The intracellular environment affects protein-protein interactions

Simultaneous measurement of multiple fluorine labelling effect on GB1 stability by 19F NMR

The incorporation of fluorinated amino acids into proteins through natural biosynthesis in E. coli often leads to the production of heterogeneous fluorinated proteins. The stabilities of proteins with different 19F labelling states can vary, but these differences are challenging to measure due to the difficulty in separating the fluorinated protein mixtures that differ by only a few 19F atoms. Here, we simultaneously incorporated both fluoro-phenylalanines (3-fluoro-phenylalanine, 3FF; or 4-fluoro-phenylalanine, 4FF) and 5-fluoro-tryptophan (5FW) into GB1 protein. We are able to measure the stability of GB1 protein with different 19F labelling states without the need for sample separation by taking the advantage of 19F NMR. The results showed that 4FF-5FW-GB1 with varying 19F labelling states exhibited significantly different protein stability, with higher 4FF labeling efficiency correlating with decreased stability. Furthermore, residues F30 and F52 show synergistic effects on GB1 stability. In contrast, the 3FF and 5FW substitution exhibits a slightly stabilizing effect on GB1 stability. The present research provides a convenient 19F NMR method to simultaneously measure fluorine labelling effects on protein stability, favouring precise understanding and analysis of fluorine labelling effects.

The proximity proteome of pre-40S pre-ribosomal particle components PNO1 and NOB1 using turboID proximity labeling technology

BACKGROUND

The ribosome assembly factors PNO1 and NOB1 play crucial roles in the maturation of the 40S ribosomal small subunit. TurboID is an efficient biotin ligase that can biotinylate proteins in proximity to the target protein and is widely used to study complex biological processes within cells. In this study, we employed this technology to investigate the complex proximity network of PNO1 and NOB1 within the cell, further revealing their key roles in ribosome biogenesis.

RESULTS

Firstly, through immunofluorescence experiments, we observed that PNO1 and NOB1 have different localizations within the cell. Subsequently, by analyzing the proximal proteins labeled by PNO1-TurboID and NOB1-TurboID, we identified 871 proximal proteins for PNO1 and 1044 for NOB1, with 663 overlapping proteins. Functional analysis revealed that these proximal proteins are predominantly enriched in biological processes related to ribosome assembly, rRNA processing, and translation, all of which are closely linked to ribosome biogenesis. Notably, we validated the mass spectrometry-identified proteins through co-IP experiments and found that PNO1 and NOB1 interact with the translation-related proteins EIF4B and EIF4G2.

CONCLUSION

Our study constructed the protein network environment of ribosome assembly factors PNO1 and NOB1 within the cell and found that their neighboring proteins are primarily involved in key biological processes such as ribosome processing, mRNA translation, and the cell cycle, all of which are critical for ribosome biogenesis. These findings provide a valuable foundation for further understanding the roles of PNO1 and NOB1 in ribosome biogenesis and how they regulate this process.

Direct Quantification of Protein-Protein Interactions in Living Bacterial Cells

Quantitative measurement of protein-protein interactions (PPIs) within living cells is vital for understanding their cellular functions at the molecular level and for applications in synthetic biology, protein engineering, and drug discovery. Although several techniques have been developed to measure PPI strength in vitro, direct measurement of PPI strength within living bacterial cells remains challenging. Here, a method for quantitatively measuring PPIs by determining the dissociation constant (Kd) in living E. coli using fluorescence resonance energy transfer (FRET), a technique termed KD-FRET, is reported. It is found that the direct excitation of the acceptor fluorophore among spectral crosstalks primarily results in non-interacting pairs exhibiting an apparent Kd, leading to false-positive signals. KD-FRET proves highly effective in quantifying various PPI Kd values, including both heterologous and homologous pairs. Moreover, KD-FRET enables the quantification of Kd for interaction pairs that are unmeasurable in vitro owing to their instability under standard buffer conditions. KD-FRET is successfully applied in the development of a novel synthetic biology tool to enhance naringenin production in E. coli and lycopene production in S. cerevisiae by precisely engineering metabolic pathway. These results demonstrate the potential of KD-FRET as a powerful tool for studying PPIs in their native cellular environments.

Crowding-induced stabilization and destabilization in a single protein

The protein concentration in cells can reach 300 g/L. These crowded conditions affect protein stability. Classic crowding theories predict entropically driven stabilization, which occurs via steric repulsion, but growing evidence shows a role for non-covalent chemical interactions. To aid our understanding of physiologically relevant crowding, we used NMR-detected 1H-2H exchange to examine a simple, semi-reductionist system: protein self-crowding at the residue level using the widely studied model globular protein, GB1 (the B1 domain streptococcal protein G) at concentrations up to its solubility limit, 100 g/L. The surprising result is that self-crowding stabilizes some residues but destabilizes others, contradicting predictions. Two other observations are also contradictory. First, temperature-dependence data show that stabilization can arise enthalpically, not just entropically. Second, concentration-dependence data show destabilization often increases with increasing concentration. These results show a key role for chemical interactions. More specifically, self-crowding increases the free energy required to expose those residues that are only exposed upon complete unfolding, and stabilization of these globally unfolding residues increases with GB1 concentration, a result we attribute to repulsive chemical interactions between GB1 molecules. On the other hand, residues exposed upon local unfolding tend to be destabilized, with destabilization increasing with concentration, a result we attribute to attractive chemical interactions between GB1 molecules.

Structural Descriptors for Subunit Interface Regions in Homodimers: Effect of Lipid Membrane and Secondary Structure Type

A total of 1311 homodimers were collected and analyzed in three different categories to highlight the impact of lipid environment and secondary structure type: 422 cytoplasmic α-helix, 411 cytoplasmic β-strand, and 478 membrane complexes. Structural features of the interface connecting two monomers were investigated and compared to those of the non-interface surface. Every residue on the surface of each monomer was explored based on four attributes: solvent-accessible surface area (SASA), protrusion index (Cx), surface planarity, and surface roughness. SASA and Cx distribution profiles clearly distinguished the interface from the surface in all categories, where the rim of the interface displayed higher SASA and Cx values than the rest of the surface. Surface residues in membrane complexes protruded less than cytoplasmic ones due to the hydrophobic environment, and consequently, the difference between surface and interface residues became less noticeable in that category. Cytoplasmic β-strand complexes displayed markedly lower SASA at the interface core than at the surface. The major distinction between the surface and interface was achieved through surface roughness, which displayed significantly higher values for the interface than the surface, especially in cytoplasmic complexes. Clearly, a surface which is relatively rugged favors the association of two monomers through multiple van der Waals interactions and hydrogen-bond formations. Another structural descriptor with strong distinguishing ability was surface planarity, which was higher at the interface than at the non-interface surface. Surface flatness would eventually facilitate the interconnectedness of an interface with a network of residue pairs bridging two complementary surfaces. Analysis of contact pairs revealed that hydrophobic pairs have the highest frequency of occurrence in the lipid environment of membrane complexes. However, despite the scarcity of polar residues at the interface, the likelihood of observing a contact between polar residues was markedly higher than that of hydrophobic ones.

Characterizing host-microbe interactions with bacterial effector proteins using proximity-dependent biotin identification (BioID)

Bacterial pathogens have evolved diverse strategies to manipulate host cells to establish infection. At a molecular level, this is often mediated by virulence factors that are secreted into host cells (herein referred to as effectors), which target host cellular pathways by initiating host-pathogen protein-protein interactions that alter cellular function in the host. By establishing this network of host-pathogen protein-protein interactions, pathogenic bacteria modulate and hijack host cell processes for the benefit of the pathogen, ultimately promoting survival, replication, and cell-to-cell spread within the host. Effector proteins also mediate diverse host-microbe interactions in nature, contributing to symbiotic relationships spanning from mutualism to commensalism to parasitism. While effector proteins play crucial roles in nature, molecular properties such as the transient nature of the underlying protein-protein interactions and their affinity for targeting host biological membranes often presents challenges to elucidating host targets and mechanism of action. Proximity-dependent biotin identification (termed BioID) has proven to be a valuable tool in the field of cell biology to identify candidate protein-protein interactions in eukaryotic cells, yet has remained relatively underexploited by bacterial pathogenesis researchers. Here, we discuss bacterial effector function at a molecular level, and challenges presented by traditional approaches to host target identification. We highlight the BioID approach and its potential strengths in the context of identifying host-pathogen protein-protein interactions, and explore BioID's implementation to study host-microbe interactions mediated by bacteria. Collectively, BioID represents a powerful tool for the study of bacterial effector proteins, providing new insight into our understanding of pathogenesis and other symbiotic relationships, and opportunities to identify new factors that contribute to host response to infection.

Crowding beyond excluded volume: A tale of two dimers

Protein-protein interactions are modulated by their environment. High macromolecular solute concentrations crowd proteins and shift equilibria between protein monomers and their assemblies. We aim to understand the mechanism of crowding by elucidating the molecular-level interactions that determine dimer stability. Using 19F-NMR spectroscopy, we studied the effects of various polyethylene glycols (PEGs) on the equilibrium thermodynamics of two protein complexes: a side-by-side and a domain-swap dimer. Analysis using our mean-field crowding model shows that, contrary to classic crowding theories, PEGs destabilize both dimers through enthalpic interactions between PEG and the monomers. The enthalpic destabilization becomes more dominant with increasing PEG concentration because the reduction in PEG mesh size with concentration diminishes the stabilizing effect of excluded volume interactions. Additionally, the partially folded domain-swap monomers fold in the presence of PEG, contributing to dimer stabilization at low PEG concentrations. Our results reveal that polymers crowd protein complexes through multiple conjoined mechanisms, impacting both their stability and oligomeric state.

Quantifying protein-drug lifetimes in human cells by 19F NMR spectroscopy

The cellular environment is a complex and crowded space, with organelles, compartments and multitudes of molecules engaged in intricate networks of communication that modulate binary protein-ligand/protein interactions. As a result, it is becoming increasingly appreciated that evaluations of protein-drug binding should be carried out in the native cellular environment. Here, we present a proof-of-concept study where we measured the lifetime (1/koff) of a protein-drug complex in human cells by 19F NMR spectroscopy using fluorinated Cyclophilin A (CypA) bound to Cyclosporine A (CsA). Harnessing the exceptional detection sensitivity of the trifluoromethyl group attached at the para position of Phe60 in CypA, high-quality 2D 19F-19F exchange spectra were obtained in cells. Essentially identical koff values were observed in cells and in vitro, suggesting that the overall impact of the cellular environment on the lifetime of tfmF60 CypA/CsA complex is minimal. Using similar approaches for quantifying protein-drug lifetimes in the native cellular environment paves the way for efficiently screening drug libraries in human cells by 19F NMR spectroscopy.

Leveraging Artificial Intelligence and Machine Learning for Characterizing Protein Corona, Nanobiological Interactions, and Advancing Drug Discovery

Proteins are essential for all living organisms, playing key roles in biochemical reactions, structural support, signal transduction, and gene regulation. Their importance in biomedical research is highlighted by their role as drug targets in various diseases. The interactions between proteins and nanoparticles (NPs), including the protein corona's formation, significantly affect NP behavior, biodistribution, cellular uptake, and toxicity. Comprehending these interactions is pivotal for advancing the design of NPs to augment their efficacy and safety in biomedical applications. While traditional nanomedicine design relies heavily on experimental work, the use of data science and machine learning (ML) is on the rise to predict the synthesis and behavior of nanomaterials (NMs). Nanoinformatics combines computational simulations with laboratory studies, assessing risks and revealing complex nanobio interactions. Recent advancements in artificial intelligence (AI) and ML are enhancing the characterization of the protein corona and improving drug discovery. This review discusses the advantages and limitations of these approaches and stresses the importance of comprehensive datasets for better model accuracy. Future developments may include advanced deep-learning models and multimodal data integration to enhance protein function prediction. Overall, systematic research and advanced computational tools are vital for improving therapeutic outcomes and ensuring the safe use of NMs in medicine.

Real-Time Dynamic Tracking of Multiple Base Excision Repair Enzymes in Living Cells

Simultaneous in situ monitoring of base excision repair (BER) correlated enzymes like apurinic/apyrimidinic endonuclease 1 (APE1) and flap endonuclease 1 (FEN1) in living cells offers valuable insights into their roles in disease development and cytotoxicity caused by pollutants, but comprehensive analysis is currently hindered by diverse enzyme functions and limited methods. In this study, we developed a dual-activatable DNA fluorescent probe (AP-FLAP) to simultaneously visualize APE1 and FEN1 activities, revealing the BER-related DNA damage caused by various environmental pollutants within living cells. The AP-FLAP probe was designed by ingeniously integrating a dumbbell structure containing a 5' flap and a hairpin structure containing AP sites into a single oligonucleotide probe. APE1 specifically hydrolyzed the AP sites, releasing a 5-carboxy-X-rhodamine (ROX) signal, while FEN1 recognized and cleaved the 5' flap, releasing a 6-carboxyfluorescein (FAM) signal. The probe allowed for independent determination of APE1 and FEN1 activities with good specificity and sensitivity. Subsequently, we applied the AP-FLAP probe to investigate base damage induced by 1-methylphenanthrene (1-MP) and 6-chlorobenzo[a]pyrene (6-Cl-BaP) in human umbilical vein endothelial cells (HUVECs). Significant base damage by 1-MP and 6-Cl-BaP exposure was revealed, with a positive correlation of damage degree with different exposure concentrations from 0.1 to 100 μM. Notably, 6-Cl-BaP caused significant damage even at 0.1 μM, in a concentration-dependent manner. Our work provides a powerful tool for elucidating BER molecular mechanisms and DNA damage repair under environmental exposure and opens new avenues for developing multifunctional nucleic acid probes for a wide range of applications in chemical biology and biomedical research.

Engineering microbial cell factories by multiplexed spatiotemporal control of cellular metabolism: Advances, challenges, and future perspectives

Generally, the metabolism in microbial organism is an intricate, spatiotemporal process that emerges from gene regulatory networks, which affects the efficiency of product biosynthesis. With the coming age of synthetic biology, spatiotemporal control systems have been explored as versatile strategies to promote product biosynthesis at both spatial and temporal levels. Meanwhile, the designer synthetic compartments provide new and promising approaches to engineerable spatiotemporal control systems to construct high-performance microbial cell factories. In this article, we comprehensively summarize recent developments in spatiotemporal control systems for tailoring advanced cell factories, and illustrate how to apply spatiotemporal control systems in different microbial species with desired applications. Future challenges of spatiotemporal control systems and perspectives are also discussed.

Identifying the minimal sets of distance restraints for FRET-assisted protein structural modeling

Proteins naturally occur in crowded cellular environments and interact with other proteins, nucleic acids, and organelles. Since most previous experimental protein structure determination techniques require that proteins occur in idealized, non-physiological environments, the effects of realistic cellular environments on protein structure are largely unexplored. Recently, Förster resonance energy transfer (FRET) has been shown to be an effective experimental method for investigating protein structure in vivo. Inter-residue distances measured in vivo can be incorporated as restraints in molecular dynamics (MD) simulations to model protein structural dynamics in vivo. Since most FRET studies only obtain inter-residue separations for a small number of amino acid pairs, it is important to determine the minimum number of restraints in the MD simulations that are required to achieve a given root-mean-square deviation (RMSD) from the experimental structural ensemble. Further, what is the optimal method for selecting these inter-residue restraints? Here, we implement several methods for selecting the most important FRET pairs and determine the number of pairsN r $$ {N}_r $$ that are needed to induce conformational changes in proteins between two experimentally determined structures. We find that enforcing only a small fraction of restraints,N r / N ≲ 0.08 $$ {N}_r/N\lesssim 0.08 $$ , whereN $$ N $$ is the number of amino acids, can induce the conformational changes. These results establish the efficacy of FRET-assisted MD simulations for atomic scale structural modeling of proteins in vivo.

Insights into the Structure and Dynamics of Proteins from 19F Solution NMR Spectroscopy

19F NMR spectroscopy has recently witnessed a resurgence as an attractive analytical tool for the study of the structure and dynamics of biomolecules in vitro and in cells, despite reports of its applications in biomolecular NMR since the 1970s. The high gyromagnetic ratio, large chemical shift dispersion, and complete absence of the spin 1/2 19F nucleus from biomolecules results in background-free, high-resolution 19F NMR spectra. The introduction of 19F probes in a few selected locations in biomolecules reduces spectral crowding despite its increased line width in comparison to typical 1H NMR line widths and allows rapid site-specific measurements from simple 1D spectra alone. The design and synthesis of novel 19F probes with reduced line widths and increased chemical shift sensitivity to the surrounding environment, together with advances in labeling techniques, NMR methodology, and hardware, have overcome several drawbacks of 19F NMR spectroscopy. The increased interest and widespread use of 19F NMR spectroscopy of biomolecules is gradually establishing it as a sensitive and high-resolution probe of biomolecular structure and dynamics, supplementing traditional 13C/15N-based methods. This Review focuses on the advances in 19F solution NMR spectroscopy of proteins in the past 5 years, with an emphasis on novel 19F tags and labeling techniques, NMR experiments to probe protein structure and conformational dynamics in vitro, and in-cell NMR applications.

Quantification of CH and NH/π-Stacking Interactions in Cells Using Nuclear Magnetic Resonance Spectroscopy

π-Stacking, a type of noncovalent interactions involving aromatic residues, plays an important role in protein folding and function. In this work, an attempt has been made to measure CH/π and NH/π stacking interactions in a protein in Escherichia coli cells using a combined double-mutant cycle and nuclear magnetic resonance spectroscopy method. The results show that the CH/π and NH/π stacking interactions are generally weaker in cells than those in the buffer. The transient intermolecular noncovalent interactions between the protein and the complex cellular environment may compete with and thus weaken the stacking interactions in the protein. The weakening of stacking interactions can enhance the local conformational opening of proteins in E. coli cells. This is evident from the faster rates of amide hydrogen/deuterium exchange observed in cells than in the buffer, for residues that undergo local conformational opening. This study highlights the influence of the cellular environment on π-stacking and the conformational dynamics of proteins.

Protein Classes Predicted by Molecular Surface Chemical Features: Machine Learning-Assisted Classification of Cytosol and Secreted Proteins

Chemical structures of protein surfaces govern intermolecular interaction, and protein functions include specific molecular recognition, transport, self-assembly, etc. Therefore, the relationship between the chemical structure and protein functions provides insights into the understanding of the mechanism underlying protein functions and developments of new biomaterials. In this study, we analyze protein surface features, including surface amino acid populations and secondary structure ratios, instead of entire sequences as input for the classifier, intending to provide deeper insights into the determination of protein classes (cytosol or secreted). We employed a random forest-based classifier for the prediction of protein locations. Our training and testing data sets consisting of secreted and cytosol proteins were constructed using filtered information from UniProt and 3D structures from AlphaFold. The classifier achieved a testing accuracy of 93.9% with a feature importance ranking and quantitative boundary values for the top three features. We discuss the significance of these features quantitatively and the hidden rules to determine the protein classes (cytosol or secreted).

Identifying the minimal sets of distance restraints for FRET-assisted protein structural modeling

Proteins naturally occur in crowded cellular environments and interact with other proteins, nucleic acids, and organelles. Since most previous experimental protein structure determination techniques require that proteins occur in idealized, non-physiological environments, the effects of realistic cellular environments on protein structure are largely unexplored. Recently, Förster resonance energy transfer (FRET) has been shown to be an effective experimental method for investigating protein structure in vivo. Inter-residue distances measured in vivo can be incorporated as restraints in molecular dynamics (MD) simulations to model protein structural dynamics in vivo. Since most FRET studies only obtain inter-residue separations for a small number of amino acid pairs, it is important to determine the minimum number of restraints in the MD simulations that are required to achieve a given root-mean-square deviation (RMSD) from the experimental structural ensemble. Further, what is the optimal method for selecting these inter-residue restraints? Here, we implement several methods for selecting the most important FRET pairs and determine the number of pairsN r that are needed to induce conformational changes in proteins between two experimentally determined structures. We find that enforcing only a small fraction of restraints,N r / N ≲ 0.08 , where N is the number of amino acids, can induce the conformational changes. These results establish the efficacy of FRET-assisted MD simulations for atomic scale structural modeling of proteins in vivo.

Effect of molecular crowders on ligand binding kinetics with G-quadruplex DNA probed by fluorescence correlation spectroscopy

Guanine-rich single-stranded DNA folds into G-quadruplex DNA (GqDNA) structures, which play crucial roles in various biological processes. These structures are also promising targets for ligands, potentially inducing antitumor effects. While thermodynamic parameters of ligand/DNA interactions are well-studied, the kinetics of ligand interaction with GqDNA, particularly in cell-like crowded environments, remain less explored. In this study, we investigate the impact of molecular crowding agents (glucose, sucrose, and ficoll 70) at physiologically relevant concentrations (20% w/v) on the association and dissociation rates of the benzophenoxazine-core based ligand, cresyl violet (CV), with human telomeric antiparallel-GqDNA. We utilized fluorescence correlation spectroscopy (FCS) along with other techniques. Our findings reveal that crowding agents decrease the binding affinity of CV to GqDNA, with the most significant effect-a nearly three-fold decrease-observed with ficoll 70. FCS measurements indicate that this decrease is primarily due to a viscosity-induced slowdown of ligand association in the crowded environment. Interestingly, dissociation rates remain largely unaffected by smaller crowders, with only small effect observed in presence of ficoll 70 due to direct but weak interaction between the ligand and ficoll. These results along with previously reported data provide valuable insights into ligand/GqDNA interactions in cellular contexts, suggesting a conserved mechanism of saccharide crowder influence, regardless of variations in GqDNA structure and ligand binding mode. This underscores the importance of considering crowding effects in the design and development of GqDNA-targeted drugs for potential cancer treatment.

Polyethylene Glycol Impacts Conformation and Dynamics of Escherichia coli Prolyl-tRNA Synthetase Via Crowding and Confinement Effects

Polyethylene glycol (PEG) is a flexible, nontoxic polymer commonly used in biological and medical research, and it is generally regarded as biologically inert. PEG molecules of variable sizes are also used as crowding agents to mimic intracellular environments. A recent study with PEG crowders revealed decreased catalytic activity of Escherichia coli prolyl-tRNA synthetase (Ec ProRS), where the smaller molecular weight PEGs had the maximum impact. The molecular mechanism of the crowding effects of PEGs is not clearly understood. PEG may impact protein conformation and dynamics, thus its function. In the present study, the effects of PEG molecules of various molecular weights and concentrations on the conformation and dynamics of Ec ProRS were investigated using a combined experimental and computational approach including intrinsic tryptophan fluorescence spectroscopy, atomic force microscopy, and atomistic molecular dynamic simulations. Results of the present study suggest that lower molecular weight PEGs in the dilute regime have modest effects on the conformational dynamics of Ec ProRS but impact the catalytic function primarily via the excluded volume effect; they form large clusters blocking the active site pocket. In contrast, the larger molecular weight PEGs in dilute to semidilute regimes have a significant impact on the protein's conformational dynamics; they wrap on the protein surface through noncovalent interactions. Thus, lower-molecular-weight PEG molecules impact protein dynamics and function via crowding effects, whereas larger PEGs induce confinement effects. These results have implications for the development of inhibitors for protein targets in a crowded cellular environment.

Chemotactic Interactions Drive Migration of Membraneless Active Droplets

In nature, chemotactic interactions are ubiquitous and play a critical role in driving the collective behavior of living organisms. Reproducing these interactions in vitro is still a paramount challenge due to the complexity of mimicking and controlling cellular features, such as tangled metabolic networks, cytosolic macromolecular crowding, and cellular migration, on a microorganism size scale. Here, we generate enzymatically active cell-sized droplets able to move freely, and by following a chemical gradient, able to interact with the surrounding droplets in a collective manner. The enzyme within the droplets generates a pH gradient that extends outside the edge of the droplets. We discovered that the external pH gradient triggers droplet migration and controls its directionality, which is selectively toward the neighboring droplets. Hence, by changing the enzyme activity inside the droplet, we tuned the droplet migration speed. Furthermore, we showed that these cellular-like features can facilitate the reconstitution of a simple and linear protometabolic pathway and increase the final reaction product generation. Our work suggests that simple and stable membraneless droplets can reproduce complex biological phenomena, opening new perspectives as bioinspired materials and synthetic biology tools.

Encoding the space of protein-protein binding interfaces by artificial intelligence

The physical interactions between proteins are largely determined by the structural properties at their binding interfaces. It was found that the binding interfaces in distinctive protein complexes are highly similar. The structural properties underlying different binding interfaces could be further captured by artificial intelligence. In order to test this hypothesis, we broke protein-protein binding interfaces into pairs of interacting fragments. We employed a generative model to encode these interface fragment pairs in a low-dimensional latent space. After training, new conformations of interface fragment pairs were generated. We found that, by only using a small number of interface fragment pairs that were generated by artificial intelligence, we were able to guide the assembly of protein complexes into their native conformations. These results demonstrate that the conformational space of fragment pairs at protein-protein binding interfaces is highly degenerate. Features in this degenerate space can be well characterized by artificial intelligence. In summary, our machine learning method will be potentially useful to search for and predict the conformations of unknown protein-protein interactions.

Protein Allostery Study in Cells Using NMR Spectroscopy

Protein allostery is commonly observed in vitro. But how protein allostery behaves in cells is unknown. In this work, a protein monomer-dimer equilibrium system was built with the allosteric effect on the binding characterized using NMR spectroscopy through mutations away from the dimer interface. A chemical shift linear fitting method was developed that enabled us to accurately determine the dissociation constant. A total of 28 allosteric mutations were prepared and grouped to negative allosteric, nonallosteric, and positive allosteric modulators. ∼ 50% of mutations displayed the allosteric-state changes when moving from a buffered solution into cells. For example, there were no positive allosteric modulators in the buffered solution but eight in cells. The change in protein allostery is correlated with the interactions between the protein and the cellular environment. These interactions presumably drive the surrounding macromolecules in cells to transiently bind to the monomer and dimer mutational sites and change the free energies of the two species differently which generate new allosteric effects. These surrounding macromolecules create a new protein allostery pathway that is only present in cells.

In-Cell 19F NMR of Proteins: Recent Progress and Future Opportunities

In vitro, 19F NMR methodology is preferably selected as a complementary and straightforward method for unveiling the conformations, dynamics, and interactions of biological molecules. Its effectiveness in vivo has seen continuous improvement, addressing challenges faced by conventional heteronuclear NMR experiments on structured proteins, such as severe line broadening, low signal-to-noise ratio, and background signals. Herein, we summarize the distinctive advantages of 19F NMR, along with recent progress in sample preparation and applications within the realm of in-cell NMR. Additionally, we offer insights into the future directions and prospects of this methodology based on our understanding.

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments

Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.

Studying protein stability in crowded environments by NMR

Most proteins perform their functions in crowded and complex cellular environments where weak interactions are ubiquitous between biomolecules. These complex environments can modulate the protein folding energy landscape and hence affect protein stability. NMR is a nondestructive and effective method to quantify the kinetics and equilibrium thermodynamic stability of proteins at an atomic level within crowded environments and living cells. Here, we review NMR methods that can be used to measure protein stability, as well as findings of studies on protein stability in crowded environments mimicked by polymer and protein crowders and in living cells. The important effects of chemical interactions on protein stability are highlighted and compared to spatial excluded volume effects.

Background signal suppression by opposite polarity subtraction for targeted DNP NMR spectroscopy on mixture samples

A novel method for background signal suppression is introduced to improve the selectivity of dynamic nuclear polarization (DNP) NMR spectroscopy in the study of target molecules within complex mixtures. The method uses subtraction between positively and negatively enhanced DNP spectra, leading to an improved contrast factor, which is the ratio between the target and background signal intensities. The proposed approach was experimentally validated using a reverse-micelle system that confines the target molecules together with the polarizing agent, OX063 trityl. A substantial increase in the contrast factor was observed, and the contrast factor was optimized through careful selection of the DNP build-up time. A simulation study based on the experimental results provides insights into a strategy for choosing the appropriate DNP build-up time and the corresponding selectivity of the method. Further analysis revealed a broad applicability of the technique, encompassing studies from large biomolecules to surface-modified polymers, depending on the nuclear spin diffusion rate with a range of gyromagnetic ratios.

Progress, Challenges and Opportunities of NMR and XL-MS for Cellular Structural Biology

The validity of protein structures and interactions, whether determined under ideal laboratory conditions or predicted by AI tools such as Alphafold2, to precisely reflect those found in living cells remains to be examined. Moreover, understanding the changes in protein structures and interactions in response to stimuli within living cells, under both normal and disease conditions, is key to grasping proteins' functionality and cellular processes. Nevertheless, achieving high-resolution identification of these protein structures and interactions within living cells presents a technical challenge. In this Perspective, we summarize the recent advancements in in-cell nuclear magnetic resonance (NMR) and in vivo cross-linking mass spectrometry (XL-MS) for studying protein structures and interactions within a cellular context. Additionally, we discuss the challenges, opportunities, and potential benefits of integrating in-cell NMR and in vivo XL-MS in future research to offer an exhaustive approach to studying proteins in their natural habitat.

In-Cell Association of a Bioorthogonal Tubulin

Studies of proteins from one organism in another organism's cells have shown that such exogenous proteins stick more, pointing toward coevolution of the cytoplasm and protein surface to minimize stickiness. Here we flip this question around by asking whether exogenous proteins can assemble efficiently into their target complexes in a non-native cytoplasm. We use as our model system the assembly of BtubA and BtubB from Prosthecobacter hosted in human U-2 OS cells. BtubA and B evolved from eukaryotic tubulins after horizontal gene transfer, but they have low surface sequence identity with the homologous human tubulins and do not respond to tubulin drugs such as nocodazole. In U-2 OS cells, BtubA and B assemble efficiently into dimers compared to in vitro, and the wild-type BtubA and B proteins subsequently are able to form microtubules as well. We find that generic crowding effects (Ficoll 70 in vitro) contribute significantly to efficient dimer assembly when compared to sticking interactions (U-2 OS cell lysate in vitro), consistent with the notion that a generic mechanism such as crowding can be effective at driving assembly of exogenous proteins, even when protein-cytoplasm quinary structure and sticking have been modified in a non-native cytoplasm. A simple Monte Carlo model of in vitro and in-cell interactions, treating BtubA and B as sticky dipoles in a matrix of sticky or nonsticky crowders, rationalizes all the experimental trends with two adjustable parameters and reveals nucleation as the likely mechanism for the time-scale separation between dimer- and tubule formation in-cell and in vitro.

Onco-Breastomics: An Eco-Evo-Devo Holistic Approach

Known as a diverse collection of neoplastic diseases, breast cancer (BC) can be hyperbolically characterized as a dynamic pseudo-organ, a living organism able to build a complex, open, hierarchically organized, self-sustainable, and self-renewable tumor system, a population, a species, a local community, a biocenosis, or an evolving dynamical ecosystem (i.e., immune or metabolic ecosystem) that emphasizes both developmental continuity and spatio-temporal change. Moreover, a cancer cell community, also known as an oncobiota, has been described as non-sexually reproducing species, as well as a migratory or invasive species that expresses intelligent behavior, or an endangered or parasite species that fights to survive, to optimize its features inside the host's ecosystem, or that is able to exploit or to disrupt its host circadian cycle for improving the own proliferation and spreading. BC tumorigenesis has also been compared with the early embryo and placenta development that may suggest new strategies for research and therapy. Furthermore, BC has also been characterized as an environmental disease or as an ecological disorder. Many mechanisms of cancer progression have been explained by principles of ecology, developmental biology, and evolutionary paradigms. Many authors have discussed ecological, developmental, and evolutionary strategies for more successful anti-cancer therapies, or for understanding the ecological, developmental, and evolutionary bases of BC exploitable vulnerabilities. Herein, we used the integrated framework of three well known ecological theories: the Bronfenbrenner's theory of human development, the Vannote's River Continuum Concept (RCC), and the Ecological Evolutionary Developmental Biology (Eco-Evo-Devo) theory, to explain and understand several eco-evo-devo-based principles that govern BC progression. Multi-omics fields, taken together as onco-breastomics, offer better opportunities to integrate, analyze, and interpret large amounts of complex heterogeneous data, such as various and big-omics data obtained by multiple investigative modalities, for understanding the eco-evo-devo-based principles that drive BC progression and treatment. These integrative eco-evo-devo theories can help clinicians better diagnose and treat BC, for example, by using non-invasive biomarkers in liquid-biopsies that have emerged from integrated omics-based data that accurately reflect the biomolecular landscape of the primary tumor in order to avoid mutilating preventive surgery, like bilateral mastectomy. From the perspective of preventive, personalized, and participatory medicine, these hypotheses may help patients to think about this disease as a process governed by natural rules, to understand the possible causes of the disease, and to gain control on their own health.

Searching for EGF Fragments Recreating the Outer Sphere of the Growth Factor Involved in Receptor Interactions

The aims of this study were to determine whether it is possible to use peptide microarrays obtained using the SPOT technique (immobilized on cellulose) and specific polyclonal antibodies to select fragments that reconstruct the outer sphere of proteins and to ascertain whether the selected peptide fragments can be useful in the study of their protein-protein and/or peptide-protein interactions. Using this approach, epidermal growth factor (EGF) fragments responsible for the interaction with the EGF receptor were searched. A library of EGF fragments immobilized on cellulose was obtained using triazine condensing reagents. Experiments on the interactions with EGFR confirmed the high affinity of the selected peptide fragments. Biological tests on cells showed the lack of cytotoxicity of the EGF fragments. Selected EGF fragments can be used in various areas of medicine.

Bridging Soft Interaction and Excluded Volume in Crowded Milieu through Subtle Protein Dynamics

The impact of macromolecular crowding on biological macromolecules has been elucidated through the excluded volume phenomenon and soft interactions. However, it has often been difficult to provide a clear demarcation between the two regions. Here, using temperature-dependent dynamics (local and global) of the multidomain protein human serum albumin (HSA) in the presence of commonly used synthetic crowders (Dextran 40, PEG 8, Ficoll 70, and Dextran 70), we have shown the presence of a transition that serves as a bridge between the soft and hard regimes. The bridging region is independent of the crowder identity and displays no apparent correlation with the critical overlap concentration of the polymeric crowding agents. Moreover, the dynamics of domains I and II and the protein gating motion respond differently, thereby bringing to the fore the asymmetry underlying the crowder influence on HSA. In addition, solvent-coupled and decoupled protein motions indicate the heterogeneity of the dynamic landscape in the crowded milieu. We also propose an intriguing correlation between protein stability and dynamics, with increased global stability being accompanied by eased local domain motion.

Enlarging the scenario of site directed 19F labeling for NMR spectroscopy of biomolecules

The possibility of using selectively incorporated 19F nuclei for NMR spectroscopic studies has retrieved increasing interest in recent years. The high gyromagnetic ratio of 19F and its absence in native biomolecular systems make this nucleus an interesting alternative to standard 1H NMR spectroscopy. Here we show how we can attach a label, carrying a 19F atom, to protein tyrosines, through the use of a specific three component Mannich-type reaction. To validate the efficacy and the specificity of the approach, we tested it on two selected systems with the aid of ESI MS measurements.

In-Cell Dynamics: The Next Focus of All-Atom Simulations

The cell is a crowded space where large biomolecules and metabolites are in continuous motion. Great strides have been made in in vitro studies of protein dynamics, folding, and protein-protein interactions, and much new data are emerging of how they differ in the cell. In this Perspective, we highlight the current progress in atomistic modeling of in-cell environments, both bacteria and mammals, with emphasis on classical all-atom molecular dynamics simulations. These simulations have been recently used to capture and characterize functional and non-functional protein-protein interactions, protein folding dynamics of small proteins with varied topologies, and dynamics of metabolites. We further discuss the challenges and efforts for updating modern force fields critical to the progress of cellular environment simulations. We also briefly summarize developments in relevant state-of-the-art experimental techniques. As computational and experimental methodologies continue to progress and produce more directly comparable data, we are poised to capture the complex atomistic picture of the cell.

Effect of the Macromolecular Crowding Agents on the Structure and Function of Human Arginase-I, a Therapeutically Important Enzyme

Macromolecular crowding has been known to influence the structure and function of many enzymes through excluded volume effects and/or soft interactions. Here, we employed two synthetic macromolecular crowders, Dextrans and poly(ethylene glycol)s (PEGs) with varying molecular masses, to examine how they affected the structure and function of a therapeutically important enzyme, human arginase-I that catalyzes the conversion of l-arginine to l-ornithine and urea. Except at greater concentrations of Dextran 200, Dextrans were observed to slightly reduce the enzymatic activity, indicating that they exert their influence mainly through the excluded volume effects. Similar outcomes were seen with PEGs, with the exception of PEG 1000, where the activity decreased with increasing PEG concentrations, showing the maximum effect at a 20 g/L concentration. This finding suggests that the enzyme function is reduced by the soft interactions of this macromolecule with the enzyme, supported by the binding measurement. Secondary and local tertiary structures and thermodynamic stability were also affected, suggesting that PEG 1000 has an impact on the protein's structure. Furthermore, molecular dynamics simulation studies suggest that the catalytic pocket is disturbed, presumably by the unwinding of neighboring helix 9. As a result, the positioning of nearby Glu277 is altered, which prevents His141 and Glu277 from making contact. This hampers the proton transfer from the catalytic His141 to the intermediate species to form ornithine, a crucial step for the substrate hydrolysis reaction by this arginase. Overall, the knowledge gained from this study might be helpful for understanding how different enzymes work in a crowded/cellular environment.

Virus-like particles nanoreactors: from catalysis towards bio-applications

Virus-like particles (VLPs) are self-assembled supramolecular structures found in nature, often used for compartmentalization. Exploiting their inherent properties, including precise nanoscale structures, monodispersity, and high stability, these architectures have been widely used as nanocarriers to protect or enrich catalysts, facilitating catalytic reactions and avoiding interference from the bulk solutions. In this review, we summarize the current progress of virus-like particles (VLPs)-based nanoreactors. First, we briefly introduce the physicochemical properties of the most commonly used virus particles to understand their roles in catalytic reactions beyond the confined space. Next, we summarize the self-assembly of nanoreactors forming higher-order hierarchical structures, highlighting the emerging field of nanoreactors as artificial organelles and their potential biomedical applications. Finally, we discuss the current findings and future perspectives of VLPs-based nanoreactors.

Thermodynamic forces from protein and water govern condensate formation of an intrinsically disordered protein domain

Liquid-liquid phase separation (LLPS) can drive a multitude of cellular processes by compartmentalizing biological cells via the formation of dense liquid biomolecular condensates, which can function as membraneless organelles. Despite its importance, the molecular-level understanding of the underlying thermodynamics of this process remains incomplete. In this study, we use atomistic molecular dynamics simulations of the low complexity domain (LCD) of human fused in sarcoma (FUS) protein to investigate the contributions of water and protein molecules to the free energy changes that govern LLPS. Both protein and water components are found to have comparably sizeable thermodynamic contributions to the formation of FUS condensates. Moreover, we quantify the counteracting effects of water molecules that are released into the bulk upon condensate formation and the waters retained within the protein droplets. Among the various factors considered, solvation entropy and protein interaction enthalpy are identified as the most important contributions, while solvation enthalpy and protein entropy changes are smaller. These results provide detailed molecular insights on the intricate thermodynamic interplay between protein- and solvation-related forces underlying the formation of biomolecular condensates.

Single stop analysis of a protein surface using molecular probe electrochemistry

Visualization of a protein in its native form and environment without any interference has always been a challenging task. Contrary to the assumption that protein surfaces are smooth, they are in fact highly irregular with undulating surfaces. Hence, in this study, we have tackled this ambiguous nature of the 'surface' of a protein by considering the 'effective' protein surface (EPS) with respect to its interaction with the geometrically well-defined and structurally inert anionic molecule [3,3'-Co(1,2-C2B9H11)2]-, abbreviated as [o-COSAN]-, whose stability, propensity for amine residues, and self-assembling abilities are well reported. This study demonstrates the intricacies of protein surfaces exploiting simple electrochemical measurements using a 'small molecule' redox-active probe. This technique offers the advantage of not utilizing any harsh experimental conditions that could alter the native structure of the protein and hence the protein integrity is retained. Identification of the amino acid residues which are most involved in the interactions with [3,3'-Co(1,2-C2B9H11)2]- and how a protein's environment affects these interactions can help in gaining insights into how to modify proteins to optimize their interactions particularly in the fields of drug design and biotechnology. In this research, we have demonstrated that [3,3'-Co(1,2-C2B9H11)2]- anionic small molecules are excellent candidates for studying and visualizing protein surfaces in their natural environment and allow proteins to be classified according to the surface composition, which imparts their properties. [3,3'-Co(1,2-C2B9H11)2]- 'viewed' each protein surface differently and hence has the potential to act as a simple and easy to handle cantilever for measuring and picturing protein surfaces.

Stabilizing Nitroxide Spin Labels for Structural and Conformational Studies of Biomolecules by Maleimide Treatment

Nitroxide (NO) spin radicals are effective in characterizing structures, interactions and dynamics of biomolecules. The EPR applications in cell lysates or intracellular milieu require stable spin labels, but NO radicals are unstable in such conditions. We showed that the destabilization of NO radicals in cell lysates or even in cells is caused by NADPH/NADH related enzymes, but not by the commonly believed reducing reagents such as GSH. Maleimide stabilizes the NO radicals in the cell lysates by consumption of the NADPH/NADH that are essential for the enzymes involved in destabilizing NO radicals, instead of serving as the solo thiol scavenger. The maleimide treatment retains the crowding properties of the intracellular components and allows to perform long-time EPR measurements of NO labeled biomolecules close to the intracellular conditions. The strategy of maleimide treatment on cell lysates for the EPR applications has been demonstrated on double electron-electron resonance (DEER) measurements on a number of NO labeled protein samples. The method opens a broad application range for the NO labeled biomolecules by EPR in conditions that resemble the intracellular milieu.

Minimum information guidelines for experiments structurally characterizing intrinsically disordered protein regions

An unambiguous description of an experiment, and the subsequent biological observation, is vital for accurate data interpretation. Minimum information guidelines define the fundamental complement of data that can support an unambiguous conclusion based on experimental observations. We present the Minimum Information About Disorder Experiments (MIADE) guidelines to define the parameters required for the wider scientific community to understand the findings of an experiment studying the structural properties of intrinsically disordered regions (IDRs). MIADE guidelines provide recommendations for data producers to describe the results of their experiments at source, for curators to annotate experimental data to community resources and for database developers maintaining community resources to disseminate the data. The MIADE guidelines will improve the interpretability of experimental results for data consumers, facilitate direct data submission, simplify data curation, improve data exchange among repositories and standardize the dissemination of the key metadata on an IDR experiment by IDR data sources.

Intracellular environment can change protein conformational dynamics in cells through weak interactions

Conformational dynamics is important for protein functions, many of which are performed in cells. How the intracellular environment may affect protein conformational dynamics is largely unknown. Here, loop conformational dynamics is studied for a model protein in Escherichia coli cells by using nuclear magnetic resonance (NMR) spectroscopy. The weak interactions between the protein and surrounding macromolecules in cells hinder the protein rotational diffusion, which extends the dynamic detection timescale up to microseconds by the NMR spin relaxation method. The loop picosecond to microsecond dynamics is confirmed by nanoparticle-assisted spin relaxation and residual dipolar coupling methods. The loop interactions with the intracellular environment are perturbed through point mutation of the loop sequence. For the sequence of the protein that interacts stronger with surrounding macromolecules, the loop becomes more rigid in cells. In contrast, the mutational effect on the loop dynamics in vitro is small. This study provides direct evidence that the intracellular environment can modify protein loop conformational dynamics through weak interactions.

Direct Observation of Membrane-Associated H-Ras in the Native Cellular Environment by In-Cell 19F-NMR Spectroscopy

Ras acts as a molecular switch to control intracellular signaling on the plasma membrane (PM). Elucidating how Ras associates with PM in the native cellular environment is crucial for understanding its control mechanism. Here, we used in-cell nuclear magnetic resonance (NMR) spectroscopy combined with site-specific ¹⁹F-labeling to explore the membrane-associated states of H-Ras in living cells. The site-specific incorporation of p-trifluoromethoxyphenylalanine (OCF₃Phe) at three different sites of H-Ras, i.e., Tyr32 in switch I, Tyr96 interacting with switch II, and Tyr157 on helix α5, allowed the characterization of their conformational states depending on the nucleotide-bound states and an oncogenic mutational state. Exogenously delivered ¹⁹F-labeled H-Ras protein containing a C-terminal hypervariable region was assimilated via endogenous membrane-trafficking, enabling proper association with the cell membrane compartments. Despite poor sensitivity of the in-cell NMR spectra of membrane-associated H-Ras, the Bayesian spectral deconvolution identified distinct signal components on three ¹⁹F-labeled sites, thus offering the conformational multiplicity of H-Ras on the PM. Our study may be helpful in elucidating the atomic-scale picture of membrane-associated proteins in living cells.

Detection of Nonsynonymous Single Variants in Human HLA-DRB1 Exon 2 Associated with Renal Transplant Rejection

Background: HLA-DRB1 is the most polymorphic gene in the human leukocyte antigen (HLA) class II, and exon 2 is critical because it encodes antigen-binding sites. This study aimed to detect functional or marker genetic variants of HLA-DRB1 exon 2 in renal transplant recipients (acceptance and rejection) using Sanger sequencing. Methods: This hospital-based case-control study collected samples from two hospitals over seven months. The 60 participants were equally divided into three groups: rejection, acceptance, and control. The target regions were amplified and sequenced by PCR and Sanger sequencing. Several bioinformatics tools have been used to assess the impact of non-synonymous single-nucleotide variants (nsSNVs) on protein function and structure. The sequences data that support the findings of this study with accession numbers (OQ747803-OQ747862) are available in National Center for Biotechnology Information (GenBank database). Results: Seven SNVs were identified, two of which were novel (chr6(GRCh38.p12): 32584356C>A (K41N) and 32584113C>A (R122R)). Three of the seven SNVs were non-synonymous and found in the rejection group (chr6(GRCh38.p12): 32584356C>A (K41N), 32584304A>G (Y59H), and 32584152T>A (R109S)). The nsSNVs had varying effects on protein function, structure, and physicochemical parameters and could play a role in renal transplant rejection. The chr6(GRCh38.p12):32584152T>A variant showed the greatest impact. This is because of its conserved nature, main domain location, and pathogenic effects on protein structure, function, and stability. Finally, no significant markers were identified in the acceptance samples. Conclusion: Pathogenic variants can affect intramolecular/intermolecular interactions of amino acid residues, protein function/structure, and disease risk. HLA typing based on functional SNVs could be a comprehensive, accurate, and low-cost method for covering all HLA genes while shedding light on previously unknown causes in many graft rejection cases.

Crowded environments tune the fold-switching in metamorphic proteins

Metamorphic proteins such as circadian clock protein KaiB and human chemokine XCL1 play vital roles in regulating biological processes, including gene expression, circadian clock and innate immune responses, and perform distinct functions in living cell by switching different structures in response to cellular environment stimuli. However, it is unclear how complex and crowded intracellular environments affect conformational rearrangement of metamorphic proteins. Here, the kinetics and thermodynamics of two well-characterized metamorphic proteins, circadian clock protein KaiB and human chemokine XCL1, were quantified in physiologically relevant environments by using NMR spectroscopy, indicating that crowded agents shift equilibrium towards the inactive form (ground-state KaiB and Ltn10-like state XCL1) without disturbing the corresponding structures, and crowded agents have predominantly impact on the exchange rate of XCL1 that switches folds on timescales of seconds, but have slightly impact on the exchange rate of KaiB that switches folds on timescales of hours. Our data shed light on how metamorphic proteins can respond immediately to the changed crowded intracellular conditions that induced by environmental cues and then execute different functions in living cell, and it also enhances our understanding of how environments enrich the sequence-structure-function paradigm.

Bacterial Subcellular Architecture, Structural Epistasis, and Antibiotic Resistance

Epistasis refers to the way in which genetic interactions between some genetic loci affect phenotypes and fitness. In this study, we propose the concept of "structural epistasis" to emphasize the role of the variable physical interactions between molecules located in particular spaces inside the bacterial cell in the emergence of novel phenotypes. The architecture of the bacterial cell (typically Gram-negative), which consists of concentrical layers of membranes, particles, and molecules with differing configurations and densities (from the outer membrane to the nucleoid) determines and is in turn determined by the cell shape and size, depending on the growth phases, exposure to toxic conditions, stress responses, and the bacterial environment. Antibiotics change the bacterial cell's internal molecular topology, producing unexpected interactions among molecules. In contrast, changes in shape and size may alter antibiotic action. The mechanisms of antibiotic resistance (and their vectors, as mobile genetic elements) also influence molecular connectivity in the bacterial cell and can produce unexpected phenotypes, influencing the action of other antimicrobial agents.

Macromolecular Crowding by Polyethylene Glycol Reduces Protein Breathing

Most efforts to understand macromolecular crowding focus on global (i.e., complete) unfolding, but smaller excursions, often called breathing, promote aggregation, which is associated with several diseases and the bane of pharmaceutical and commercial protein production. We used NMR to assess the effects of ethylene glycol (EG) and polyethylene glycols (PEGs) on the structure and stability of the B1 domain of protein G (GB1). Our data show that EG and PEGs stabilize GB1 differently. EG interacts with GB1 more strongly than PEGs, but neither affects the structure of the folded state. EG and 12000 g/mol PEG stabilize GB1 more than PEGs of intermediate size, but EG and smaller PEGs stabilize GB1 enthalpically while the largest PEG acts entropically. Our key finding is that PEGs turn local unfolding into global unfolding, and meta-analysis of published data supports this conclusion. These efforts provide knowledge that can be applied to improve biological drugs and commercial enzymes.

Host–Pathogen Interactions Influencing Zoonotic Spillover Potential and Transmission in Humans

Emerging infectious diseases of zoonotic origin are an ever-increasing public health risk and economic burden. The factors that determine if and when an animal virus is able to spill over into the human population with sufficient success to achieve ongoing transmission in humans are complex and dynamic. We are currently unable to fully predict which pathogens may appear in humans, where and with what impact. In this review, we highlight current knowledge of the key host–pathogen interactions known to influence zoonotic spillover potential and transmission in humans, with a particular focus on two important human viruses of zoonotic origin, the Nipah virus and the Ebola virus. Namely, key factors determining spillover potential include cellular and tissue tropism, as well as the virulence and pathogenic characteristics of the pathogen and the capacity of the pathogen to adapt and evolve within a novel host environment. We also detail our emerging understanding of the importance of steric hindrance of host cell factors by viral proteins using a “flytrap”-type mechanism of protein amyloidogenesis that could be crucial in developing future antiviral therapies against emerging pathogens. Finally, we discuss strategies to prepare for and to reduce the frequency of zoonotic spillover occurrences in order to minimize the risk of new outbreaks.

Chemical Features of Polyanions Modulate Tau Aggregation and Conformational States

The aggregation of tau into insoluble fibrils is a defining feature of neurodegenerative tauopathies. However, tau has a positive overall charge and is highly soluble; so, polyanions, such as heparin, are typically required to promote its aggregation in vitro. There are dozens of polyanions in living systems, and it is not clear which ones might promote this process. Here, we systematically measure the ability of 37 diverse, anionic biomolecules to initiate tau aggregation using either wild-type (WT) tau or the disease-associated P301S mutant. We find that polyanions from many different structural classes can promote fibril formation and that P301S tau is sensitive to a greater number of polyanions (28/37) than WT tau (21/37). We also find that some polyanions preferentially reduce the lag time of the aggregation reactions, while others enhance the elongation rate, suggesting that they act on partially distinct steps. From the resulting structure-activity relationships, the valency of the polyanion seems to be an important chemical feature such that anions with low valency tend to be weaker aggregation inducers, even at the same overall charge. Finally, the identity of the polyanion influences fibril morphology based on electron microscopy and limited proteolysis. These results provide insights into the crucial role of polyanion-tau interactions in modulating tau conformational dynamics with implications for understanding the tau aggregation landscape in a complex cellular environment.

Solvent Effects Used for Optimal Simultaneous Analysis of Amino Acids via 19F NMR Spectroscopy

¹⁹F NMR has been extensively used in simultaneous analysis of multicomponent due to its 100% natural isotope abundance, high NMR-sensitivity, and wide-range chemical shifts. The solvent effects are usually observed in NMR spectroscopy and cause large changes in ¹⁹F chemical shifts. Herein, we propose that the simultaneous analysis of a complex mixture can be achieved using solvent effects via ¹⁹F NMR spectroscopy, such as a mixture solution of amino acids (AAs). AAs are not only cell-signaling molecules, but are also considered as biomarkers of some diseases. Hence, the analysis of AAs is important for human health and the diagnosis of diseases. In this work, the key to the success of sensing 19 biogenic AAs is the use of 2-fluorobenzaldehyde (2FBA) as a highly sensitive derivatizing agent and solvent effects to produce distinguishable ¹⁹F NMR signals. As a result, the resolution of ¹⁹F NMR spectroscopy of multiple 2FBA-labeled AAs is obviously higher than other methods based on ¹⁹F NMR. Moreover, 14 and 18 AAs can be satisfactorily differentiated and unambiguously identified in different complicated media supporting the growth of mammalian cells. Furthermore, quantification of the concentration of AAs can be made, and the limit of detection reaches 10 μM. Our work provides new insights into the simultaneous analysis of a multicomponent mixture based on solvent effects by ¹⁹F NMR spectroscopy.

Direct Expression of Fluorinated Proteins in Human Cells for 19F In-Cell NMR Spectroscopy

In-cell NMR spectroscopy is a powerful approach to study protein structure and function in the native cellular environment. It provides precious insights into the folding, maturation, interactions, and ligand binding of important pharmacological targets directly in human cells. However, its widespread application is hampered by the fact that soluble globular proteins often interact with large cellular components, causing severe line broadening in conventional heteronuclear NMR experiments. ¹⁹F NMR can overcome this issue, as fluorine atoms incorporated in proteins can be detected by simple background-free 1D NMR spectra. Here, we show that fluorinated amino acids can be easily incorporated in proteins expressed in human cells by employing a medium switch strategy. This straightforward approach allows the incorporation of different fluorinated amino acids in the protein of interest, reaching fluorination efficiencies up to 60%, as confirmed by mass spectrometry and X-ray crystallography. The versatility of the approach is shown by performing ¹⁹F in-cell NMR on several proteins, including those that would otherwise be invisible by ¹H-¹⁵N in-cell NMR. We apply the approach to observe the interaction between an intracellular target, carbonic anhydrase 2, and its inhibitors, and to investigate how the formation of a complex between superoxide dismutase 1 and its chaperone CCS modulates the interaction of the chaperone subunit with the cellular environment.

Water Adsorption on Mica Surfaces with Hydrophilicity Tuned by Counterion Types (Na, K, and Cs) and Structural Fluorination

The stability of adsorbed water films on mineral surfaces has far-reaching implications in the Earth, environmental, and materials sciences. Here, we use the basal plane of phlogopite mica, an atomically smooth surface of a natural mineral, to investigate water film structure and stability as a function of two features that modulate surface hydrophilicity: the type of adsorbed counterions (Na, K, and Cs) and the substitution of structural OH groups by F atoms. We use molecular dynamics simulations combined with in situ high-resolution X-ray reflectivity to examine surface hydration over a range of water loadings, from the adsorption of isolated water molecules to the formation of clusters and films. We identify four regimes characterized by distinct adsorption energetics and different sensitivities to cation type and mineral fluorination: from 0 to 0.5 monolayer film thickness, the hydration of adsorbed ions; from 0.5 to 1 monolayer, the hydration of uncharged regions of the siloxane surface; from 1 to 1.5 monolayer, the attachment of isolated water molecules on the surface of the first monolayer; and for >1.5 monolayer, the formation of an incipient electrical double layer at the mineral-water interface.

Label-Free Single-Molecule Pulldown for the Detection of Released Cellular Protein Complexes

Precise and sensitive detection of intracellular proteins and complexes is key to the understanding of signaling pathways and cell functions. Here, we present a label-free single-molecule pulldown (LFSMP) technique for the imaging of released cellular protein and protein complexes with single-molecule sensitivity and low sample consumption down to a few cells per mm². LFSMP is based on plasmonic scattering imaging and thus can directly image the surface-captured molecules without labels and quantify the binding kinetics. In this paper, we demonstrate the detection principle for LFSMP, study the phosphorylation of protein complexes involved in a signaling pathway, and investigate how kinetic analysis can be used to improve the pulldown specificity. We wish our technique can contribute to uncovering the molecular mechanisms in cells with single-molecule resolution.