Institute of Fundamental Technological Research

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.

SARS-CoV-2, GōMartini 3, Nanomechanics, Protein complexes, protein engineering, MD, native contacts

We present a review of a series of contact maps for the determination of native interactions in proteins and nucleic acids based on a distance threshold. Such contact maps are mostly based on physical and chemical construction, and yet they are sensitive to some parameters (e.g., distances or atomic radii) and can neglect some key interactions. Furthermore, we also comment on a new class of contact maps that only requires geometric arguments. The contact map is a necessary ingredient to build a robust Gō-Martini model for proteins and their complexes in the Martini 3 force field. We present the extension of a popular structure-based Gō--like approach to the study of protein–sugar complexes, and the limitations of this approach are also discussed. The Gō-Martini approach was first introduced by Poma et al. (J. Chem. Theory Comput. 13, 1366 (2017)) in Martini 2 force field, and recently, it has gained the status of gold standard for protein simulation undergoing conformational changes in Martini 3 force field. We discuss several studies that have provided support for this approach in the context of the biophysical community.

Martini 3,Structure-based coarse-graining,SMFS,biomolecules,GoMartini

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.

SARS-Cov-2,Molecular Dynamics ,Immunity,SMFS,Nanomechanics,Free Energy,Jarzynski,Receptor,Protein complex,interfaces

coarse-grained method, machine learning, multiscale approach, biopolymers, aggregation, GōMartini approach, Martini 3, nanomechanics

We used single-molecule AFM force spectroscopy (AFM-SMFS) in combination with click chemistry to mechanically dissociate anticalin, a non-antibody protein binding scaffold, from its target (CTLA-4), by pulling from eight different anchor residues. We found that pulling on the anticalin from residue 60 or 87 resulted in significantly higher rupture forces and a decrease in koff by 2–3 orders of magnitude over a force range of 50–200 pN. Five of the six internal anchor points gave rise to complexes significantly more stable than N- or C-terminal anchor points, rupturing at up to 250 pN at loading rates of 0.1–10 nN s^–1. Anisotropic network modeling and molecular dynamics simulations helped to explain the geometric dependency of mechanostability. These results demonstrate that optimization of attachment residue position on therapeutic binding scaffolds can provide large improvements in binding strength, allowing for mechanical affinity maturation under shear stress without mutation of binding interface residues.

atomic force microscopy, protein engineering, single-molecule force spectroscopy, mechanical anisotropy, click chemistry, Go̅-Martini model, PCA

The self-assembly process of β-D-glucose oligomers on the surface of cellulose Iβ microfibril involves crystallization, and this process is analyzed herein, in terms of the length and flexibility of the oligomer chain, by means of molecular dynamics (MD) simulations. The characterization of this process involves the structural relaxation of the oligomer, the recognition of the cellulose I microfibril, and the formation of several hydrogen bonds (HBs). This process is monitored on the basis of the changes in non-bonded energies and the interaction with hydrophilic and hydrophobic crystal faces. The oligomer length is considered a parameter for capturing insight into the energy landscape and its stability in the bound form with the cellulose I microfibril. We notice that the oligomer–microfibril complexes are more stable by increasing the number of hydrogen bond interactions, which is consistent with a gain in electrostatic energy. Our studies highlight the interaction with hydrophilic crystal planes on the microfibril and the acceptor role of the flexible oligomers in HB formation. In addition, we study by MD simulation the interaction between a protofibril and the cellulose I microfibril in solution. In this case, the main interaction consists of the formation of hydrogen bonds between hydrophilic faces, and those HBs involve donor groups in the protofibril.

cellulose I, self-assembly, stability, molecular dynamics, Charmm36, β-D-glucose

High resolution data from all-atom molecular simulations is used to parameterize a Martini 3 coarse-grained (CG) model of cellulose I allomorphs and cellulose type-II fibrils. In this case, elementary molecules are represented by four effective beads centred in the positions of O2, O3, C6, and O6 atoms in the D-glucose cellulose subunit. Non-bonded interactions between CG beads are tuned according to a low statistical criterion of structural deviation using the Martini 3 type of interactions and are capable of being indistinguishable for all studied cases. To maintain the crystalline structure of each single cellulose chain in the microfibrils, elastic potentials are employed to retain the ribbon-like structure in each chain. We find that our model is capable of describing different fibril-twist angles associated with each type of cellulose fibril in close agreement with atomistic simulation. Furthermore, our CG model poses a very small deviation from the native-like structure, making it appropriate to capture large conformational changes such as those that occur during the self-assembly process. We expect to provide a computational model suitable for several new applications such as cellulose self-assembly in different aqueous solutions and the thermal treatment of fibrils of great importance in bioindustrial applications.

cellulose I allomorphs, cellulose II, Martini 3, large conformational changes, twist, molecular dynamics, coarse-grained model, aggregation

Despite an unprecedented global gain in knowledge since the emergence of SARS-CoV-2, almost all mechanistic knowledge related to the molecular and cellular details of viral replication, pathology and virulence has been generated using early prototypic isolates of SARS-CoV-2. Here, using atomic force microscopy and molecular dynamics, we investigated how these mutations quantitatively affected the kinetic, thermodynamic and structural properties of RBD—ACE2 complex formation. We observed for several variants of concern a significant increase in the RBD—ACE2 complex stability. While the N501Y and E484Q mutations are particularly important for the greater stability, the N501Y mutation is unlikely to significantly affect antibody neutralization. This work provides unprecedented atomistic detail on the binding of SARS-CoV-2 variants and provides insight into the impact of viral mutations on infection-induced immunity.

nanomechanics, stability, spike protein, antibody neutralization

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.

Amyloid beta (Aβ) oligomers are the most neurotoxic aggregates causing neuronal death and cognitive damage. A detailed elucidation of the aggregation pathways from oligomers to fibril formation is crucial to develop therapeutic strategies for Alzheimer’s disease (AD). Although experimental techniques rely on the measure of time- and space-average properties, they face severe difficulties in the investigation of Aβ peptide aggregation due to their intrinsically disorder character. Computer simulation is a tool that allows tracing the molecular motion of molecules; hence it complements Aβ experiments, as it allows to explore the binding mechanism between metal ions and Aβ oligomers close to the cellular membrane at the atomic resolution. In this context, integrated studies of experiments and computer simulations can assist in mapping the complete pathways of aggregation and toxicity of Aβ peptides. Aβ oligomers are disordered proteins, and due to a rapid exploration of their intrinsic conformational space in real-time, they are challenging therapeutic targets. Therefore, no good drug candidate could have been identified for clinical use. Our previous investigations identified two small molecules, M30 (2-Octahydroisoquinolin-2(1H)-ylethanamine) and Gabapentin, capable of Aβ binding and inhibiting molecular aggregation, synaptotoxicity, intracellular calcium signaling, cellular toxicity and memory losses induced by Aβ. Thus, we recommend these molecules as novel candidates to assist anti-AD drug discovery in the near future. This review discusses the most recent research investigations about the Aβ dynamics in water, close contact with cell membranes, and several therapeutic strategies to remove plaque formation.

Alzheimer’s disease, amyloid β peptide, plaque formation, small molecules, M30, gabapentin, MD simulation

Coarse-grained (CG) molecular dynamics (MD) simulations allow us to access much larger length and time scales than atomistic MD simulations, providing an attractive alternative to the conventional simulations. Based on the well-known MARTINI CG force field, the recently developed Gō-MARTINI model for proteins describes large-amplitude structural dynamics, which has not been possible with the commonly used elastic network model. Using the Gō-MARTINI model, we conduct MD simulations of the F-BAR Pacsin1 protein on lipid membrane. We observe that structural changes of the non-globular protein are largely dependent on the definition of the native contacts in the Gō model. To address this issue, we introduced a simple cutoff scheme and tuned the cutoff distance of the native contacts and the interaction strength of the Lennard-Jones potentials in the Gō-MARTINI model. With the optimized Gō-MARTINI model, we show that it reproduces structural fluctuations of the Pacsin1 dimer from atomistic simulations. We also show that two Pacsin1 dimers properly assemble through lateral interaction on the lipid membrane. Our work presents a first step towards describing membrane remodeling processes in the Gō-MARTINI CG framework by simulating a crucial step of protein assembly on the membrane.

Gō-MARTINI, protein complex, Pacsin, membrane remodeling, molecular dynamics, principal component analysis, RMSIP, assembly, protein contacts

The novel coronavirus disease 2019 (COVID-19) pandemic has disrupted modern societies and their economies. The resurgence in COVID-19 cases as part of the second wave is observed across Europe and the Americas. The scientific response has enabled a complete structural characterization of the Severe Acute Respiratory Syndrome—novel Coronavirus 2 (SARS-CoV-2). Among the most relevant proteins required by the novel coronavirus to facilitate the cell entry mechanism is the spike protein. This protein possesses a receptor-binding domain (RBD) that binds the cellular angiotensin-converting enzyme 2 (ACE2) and then triggers the fusion of viral and host cell membranes. In this regard, a comprehensive characterization of the structural stability of the spike protein is a crucial step to find new therapeutics to interrupt the process of recognition. On the other hand, it has been suggested that the participation of more than one RBD is a possible mechanism to enhance cell entry. Here, we discuss the protein structural stability based on the computational determination of the dynamic contact map and the energetic difference of the spike protein conformations via the mapping of the hydration free energy by the Poisson–Boltzmann method. We expect our result to foster the discussion of the number of RBD involved during recognition and the repurposing of new drugs to disable the recognition by discovering new hotspots for drug targets apart from the flexible loop in the RBD that binds the ACE2.

COVID-19, SARS-CoV-2, spike protein, RBD, structural stability, large conformational changes, protein complexes, free energy, molecular dynamics, dynamics contact analysis

We report on the novel observation about the gain in mechanical stability of the SARS-CoV-2 (CoV2) spike (S) protein in comparison with SARS-CoV from 2002 (CoV1). Our findings have several biological implications in the subfamily of coronaviruses, as they suggest that the receptor binding domain (RBD) (~200 amino acids) plays a fundamental role as a damping element of the massive viral particle's motion prior to cell-recognition, while also facilitating viral attachment, fusion and entry. The mechanical stability via pulling of the RBD is 250 pN and 200 pN for CoV2 and CoV1 respectively, and the additional stability observed for CoV2 (~50 pN) might play a role in the increasing spread of COVID-19.

Molecular simulations of large biological systems, such as viral capsids, remains a challenging task in soft matter research. On one hand, coarse-grained (CG) models attempt to make feasible the description of the entire viral capsid disassembly. On the other hand, a permanent development of novel molecular dynamics (MD) simulation approaches like enhance sampling methods attempt to overcome the large time scales required for such simulations. Those methods have a potential for delivering molecular structures and properties of biological systems. Nonetheless, exploring the process on how a viral capsid disassembles by all-atom MD simulations has been rarely attempted. Here, we propose a methodology to analyze the disassembly process of viral capsids from a free energy perspective, through an efficient combination of dynamics using coarse-grained models and Poisson-Boltzmann simulations. In particular, we look at the effect of pH and charge of the genetic material inside the capsid, and compute the free energy of a disassembly trajectory precalculated using CG simulations with the SIRAH force field. We used our multiscale approach on the Triatoma virus (TrV) as a test case, and find that even though an alkaline environment enhances the stability of the capsid, the resulting deprotonation of the genetic material generates a Coulomb-type electrostatic repulsion that triggers disassembly.

In the past two decades, the world has faced several infectious disease outbreaks. Ebola, Influenza A (H1N1), SARS, MERS, and Zika virus have had a massive global impact in terms of economic disruption, the strain on local and global public health. Most recently, the global outbreak of novel coronavirus 2019 (SARS-CoV-2) that causes COVID-19 is a newly discovered virus from the coronavirus family in Wuhan city, China, known to be a great threat to the public health systems. As of 15 April 2020, The Johns Hopkins University estimated that the COVID-19 affected more than two million people, resulting in a death toll above 130,000 around the world. Infected people in Europe and America correspond about 40% and 30% of the total reported cases respectively. At this moment only few Asian countries have controlled the disease, but a second wave of new infections is expected. Predicting inhibitor and target to the COVID-19 is an urgent need to protect human from the disease. Therefore, a protocol to identify anti-COVID-19 candidate based on computer-aided drug design is urgently needed. Thousands of compounds including approved drugs and drugs in the clinical trial are available in the literature. In practice, experimental techniques can measure the time and space average properties but they cannot be captured the structural variation of the COVID-19 during the interaction of inhibitor. Computer simulation is particularly suitable to complement experiments to elucidate conformational changes at the molecular level which are related to inhibition process of the COVID-19. Therefore, computational simulation is essential tool to elucidate the phenomenon. The structure-based virtual screening computational approach will be used to filter the best drugs from the literature, the investigate the structural variation of COVID-19 with the interaction of the best inhibitor is a fundamental step to design new drugs and vaccines which can combat the coronavirus. This mini-review will address novel coronavirus structure, mechanism of action, and trial test of antiviral drugs in the lab and patients with COVID-19.

coronavirus, computational simulation, coronavirus spike, ACE2 receptor, antiviral drugs, COVID-19

Membrane proteins, including G protein-coupled receptors (GPCRs), present a challenge in studying their structural properties under physiological conditions. Moreover, to better understand the activity of proteins requires examination of single molecule behaviors rather than ensemble averaged behaviors. Force–distance curve-based AFM (FD-AFM) was utilized to directly probe and localize the conformational states of a GPCR within the membrane at nanoscale resolution based on the mechanical properties of the receptor. FD-AFM was applied to rhodopsin, the light receptor and a prototypical GPCR, embedded in native rod outer segment disc membranes from photoreceptor cells of the retina in mice. Both FD-AFM and computational studies on coarse-grained models of rhodopsin revealed that the active state of the receptor has a higher Young's modulus compared to the inactive state of the receptor. Thus, the inactive and active states of rhodopsin could be differentiated based on the stiffness of the receptor. Differentiating the states based on the Young's modulus allowed for the mapping of the different states within the membrane. Quantifying the active states present in the membrane containing the constitutively active G90D rhodopsin mutant or apoprotein opsin revealed that most receptors adopt an active state. Traditionally, constitutive activity of GPCRs has been described in terms of two-state models where the receptor can achieve only a single active state. FD-AFM data are inconsistent with a two-state model but instead require models that incorporate multiple active states.

nanoindentation, rhodopsin, GPCR, membrane, biophysics, AFM, active, inactive, molecular dynamics, coarse graining, go-like model

We perform molecular dynamics simulation on several relevant biological fibrils associated with neurodegenerative diseases such as Aβ40, Aβ42, and α-synuclein systems to obtain a molecular understanding and interpretation of nanomechanical characterization experiments. The computational method is versatile and addresses a new subarea within the mechanical characterization of heterogeneous soft materials. We investigate both the elastic and thermodynamic properties of the biological fibrils in order to substantiate experimental nanomechanical characterization techniques that are quickly developing and reaching dynamic imaging with video rate capabilities. The computational method qualitatively reproduces results of experiments with biological fibrils, validating its use in extrapolation to macroscopic material properties. Our computational techniques can be used for the co-design of new experiments aiming to unveil nanomechanical properties of biological fibrils from a point of view of molecular understanding. Our approach allows a comparison of diverse elastic properties based on different deformations, i.e., tensile (YL), shear (S), and indentation (YT) deformation. From our analysis, we find a significant elastic anisotropy between axial and transverse directions (i.e., YT > YL) for all systems. Interestingly, our results indicate a higher mechanostability of Aβ42 fibrils compared to Aβ40, suggesting a significant correlation between mechanical stability and aggregation propensity (rate) in amyloid systems. That is, the higher the mechanical stability the faster the fibril formation. Finally, we find that α-synuclein fibrils are thermally less stable than β-amyloid fibrils. We anticipate that our molecular-level analysis of the mechanical response under different deformation conditions for the range of fibrils considered here will provide significant insights for the experimental observations.

β-amyloid, atomic force microscopy, mechanical deformation, molecular simulation, proteins, α-synuclein

The elastic network (EN) is a prime model that describes the long-time dynamics of biomolecules. However, the use of harmonic potentials renders this model insufficient for studying large conformational changes of proteins (e.g. stretching of proteins, folding and thermal unfolding). Here, we extend the capabilities of the EN model by using a harmonic approximation described by Lennard-Jones (LJ) interactions for far contacts and native contacts obtained from the standard overlap criterion as in the case of Gō-like models. While our model is validated against the EN model by reproducing the equilibrium properties for a number of proteins, we also show that the model is suitable for the study of large conformation changes by providing various examples. In particular, this is illustrated on the basis of pulling simulations that predict with high accuracy the experimental data on the rupture force of the studied proteins. Furthermore, in the case of DDFLN4 protein, our pulling simulations highlight the advantages of our model with respect to Gō-like approaches, where the latter fail to reproduce previous results obtained by all-atom simulations that predict an additional characteristic peak for this protein. In addition, folding simulations of small peptides yield different folding times for α-helix and β-hairpin, in agreement with experiment, in this way providing further opportunities for the application of our model in studying large conformational changes of proteins. In contrast to the EN model, our model is suitable for both normal mode analysis and molecular dynamics simulation. We anticipate that the proposed model will find applications in a broad range of problems in biology, including, among others, protein folding and thermal unfolding.

Free Energy, protein, elastic network, molecular dynamics, normal mode analysis

We study the mechanical response of cellulose and β-amyloid microfibrils to three types of deformation: tensile, indentational, and shear. The cellulose microfibrils correspond to the allomorphs Iα or Iβ whereas the β-amyloid microfibrils correspond to the polymorphs of either two- or three-fold symmetry. This response can be characterized by three elastic moduli, namely, YL, YT, and S. We use a structure-based coarse-grained model to analyze the deformations in a unified manner. We find that each of the moduli is almost the same for the two allomorphs of cellulose but YL is about 20 times larger than YT (140 GPa vs. 7 GPa), indicating the existence of significant anisotropy. For cellulose we note that the anisotropy results from the involvement of covalent bonds in stretching. For β-amyloid, the sense of anisotropy is opposite to that of cellulose. In the three-fold symmetry case, YL is about half of YT (3 vs. 7) whereas for two-fold symmetry the anisotropy is much larger (1.6 vs. 21 GPa). The S modulus is derived to be 1.2 GPa for three-fold symmetry and one half of it for the other symmetry and 3.0 GPa for cellulose. The values of the moduli reflect deformations in the hydrogen-bond network. Unlike in our theoretical approach, no experiment can measure all three elastic moduli with the same apparatus. However, our theoretical results are consistent with various measured values: typical YL for cellulose Iβ ranges from 133 to 155 GPa, YT from 2 to 25 GPa, and S from 1.8 to 3.8 GPa. For β-amyloid, the experimental values of S and YT are about 0.3 GPa and 3.3 GPa respectively, while the value of YL has not been reported.

Tensile, shear, indentation, Atomic Force Microscopy, amyloid, cellulose

The application of coarse-grained (CG) models in biology is essential to access large length and time scales required for the description of many biological processes. The ELNEDIN protein model is based on the well-known MARTINI CG force-field and incorporates additionally harmonic bonds of a certain spring constant within a defined cutoff distance between pairs of residues, in order to preserve the native structure of the protein. In this case, the use of unbreakable harmonic bonds hinders the study of unfolding and folding processes. To overcome this barrier we have replaced the harmonic bonds with Lennard–Jones interactions based on the contact map of the native protein structure as is done in Go̅-like models. This model exhibits very good agreement with all-atom simulations and the ELNEDIN. Moreover, it can capture the structural motion linked to particular catalytic activity in the Man5B protein, in agreement with all-atom simulations. In addition, our model is based on the van der Waals radii, instead of a cutoff distance, which results in a smaller contact map. In conclusion, we anticipate that our model will provide further possibilities for studying biological systems based on the MARTINI CG force-field by using advanced-sampling methods, such as parallel tempering and metadynamics.

Martini force field, protein, molecular simulation, stretching AFM, large conformational changes

All-atom simulations are used to derive effective parameters for a coarse-grained description of the crystalline cellulose I

Cellulose, microfibril, allomorphs, structural transition, molecular dynamics, free energy

We construct two variants of coarse-grained models of three hexaoses: one based on the centers of mass of the monomers and the other associated with the C4 atoms. The latter is found to be better defined and more suitable for studying interactions with proteins described within α-C based models. We determine the corresponding effective stiffness constants through all-atom simulations and two statistical methods. One method is the Boltzmann inversion (BI) and the other, named energy-based (EB), involves direct monitoring of energies as a function of the variables that define the stiffness potentials. The two methods are generally consistent in their account of the stiffness. We find that the elastic constants differ between the hexaoses and are noticeably different from those determined for the crystalline cellulose Iβ. The nonbonded couplings through hydrogen bonds between different sugar molecules are modeled by the Lennard-Jones potentials and are found to be stronger than the hydrogen bonds in proteins. We observe that the EB method agrees with other theoretical and experimental determinations of the nonbonded parameters much better than BI. We then consider the hexaose-Man5B catalytic complexes and determine the contact energies between their the C4−α-C atoms. These interactions are found to be stronger than the proteinic hydrogen bonds: about four times as strong for cellohexaose and two times for mannohexaose. The fluctuational dynamics of the coarse-grained complexes are found to be compatible with previous all-atom studies by Bernardi et al.

Polysaccharide, protein, principal component analysis, coarse graining, molecular simulation

We propose to improve and simplify protein refinement procedures through consideration of which pairs of amino acid residues should form native contacts. We first consider 11 330 proteins from the CATH database to determine statistical distributions of contacts associated with a given type of amino acid. The distributions are set across the distances between the α-C atoms that are in contact. Based on this data, we determine typical radii of effective spheres that can be placed on the α-C atoms in order to reconstruct the distribution of the contact lengths. This is done by checking for overlaps with enlarged van der Waals spheres associated with heavy atoms on other amino acids.The resulting contacts can be used to identify non-native contacts that may arise during the time evolution of structure-based models. Here, the radii are used to guide reconstruction of nine missing side chains in a type I cohesin domain with the Protein Data Bank code 1AOH. We first identify the likely missing contacts and then sculpt the corresponding side chains by standard refinement tools to achieve consistency with the expected contact map. One ambiguity in refinement is resolved by determining all-atom conformational energies.

Cohesin, Go-like model, protein prediction, proteins, AFM, stretching

The path integral single sweep method is used to assess quantum effects on the free energy barrier for hydrogen vacancy diffusion in a defective Na3AlH6 crystal. This process has been investigated via experiments and simulations due to its potential relevance in the H release mechanism in sodium alanates, prototypical materials for solid state hydrogen storage. Previous computational studies, which used density functional methods for the electronic structure, were restricted to a classical treatment of the nuclear degrees of freedom. We show that, although they do not change the qualitative picture of the process, nuclear quantum effects reduce the free energy barrier height by about 18% with respect to the classical calculation improving agreement with available neutron scattering data.

Alanate, proton transfer, electron hopping, Car-Parrinello MD, molecular dynamics, Free Energy, Path Integral

Simulations that couple different molecular models in an adaptive way by changing resolution on the fly allow us to identify the relevant degrees of freedom of a system. This, in turn, leads to a detailed understanding of the essential physics which characterizes a system. While the delicate process of transition from one model to another is well understood for the adaptivity between classical molecular models the same cannot be said for the quantum-classical adaptivity. The main reason for this is the difficulty in describing a continuous transition between two different kinds of physical principles: probabilistic for the quantum and deterministic for the classical. Here we report the basic principles of an algorithm that allows for a continuous and smooth transition by employing the path integral description of atoms.

path integral, classical-quantum coupling, adaptive resolution scheme, polymer ring, quantum structure

Adaptive resolution simulations for classical systems are currently made within a reasonably consistent theoretical framework. Recently we have extended this approach to the quantum-classical coupling by mapping the quantum nature of an atom onto a classical polymer ring representation within the path integral approach [Poma & Delle Site, Phys. Rev. Lett., 2010, 104, 250201]. In this way the process of interfacing adaptively a quantum representation to a classical one corresponds to the problem of interfacing two regions with a different number of effective “classical” degrees of freedom; thus the classical formulation of the adaptive algorithm applies straightforwardly to the quantum-classical problem. In this work we show the robustness of such an approach for a liquid of para-hydrogen at low temperature. This system represents a highly challenging conceptual and technical test for the adaptive approach due to the extreme thermodynamical conditions where quantum effects play a central role.

Adaptive resolution Scheme, parahydrogen, path integral, polymer ring, quantum fluid

We propose a simple method to evaluate the approximation of separation of variables in molecular dynamics (MD) and related fields. It is based on a point-by-point evaluation of the difference between the true potential and the corresponding potential where the separation of variables is applied. The major advantage of such an approach is the fact that it requires only the analytical form of the potential as provided in most of the MD codes. We provide two examples of application, namely, a diatomic molecule adsorbing on a flat surface and an alkane (aliphatic) chain.

Quality control, independent DOF, coarse graining, aliphatic chain, intramolecular

Our undeniable dependency on plastics is justified by the their technological versatility in different sectors of our societies. However, since their birth in our planet, it was noticed their lack of degradability under ambient conditions. Todays production worldwide has overcome 350 millions tonnes and this amount has created a global crisis known as the plastic pollution. We plan to show the steps towards the design of the new enzymatic paradigm for plastic degradation. Our project envision to stop the progress of the plastic pollution crisis and to make it fully part of the circular economy. Our approach will employ a rational design of novel enzymatic complex not reported before in nature in analogy as the plant cell wall degrading enzymes. The key feature of such nanomachine is the process of binding of several plastic degrading enzymes to a protein-scaffolding. It will be composed of multiple proteins that serve to integrate the enzymes and a substrate binding module. In contrast to the current paradigm free enzyme which is dominated by a non concerted degradation process, we expect our novel system to exploit the effect of having the enzymes very close to the plastic substrate and their synergy. Moreover, the modular character of our approach and the vast information in the field of hydrolases (endoglucanases) will boost the search of novel enzymes.

Plasticsome, bioengineering, molecular simulation, linker, esterase, Petase, CBM, enzyme, activity, polymer, PET

Molecular dynamics (MD) simulation is a powerful tool for revealing the underlying mechanisms governing protein mechanostability. A typical disadvantage of the all-atom representation is the use of pulling speeds several orders of magnitude higher than those employed in single- molecule force spectroscopy (SMFS). In contrast, coarse-grained (CG) representation has the advantage of reducing the computational cost at the cost of losing information on the interaction strength at protein interfaces. This effect is more pronounced in protein complexes. The GōMartini approach is analternative tool to circumvent this limitation, and in its recent implementation, it employs virtual sites near the C-alpha atom positions in the Martini 3 force field. This approach requires the determination of a contact map that includes the most relevant interactions between residues (i.e., native contacts). Large-scale applications, including mechanical stability and conformational changes, can be studied using the GōMartini. In this work, we have applied this approach to study the mechanostability associated with the immune response. Through refinement of the interaction potential between residues at the interface of the protein complex, we reproduced the results of all-atom MD and contrasted them with reported experimental values. GōMartini approach allows us to approach the speeds of atomic force microscopy (AFM) cantilevers in SMFS while preserving crucial information about the interaction between residues. This method is extremely useful in identifying the most crucial interactions that are responsible for the enhanced mechanostability in SARS-CoV-2 variants, information that can be used to develop antibodies with greater affinity.

SARS-CoV-2, immune evasion, coarse-graining, GōMartini, MD simulation, mAb, nanomechanics

Anticalin is a non-immunoglobulin protein scaffold with potential as an alternative to monoclonal antibodies for nanoparticle-based drug delivery to cells displaying cytotoxic T-lymphocyte antigen 4 (CTLA-4). In this context, one limiting factor is the resistance of the anticalin:CTLA-4 complex to mechanical forces exerted by fluid shear stress. Here, we used single-molecule AFM force spectroscopy to screen residues along the anticalin backbone and determine the optimal pulling point that achieves maximum mechanical stability of the anticalin:CTLA-4 complex. We used non-canonical amino acid incorporation by amber suppression in the anticalin combined with click chemistry to attach an Fgβ peptide at internal residues of the anticalin. We then used the Fgβ peptide as a handle to mechanically dissociate anticalin from CTLA-4 by applying tension at 8 different anchor residues, and measure the unbinding energy landscape for each pulling geometry. We found that pulling from amino acid position 60 on the anticalin resulted in ∼100% higher mechanical stability of the complex as compared with either the N- or C-terminus. Molecular dynamics (MD) simulations using the coarse-grained Martini force field showed strong agreement with experiments and help explain the mechanisms underlying the geometric dependency of mechanical stability in this therapeutic molecular complex. These results demonstrate that the mechanical stability of receptor-ligand complexes can be optimized by controlling the loading geometry without making any changes to the binding interface.

Type IV pili (T4P) are biopolymers comprised of many protein subunits called pilin. These pilin subunits are not covalently bonded to one another, however remarkably T4P filaments are very strong and flexible. T4P emanate from the surface of prokaryotic cells and are utilized for many functions, including biofilm formation, surface adhesion, motility, and infection. The recent cryo-EM based structures for T4P from Escherichia coli, Neisseria meningitidis, Pseudomonas aeruginosa, and Neisseria gonorrhoeae have provided unprecedented insights into the structures of these filaments. However, although the structures of T4P are known, the dynamics of these filaments at the molecular scale at equilibrium and under tensile forces is not well characterized. In this work we provide an overview of our research into these various T4P filaments and their constituent pilin monomers under force. Specifically we carried out steered molecular dynamics simulations using a multiscale approach encompassing all-atom simulations and two levels of coarse-grained simulation. We have analyzed the changes in secondary structure of pilin subunits, global changes in filament architecture, and calculated the Young's modulus of each of the different T4P filaments. By drawing comparisons between all of these filament systems, we are able to obtain a broader picture of T4P dynamics than experimental structures alone can provide. In particular, we observe elongation of the alpha helix region of pilin subunits in each of these systems, which has been previously attributed to T4P flexibility and strength.

filament, molecular dynamics, coarse graining, T4P

A variety of non-immunoglobulin protein scaffolds with potential as alternatives to monoclonal antibodies for nanoparticle-based drug delivery are of high interest for targeting T-cells displaying cytotoxic T-lymphocyte antigen 4 (CTLA-4), a limiting factor is the resistance of the anticalin:CTLA-4 complex to mechanical forces exerted by local shear stress. Here, we used a multi scale approach based on Go-MARTINI approach and single-molecule AFM force spectroscopy (AFM-SMFS) to screen residues along the anticalin backbone and determine the optimal anchor point that maximizes binding strength of the anticalin:CTLA-4 complex. We parametrize the Go-MARTINI approach based on the AFM_SMFS data and the molecular dynamics (MD) simulations using parametrized approach help to explain the mechanisms underlying the geometric dependency of mechanostability in the complex. This process can be related to an unzipping-shear mechanism which is commonly seen in nucleic acids strands. These results suggest that optimization of attachment residue position for therapeutic and diagnostic cargo can provide large improvements without requiring genetic mutation of binding interface residues.

Biomechanics, CTLA4-anticalin complex, SMFS, Gō-Martini, mechanostabiity, MD simulation, PCA, protein engineering

Molecular simulation of large biological systems, such as viral capsids, remains a challenging task in soft matter research. On one hand, coarse-grained (CG) models attempt to make feasible the description of the entire viral capsids. On the other hand, novel development of molecular dynamics (MD) simulation approaches, like enhance sampling which attempt to overcome the time scales required in biophysics. Those methods have a potential for delivering molecular structures and properties of biological systems. Nonetheless, exploring the process on how a capsid disassembles by all-atom MD simulations has been rarely attempted. Here, we propose a methodology to analyze the disassembly process of viral capsids quantitatively. In particular, we look at the effect of pH and charge of the genetic material inside the capsid, and compute the free energy of a disassembly trajectory by combining CG simulatiosn to a Poisson-Boltzmann solver. We employ such multiscale approach on the triatoma virus as a test case, and find that even though an alkaline environment enhances the stability of the capsid, the resulting deprotonation of the internal solvent generates an electrostatic repulsion that triggers disassembly.

Poisson Boltzmann, free energy, viral capsid, molecular dynamics, multiscale simulation, coarse graining, pH, protein assemblies

Several membrane proteins, including G protein-coupled receptors (GPCRs), present a challenge in studying their structural and dynamical properties under physiological conditions. Moreover, to better understand the activity of proteins requires examination of single molecule behaviors rather than ensemble averaged behaviors. In this work we report the Force-distance curve-based AFM (FD-AFM) which was utilized to directly probe and localize the confor- mational states of a GPCR within an artificial membrane at nanoscale resolution. We have further validated the experimental results by molecular scale coarse-grained (CG) simulations of rhodopsin biomolecules. In the past, our CG model has been applied successfully for the study of the mechanical properties of large biological assemblies such as b-amyloid and a-synuclein fibrils. Both FD-AFM experimental results and the computational force profiles revealed that the active state of the receptor has a higher Young’s modulus compared to the inactive state of the receptor. We show how the deformation of the hydrogen bond network triggers this difference and by the statistical analysis of the native contacts we highlight the underlying mechanism. Hence, the inactive and active states of rhodopsin could be differentiated based on the stiffness of the receptor. Our work paves the route towards the molecular characterization of protein states based on the Young's modulus, which is clear indication of the mechanochemical interplay of proteins within the cell membrane.

Nanomechanics, GPCR. lipids, molecular dynamics, coarse graining, Go-like model, indentation, AFM, two-state model

Atomic force microscopy (AFM) is a versatile tool to characterise the mechanical properties of biological systems. However, AFM deformations are tiny, which makes impossible the analysis of the mechanical response by experiment. Here, we have employed a simulation protocol to determine the elastic properties of several biopolymers (i.e. biological fibrils). For these systems, the simulation approach is sufficient to provide reliable values for three different types of elastic deformation, i.e. tensile (YL), shear (S), and indentation (YT). Our results enable the comparison of the mechanical properties of these fibrils. In particular, we find a significant elastic anisotropy between axial and transverse directions for all systems. In addition, our methodology is sensitive to molecular packing of the fibrils. Interestingly, our results suggest a significant correlation between mechanical stability and aggregation propensity (rate) in amyloid systems, that is, the higher the mechanical stability the faster the fibril formation takes place.

β-amyloid, α-synuclein, nanoindentation, molecular dynamics, fibril, thermodynamics, nanomechanics, coarse graining

The Elastic Network (EN) is a prime model that describes the long-time dynamics of biomolecules. However, the use of harmonic potentials renders this model insufficient for studying large conformational changes. Here, we propose a model based on the EN, a harmonic approximation described by Lennard-Jones interactions for far contacts, and Go-type native contacts obtained from the standard overlap criterion with the latter describing hydrogen bonds, ionic bridges and hydrophobic/hydrophilic interactions. Our results based on Normal Mode Analysis show excellent agreement with the EN model. Moreover, we apply large forces along the N- and C-termini in order to study a large conformational change (i.e. protein stretching), our pulling simulations reproduce the experimental data on the maximum force of the unfolding of a protein domain. We anticipate that our work will provide new venues for the EN in a broader range of problems in biology, including folding of proteins and protein-docking prediction

Protein, Biomolecules, deformation, AFM, stretching, Normal Modes