a relatively weakly-binding ligand can significantly increase the CuAAC reactivity of the Cu(I) complexes, but the concomitant higher degree of oxidation cannot be avoided, which leads to rapid degradation of a histidine-containing peptide as a model of proteins. The oxidation of the peptide can be reduced by attaching oligo(ethylene glycol) chains to the ligands as sacrificing reagents. Using electrospray ionization mass spectrometry (ESI-MS), we directly observed the tri- and di-copper(I)-acetylide complexes in CuAAC reaction in the [5,5,5] ligand system and a small amount of di-Cu(I)-acetylide in the [5,5,6] ligand system. Only the mono-Cu(I) ligand adducts were observed in the [6,6,6] and [5,6,6] ligand systems.

Efficient Binding of the NOS1AP C-Terminus to the nNOS PDZ Pocket Requires the Concerted Action of the PDZ Ligand Motif, the Internal ExF Site and Structural Integrity of an Independent Element

Neuronal nitric oxide synthase is widely regarded as an important contributor to a number of disorders of excitable tissues. Recently the adaptor protein NOS1AP has emerged as a contributor to several nNOS-linked conditions. As a consequence, the unexpectedly complex mechanisms of interaction between nNOS and its effector NOS1AP have become a particularly interesting topic from the point of view of both basic research and the potential for therapeutic applications. Here we demonstrate that the concerted action of two previously described motif regions contributing to the interaction of nNOS with NOS1AP, the ExF region and the PDZ ligand motif, efficiently excludes an alternate ligand from the nNOS-PDZ ligand-binding pocket. Moreover, we identify an additional element with a denaturable structure that contributes to interaction of NOS1AP with nNOS. Denaturation does not affect the functions of the individual motifs and results in a relatively mild drop, ∼3-fold, of overall binding affinity of the C-terminal region of NOS1AP for nNOS. However, denaturation selectively prevents the concerted action of the two motifs that normally results in efficient occlusion of the PDZ ligand-binding pocket, and results in 30-fold reduction of competition between NOS1AP and an alternate PDZ ligand.

(S)Pinning down protein interactions by NMR

Protein molecules are highly diverse communication platforms and their interaction repertoire stretches from atoms over small molecules such as sugars and lipids to macromolecules. An important route to understanding molecular communication is to quantitatively describe their interactions. These types of analyses determine the amounts and proportions of individual constituents that participate in a reaction as well as their rates of reactions and their thermodynamics. Although many different methods are available, there is currently no single method able to quantitatively capture and describe all types of protein reactions, which can span orders of magnitudes in affinities, reaction rates, and lifetimes of states. As the more versatile technique, solution NMR spectroscopy offers a remarkable catalogue of methods that can be successfully applied to the quantitative as well as qualitative descriptions of protein interactions. In this review we provide an easy-access approach to NMR for the non-NMR specialist and describe how and when solution state NMR spectroscopy is the method of choice for addressing protein ligand interaction. We describe very briefly the theoretical background and illustrate simple protein-ligand interactions as well as typical strategies for measuring binding constants using NMR spectroscopy. Finally, this review provides examples of caveats of the method as well as the options to improve the outcome of an NMR analysis of a protein interaction reaction.

Measuring the sequence-affinity landscape of antibodies with massively parallel titration curves

Despite the central role that antibodies play in the adaptive immune system and in biotechnology, much remains unknown about the quantitative relationship between an antibody’s amino acid sequence and its antigen binding affinity. Here we describe a new experimental approach, called Tite-Seq, that is capable of measuring binding titration curves and corresponding affinities for thousands of variant antibodies in parallel. The measurement of titration curves eliminates the confounding effects of antibody expression and stability that arise in standard deep mutational scanning assays. We demonstrate Tite-Seq on the CDR1H and CDR3H regions of a well-studied scFv antibody. Our data shed light on the structural basis for antigen binding affinity and suggests a role for secondary CDR loops in establishing antibody stability. Tite-Seq fills a large gap in the ability to measure critical aspects of the adaptive immune system, and can be readily used for studying sequence-affinity landscapes in other protein systems.

DOI:http://dx.doi.org/10.7554/eLife.23156.001

Antibodies are proteins produced by cells of the immune system to tag or neutralize potential threats to the body, such as foreign substances and disease-causing microbes. Antibodies do this by binding to target molecules called antigens. An antibody’s ability to bind to an antigen depends on the sequence of amino acids – the building blocks of proteins – that make up the antibody. Through a process that randomizes this sequence of amino acids, the immune system generates a vast pool of antibodies that are able to target almost any foreign antigen that exists in nature.

Currently, little is understood about how the sequence of amino acids in an antibody determines how strongly that antibody binds to its antigen target – a property referred to as the antibody’s binding affinity. Answering this fundamental question requires techniques that can measure the affinities of many different antibodies at the same time. However, previous high-throughput methods have been unable to provide quantitative measurements of binding affinities. These kinds of measurements are difficult because an antibody’s amino acid sequence governs more than just binding affinity: it also affects how easy it is to produce that antibody, and what fraction of antibody molecules work properly.

Adams et al. now describe a new method, named “Tite-Seq”, that overcomes these issues. First, thousands of different antibodies are displayed on the surface of yeast cells, with each cell carrying a single kind of antibody. These cells are then incubated with fluorescently labeled antigen at a wide range of different concentrations. Next, the yeast cells are sorted based on how brightly they glow; brighter cells have more antigen bound to them, and so it is possible to calculate how much of the antigen is bound to each kind of antibody at each concentration. Plotting these data provides a “binding curve” for each antibody, which is then used to read off the antibody’s binding affinity in a way that is not affected by the factors that have plagued other high-throughput methods.

Tite-Seq is thus able to measure the binding affinities for thousands of different antibodies at the same time. This will potentially allow researchers to address many fundamental and yet unanswered questions about how the immune system works. Tite-Seq can also be used to measure how amino acid sequence affects the binding affinity of proteins other than antibodies.

DOI:http://dx.doi.org/10.7554/eLife.23156.002

Nanoparticles Self-Assembly Driven by High Affinity Repeat Protein Pairing

Proteins are the most specific yet versatile biological self-assembling agents with a rich chemistry. Nevertheless, the design of new proteins with recognition capacities is still in its infancy and has seldom been exploited for the self-assembly of functional inorganic nanoparticles. Here, we report on the protein-directed assembly of gold nanoparticles using purpose-designed artificial repeat proteins having a rigid but modular 3D architecture. αRep protein pairs are selected for their high mutual affinity from a library of 10(9) variants. Their conjugation onto gold nanoparticles drives the massive colloidal assembly of free-standing, one-particle thick films. When the average number of proteins per nanoparticle is lowered, the extent of self-assembly is limited to oligomeric particle clusters. Finally, we demonstrate that the aggregates are reversibly disassembled by an excess of one free protein. Our approach could be optimized for applications in biosensing, cell targeting, or functional nanomaterials engineering.

An ELISA Based Binding and Competition Method to Rapidly Determine Ligand-receptor Interactions

A comprehensive understanding of signaling pathways requires detailed knowledge regarding ligand-receptor interaction. This article describes two fast and reliable point-by-point protocols of enzyme-linked immunosorbent assays (ELISAs) for the investigation of ligand-receptor interactions: the direct ligand-receptor interaction assay (LRA) and the competition LRA. As a case study, the ELISA based analysis of the interaction between different lambda interferons (IFNLs) and the alpha subunit of their receptor (IL28RA) is presented: the direct LRA is used for the determination of dissociation constants (KD values) between receptor and IFN ligands, and the competition LRA for the determination of the inhibitory capacity of an oligopeptide, which was designed to compete with the IFNLs at their receptor binding site. Analytical steps to estimate KD and half maximal inhibitory concentration (IC50) values are described. Finally, the discussion highlights advantages and disadvantages of the presented method and how the results enable a better molecular understanding of ligand-receptor interactions.

Analysis of Molecular Parameters Determining the Antimalarial Activity of Polymer-Based Nanomimics

Malaria and other infectious diseases are major global public health problems, which need to be tackled using new technologies to cope with the lack of efficacious vaccines and emerging drug resistance. A recently developed anti-infectious concept based on nanomimics tested with Plasmodium falciparum is analyzed for the molecular parameters determining its applicability. Nanomimics-nanoscaled polymer-based mimics of host cell membranes-are designed with a reduced number of surface-exposed malaria parasite receptor molecules (heparin), resulting in less potent invasion inhibition as determined in antimalarial assays. In contrast, when shorter receptor molecules are used to form nanomimics, more molecules are needed to obtain nanomimic potency similar to nanomimics with longer receptor molecules. The interaction of heparin on nanomimics with the processed Plasmodium falciparum merozoite surface protein 1-42 (PfMSP1₄₂ ) have a high affinity, K_d = 12.1 ± 1.6 × 10^-9 m, as measured by fluorescence cross-correlation spectroscopy (FCCS). This detailed characterization of nanomimics and their molecular variants are an important step towards defining and optimizing possible nanomimic therapies for infectious diseases.

Characterization of the periplasmic redox network that sustains the versatile anaerobic metabolism of Shewanella oneidensis MR-1

The versatile anaerobic metabolism of the Gram-negative bacterium Shewanella oneidensis MR-1 (SOMR-1) relies on a multitude of redox proteins found in its periplasm. Most are multiheme cytochromes that carry electrons to terminal reductases of insoluble electron acceptors located at the cell surface, or bona fide terminal reductases of soluble electron acceptors. In this study, the interaction network of several multiheme cytochromes was explored by a combination of NMR spectroscopy, activity assays followed by UV-visible spectroscopy and comparison of surface electrostatic potentials. From these data the small tetraheme cytochrome (STC) emerges as the main periplasmic redox shuttle in SOMR-1. It accepts electrons from CymA and distributes them to a number of terminal oxidoreductases involved in the respiration of various compounds. STC is also involved in the electron transfer pathway to reduce nitrite by interaction with the octaheme tetrathionate reductase (OTR), but not with cytochrome c nitrite reductase (ccNiR). In the main pathway leading the metal respiration STC pairs with flavocytochrome c (FccA), the other major periplasmic cytochrome, which provides redundancy in this important pathway. The data reveals that the two proteins compete for the binding site at the surface of MtrA, the decaheme cytochrome inserted on the periplasmic side of the MtrCAB-OmcA outer-membrane complex. However, this is not observed for the MtrA homologues. Indeed, neither STC nor FccA interact with MtrD, the best replacement for MtrA, and only STC is able to interact with the decaheme cytochrome DmsE of the outer-membrane complex DmsEFABGH. Overall, these results shown that STC plays a central role in the anaerobic respiratory metabolism of SOMR-1. Nonetheless, the trans-periplasmic electron transfer chain is functionally resilient as a consequence of redundancies that arise from the presence of alternative pathways that bypass/compete with STC.