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

Broad-spectrum coronavirus inhibitors discovered by modeling viral fusion dynamics

Development of oral, broad-spectrum therapeutics targeting SARS-CoV-2, its variants, and related coronaviruses could curb the spread of COVID-19 and avert future pandemics. We created a novel computational discovery pipeline that employed molecular dynamics simulation (MDS), artificial intelligence (AI)-based docking predictions, and medicinal chemistry to design viral entry inhibitors that target a conserved region in the SARS-CoV-2 spike (S) protein that mediates membrane fusion. DrugBank library screening identified the orally available, FDA-approved AXL kinase inhibitor bemcentinib as binding this site and we demonstrated that it inhibits viral entry in a kinase-independent manner. Novel analogs predicted to bind to the same region and disrupt S protein conformational changes were designed using MDS and medicinal chemistry. These compounds significantly suppressed SARS-CoV-2 infection and blocked the entry of S protein-bearing pseudotyped α,β,γ,δ,ο variants as well as SARS CoV and MERS-CoV in human ACE2-expressing or DPP4-expressing cells more effectively than bemcentinib. When administered orally, the optimized lead compound also significantly inhibited SARS-CoV2 infection in mice. This computational design strategy may accelerate drug discovery for a broad range of applications.

GōMartini 3: From large conformational changes in proteins to environmental bias corrections

Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The GōMartini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced GōMartini model, which combines a virtual-site implementation of Gō models with Martini 3. The implementation has been extensively tested by the community since the release of the reparametrized version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with Gō models.

Atomistic Insights into gp82 Binding: A Microsecond, Million-Atom Exploration of Trypanosoma cruzi Host-Cell Invasion

Chagas disease, caused by the protozoan Trypanosoma cruzi, affects millions globally, leading to severe cardiac and gastrointestinal complications in its chronic phase. The invasion of host cells by T. cruzi is mediated by the interaction between the parasite's glycoprotein gp82 and the human receptor lysosome-associated membrane protein 2 (LAMP2). While experimental studies have identified a few residues involved in this interaction, a comprehensive molecular-level understanding has been lacking. In this study, we present a 1.44-million-atom computational model of the gp82 complex, including over 3300 lipids, glycosylation sites, and full molecular representations of gp82 and LAMP2, making it the most complete model of a parasite-host interaction to date. Using microsecond-long molecular dynamics simulations and dynamic network analysis, we identified critical residue interactions, including novel regions of contact that were previously uncharacterized. Our findings also highlight the significance of the transmembrane domain of LAMP2 in stabilizing the complex. These insights extend beyond traditional hydrogen bond interactions, revealing a complex network of cooperative motions that facilitate T. cruzi invasion. This study not only confirms key experimental observations but also uncovers new molecular targets for therapeutic intervention, offering a potential pathway to disrupt T. cruzi infection and combat Chagas disease.

Accurate drift-invariant single-molecule force calibration using the Hadamard variance

Single-molecule force spectroscopy (SMFS) techniques play a pivotal role in unraveling the mechanics and conformational transitions of biological macromolecules under external forces. Among these techniques, multiplexed magnetic tweezers (MT) are particularly well suited to probe very small forces, ≤1 pN, critical for studying noncovalent interactions and regulatory conformational changes at the single-molecule level. However, to apply and measure such small forces, a reliable and accurate force-calibration procedure is crucial. Here, we introduce a new approach to calibrate MT based on thermal motion using the Hadamard variance (HV). To test our method, we perform bead-tether Brownian dynamics simulations that mimic our experimental system and compare the performance of the HV method against two established techniques: power spectral density (PSD) and Allan variance (AV) analyses. Our analysis includes an assessment of each method's ability to mitigate common sources of additive noise, such as white and pink noise, as well as drift, which often complicate experimental data analysis. We find that the HV method exhibits overall similar or higher precision and accuracy, yielding lower force estimation errors across a wide range of signal-to-noise ratios (SNRs) and drift speeds compared with the PSD and AV methods. Notably, the HV method remains robust against drift, maintaining consistent uncertainty levels across the entire studied SNR and drift speed spectrum. We also explore the HV method using experimental MT data, where we find overall smaller force estimation errors compared with PSD and AV approaches. Overall, the HV method offers a robust method for achieving sub-pN resolution and precision in multiplexed MT measurements. Its potential extends to other SMFS techniques, presenting exciting opportunities for advancing our understanding of mechanosensitivity and force generation in biological systems. To make our methods widely accessible to the research community, we provide a well-documented Python implementation of the HV method as an extension to the Tweezepy package.

Atomistic Insights into gp82 Binding: A Microsecond, Million-Atom Exploration of Trypanosoma cruzi Host-Cell Invasion

Chagas disease, caused by the protozoan Trypanosoma cruzi , affects millions globally, leading to severe cardiac and gastrointestinal complications in its chronic phase. The invasion of host cells by T. cruzi is mediated by the interaction between the parasite's glycoprotein gp82 and the human receptor lysosome-associated membrane protein 2 (LAMP2). While experimental studies have identified a few residues involved in this interaction, a comprehensive molecular-level understanding has been lacking. In this study, we present a 1.44-million-atom computational model of the gp82 complex, including over 3,300 lipids, glycosylation sites, and full molecular representations of gp82 and LAMP2, making it the most complete model of a parasite-host interaction to date. Using microsecond-long molecular dynamics simulations and dynamic network analysis, we identified critical residue interactions, including novel regions of contact that were previously uncharacterized. Our findings also highlight the significance of the transmembrane domain of LAMP2 in stabilizing the complex. These insights extend beyond traditional hydrogen bond interactions, revealing a complex network of cooperative motions that facilitate T. cruzi invasion. This study not only confirms key experimental observations but also uncovers new molecular targets for therapeutic intervention, offering a potential pathway to disrupt T. cruzi infection and combat Chagas disease.

Nanomechanical footprint of SARS-CoV-2 variants in complex with a potent nanobody by molecular simulations

Rational design of novel antibody therapeutics against viral infections such as coronavirus relies on surface complementarity and high affinity for their effectiveness. Here, we explore an additional property of protein complexes, the intrinsic mechanical stability, in SARS-CoV-2 variants when complexed with a potent antibody. In this study, we utilized a recent implementation of the GōMartini 3 approach to investigate large conformational changes in protein complexes with a focus on the mechanostability of the receptor-binding domain (RBD) from WT, Alpha, Delta, and XBB.1.5 variants in complex with the H11-H4 nanobody. The analysis revealed moderate differences in mechanical stability among these variants. Also, we identified crucial residues in both the RBD and certain protein segments in the nanobody that contribute to this property. By performing pulling simulations and monitoring the presence of specific native and non-native contacts across the protein complex interface, we provided mechanistic insights into the dissociation process. Force-displacement profiles indicate a tensile force clamp mechanism associated with the type of protein complex. Our computational approach not only highlights the key mechanostable interactions that are necessary to maintain overall stability, but it also paves the way for the rational design of potent antibodies that are mechanostable and effective against emergent SARS-CoV-2 variants.

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.

Adsorption-Driven Deformation and Footprints of the RBD Proteins in SARS-CoV-2 Variants on Biological and Inanimate Surfaces

Respiratory viruses, carried through airborne microdroplets, frequently adhere to surfaces, including plastics and metals. However, our understanding of the interactions between viruses and materials remains limited, particularly in scenarios involving polarizable surfaces. Here, we investigate the role of the receptor-binding domain (RBD) of the spike protein mutations on the adsorption of SARS-CoV-2 to hydrophobic and hydrophilic surfaces employing molecular simulations. To contextualize our findings, we contrast the interactions on inanimate surfaces with those on native biological interfaces, specifically the angiotensin-converting enzyme 2. Notably, we identify a 2-fold increase in structural deformations for the protein's receptor binding motif (RBM) onto inanimate surfaces, indicative of enhanced shock-absorbing mechanisms. Furthermore, the distribution of adsorbed amino acids (landing footprints) on the inanimate surface reveals a distinct regional asymmetry relative to the biological interface, with roughly half of the adsorbed amino acids arranged in opposite sites. In spite of the H-bonds formed at the hydrophilic substrate, the simulations consistently show a higher number of contacts and interfacial area with the hydrophobic surface, where the wild-type RBD adsorbs more strongly than the Delta or Omicron RBDs. In contrast, the adsorption of Delta and Omicron to hydrophilic surfaces was characterized by a distinctive hopping-pattern. The novel shock-absorbing mechanisms identified in the virus adsorption on inanimate surfaces show the embedded high-deformation capacity of the RBD without losing its secondary structure, which could lead to current experimental strategies in the design of virucidal surfaces.

Rolosense: Mechanical Detection of SARS-CoV-2 Using a DNA-Based Motor

Assays that detect viral infections play a significant role in limiting the spread of diseases such as SARS-CoV-2. Here, we present Rolosense, a virus sensing platform that leverages the motion of 5 μm DNA-based motors on RNA fuel chips to transduce the presence of viruses. Motors and chips are modified with aptamers, which are designed for multivalent binding to viral targets and lead to stalling of motion. Therefore, the motors perform a "mechanical test" of the viral target and stall in the presence of whole virions, which represents a unique mechanism of transduction distinct from conventional assays. Rolosense can detect SARS-CoV-2 spiked in artificial saliva and exhaled breath condensate with a sensitivity of 103 copies/mL and discriminates among other respiratory viruses. The assay is modular and amenable to multiplexing, as demonstrated by our one-pot detection of influenza A and SARS-CoV-2. As a proof of concept, we show that readout can be achieved using a smartphone camera with a microscopic attachment in as little as 15 min without amplification reactions. Taken together, these results show that mechanical detection using Rolosense can be broadly applied to any viral target and has the potential to enable rapid, low-cost point-of-care screening of circulating viruses.

A Handle-Free, All-Protein-Based Optical Tweezers Method to Probe Protein Folding-Unfolding Dynamics

Optical tweezers (OT) have evolved into powerful single molecule force spectroscopy tools to investigate protein folding-unfolding dynamics. To stretch a protein of interest using OT, the protein must be flanked with two double stranded DNA (dsDNA) handles. However, coupling dsDNA handles to the protein is often of low yield, representing a bottleneck in OT experiments. Here, we report a handle-free, all-protein-based OT method for investigating protein folding/unfolding dynamics. In this new method, we employed disordered elastin-like polypeptides (ELPs) as a molecular linker and the mechanically stable cohesin-dockerin (Coh-Doc) pair as the prey-bait system to enable the efficient capture and stretching of individual protein molecules. This novel approach was validated by using model proteins NuG2 and RTX-v, yielding experimental results comparable to those obtained by using the dsDNA handle approach. This new method provides a streamlined and efficient OT approach to investigate the folding-unfolding dynamics of proteins at the single molecule level, thus expanding the toolbox of OT-based single molecule force spectroscopy.

Single-molecule magnetic tweezers to probe the equilibrium dynamics of individual proteins at physiologically relevant forces and timescales

The reversible unfolding and refolding of proteins is a regulatory mechanism of tissue elasticity and signalling used by cells to sense and adapt to extracellular and intracellular mechanical forces. However, most of these proteins exhibit low mechanical stability, posing technical challenges to the characterization of their conformational dynamics under force. Here, we detail step-by-step instructions for conducting single-protein nanomechanical experiments using ultra-stable magnetic tweezers, which enable the measurement of the equilibrium conformational dynamics of single proteins under physiologically relevant low forces applied over biologically relevant timescales. We report the basic principles determining the functioning of the magnetic tweezer instrument, review the protein design strategy and the fluid chamber preparation and detail the procedure to acquire and analyze the unfolding and refolding trajectories of individual proteins under force. This technique adds to the toolbox of single-molecule nanomechanical techniques and will be of particular interest to those interested in proteins involved in mechanosensing and mechanotransduction. The procedure takes 4 d to complete, plus an additional 6 d for protein cloning and production, requiring basic expertise in molecular biology, surface chemistry and data analysis.

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 Investigation of the Binding Interface Stability of SARS-CoV-2 Variants with ACE2

The SARS-CoV-2 pandemic spurred numerous research endeavors to comprehend the virus and mitigate its global severity. Understanding the binding interface between the virus and human receptors is pivotal to these efforts and paramount to curbing infection and transmission. Here we employ atomic force microscopy and steered molecular dynamics simulation to explore SARS-CoV-2 receptor binding domain (RBD) variants and angiotensin-converting enzyme 2 (ACE2), examining the impact of mutations at key residues upon binding affinity. Our results show that the Omicron and Delta variants possess strengthened binding affinity in comparison to the Mu variant. Further, using sera from individuals either vaccinated or with acquired immunity following Delta strain infection, we assess the impact of immunity upon variant RBD/ACE2 complex formation. Single-molecule force spectroscopy analysis suggests that vaccination before infection may provide stronger protection across variants. These results underscore the need to monitor antigenic changes in order to continue developing innovative and effective SARS-CoV-2 abrogation strategies.

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.

Deciphering the free energy landscapes of SARS-CoV-2 wild type and Omicron variant interacting with human ACE2

The binding of the receptor binding domain (RBD) of the SARS-CoV-2 spike protein to the host cell receptor angiotensin-converting enzyme 2 (ACE2) is the first step in human viral infection. Therefore, understanding the mechanism of interaction between RBD and ACE2 at the molecular level is critical for the prevention of COVID-19, as more variants of concern, such as Omicron, appear. Recently, atomic force microscopy has been applied to characterize the free energy landscape of the RBD-ACE2 complex, including estimation of the distance between the transition state and the bound state, xu. Here, using a coarse-grained model and replica-exchange umbrella sampling, we studied the free energy landscape of both the wild type and Omicron subvariants BA.1 and XBB.1.5 interacting with ACE2. In agreement with experiment, we find that the wild type and Omicron subvariants have similar xu values, but Omicron binds ACE2 more strongly than the wild type, having a lower dissociation constant KD.

An Introduction to Magnetic Tweezers

Magnetic tweezers are a single-molecule force and torque spectroscopy technique that enable the mechanical interrogation in vitro of biomolecules, such as nucleic acids and proteins. They use a magnetic field originating from either permanent magnets or electromagnets to attract a magnetic particle, thus stretching the tethering biomolecule. They nicely complement other force spectroscopy techniques such as optical tweezers and atomic force microscopy (AFM) as they operate as a very stable force clamp, enabling long-duration experiments over a very broad range of forces spanning from 10 fN to 1 nN, with 1-10 milliseconds time and sub-nanometer spatial resolution. Their simplicity, robustness, and versatility have made magnetic tweezers a key technique within the field of single-molecule biophysics, being broadly applied to study the mechanical properties of, e.g., nucleic acids, genome processing molecular motors, protein folding, and nucleoprotein filaments. Furthermore, magnetic tweezers allow for high-throughput single-molecule measurements by tracking hundreds of biomolecules simultaneously both in real-time and at high spatiotemporal resolution. Magnetic tweezers naturally combine with surface-based fluorescence spectroscopy techniques, such as total internal reflection fluorescence microscopy, enabling correlative fluorescence and force/torque spectroscopy on biomolecules. This chapter presents an introduction to magnetic tweezers including a description of the hardware, the theory behind force calibration, its spatiotemporal resolution, combining it with other techniques, and a (non-exhaustive) overview of biological applications.

Piconewton Forces Mediate GAIN Domain Dissociation of the Latrophilin-3 Adhesion GPCR

Latrophilins are adhesion G-protein coupled receptors (aGPCRs) that control excitatory synapse formation. Most aGPCRs, including latrophilins, are autoproteolytically cleaved at their GPCR-autoproteolysis inducing (GAIN) domain, but the two resulting fragments remain noncovalently associated on the cell surface. Force-mediated dissociation of the fragments is thought to activate G-protein signaling, but how this mechanosensitivity arises is poorly understood. Here, we use magnetic tweezer assays to show that physiologically relevant forces in the 1-10 pN range lead to dissociation of the latrophilin-3 GAIN domain on the seconds-to-minutes time scale, compared to days in the absence of force. In addition, we find that the GAIN domain undergoes large changes in length in response to increasing mechanical load. These data are consistent with a model in which a force-sensitive equilibrium between compact and extended GAIN domain states precedes dissociation, suggesting a mechanism by which latrophilins and other aGPCRs may mediate mechanically induced signal transduction.

Probing nanomechanical interactions of SARS-CoV-2 variants Omicron and XBB with common surfaces

The emergence of SARS-CoV-2 variants has further raised concerns about viral transmission. A fundamental understanding of the intermolecular interactions between the coronavirus and different surfaces is needed to address the transmission of SARS-CoV-2 through respiratory droplet-contaminated surfaces or fomites. The receptor-binding domain (RBD) of the spike protein is a key target for the adhesion of SARS-CoV-2 on the surface. To understand the effect of mutations on adhesion, atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS) was used to quantify the interactions between wild-type, Omicron, and XBB with several surfaces. The measurement revealed that RBD exhibits relatively higher forces on paper and gold surfaces, with the average force being 1.5 times greater compared to that on plastic surface. In addition, the force elevation on paper and gold surfaces for the variants can reach ∼28% relative to the wild type. These findings enhance our understanding of the nanomechanical interactions of the virus on common surfaces.

Binding of synthetic nanobodies to the SARS-CoV-2 receptor-binding domain: the importance of salt bridges

In this study, five different SARS-CoV-2 receptor-binding domain (RBD) models were created based on the crystal structures of RBD complexes with two synthetic nanobodies (Sb16 and Sb45). Microsecond all-atom MD simulations revealed that Sb16 and Sb45 substantially stabilized the flexible RBD loop (residues GLU471-SER494) due to the salt bridges and hydrogen bonding interactions between RBD and the synthetic nanobodies. However, the calculation of binding free energy displayed that Sb45 had a higher binding affinity to RBD than Sb16, in agreement with the experimental result. This is because Sb45 has stronger electrostatic attraction to RBD as compared to Sb16. In particular, the salt bridge GLU484-ARG33 in Sb45-RBD is stronger than the GLU484-LYS32 in Sb16-RBD. Furthermore, by comparing the binding affinity of Sb16 for two RBD mutants (E484K and K417N), we found that E484K mutation substantially reduced the binding affinity to Sb16, and K417N mutation had no significant effect, qualitatively in agreement with experimental studies. According to the binding free energy calculation, the strong electrostatic repulsion between LYS32 and LYS484 caused by E484K mutation destroys the salt bridge between LYS32 and GLU484 in the RBD wild type (WT). In contrast, the binding of the K417N mutant to Sb16 effectively maintains the salt bridge between LYS32 and GLU484. Therefore, our research suggests that the salt bridges between RBD and synthetic nanobodies are crucial for binding synthetic nanobodies to RBD, and a SARS-CoV-2 variant can escape neutralization from nanobodies by creating electrostatic repulsion between them.

Probing conformational landscapes of binding and allostery in the SARS-CoV-2 omicron variant complexes using microsecond atomistic simulations and perturbation-based profiling approaches: hidden role of omicron mutations as modulators of allosteric signaling and epistatic relationships

In this study, we systematically examine the conformational dynamics, binding and allosteric communications in the Omicron BA.1, BA.2, BA.3 and BA.4/BA.5 spike protein complexes with the ACE2 host receptor using molecular dynamics simulations and perturbation-based network profiling approaches. Microsecond atomistic simulations provided a detailed characterization of the conformational landscapes and revealed the increased thermodynamic stabilization of the BA.2 variant which can be contrasted with the BA.4/BA.5 variants inducing a significant mobility of the complexes. Using the dynamics-based mutational scanning of spike residues, we identified structural stability and binding affinity hotspots in the Omicron complexes. Perturbation response scanning and network-based mutational profiling approaches probed the effect of the Omicron mutations on allosteric interactions and communications in the complexes. The results of this analysis revealed specific roles of Omicron mutations as conformationally plastic and evolutionary adaptable modulators of binding and allostery which are coupled to the major regulatory positions through interaction networks. Through perturbation network scanning of allosteric residue potentials in the Omicron variant complexes performed in the background of the original strain, we characterized regions of epistatic couplings that are centered around the binding affinity hotspots N501Y and Q498R. Our results dissected the vital role of these epistatic centers in regulating protein stability, efficient ACE2 binding and allostery which allows for accumulation of multiple Omicron immune escape mutations at other sites. Through integrative computational approaches, this study provides a systematic analysis of the effects of Omicron mutations on thermodynamics, binding and allosteric signaling in the complexes with ACE2 receptor.

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.

Combining DNA scaffolds and acoustic force spectroscopy to characterize individual protein bonds

Single-molecule data are of great significance in biology, chemistry, and medicine. However, new experimental tools to characterize, in a multiplexed manner, protein bond rupture under force are still needed. Acoustic force spectroscopy is an emerging manipulation technique which generates acoustic waves to apply force in parallel on multiple microbeads tethered to a surface. We here exploit this configuration in combination with the recently developed modular junctured-DNA scaffold that has been designed to study protein-protein interactions at the single-molecule level. By applying repetitive constant force steps on the FKBP12-rapamycin-FRB complex, we measure its unbinding kinetics under force at the single-bond level. Special efforts are made in analyzing the data to identify potential pitfalls. We propose a calibration method allowing in situ force determination during the course of the unbinding measurement. We compare our results with well-established techniques, such as magnetic tweezers, to ensure their accuracy. We also apply our strategy to study the force-dependent rupture of a single-domain antibody with its antigen. Overall, we get a good agreement with the published parameters that have been obtained at zero force and population level. Thus, our technique offers single-molecule precision for multiplexed measurements of interactions of biotechnological and medical interest.

Probing Conformational Landscapes of Binding and Allostery in the SARS-CoV-2 Omicron Variant Complexes Using Microsecond Atomistic Simulations and Perturbation-Based Profiling Approaches: Hidden Role of Omicron Mutations as Modulators of Allosteric Signaling and Epistatic Relationships

In this study, we systematically examine the conformational dynamics, binding and allosteric communications in the Omicron BA.1, BA.2, BA.3 and BA.4/BA.5 complexes with the ACE2 host receptor using molecular dynamics simulations and perturbation-based network profiling approaches. Microsecond atomistic simulations provided a detailed characterization of the conformational landscapes and revealed the increased thermodynamic stabilization of the BA.2 variant which is contrasted with the BA.4/BA.5 variants inducing a significant mobility of the complexes. Using ensemble-based mutational scanning of binding interactions, we identified binding affinity and structural stability hotspots in the Omicron complexes. Perturbation response scanning and network-based mutational profiling approaches probed the effect of the Omicron variants on allosteric communications. The results of this analysis revealed specific roles of Omicron mutations as "plastic and evolutionary adaptable" modulators of binding and allostery which are coupled to the major regulatory positions through interaction networks. Through perturbation network scanning of allosteric residue potentials in the Omicron variant complexes, which is performed in the background of the original strain, we identified that the key Omicron binding affinity hotspots N501Y and Q498R could mediate allosteric interactions and epistatic couplings. Our results suggested that the synergistic role of these hotspots in controlling stability, binding and allostery can enable for compensatory balance of fitness tradeoffs with conformationally and evolutionary adaptable immune-escape Omicron mutations. Through integrative computational approaches, this study provides a systematic analysis of the effects of Omicron mutations on thermodynamics, binding and allosteric signaling in the complexes with ACE2 receptor. The findings support a mechanism in which Omicron mutations can evolve to balance thermodynamic stability and conformational adaptability in order to ensure proper tradeoff between stability, binding and immune escape.

Rolosense: Mechanical detection of SARS-CoV-2 using a DNA-based motor

Assays detecting viral infections play a significant role in limiting the spread of diseases such as SARS-CoV-2. Here we present Rolosense, a virus sensing platform that transduces the motion of synthetic DNA-based motors transporting 5-micron particles on RNA fuel chips. Motors and chips are modified with virus-binding aptamers that lead to stalling of motion. Therefore, motors perform a "mechanical test" of viral target and stall in the presence of whole virions which represents a unique mechanism of transduction distinct from conventional assays. Rolosense can detect SARS-CoV-2 spiked in artificial saliva and exhaled breath condensate with a sensitivity of 103 copies/mL and discriminates among other respiratory viruses. The assay is modular and amenable to multiplexing, as we demonstrated one-pot detection of influenza A and SARS-CoV-2. As a proof-of-concept, we show readout can be achieved using a smartphone camera in as little as 15 mins without any sample preparation steps. Taken together, mechanical detection using Rolosense can be broadly applied to any viral target and has the potential to enable rapid, low-cost, point-of-care screening of circulating viruses.

A covalent opsonization approach to enhance synthetic immunity against viral escape variants

The sensitivity of therapeutic antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral "escape" mutations has inspired efforts to develop treatment strategies that are still effective in the face of rapidly mutating viral surface proteins. Here, we demonstrate a chemical strategy that enforces viral opsonization by natural serum antibodies. This strategy uses chimeric molecules that we call covalent viral opsonizers, which covalently label viral surface proteins, with synthetic antibody-binding ligands. As a proof of concept, we develop covalent viral opsonizers that covalently label the spike protein on SARS-CoV-2 using a "mutation-proof" small-molecule-binding ligand for anti-dinitrophenyl serum antibodies. In model assays, we observe that covalent viral opsonizers can rapidly and selectively covalently label the receptor-binding domain of both native and mutant spike proteins, leading to antibody opsonization. Opsonization mediated by this strategy is able to efficiently block the key binding domain interactions, in contrast to non-covalent analogs. We also show that covalent viral opsonizers enact targeted anti-viral phagocytotic immune function. This strategy has potential general utility for the rapid deployment of anti-viral synthetic immunotherapeutics at the onset of a new pandemic to reinforce vaccination and antibody engineering efforts.

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.

Physical-Chemical Regulation of Membrane Receptors Dynamics in Viral Invasion and Immune Defense

Mechanical cues dynamically regulate membrane receptors functions to trigger various physiological and pathological processes from viral invasion to immune defense. These cues mainly include various types of dynamic mechanical forces and the spatial confinement of plasma membrane. However, the molecular mechanisms of how they couple with biochemical cues in regulating membrane receptors functions still remain mysterious. Here, we review recent advances in methodologies of single-molecule biomechanical techniques and in novel biomechanical regulatory mechanisms of critical ligand recognition of viral and immune receptors including SARS-CoV-2 spike protein, T cell receptor (TCR) and other co-stimulatory immune receptors. Furthermore, we provide our perspectives of the general principle of how force-dependent kinetics determine the dynamic functions of membrane receptors and of biomechanical-mechanism-driven SARS-CoV-2 neutralizing antibody design and TCR engineering for T-cell-based therapies.

Piconewton forces mediate GAIN domain dissociation of the latrophilin-3 adhesion GPCR

Latrophilins are adhesion G-protein coupled receptors (aGPCRs) that control excitatory synapse formation. aGPCRs, including latrophilins, are autoproteolytically cleaved at their GPCR-Autoproteolysis Inducing (GAIN) domain, but the two resulting fragments remain associated on the cell surface. It is thought that force-mediated dissociation of the fragments exposes a peptide that activates G-protein signaling of aGPCRs, but whether GAIN domain dissociation can occur on biologically relevant timescales and at physiological forces is unknown. Here, we show using magnetic tweezers that physiological forces dramatically accelerate the dissociation of the latrophilin-3 GAIN domain. Forces in the 1-10 pN range were sufficient to dissociate the GAIN domain on a seconds-to-minutes timescale, and the GAIN domain fragments reversibly reassociated after dissociation. Thus, mechanical force may be a key driver of latrophilin signaling during synapse formation, suggesting a physiological mechanism by which aGPCRs may mediate mechanically-induced signal transduction.

Supported Natural Membranes on Microspheres for Protein-Protein Interaction Studies

Multiple biological and pathological processes, such as signaling, cell-cell communication, and infection by various viruses, occur at the plasma membrane. The eukaryotic plasma membrane is made up of thousands of different lipids, membrane proteins, and glycolipids, and its composition is dynamic and constantly changing. Due to the central importance of membranes on the one hand and their complexity on the other, membrane model systems are instrumental for interrogating membrane-related biological processes. Here, we develop a new tool for protein-membrane interaction studies. Our method is based on natural membranes obtained from extracellular vesicles. We form membrane bilayers supported on polystyrene microspheres that can be trapped and manipulated using optical tweezers. This method allows working with membrane proteins of interest within a background of native membrane components where their correct orientation is preserved. We demonstrate our method's applicability by successfully measuring the interaction forces between the Spike protein of SARS-CoV-2 and its human receptor, ACE2. We further show that these interactions are blocked by the addition of an antibody against the receptor binding domain of the Spike protein. Our approach is versatile and broadly applicable for various membrane biology and biophysics questions.

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.

Mechanosensing view of SARS-CoV-2 infection by a DNA nano-assembly

The mechanical force between a virus and its host cell plays a critical role in viral infection. However, characterization of the virus-cell mechanical force at the whole-virus level remains a challenge. Herein, we develop a platform in which the virus is anchored with multivalence-controlled aptamers to achieve transfer of the virus-cell mechanical force to a DNA tension gauge tether (Virus-TGT). When the TGT is ruptured, the complex of binding module-virus-cell is detached from the substrate, accompanied by decreased host cell-substrate adhesion, thus revealing the mechanical force between whole-virus and cell. Using Virus-TGT, direct evidence about the biomechanical force between SARS-CoV-2 and the host cell is obtained. The relative mechanical force gap (<10 pN) at the cellular level between the wild-type virus to cell and a variant virus to cell is measured, suggesting a possible positive correlation between virus-cell mechanical force and infectivity. Overall, this strategy provides a new perspective to probe the SARS-CoV-2 mechanical force.

Interdomain Linker Effect on the Mechanical Stability of Ig Domains in Titin

Titin is the largest protein in humans, composed of more than one hundred immunoglobulin (Ig) domains, and plays a critical role in muscle’s passive elasticity. Thus, the molecular design of this giant polyprotein is responsible for its mechanical function. Interestingly, most of these Ig domains are connected directly with very few interdomain residues/linker, which suggests such a design is necessary for its mechanical stability. To understand this design, we chose six representative Ig domains in titin and added nine glycine residues (9G) as an artificial interdomain linker between these Ig domains. We measured their mechanical stabilities using atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS) and compared them to the natural sequence. The AFM results showed that the linker affected the mechanical stability of Ig domains. The linker mostly reduces its mechanical stability to a moderate extent, but the opposite situation can happen. Thus, this effect is very complex and may depend on each particular domain’s property.

Integrating Conformational Dynamics and Perturbation-Based Network Modeling for Mutational Profiling of Binding and Allostery in the SARS-CoV-2 Spike Variant Complexes with Antibodies: Balancing Local and Global Determinants of Mutational Escape Mechanisms

In this study, we combined all-atom MD simulations, the ensemble-based mutational scanning of protein stability and binding, and perturbation-based network profiling of allosteric interactions in the SARS-CoV-2 spike complexes with a panel of cross-reactive and ultra-potent single antibodies (B1-182.1 and A23-58.1) as well as antibody combinations (A19-61.1/B1-182.1 and A19-46.1/B1-182.1). Using this approach, we quantify the local and global effects of mutations in the complexes, identify protein stability centers, characterize binding energy hotspots, and predict the allosteric control points of long-range interactions and communications. Conformational dynamics and distance fluctuation analysis revealed the antibody-specific signatures of protein stability and flexibility of the spike complexes that can affect the pattern of mutational escape. A network-based perturbation approach for mutational profiling of allosteric residue potentials revealed how antibody binding can modulate allosteric interactions and identified allosteric control points that can form vulnerable sites for mutational escape. The results show that the protein stability and binding energetics of the SARS-CoV-2 spike complexes with the panel of ultrapotent antibodies are tolerant to the effect of Omicron mutations, which may be related to their neutralization efficiency. By employing an integrated analysis of conformational dynamics, binding energetics, and allosteric interactions, we found that the antibodies that neutralize the Omicron spike variant mediate the dominant binding energy hotpots in the conserved stability centers and allosteric control points in which mutations may be restricted by the requirements of the protein folding stability and binding to the host receptor. This study suggested a mechanism in which the patterns of escape mutants for the ultrapotent antibodies may not be solely determined by the binding interaction changes but are associated with the balance and tradeoffs of multiple local and global factors, including protein stability, binding affinity, and long-range interactions.