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 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

In this work, we use methods and concepts of applied algebraic topology to comprehensively explore the recent idea of topological phase transitions (TPT) in complex systems. TPTs are characterized by the emergence of nontrivial homology groups as a function of a threshold parameter. Under certain conditions, one can identify TPT's via the zeros of the Euler characteristic or by singularities of the Euler entropy. Recent works provide strong evidence that TPTs can be interpreted as a complex network's intrinsic fingerprint. This work illustrates this possibility by investigating some classic network and empirical protein interaction networks under a topological perspective. We first investigate TPT in protein-protein interaction networks (PPIN) using methods of topological data analysis for two variants of the Duplication-Divergence model, namely, the totally asymmetric model and the heterodimerization model. We compare our theoretical and computational results to experimental data freely available for gene co-expression networks (GCN) of Saccharomyces cerevisiae, also known as baker's yeast, as well as of the nematode Caenorhabditis elegans. Supporting our theoretical expectations, we can detect topological phase transitions in both networks obtained according to different similarity measures. Later, we perform numerical simulations of TPTs in four classical network models: the Erdos-Renyi, the Watts-Strogatz model, the Random Geometric Graph, and the Barabasi-Albert. Finally, we discuss some perspectives and insights on the topic. Given the universality and wide use of those models across disciplines, our work indicates that TPT permeates a wide range of theoretical and empirical networks.

complex systems,Euler characteristic,topological phase transition,percolation,functional brain networks,neuroscience

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

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.

Basicity is an important parameter with impact on biological systems and technological problems. The HOMO-LUMO and FERMO theoretical approaches can describe the acid-base behavior of compounds as amines, carboxylic acids and alcohols. In this work, a method was developed using the localization degree ГFERMO parameter based on projection operators to quantify the localization of molecular orbitals. This new method was employed for the analysis of the protonation reaction of 30 organic compounds. The quantitative data from our findings were able to reproduce experimental data, pointing out that the FERMO approach could better describe the acid-base behavior of the investigated compounds.

molecular orbital, HOMO-LUMO, FERMO, Acid-base behaviour, Localization degree, ГFERMO

Current model Hamiltonians and ab initio manybody quantum treatments of π-conjugated polyradicals formed from hydrocarbons produce divergent results because of numerical complexity and large size of the basis-function set used. We propose an alternative, three-term Hamiltonian, to describe these various polyradicals that simplifies considerably the computational cost while providing a physical interpretation for all three terms and a high degree of model universality. The essential feature of this Hamiltonian is a term, not present in previous models, describing the three-sited through-bond interaction that governs the noninteracting spin-up and spin-down sectors. A computation of the lowest energy gaps and spin configurations for the smaller polyradicals demonstrates the efficacy of the model and its potential in applications in revealing electrical conductivity and ferromagnetism of the more complicated substituted polyradicals.

Based on the diagonalization of an effective Hamiltonian, we investigate the role of electronic correlation on the aromatic behavior of polycyclic aromatic hydrocarbons (PAHs). We show that for benzene and several examples of PAHs, a singular change in the electronic distribution happens at a relatively narrow range of the Coulomb interaction strength; in each case, the CC bond distribution pattern agrees with the known chemical behavior of the corresponding compound. We explore the link between electronic correlation and information entropy and show that several signatures of fluctuations in the one-particle entropy occur at the same range of values of the Coulomb parameter that correspond to a realistic bond-order distribution of the PAHs. These results indicate that the singular stability of the electronic distribution of aromatic compounds is associated with an optimum range of correlation effects, which can be understood in terms of the entanglement of the two sub-lattices of alternating carbon atoms and the presence of a localization transition of the overall electronic density.

Aromatic compounds, Model Hamiltonian, Exact diagonalization, Electronic correlation, Information entropy

Based on a quantum chemical valence formalism that allows the rigorous construction of best-localized molecular orbitals on specific parts of an extended system, we examined the separability of individual components of model systems relevant to the description of electron transport in molecular devices. We started by examining how to construct the maximally localized electronic density at the tip of a realistic model of a gold electrode. By varying the number of gold atoms included in the local region where to project the total electronic density, we quantitatively assess how many molecular orbitals are entirely localized in that region. We then considered a 1,4-benzene-di-thiol molecule connected to two model gold electrodes and examined how to localize the electronic density of the total system in the extended molecule, a fractional entity comprising the organic molecule plus an increasing number of the closest metal atoms. We were able to identify in a rigorous manner the existence of three physically different electronic populations, each one corresponding to a distinct set of molecular orbitals. First, there are those entirely localized in the extended molecule, then there is a second group of those completely distributed in the gold atoms external to that region, and, finally, there are those delocalized over the entire system. This latter group can be associated to the shared electronic population between the extended molecule and the rest of the system. We suggest that the treatment here presented could be useful in the theoretical analysis of the electronic transport in nanodevices whenever the use of localized molecular states are required by the physics of the specific problem, such as in cases of weak coupling and super-exchange limits.

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.

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