Mechanisms of Nanonewton Mechanostability in a Protein Complex Revealed by Molecular Dynamics Simulations and Single-Molecule Force Spectroscopy

OLIVES: A Go̅-like Model for Stabilizing Protein Structure via Hydrogen Bonding Native Contacts in the Martini 3 Coarse-Grained Force Field

Coarse-grained molecular dynamics simulations enable the modeling of increasingly complex systems at millisecond timescales. The transferable coarse-grained force field Martini 3 has shown great promise in modeling a wide range of biochemical processes, yet folded proteins in Martini 3 are not stable without the application of external bias potentials, such as elastic networks or Go̅-like models. We herein develop an algorithm, called OLIVES, which identifies native contacts with hydrogen bond capabilities in coarse-grained proteins and use it to implement a novel Go̅-like model for Martini 3. We show that the protein structure instability originates in part from the lack of hydrogen bond energy in the coarse-grained force field representation. By using realistic hydrogen bond energies obtained from literature ab initio calculations, it is demonstrated that protein stability can be recovered by the reintroduction of a coarse-grained hydrogen bond network and that OLIVES removes the need for secondary structure restraints. OLIVES is validated against known protein complexes and at the same time addresses the open question of whether there is a need for protein quaternary structure bias in Martini 3 simulations. It is shown that OLIVES can reduce the number of bias terms, hereby speeding up Martini 3 simulations of proteins by up to ≈30% on a GPU architecture compared to the established Go̅MARTINI Go̅-like model.

Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1:Affibody Interactions

Understanding binding epitopes involved in protein-protein interactions and accurately determining their structure are long-standing goals with broad applicability in industry and biomedicine. Although various experimental methods for binding epitope determination exist, these approaches are typically low throughput and cost-intensive. Computational methods have potential to accelerate epitope predictions; however, recently developed artificial intelligence (AI)-based methods frequently fail to predict epitopes of synthetic binding domains with few natural homologues. Here we have developed an integrated method employing generalized-correlation-based dynamic network analysis on multiple molecular dynamics (MD) trajectories, initiated from AlphaFold2Multimer structures, to unravel the structure and binding epitope of the therapeutic PD-L1:Affibody complex. Both AlphaFold2 and conventional molecular dynamics trajectory analysis were ineffective in distinguishing between two proposed binding models, parallel and perpendicular. However, our integrated approach, utilizing dynamic network analysis, demonstrated that the perpendicular mode was significantly more stable. These predictions were validated using a suite of experimental epitope mapping protocols, including cross-linking mass spectrometry and next-generation sequencing-based deep mutational scanning. Conversely, AlphaFold3 failed to predict a structure bound in the perpendicular pose, highlighting the necessity for exploratory research in the search for binding epitopes and challenging the notion that AI-generated protein structures can be accepted without scrutiny. Our research underscores the potential of employing dynamic network analysis to enhance AI-based structure predictions for more accurate identification of protein-protein interaction interfaces.

Molecular Mechanism of Interaction between DNA Aptamer and Receptor-Binding Domain of Severe Acute Respiratory Syndrome Coronavirus 2 Variants Revealed by Steered Molecular Dynamics Simulations

The ongoing SARS-CoV-2 pandemic has underscored the urgent need for versatile and rapidly deployable antiviral strategies. While vaccines have been pivotal in controlling the spread of the virus, the emergence of new variants continues to pose significant challenges to global health. Here, our study focuses on a novel approach to antiviral therapy using DNA aptamers, short oligonucleotides with high specificity and affinity for their targets, as potential inhibitors against the spike protein of SARS-CoV-2 variants Omicron and JN.1. Our research utilizes steered molecular dynamics (SMD) simulations to elucidate the binding mechanisms of a specifically designed DNA aptamer, AM032-4, to the receptor-binding domain (RBD) of the aforementioned variants. The simulations reveal detailed molecular insights into the aptamer-RBD interaction, demonstrating the aptamer's potential to maintain effective binding in the face of rapid viral evolution. Our work not only demonstrates the dynamic interaction between aptamer-RBD for possible antiviral therapy but also introduces a computational method to study aptamer-protein interactions.

Single-molecule force stability of the SARS-CoV-2-ACE2 interface in variants-of-concern

Mutations in SARS-CoV-2 have shown effective evasion of population immunity and increased affinity to the cellular receptor angiotensin-converting enzyme 2 (ACE2). However, in the dynamic environment of the respiratory tract, forces act on the binding partners, which raises the question of whether not only affinity but also force stability of the SARS-CoV-2-ACE2 interaction might be a selection factor for mutations. Using magnetic tweezers, we investigate the impact of amino acid substitutions in variants of concern (Alpha, Beta, Gamma and Delta) and on force-stability and bond kinetic of the receptor-binding domain-ACE2 interface at a single-molecule resolution. We find a higher affinity for all of the variants of concern (>fivefold) compared with the wild type. In contrast, Alpha is the only variant of concern that shows higher force stability (by 17%) compared with the wild type. Using molecular dynamics simulations, we rationalize the mechanistic molecular origins of this increase in force stability. Our study emphasizes the diversity of contributions to the transmissibility of variants and establishes force stability as one of the several factors for fitness. Understanding fitness advantages opens the possibility for the prediction of probable mutations, allowing a rapid adjustment of therapeutics, vaccines and intervention measures.

Iterative Machine Learning for Classification and Discovery of Single-Molecule Unfolding Trajectories from Force Spectroscopy Data

We report the application of machine learning techniques to expedite classification and analysis of protein unfolding trajectories from force spectroscopy data. Using kernel methods, logistic regression, and triplet loss, we developed a workflow called Forced Unfolding and Supervised Iterative Online (FUSION) learning where a user classifies a small number of repeatable unfolding patterns encoded as images, and a machine is tasked with identifying similar images to classify the remaining data. We tested the workflow using two case studies on a multidomain XMod-Dockerin/Cohesin complex, validating the approach first using synthetic data generated with a Monte Carlo algorithm and then deploying the method on experimental atomic force spectroscopy data. FUSION efficiently separated traces that passed quality filters from unusable ones, classified curves with high accuracy, and identified unfolding pathways that were undetected by the user. This study demonstrates the potential of machine learning to accelerate data analysis and generate new insights in protein biophysics.

Fostering discoveries in the era of exascale computing: How the next generation of supercomputers empowers computational and experimental biophysics alike

Over a century ago, physicists started broadly relying on theoretical models to guide new experiments. Soon thereafter, chemists began doing the same. Now, biological research enters a new era when experiment and theory walk hand in hand. Novel software and specialized hardware became essential to understand experimental data and propose new models. In fact, current petascale computing resources already allow researchers to reach unprecedented levels of simulation throughput to connect in silico and in vitro experiments. The reduction in cost and improved access allowed a large number of research groups to adopt supercomputing resources and techniques. Here, we outline how large-scale computing has evolved to expand decades-old research, spark new research efforts, and continuously connect simulation and observation. For instance, multiple publicly and privately funded groups have dedicated extensive resources to develop artificial intelligence tools for computational biophysics, from accelerating quantum chemistry calculations to proposing protein structure models. Moreover, advances in computer hardware have accelerated data processing from single-molecule experimental observations and simulations of chemical reactions occurring throughout entire cells. The combination of software and hardware has opened the way for exascale computing and the production of the first public exascale supercomputer, Frontier, inaugurated by the Oak Ridge National Laboratory in 2022. Ultimately, the popularization and development of computational techniques and the training of researchers to use them will only accelerate the diversification of tools and learning resources for future generations.

S373P Mutation Stabilizes the Receptor-Binding Domain of the Spike Protein in Omicron and Promotes Binding

A cluster of several newly occurring mutations on Omicron is found at the β-core region of the spike protein's receptor-binding domain (RBD), where mutation rarely happened before. Notably, the binding of SARS-CoV-2 to human receptor ACE2 via RBD happens in a dynamic airway environment, where mechanical force caused by coughing or sneezing occurs. Thus, we used atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS) to measure the stability of RBDs and found that the mechanical stability of Omicron RBD increased by ∼20% compared with the wild type. Molecular dynamics (MD) simulations revealed that Omicron RBD showed more hydrogen bonds in the β-core region due to the closing of the α-helical motif caused primarily by the S373P mutation. In addition to a higher unfolding force, we showed a higher dissociation force between Omicron RBD and ACE2. This work reveals the mechanically stabilizing effect of the conserved mutation S373P for Omicron and the possible evolution trend of the β-core region of RBD.

Dissociation Rate Calculation via Constant-Force Steered Molecular Dynamics Simulation

Steered molecular dynamics (SMD) simulations are used to study molecular dissociation events by applying a harmonic force to the molecules and pulling them at a constant velocity. Instead of constant-velocity pulling, we use a constant force: the constant-force SMD (CF-SMD) simulation. The CF-SMD simulation employs a constant force to reduce the activation barrier of molecular dissociation, thereby enhancing the dissociation event. Here, we present the capability of the CF-SMD simulation to estimate the dissociation time at equilibrium. We performed all-atom CF-SMD simulations for NaCl and protein-ligand systems, producing dissociation time at various forces. We extrapolated these values to the dissociation rate without a constant force using Bell's model or the Dudko-Hummer-Szabo model. We demonstrate that the CF-SMD simulations with the models predicted the dissociation time in equilibrium. A CF-SMD simulation is a powerful tool for estimating the dissociation rate in a direct and computationally efficient manner.

Kaleidoscope megamolecules synthesis and application using self-assembly technology

The megamolecules with high ordered structures play an important role in chemical biology and biomedical engineering. Self-assembly, a long-discovered but very appealing technique, could induce many reactions between biomacromolecules and organic linking molecules, such as an enzyme domain and its covalent inhibitors. Enzyme and its small-molecule inhibitors have achieved many successes in medical application, which realize the catalysis process and theranostic function. By employing the protein engineering technology, the building blocks of enzyme fusion protein and small molecule linker can be assembled into a novel architecture with the specified organization and conformation. Molecular level recognition of enzyme domain could provide both covalent reaction sites and structural skeleton for the functional fusion protein. In this review, we will discuss the range of tools available to combine functional domains by using the recombinant protein technology, which can assemble them into precisely specified architectures/valences and develop the kaleidoscope megamolecules for catalytic and medical application.

May the force be with you: The role of hyper-mechanostability of the bone sialoprotein binding protein during early stages of Staphylococci infections

The bone sialoprotein-binding protein (Bbp) is a mechanoactive MSCRAMM protein expressed on the surface of Staphylococcus aureus that mediates adherence of the bacterium to fibrinogen-α (Fgα), a component of the bone and dentine extracellular matrix of the host cell. Mechanoactive proteins like Bbp have key roles in several physiological and pathological processes. Particularly, the Bbp: Fgα interaction is important in the formation of biofilms, an important virulence factor of pathogenic bacteria. Here, we investigated the mechanostability of the Bbp: Fgα complex using in silico single-molecule force spectroscopy (SMFS), in an approach that combines results from all-atom and coarse-grained steered molecular dynamics (SMD) simulations. Our results show that Bbp is the most mechanostable MSCRAMM investigated thus far, reaching rupture forces beyond the 2 nN range in typical experimental SMFS pulling rates. Our results show that high force-loads, which are common during initial stages of bacterial infection, stabilize the interconnection between the protein's amino acids, making the protein more "rigid". Our data offer new insights that are crucial on the development of novel anti-adhesion strategies.

Novel perspective for protein-drug interaction analysis: atomic force microscope

Proteins are major drug targets, and drug-target interaction identification and analysis are important factors for drug discovery. Atomic force microscopy (AFM) is a powerful tool making it possible to image proteins with nanometric resolution and probe intermolecular forces under physiological conditions. We review recent studies conducted in the field of target protein drug discovery using AFM-based analysis technology, including drug-driven changes in nanomechanical properties of protein morphology and interactions. Underlying mechanisms (including thermodynamic and kinetic parameters) of the drug-target interaction and drug-modulating protein-protein interaction (PPI) on the surfaces of models or living cells are discussed. Furthermore, challenges and the outlook for the field are likewise discussed. Overall, this insight into the mechanical properties of protein-drug interactions provides an unprecedented information framework for rational drug discovery in the pharmaceutical field.

Emulating Titin by a Multidomain DNA Structure

Titin, a giant protein containing multiple tandem domains, is essential in maintaining the superior mechanical performance of muscle. The consecutive and reversible unfolding and refolding of the domains are crucial for titin to serve as a modular spring. Since the discovery of the mechanical features of a single titin molecule, the exploration of biomimetic materials with titin-emulating modular structures has been an active field. However, it remains a challenge to prepare these modular polymers on a large scale due to the complex synthesis process. In this study, we propose modular DNA with multiple hairpins (MH-DNA) as the fundamental block for the bottom-up design of advanced materials. By analyzing the unfolding and refolding dynamics of modular hairpins by atomic force microscopy (AFM)-based single-molecule force spectroscopy (SMFS), we find that MH-DNA shows comparable stability to those of polyproteins like titin. The unique low hysteresis of modular hairpin makes it an ideal molecular spring with remarkable mechanical efficiency. On the basis of the well-established DNA synthesis techniques, we anticipate that MH-DNA can be used as a promising building block for advanced materials with a combination of superior structural stability, considerable extensibility, and high mechanical efficiency.

Molecular Origins of Force-Dependent Protein Complex Stabilization during Bacterial Infections

The unbinding pathway of a protein complex can vary significantly depending on biochemical and mechanical factors. Under mechanical stress, a complex may dissociate through a mechanism different from that used in simple thermal dissociation, leading to different dissociation rates under shear force and thermal dissociation. This is a well-known phenomenon studied in biomechanics whose molecular and atomic details are still elusive. A particularly interesting case is the complex formed by bacterial adhesins with their human peptide target. These protein interactions have a force resilience equivalent to those of covalent bonds, an order of magnitude stronger than the widely used streptavidin:biotin complex, while having an ordinary affinity, much lower than that of streptavidin:biotin. Here, in an in silico single-molecule force spectroscopy approach, we use molecular dynamics simulations to investigate the dissociation mechanism of adhesin/peptide complexes. We show how the Staphylococcus epidermidis adhesin SdrG uses a catch-bond mechanism to increase complex stability with increasing mechanical stress. While allowing for thermal dissociation in a low-force regime, an entirely different mechanical dissociation path emerges in a high-force regime, revealing an intricate mechanism that does not depend on the peptide's amino acid sequence. Using a dynamic network analysis approach, we identified key amino acid contacts that describe the mechanics of this complex, revealing differences in dynamics that hinder thermal dissociation and establish the mechanical dissociation path. We then validate the information content of the selected amino acid contacts using their dynamics to successfully predict the rupture forces for this complex through a machine learning model.

Single-Particle Optical Imaging for Ultrasensitive Bioanalysis

The quantitative detection of critical biomolecules and in particular low-abundance biomarkers in biofluids is crucial for early-stage diagnosis and management but remains a challenge largely owing to the insufficient sensitivity of existing ensemble-sensing methods. The single-particle imaging technique has emerged as an important tool to analyze ultralow-abundance biomolecules by engineering and exploiting the distinct physical and chemical property of individual luminescent particles. In this review, we focus and survey the latest advances in single-particle optical imaging (OSPI) for ultrasensitive bioanalysis pertaining to basic biological studies and clinical applications. We first introduce state-of-the-art OSPI techniques, including fluorescence, surface-enhanced Raman scattering, electrochemiluminescence, and dark-field scattering, with emphasis on the contributions of various metal and nonmetal nano-labels to the improvement of the signal-to-noise ratio. During the discussion of individual techniques, we also highlight their applications in spatial-temporal measurement of key biomarkers such as proteins, nucleic acids and extracellular vesicles with single-entity sensitivity. To that end, we discuss the current challenges and prospective trends of single-particle optical-imaging-based bioanalysis.

Interaction of the Staphylococcus aureus Surface Protein FnBPB with Corneodesmosin Involves Two Distinct, Extremely Strong Bonds

Attachment of Staphylococcus aureus to human skin corneocyte cells plays a critical role in exacerbating the severity of atopic dermatitis (AD). Pathogen-skin adhesion is mediated by bacterial cell-surface proteins called adhesins, including fibronectin-binding protein B (FnBPB). FnBPB binds to corneodesmosin (CDSN), a glycoprotein exposed on AD patient corneocytes. Using single-molecule experiments, we demonstrate that CDSN binding by FnBPB relies on a sophisticated two-site mechanism. Both sites form extremely strong bonds with binding forces of ∼1 and ∼2.5 nN albeit with faster dissociation rates than those reported for homologues of the adhesin. This previously unidentified two-binding site interaction in FnBPB illustrates its remarkable variety of adhesive functions and is of biological significance as the high strength and short bond lifetime will favor efficient skin colonization by the pathogen.

Protein structure prediction in the era of AI: Challenges and limitations when applying to in silico force spectroscopy

Mechanoactive proteins are essential for a myriad of physiological and pathological processes. Guided by the advances in single-molecule force spectroscopy (SMFS), we have reached a molecular-level understanding of how mechanoactive proteins sense and respond to mechanical forces. However, even SMFS has its limitations, including the lack of detailed structural information during force-loading experiments. That is where molecular dynamics (MD) methods shine, bringing atomistic details with femtosecond time-resolution. However, MD heavily relies on the availability of high-resolution structural data, which is not available for most proteins. For instance, the Protein Data Bank currently has 192K structures deposited, against 231M protein sequences available on Uniprot. But many are betting that this gap might become much smaller soon. Over the past year, the AI-based AlphaFold created a buzz on the structural biology field by being able to predict near-native protein folds from their sequences. For some, AlphaFold is causing the merge of structural biology with bioinformatics. Here, using an in silico SMFS approach pioneered by our group, we investigate how reliable AlphaFold structure predictions are to investigate mechanical properties of Staphylococcus bacteria adhesins proteins. Our results show that AlphaFold produce extremally reliable protein folds, but in many cases is unable to predict high-resolution protein complexes accurately. Nonetheless, the results show that AlphaFold can revolutionize the investigation of these proteins, particularly by allowing high-throughput scanning of protein structures. Meanwhile, we show that the AlphaFold results need to be validated and should not be employed blindly, with the risk of obtaining an erroneous protein mechanism.

Implementation of Telescoping Boxes in Adaptive Steered Molecular Dynamics

Long-time dynamical processes, such as those involving protein unfolding and ligand interactions, can be accelerated and realized through steered molecular dynamics (SMD). The challenge has been the extraction of information from such simulations that generalize for complex nonequilibrium processes. The use of Jarzynski's equality opened the possibility of determining the free energy along the steered coordinate, but sampling over the nonequilibrium trajectories is slow to converge. Adaptive steered molecular dynamics (ASMD) and other related techniques have been introduced to overcome this challenge through the use of stages. Here, we take advantage of these stages to address the numerical cost that arises from the required use of very large solvent boxes. We introduce telescoping box schemes within adaptive steered molecular dynamics (ASMD) in which we adjust the solvent box between stages and thereby vary (and optimize) the required number of solvent molecules. We have benchmarked the method on a relatively long α-helical peptide, Ala₃₀, with respect to the potential of mean force and hydrogen bonds. We show that the use of telescoping boxes introduces little numerical error while significantly reducing the computational cost.

Single-Molecule Force Spectroscopy Reveals the Dynamic HgS Coordination Site in the De Novo-Designed Metalloprotein α3DIV

The de novo-designed metalloprotein α3DIV binds to mercury via three cysteine residues under dynamic conditions. An unusual trigonal three-coordinate HgS3 site is formed in the protein in basic solution, whereas a linear two-coordinate HgS2 site is formed in acidic solution. Furthermore, it is unknown whether the two coordinated cysteines in the HgS2 site are fixed or not, which may lead to more dynamics. However, the signal for HgS2 sites with different cysteines may be similar or may be averaged and indistinguishable. To circumvent this problem, we adopt a single-molecule approach to study one mercury site at a time. Using atomic force microscopy-based single-molecule force spectroscopy, the protein is unfolded, and the HgS site is ruptured. The results confirm the formation of HgS3 and HgS2 sites at different pH values. Moreover, it is found that any two of the three cysteines in the protein bind to mercury in the HgS2 site.

A tethered ligand assay to probe SARS-CoV-2:ACE2 interactions

In the dynamic environment of the airways, where SARS-CoV-2 infections are initiated by binding to human host receptor ACE2, mechanical stability of the viral attachment is a crucial fitness advantage. Using single-molecule force spectroscopy techniques, we mimic the effect of coughing and sneezing, thereby testing the force stability of SARS-CoV-2 RBD:ACE2 interaction under physiological conditions. Our results reveal a higher force stability of SARS-CoV-2 binding to ACE2 compared to SARS-CoV-1, causing a possible fitness advantage. Our assay is sensitive to blocking agents preventing RBD:ACE2 bond formation. It will thus provide a powerful approach to investigate the modes of action of neutralizing antibodies and other agents designed to block RBD binding to ACE2 that are currently developed as potential COVID-19 therapeutics.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are initiated by attachment of the receptor-binding domain (RBD) on the viral Spike protein to angiotensin-converting enzyme-2 (ACE2) on human host cells. This critical first step occurs in dynamic environments, where external forces act on the binding partners and avidity effects play an important role, creating an urgent need for assays that can quantitate SARS-CoV-2 interactions with ACE2 under mechanical load. Here, we introduce a tethered ligand assay that comprises the RBD and the ACE2 ectodomain joined by a flexible peptide linker. Using magnetic tweezers and atomic force spectroscopy as highly complementary single-molecule force spectroscopy techniques, we investigate the RBD:ACE2 interaction over the whole physiologically relevant force range. We combine the experimental results with steered molecular dynamics simulations and observe and assign fully consistent unbinding and unfolding events across the three techniques, enabling us to establish ACE2 unfolding as a molecular fingerprint. Measuring at forces of 2 to 5 pN, we quantify the force dependence and kinetics of the RBD:ACE2 bond in equilibrium. We show that the SARS-CoV-2 RBD:ACE2 interaction has higher mechanical stability, larger binding free energy, and a lower dissociation rate compared to SARS-CoV-1, which helps to rationalize the different infection patterns of the two viruses. By studying how free ACE2 outcompetes tethered ACE2, we show that our assay is sensitive to prevention of bond formation by external binders. We expect our results to provide a way to investigate the roles of viral mutations and blocking agents for targeted pharmaceutical intervention.

Understanding the Adhesion Mechanism of Hydroxyapatite-Binding Peptide

Understanding the interactions between the protein collagen and hydroxyapatite is of high importance for understanding biomineralization and bone formation. Here, we undertook a reductionist approach and studied the interactions between a short peptide and hydroxyapatite. The peptide was selected from a phage-display library for its high affinity to hydroxyapatite. To study its interactions with hydroxyapatite, we performed an alanine scan to determine the contribution of each residue. The interactions of the different peptide derivatives were studied using a quartz crystal microbalance with dissipation monitoring and with single-molecule force spectroscopy by atomic force microscopy. Our results suggest that the peptide binds via electrostatic interactions between cationic moieties of the peptide and the negatively charged groups on the crystal surface. Furthermore, our findings show that cationic residues have a crucial role in binding. Using molecular dynamics simulations, we show that the peptide structure is a contributing factor to the adhesion mechanism. These results suggest that even small conformational changes can have a significant effect on peptide adhesion. We suggest that a bent structure of the peptide allows it to strongly bind hydroxyapatite. The results presented in this study improve our understanding of peptide adhesion to hydroxyapatite. On top of physical interactions between the peptide and the surface, peptide structure contributes to adhesion. Unveiling these processes contributes to our understanding of more complex biological systems. Furthermore, it may help in the design of de novo peptides to be used as functional groups for modifying the surface of hydroxyapatite.

Enzymatic Protein-Protein Conjugation through Internal Site Verified at the Single-Molecule Level

Enzymes are widely used for protein ligation because of their efficient and site-specific connections under mild conditions. However, many enzymatic ligations are restricted to connections between protein termini while protein-protein conjugation at a specific internal site is limited. Previous work has found that Sortase A (SrtA) conjugates small molecules/peptides to a pilin protein at an internal lysine site via an isopeptide bond. Herein, we apply this noncanonical ligation property of SrtA for protein-protein conjugation at a designed YPKH site. Both a small protein domain, I27, and a large protein, GFP, were ligated at the designed internal site. Moreover, besides characterization by classic methods at the ensemble level, the specific ligation site at the interior YPKH motif is unambiguously verified by atomic force microscopy-based single-molecule force spectroscopy, showing the characteristic unfolding signature at the single-molecule level. Finally, steered molecular dynamics simulations also agreed with the results.

AFM Identifies a Protein Complex Involved in Pathogen Adhesion Which Ruptures at Three Nanonewtons

Staphylococci bind to the blood protein von Willebrand Factor (vWF), thereby causing endovascular infections. Whether and how this interaction occurs with the medically important pathogen Staphylococcus epidermidis is unknown. Using single-molecule experiments, we demonstrate that the S. epidermidis protein Aap binds vWF via an ultrastrong force, ∼3 nN, the strongest noncovalent biological bond ever reported, and we show that this interaction is activated by tensile loading, suggesting a catch-bond behavior. Aap-vWF binding involves exclusively the A1 domain of vWF but requires both the A and B domains of Aap, as revealed by inhibition assays using specific monoclonal antibodies. Collectively, our results point to a mechanism where force-induced unfolding of the B repeats activates the A domain of Aap, shifting it from a weak- to a strong-binding state, which then engages into an ultrastrong interaction with vWF A1. This shear-dependent function of Aap offers promise for innovative antistaphylococcal therapies.

Details of Single-Molecule Force Spectroscopy Data Decoded by a Network-Based Automatic Clustering Algorithm

Atomic force microscopy-single-molecule force spectroscopy (AFM-SMFS) is a powerful methodology to probe intermolecular and intramolecular interactions in biological systems because of its operability in physiological conditions, facile and rapid sample preparation, versatile molecular manipulation, and combined functionality with high-resolution imaging. Since a huge number of AFM-SMFS force-distance curves are collected to avoid human bias and errors and to save time, numerous algorithms have been developed to analyze the AFM-SMFS curves. Nevertheless, there is still a need to develop new algorithms for the analysis of AFM-SMFS data since the current algorithms cannot specify an unbinding force to a corresponding/each binding site due to the lack of networking functionality to model the relationship between the unbinding forces. To address this challenge, herein, we develop an unsupervised method, i.e., a network-based automatic clustering algorithm (NASA), to decode the details of specific molecules, e.g., the unbinding force of each binding site, given the input of AFM-SMFS curves. Using the interaction of heparan sulfate (HS)-antithrombin (AT) on different endothelial cell surfaces as a model system, we demonstrate that NASA is able to automatically detect the peak and calculate the unbinding force. More importantly, NASA successfully identifies three unbinding force clusters, which could belong to three different binding sites, for both Ext1^f/f and Ndst1^f/f cell lines. NASA has great potential to be applied either readily or slightly modified to other AFM-based SMFS measurements that result in "saw-tooth"-shaped force-distance curves showing jumps related to the force unbinding, such as antibody-antigen interaction and DNA-protein interaction.

An ester bond underlies the mechanical strength of a pathogen surface protein

Gram-positive bacteria can resist large mechanical perturbations during their invasion and colonization by secreting various surface proteins with intramolecular isopeptide or ester bonds. Compared to isopeptide bonds, ester bonds are prone to hydrolysis. It remains elusive whether ester bonds can completely block mechanical extension similarly to isopeptide bonds, or whether ester bonds dissipate mechanical energy by bond rupture. Here, we show that an ester-bond containing stalk domain of Cpe0147 is inextensible even at forces > 2 nN. The ester bond locks the structure to a partially unfolded conformation, in which the ester bond remains largely water inaccessible. This allows the ester bond to withstand considerable mechanical forces and in turn prevent complete protein unfolding. However, the protecting effect might be reduced at non-physiological basic pHs or low calcium concentrations due to destabilizing the protein structures. Inspired by this design principle, we engineer a disulfide mutant resistant to mechanical unfolding under reducing conditions.

Bacterial surface adhesion proteins are characterized by unusual mechanical properties. Here, the authors use atomic force microscopy-based technique to study a surface-anchoring protein Cpe0147 from Clostridium perfringens and show that an ester bond can withstand considerable mechanical forces and prevent complete protein unfolding.

Nanomechanical Stability of Aβ Tetramers and Fibril-like Structures: Molecular Dynamics Simulations

Alzheimer's disease (AD) is a neurodegenerative disorder and one of the main causes of dementia. The disease is associated with amyloid beta (Aβ) peptide aggregation forming initial clusters and then fibril structure and plaques. Other neurodegenerative diseases such as type 2 diabetes, amyotrophic lateral sclerosis, and Parkinson's disease follow a similar mechanism. Therefore, inhibition of Aβ aggregation is considered an effective way to prevent AD. Recent experiments have provided evidence that oligomers are more toxic agents than mature fibrils, prompting researchers to investigate various factors that may influence their properties. One of these factors is nanomechanical stability, which plays an important role in the self-assembly of Aβ and possibly other proteins. This stability is also likely to be related to cell toxicity. In this work, we compare the mechanical stability of Aβ-tetramers and fibrillar structures using a structure-based coarse-grained (CG) approach and all-atom molecular dynamics simulation. Our results support the evidence for an increase in mechanical stability during the Aβ fibrillization process, which is consistent with in vitro AFM characterization of Aβ42 oligomers. Namely, using a CG model, we showed that the Young modulus of tetramers is lower than that of fibrils and, as follows from the experiment, is about 1 GPa. Hydrogen bonds are the dominant contribution to the detachment of one chain from the Aβ fibril fragment. They tend to be more organized along the pulling direction, whereas in the Aβ tetramers no preference is observed.

Highly Dynamic Polynuclear Metal Cluster Revealed in a Single Metallothionein Molecule

Human metallothionein (MT) is a small-size yet efficient metal-binding protein, playing an essential role in metal homeostasis and heavy metal detoxification. MT contains two domains, each forming a polynuclear metal cluster with an exquisite hexatomic ring structure. The apoprotein is intrinsically disordered, which may strongly influence the clusters and the metal-thiolate (M-S) bonds, leading to a highly dynamic structure. However, these features are challenging to identify due to the transient nature of these species. The individual signal from dynamic conformations with different states of the cluster and M-S bond will be averaged and blurred in classic ensemble measurement. To circumvent these problems, we combined a single-molecule approach and multiscale molecular simulations to investigate the rupture mechanism and chemical stability of the metal cluster by a single MT molecule, focusing on the Zn₄S₁₁ cluster in the α domain upon unfolding. Unusual multiple unfolding pathways and intermediates are observed for both domains, corresponding to different combinations of M-S bond rupture. None of the pathways is clearly preferred suggesting that unfolding proceeds from the distribution of protein conformational substates with similar M-S bond strengths. Simulations indicate that the metal cluster may rearrange, forming and breaking metal-thiolate bonds even when MT is folded independently of large protein backbone reconfiguration. Thus, a highly dynamic polynuclear metal cluster with multiple conformational states is revealed in MT, responsible for the binding promiscuity and diverse cellular functions of this metal-carrier protein.

Facile tethering of stable and unstable proteins for optical tweezers experiments

Single-molecule force spectroscopy with optical tweezers has emerged as a powerful tool for dissecting protein folding. The requirement to stably attach "molecular handles" to specific points in the protein of interest by preparative biochemical techniques is a limiting factor in applying this methodology, especially for large or unstable proteins that are difficult to produce and isolate. Here, we present a streamlined approach for creating stable and specific attachments using autocatalytic covalent tethering. The high specificity of coupling allowed us to tether ribosome-nascent chain complexes, demonstrating its suitability for investigating complex macromolecular assemblies. We combined this approach with cell-free protein synthesis, providing a facile means of preparing samples for single-molecule force spectroscopy. The workflow eliminates the need for biochemical protein purification during sample preparation for single-molecule measurements, making structurally unstable proteins amenable to investigation by this powerful single-molecule technique. We demonstrate the capabilities of this approach by carrying out pulling experiments with an unstructured domain of elongation factor G that had previously been refractory to analysis. Our approach expands the pool of proteins amenable to folding studies, which should help to reduce existing biases in the currently available set of protein folding models.

Proton Transfer in Nitromethane-Ammonia Clusters under VUV Single-Photon Ionization Explored by Infrared Spectroscopy and Theoretical Calculations

It is known that the acidity and reactivity of the CH bond can be enhanced after ionization. Also, this property plays a pivotal role in proton transfer reaction and in the formation of new molecules. Herein, infrared spectroscopy and high-precision quantum chemical calculations are used to study the neutral and cationic clusters of nitromethane-ammonia (CH₃NO₂-NH₃). It is found that in the neutral cluster, CH₃NO₂ and NH₃ are mainly bonded by three intermolecular hydrogen bonds, in which electrostatic contribution plays a major role. After vacuum ultraviolet (VUV) single-photon ionization of CH₃NO₂-NH₃, the positive charge redistributes from the ionized nitrogen atom of NH₃ to the CH₃NO₂ molecule immediately. Then, the proton of CH₃NO₂ transfers to NH₃ to form a proton-transferred type structure CH₂NO₂-NH₄⁺, without any effective energy barrier, due to the positive hyperconjugation of cationic nitromethane. A closed loop of positive charge transfer takes place in the CH₃NO₂-NH₃ cluster after VUV ionization. The present work demonstrates that both the proton transfer reaction and charge transfer process have occurred in the ionized CH₃NO₂-NH₃ cluster. Moreover, it is found that the proton transfer reaction is a result of the highly acidic CH bond caused by hyperconjugation between the σ (CH) bond and π orbital.

Pioglitazone Inhibits Metal Cluster Transfer of mitoNEET by Stabilizing the Labile Fe-N Bond Revealed at Single-Bond Level

Outer mitochondrial membrane protein mitoNEET (mNT) is a target of the type 2 diabetes drug pioglitazone. It contains a labile Fe₂S₂(His)₁(Cys)₃ metal cluster with a single Fe-N(His87) coordinating bond and can transfer its cluster to acceptor proteins. Previous ensemble studies showed that pioglitazone's binding inhibited the transfer by stabilizing the cluster, and histidine 87 may be the key mediator. Here we used atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS) to study the unfolding process of mNT dimer in the absence and presence of pioglitazone, which can distinguish the binding effect for different regions of a protein. By developing a two-step strategy using different mNT monomers with respective purification tags, we solve the problem that the classic polyprotein formation disables the mNT to dimerize. As a result, a polyprotein including a stable, naturally noncovalently bound mNT homodimer is obtained, which is required for reliable AFM measurement and pioglitazone binding. Then, the dissociation rate (k_off) of the metal cluster was measured, showing a 10-fold decrease upon pioglitazone binding, while the other parts decreased only 3-fold, verifying that pioglitazone mainly stabilizes the cluster. Moreover, when the Fe(III)-N(His87) bond was ruptured, this effect for the remaining Fe₂S₂(Cys)₃ intermediate largely disappeared. Consequently, AFM results revealed that pioglitazone inhibited the metal cluster transfer of mNT by stabilizing the labile Fe(III)-N(His87) bond. In addition, an alternative method to build a natural, noncovalently bound protein dimer or complex for reliable single-molecule measurement was developed.

Influence of Fluorination on Single-Molecule Unfolding and Rupture Pathways of a Mechanostable Protein Adhesion Complex

We investigated the influence of fluorination on unfolding and unbinding reaction pathways of a mechanostable protein complex comprising the tandem dyad XModule-Dockerin bound to Cohesin. Using single-molecule atomic force spectroscopy, we mapped the energy landscapes governing the unfolding and unbinding reactions. We then used sense codon suppression to substitute trifluoroleucine in place of canonical leucine globally in XMod-Doc. Although TFL substitution thermally destabilized XMod-Doc, it had little effect on XMod-Doc:Coh binding affinity at equilibrium. When we mechanically dissociated global TFL-substituted XMod-Doc from Coh, we observed the emergence of a new unbinding pathway with a lower energy barrier. Counterintuitively, when fluorination was restricted to Doc, we observed mechano-stabilization of the non-fluorinated neighboring XMod domain. This suggests that intramolecular deformation is modulated by fluorination and highlights the differences between equilibrium thermostability and non-equilibrium mechanostability. Future work is poised to investigate fluorination as a means to modulate mechanical properties of synthetic proteins and hydrogels.

Force-clamp spectroscopy identifies a catch bond mechanism in a Gram-positive pathogen

Physical forces have profound effects on cellular behavior, physiology, and disease. Perhaps the most intruiguing and fascinating example is the formation of catch-bonds that strengthen cellular adhesion under shear stresses. Today mannose-binding by the Escherichia coli FimH adhesin remains one of the rare microbial catch-bond thoroughly characterized at the molecular level. Here we provide a quantitative demonstration of a catch-bond in living Gram-positive pathogens using force-clamp spectroscopy. We show that the dock, lock, and latch interaction between staphylococcal surface protein SpsD and fibrinogen is strong, and exhibits an unusual catch-slip transition. The bond lifetime first grows with force, but ultimately decreases to behave as a slip bond beyond a critical force (~1 nN) that is orders of magnitude higher than for previously investigated complexes. This catch-bond, never reported for a staphylococcal adhesin, provides the pathogen with a mechanism to tightly control its adhesive function during colonization and infection.

Single-Molecule Force Spectroscopy Reveals that the Fe-N Bond Enables Multiple Rupture Pathways of the 2Fe2S Cluster in a MitoNEET Monomer

The mitochondrial outer membrane protein, mitoNEET (mNT), is an iron-sulfur protein containing an Fe₂S₂(His)₁(Cys)₃ cluster with a unique single Fe-N bond. Previous studies have shown that this Fe(III)-N(His) bond is essential for metal cluster transfer and protein function. To further understand the effect of this unique Fe-N bond on the metal cluster and protein, we used atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS) to investigate the mechanical unfolding mechanism of an mNT monomer, focusing on the rupture pathway and kinetic stability of the cluster. We found that the Fe-N bond was the weakest point of the cluster, the rupture of which occurred first, and could be independent of the cluster break. Moreover, this Fe-N bond enabled a dynamic and labile iron-sulfur cluster, as multiple unfolding pathways of mNT with a unique Fe₂S₂(Cys)₃ intermediate were observed accordingly.

High force catch bond mechanism of bacterial adhesion in the human gut

Bacterial colonization of the human intestine requires firm adhesion of bacteria to insoluble substrates under hydrodynamic flow. Here we report the molecular mechanism behind an ultrastable protein complex responsible for resisting shear forces and adhering bacteria to cellulose fibers in the human gut. Using single-molecule force spectroscopy (SMFS), single-molecule FRET (smFRET), and molecular dynamics (MD) simulations, we resolve two binding modes and three unbinding reaction pathways of a mechanically ultrastable R. champanellensis (Rc) Dockerin:Cohesin (Doc:Coh) complex. The complex assembles in two discrete binding modes with significantly different mechanical properties, with one breaking at ~500 pN and the other at ~200 pN at loading rates from 1-100 nN s-1. A neighboring X-module domain allosterically regulates the binding interaction and inhibits one of the low-force pathways at high loading rates, giving rise to a catch bonding mechanism that manifests under force ramp protocols. Multi-state Monte Carlo simulations show strong agreement with experimental results, validating the proposed kinetic scheme. These results explain mechanistically how gut microbes regulate cell adhesion strength at high shear stress through intricate molecular mechanisms including dual-binding modes, mechanical allostery and catch bonds.

Does protein unfolding play a functional role in vivo?

Unfolding and refolding of multidomain proteins under force have yet to be recognized as a major mechanism of function for proteins in vivo. In this review, we discuss the inherent properties of multidomain proteins under a force vector from a structural and functional perspective. We then characterize three main systems where multidomain proteins could play major roles through mechanical unfolding: muscular contraction, cellular mechanotransduction, and bacterial adhesion. We analyze how key multidomain proteins for each system can produce a gain-of-function from the perspective of a fine-tuned quantized response, a molecular battery, delivery of mechanical work through refolding, elasticity tuning, protection and exposure of cryptic sites, and binding-induced mechanical changes. Understanding how mechanical unfolding and refolding affect function will have important implications in designing mechano-active drugs against conditions such as muscular dystrophy, cancer, or novel antibiotics.

A Biological Nanomachine at Work: Watching the Cellulosome Degrade Crystalline Cellulose

The cellulosome is a supramolecular multienzymatic protein complex that functions as a biological nanomachine of cellulosic biomass degradation. How the megadalton-size cellulosome adapts to a solid substrate is central to its mechanism of action and is also key for its efficient use in bioconversion applications. We report time-lapse visualization of crystalline cellulose degradation by individual cellulosomes from Clostridium thermocellum by atomic force microscopy. Upon binding to cellulose, the cellulosomes switch to elongated, even filamentous shapes and morph these dynamically at below 1 min time scale according to requirements of the substrate surface under attack. Compared with noncomplexed cellulases that peel off material while sliding along crystalline cellulose surfaces, the cellulosomes remain bound locally for minutes and remove the material lying underneath. The consequent roughening up of the surface leads to an efficient deconstruction of cellulose nanocrystals both from the ends and through fissions within. Distinct modes of cellulose nanocrystal deconstruction by nature's major cellulase systems are thus revealed.

Next Generation Methods for Single-Molecule Force Spectroscopy on Polyproteins and Receptor-Ligand Complexes

Single-molecule force spectroscopy with the atomic force microscope provides molecular level insights into protein function, allowing researchers to reconstruct energy landscapes and understand functional mechanisms in biology. With steadily advancing methods, this technique has greatly accelerated our understanding of force transduction, mechanical deformation, and mechanostability within single- and multi-domain polyproteins, and receptor-ligand complexes. In this focused review, we summarize the state of the art in terms of methodology and highlight recent methodological improvements for AFM-SMFS experiments, including developments in surface chemistry, considerations for protein engineering, as well as theory and algorithms for data analysis. We hope that by condensing and disseminating these methods, they can assist the community in improving data yield, reliability, and throughput and thereby enhance the information that researchers can extract from such experiments. These leading edge methods for AFM-SMFS will serve as a groundwork for researchers cognizant of its current limitations who seek to improve the technique in the future for in-depth studies of molecular biomechanics.

Mechanical Forces between Mycobacterial Antigen 85 Complex and Fibronectin

Adhesion to extracellular matrix proteins is an important first step in host invasion, employed by many bacterial pathogens. In mycobacteria, the secreted Ag85 complex proteins, involved in the synthesis of the cell envelope, are known to bind to fibronectin (Fn) through molecular forces that are currently unknown. In this study, single-molecule force spectroscopy is used to study the strength, kinetics and thermodynamics of the Ag85-Fn interaction, focusing on the multidrug-resistant Mycobacterium abscessus species. Single Ag85 proteins bind Fn with a strength of ~75 pN under moderate tensile loading, which compares well with the forces reported for other Fn-binding proteins. The binding specificity is demonstrated by using free Ag85 and Fn peptides with active binding sequences. The Ag85-Fn rupture force increases with mechanical stress (i.e., loading rate) according to the Friddle–Noy–de Yoreo theory. From this model, we extract thermodynamic parameters that are in good agreement with previous affinity determinations by surface plasmon resonance. Strong bonds (up to ~500 pN) are observed under high tensile loading, which may favor strong mycobacterial attachment in the lung where cells are exposed to high shear stress or during hematogenous spread which leads to a disseminated infection. Our results provide new insight into the pleiotropic functions of an important mycobacterial virulence factor that acts as a stress-sensitive adhesin.

Streptavidin/biotin: Tethering geometry defines unbinding mechanics

Macromolecules tend to respond to applied forces in many different ways. Chemistry at high shear forces can be intriguing, with relatively soft bonds becoming very stiff in specific force-loading geometries. Largely used in bionanotechnology, an important case is the streptavidin (SA)/biotin interaction. Although SA's four subunits have the same affinity, we find that the forces required to break the SA/biotin bond depend strongly on the attachment geometry. With AFM-based single-molecule force spectroscopy (SMFS), we measured unbinding forces of biotin from different SA subunits to range from 100 to more than 400 pN. Using a wide-sampling approach, we carried out hundreds of all-atom steered molecular dynamics (SMD) simulations for the entire system, including molecular linkers. Our strategy revealed the molecular mechanism that causes a fourfold difference in mechanical stability: Certain force-loading geometries induce conformational changes in SA's binding pocket lowering the energy barrier, which biotin has to overcome to escape the pocket.

Advances in molecular simulations of protein mechanical properties and function

Single-molecule force spectroscopy and classical molecular dynamics are natural allies. Recent advances in both experiments and simulations have increasingly facilitated a direct comparison of SMFS and MD data, most importantly by closing the gap between time scales, which has been traditionally at least 5 orders of magnitudes wide. In this review, we will explore these advances chiefly on the computational side. We focus on protein dynamics under force and highlight recent studies that showcase how lower loading rates and more statistics help to better interpret previous experiments and to also motivate new ones. At the same time, steadily increasing system sizes are used to mimic more closely the mechanical environment in the biological context. We showcase some of these advances on atomistic and coarse-grained scale, from asymmetric membrane tension to larger (multidomain/multimeric) protein assemblies under force.

Verification of sortase for protein conjugation by single-molecule force spectroscopy and molecular dynamics simulations

SMFS and MD simulations revealed a closed conformation and a decreased stability of sortase-mediated polyprotein I27 when a linker with a high content of glycine is used.

The molecular mechanisms underlying mussel adhesion

Marine mussels are able to firmly affix on various wet surfaces by the overproduction of special mussel foot proteins (mfps). Abundant fundamental studies have been conducted to understand the molecular basis of mussel adhesion, where the catecholic amino acid, l-3,4-dihydroxyphenylalanine (DOPA) has been found to play the major role. These studies continue to inspire the engineering of novel adhesives and coatings with improved underwater performances. Despite the fact that the recent advances of adhesives and coatings inspired by mussel adhesive proteins have been intensively reviewed in literature, the fundamental biochemical and biophysical studies on the origin of the strong and versatile wet adhesion have not been fully covered. In this review, we show how the force measurements at the molecular level by surface force apparatus (SFA) and single molecule atomic force microscopy (AFM) can be used to reveal the direct link between DOPA and the wet adhesion strength of mussel proteins. We highlight a few important technical details that are critical to the successful experimental design. We also summarize many new insights going beyond DOPA adhesion, such as the surface environment and protein sequence dependent synergistic and cooperative binding. We also provide a perspective on a few uncharted but outstanding questions for future studies. A comprehensive understanding on mussel adhesion will be beneficial to the design of novel synthetic wet adhesives for various biomedical applications.