Multi-eGO: Model Improvements toward the Study of Complex Self-Assembly Processes.

Structure-based models have been instrumental in simulating protein folding and suggesting hypotheses about the mechanisms involved. Nowadays, at least for fast-folding proteins, folding can be simulated in explicit solvent using classical molecular dynamics. However, other self-assembly processes, such as protein aggregation, are still far from being accessible. Recently, we proposed that a hybrid multistate structure-based model, multi-eGO, could help to bridge the gap toward the simulation of out-of-equilibrium, concentration-dependent self-assembly processes. Here, we further improve the model and show how multi-eGO can effectively and accurately learn the conformational ensemble of the amyloid ß42 intrinsically disordered peptide, reproduce the well-established folding mechanism of the B1 immunoglobulin-binding domain of streptococcal protein G, and reproduce the aggregation as a function of the concentration of the transthyretin 105-115 amyloidogenic peptide. We envision that by learning from the dynamics of a few minima, multi-eGO can become a platform for simulating processes inaccessible to other simulation techniques.

Accurate and Efficient SAXS/SANS Implementation Including Solvation Layer Effects Suitable for Molecular Simulations.

Small-angle X-ray and neutron scattering (SAXS/SANS) provide valuable insights into the structure and dynamics of biomolecules in solution, complementing a wide range of structural techniques, including molecular dynamics simulations. As contrast-based methods, they are sensitive not only to structural properties but also to solvent-solute interactions. Their use in molecular dynamics simulations requires a forward model that should be as fast and accurate as possible. In this work, we demonstrate the feasibility of calculating SAXS and SANS intensities using a coarse-grained representation consisting of one bead per amino acid and three beads per nucleic acid, with form factors that can be corrected on the fly to account for solvation effects at no additional computational cost. By coupling this forward model with molecular dynamics simulations restrained with SAS data, it is possible to determine conformational ensembles or refine the structure and dynamics of proteins and nucleic acids in agreement with the experimental results. To assess the robustness of this approach, we applied it to gelsolin, for which we acquired SAXS data on its closed state, and to a UP1-microRNA complex, for which we used previously collected measurements. Our hybrid-resolution small-angle scattering (hySAS) implementation, being distributed in PLUMED, can be used with atomistic and coarse-grained simulations using diverse restraining strategies.

Spike mutation resilient scFv76 antibody counteracts SARS-CoV-2 lung damage upon aerosol delivery.

The uneven worldwide vaccination coverage against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and emergence of variants escaping immunity call for broadly effective and easily deployable therapeutic agents. We have previously described the human single-chain scFv76 antibody, which recognizes SARS-CoV-2 Alpha, Beta, Gamma and Delta variants. We now show that scFv76 also neutralizes the infectivity and fusogenic activity of the Omicron BA.1 and BA.2 variants. Cryoelectron microscopy (cryo-EM) analysis reveals that scFv76 binds to a well-conserved SARS-CoV-2 spike epitope, providing the structural basis for its broad-spectrum activity. We demonstrate that nebulized scFv76 has therapeutic efficacy in a severe hACE2 transgenic mouse model of coronavirus disease 2019 (COVID-19) pneumonia, as shown by body weight and pulmonary viral load data. Counteraction of infection correlates with inhibition of lung inflammation, as observed by histopathology and expression of inflammatory cytokines and chemokines. Biomarkers of pulmonary endothelial damage were also significantly reduced in scFv76-treated mice. The results support use of nebulized scFv76 for COVID-19 induced by any SARS-CoV-2 variants that have emerged so far.

Multi-eGO: An in silico lens to look into protein aggregation kinetics at atomic resolution.

Protein aggregation into amyloid fibrils is the archetype of aberrant biomolecular self-assembly processes, with more than 50 associated diseases that are mostly uncurable. Understanding aggregation mechanisms is thus of fundamental importance and goes in parallel with the structural characterization of the transient oligomers formed during the process. Oligomers have been proven elusive to high-resolution structural techniques, while the large sizes and long time scales, typical of aggregation processes, have limited the use of computational methods to date. To surmount these limitations, we here present multi-eGO, an atomistic, hybrid structure-based model which, leveraging the knowledge of monomers conformational dynamics and of fibril structures, efficiently captures the essential structural and kinetics aspects of protein aggregation. Multi-eGO molecular dynamics simulations can describe the aggregation kinetics of thousands of monomers. The concentration dependence of the simulated kinetics, as well as the structural features of the resulting fibrils, are in qualitative agreement with in vitro experiments carried out on an amyloidogenic peptide from Transthyretin, a protein responsible for one of the most common cardiac amyloidoses. Multi-eGO simulations allow the formation of primary nuclei in a sea of transient lower-order oligomers to be observed over time and at atomic resolution, following their growth and the subsequent secondary nucleation events, until the maturation of multiple fibrils is achieved. Multi-eGO, combined with the many experimental techniques deployed to study protein aggregation, can provide the structural basis needed to advance the design of molecules targeting amyloidogenic diseases.

Disordered Regions Flanking the Binding Interface Modulate Affinity between CBP and NCOA.

Recognition motifs that mediate protein-protein interactions are usually embedded within longer intrinsically disordered regions. While binding interfaces involving the recognition motif in such interactions are well studied, less is known about the role of disordered regions flanking the motifs. The interaction between the transcriptional co-activators NCOA3 (ACTR) and CBP is mediated by coupled binding and folding of the two domains CID and NCBD. Here, we used circular dichroism and kinetics to directly quantify the contribution of the adjacent flanking regions of CID to its interaction with NCBD. Using N- and C-terminal combinatorial variants we found that the flanking regions promote binding in an additive fashion while retaining a large degree of disorder in the complex. Experiments at different ionic strengths demonstrated that the increase in affinity is not mediated by electrostatic interactions from the flanking regions. Instead, site-directed mutagenesis and molecular dynamics simulations suggest that binding is promoted by short-lived non-specific hydrophobic contacts between the flanking regions and NCBD. Our findings are consistent with highly frustrated interactions outside of the canonical binding interface resulting in a slightly energetically favorable fuzzy binding. Modulation of affinity via flanking regions could represent a general mechanism for functional regulation by intrinsically disordered protein regions.

l- to d-Amino Acid Substitution in the Immunodominant LCMV-Derived Epitope gp33 Highlights the Sensitivity of the TCR Recognition Mechanism for the MHC/Peptide Structure and Dynamics.

Presentation of pathogen-derived epitopes by major histocompatibility complex I (MHC-I) can lead to the activation and expansion of specific CD8+ T cell clones, eventually resulting in the destruction of infected target cells. Altered peptide ligands (APLs), designed to elicit immunogenicity toward a wild-type peptide, may affect the overall stability of MHC-I/peptide (pMHC) complexes and modulate the recognition by T cell receptors (TCR). Previous works have demonstrated that proline substitution at position 3 (p3P) of different MHC-restricted epitopes, including the immunodominant LCMV-derived epitope gp33 and escape variants, may be an effective design strategy to increase epitope immunogenicity. These studies hypothesized that the p3P substitution increases peptide rigidity, facilitating TCR binding. Here, molecular dynamics simulations indicate that the p3P modification rigidifies the APLs in solution predisposing them for the MHC-I loading as well as once bound to H-2Db, predisposing them for TCR binding. Our results also indicate that peptide position 6, key for interaction of H-2Db/gp33 with the TCR P14, takes a suboptimal conformation before as well as after binding to the TCR. Analyses of H-2Db in complex with APLs, in which position 6 was subjected to an l- to d-amino acid modification, revealed small conformational changes and comparable pMHC thermal stability. However, the l- to d-modification reduced significantly the binding to P14 even in the presence of the p3P modification. Our combined data highlight the sensitivity of the TCR for the conformational dynamics of pMHC and provide further tools to dissect and modulate TCR binding and immunogenicity via APLs.

High Conformational Flexibility of the E2F1/DP1/DNA Complex.

The E2F1 transcription factor is a master regulator of cell-cycle progression whose uncontrolled activation contributes to tumor cells growth. E2F1 binds DNA as a heterodimer with DP partners, resulting in a multi-domain quaternary-structure complex composed of DNA binding domains, a coiled coil domain and a marked box domain separated by short linkers. Building on the 3D knowledge of the single domains of E2F and DPs, we characterized the structure and dynamics of the complete E2F1/DP1/DNA complex by a combination of small-angle X-ray scattering and molecular dynamics simulations. It shows an asymmetric contribution of the dynamics of the two proteins. Namely, the coiled-coil domain leans toward the DP1 side of the complex; the DP1 loop between α2 and α3 of the DBD partially populates a helical structure leaning far from the DNA and in the same direction of the coiled-coil domain; and the N-terminal disordered region of DP1, rich in basic residues, contributes to DNA binding stabilization. Intriguingly, tumor mutations in the flexible regions of the complex suggest that perturbation of protein dynamics could affect protein function in a context-dependent way. Our data suggest fundamental contributions of DP proteins in distinct aspects of E2F biology.

How to Determine Accurate Conformational Ensembles by Metadynamics Metainference: A Chignolin Study Case.

The reliability and usefulness of molecular dynamics simulations of equilibrium processes rests on their statistical precision and their capability to generate conformational ensembles in agreement with available experimental knowledge. Metadynamics Metainference (M&M), coupling molecular dynamics with the enhanced sampling ability of Metadynamics and with the ability to integrate experimental information of Metainference, can in principle achieve both goals. Here we show that three different Metadynamics setups provide converged estimate of the populations of the three-states populated by a model peptide. Errors are estimated correctly by block averaging, but higher precision is obtained by performing independent replicates. One effect of Metadynamics is that of dramatically decreasing the number of effective frames resulting from the simulations and this is relevant for M&M where the number of replicas should be large enough to capture the conformational heterogeneity behind the experimental data. Our simulations allow also us to propose that monitoring the relative error associated with conformational averaging can help to determine the minimum number of replicas to be simulated in the context of M&M simulations. Altogether our data provides useful indication on how to generate sound conformational ensemble in agreement with experimental data.

Converging experimental and computational views of the knotting mechanism of a small knotted protein.

MJ0366 from Methanocaldococcus jannaschii is the smallest topologically knotted protein known to date. 92 residues in length, MJ0366 ties a trefoil (31) knot by threading its C-terminal helix through a buttonhole formed by the remainder of the secondary structure elements. By generating a library of point mutations at positions pertinent to the knot formation, we systematically evaluated the contributions of individual residues to the folding stability and kinetics of MJ0366. The experimental Φ-values were used as restraints to computationally generate an ensemble of conformations that correspond to the transition state of MJ0366, which revealed several nonnative contacts. The importance of these nonnative contacts in stabilizing the transition state of MJ0366 was confirmed by a second round of mutagenesis, which also established the pivotal role of F15 in stapling the network of hydrophobic interactions around the threading C-terminal helix. Our converging experimental and computational results show that, despite the small size, the transition state of MJ0366 is formed at a very late stage of the folding reaction coordinate, following a polarized pathway. Eventually, the formation of extensive native contacts, as well as a number of nonnative ones, leads to the threading of the C-terminal helix that defines the topological knot.

The dynamics of linear polyubiquitin.

Polyubiquitin chains are flexible multidomain proteins, whose conformational dynamics enable them to regulate multiple biological pathways. Their dynamic is determined by the linkage between ubiquitins and by the number of ubiquitin units. Characterizing polyubiquitin behavior as a function of their length is hampered because of increasing system size and conformational variability. Here, we introduce a new approach to efficiently integrating small-angle x-ray scattering with simulations allowing us to accurately characterize the dynamics of linear di-, tri-, and tetraubiquitin in the free state as well as of diubiquitin in complex with NEMO, a central regulator in the NF-κB pathway. Our results show that the behavior of the diubiquitin subunits is independent of the presence of additional ubiquitin modules and that the dynamics of polyubiquitins with different lengths follow a simple model. Together with experimental data from multiple biophysical techniques, we then rationalize the 2:1 NEMO:polyubiquitin binding.

Determination of Protein Structural Ensembles by Hybrid-Resolution SAXS Restrained Molecular Dynamics.

Small-angle X-ray scattering (SAXS) experiments provide low-resolution but valuable information about the dynamics of biomolecular systems, which could be ideally integrated into molecular dynamics (MD) simulations to accurately determine conformational ensembles of flexible proteins. The applicability of this strategy is hampered by the high computational cost required to calculate scattering intensities from three-dimensional structures. We previously presented a hybrid resolution method that makes atomistic SAXS-restrained MD simulation feasible by adopting a coarse-grained approach to efficiently back-calculate scattering intensities; here, we extend this technique, applying it in the framework of metainference with the aim to investigate the dynamical behavior of flexible biomolecules. The efficacy of the method is assessed on the K63-diubiquitin, showing that the inclusion of SAXS restraints is effective in generating a reliable conformational ensemble, improving the agreement with independent experimental data.

Mapping the transition state for a binding reaction between ancient intrinsically disordered proteins.

Intrinsically disordered protein domains often have multiple binding partners. It is plausible that the strength of pairing with specific partners evolves from an initial low affinity to a higher affinity. However, little is known about the molecular changes in the binding mechanism that would facilitate such a transition. We previously showed that the interaction between two intrinsically disordered domains, NCBD and CID, likely emerged in an ancestral deuterostome organism as a low-affinity interaction that subsequently evolved into a higher-affinity interaction before the radiation of modern vertebrate groups. Here we map native contacts in the transition states of the low-affinity ancestral and high-affinity human NCBD/CID interactions. We show that the coupled binding and folding mechanism is overall similar but with a higher degree of native hydrophobic contact formation in the transition state of the ancestral complex and more heterogeneous transient interactions, including electrostatic pairings, and an increased disorder for the human complex. Adaptation to new binding partners may be facilitated by this ability to exploit multiple alternative transient interactions while retaining the overall binding and folding pathway.

Cryo-EM structure of cardiac amyloid fibrils from an immunoglobulin light chain AL amyloidosis patient.

Systemic light chain amyloidosis (AL)  is a life-threatening disease caused by aggregation and deposition of monoclonal immunoglobulin light chains (LC) in target organs. Severity of heart involvement is the most important factor determining prognosis. Here, we report the 4.0 Å resolution cryo-electron microscopy map and molecular model of amyloid fibrils extracted from the heart of an AL amyloidosis patient with severe amyloid cardiomyopathy. The helical fibrils are composed of a single protofilament, showing typical 4.9 Å stacking and cross-ß architecture. Two distinct polypeptide stretches (total of 77 residues) from the LC variable domain (Vl) fit the fibril density. Despite Vl high sequence variability, residues stabilizing the fibril core are conserved through different cardiotoxic Vl, highlighting structural motifs that may be common to misfolding-prone LCs. Our data shed light on the architecture of LC amyloids, correlate amino acid sequences with fibril assembly, providing the grounds for development of innovative medicines.

Succinimide-Based Conjugates Improve IsoDGR Cyclopeptide Affinity to αvß3 without Promoting Integrin Allosteric Activation.

The isoDGR sequence is an integrin-binding motif that has been successfully employed as a tumor-vasculature-homing molecule or for the targeted delivery of drugs and diagnostic agents to tumors. In this context, we previously demonstrated that cyclopeptide 2, the product of the conjugation of c(CGisoDGRG) (1) to 4-( N-maleimidomethyl)cyclohexane-1-carboxamide, can be successfully used as a tumor-homing ligand for nanodrug delivery to neoplastic tissues. Here, combining NMR, computational, and biochemical methods, we show that the succinimide ring contained in 2 contributes to stabilizing interactions with αvß3, an integrin overexpressed in the tumor vasculature. Furthermore, we demonstrate that various cyclopeptides containing the isoDGR sequence embedded in different molecular scaffolds do not induce αvß3 allosteric activation and work as pure integrin antagonists. These results could be profitably exploited for the rational design of novel isoDGR-based ligands and tumor-targeting molecules with improved αvß3-binding properties and devoid of adverse integrin-activating effects.

Metadynamics Simulations Rationalise the Conformational Effects Induced by N-Methylation of RGD Cyclic Hexapeptides.

We combined metadynamics, docking and molecular mechanics/generalised born surface area (MM/GBSA) re-scoring methods to investigate the impact of single and multiple N-methylation on a set of RGD cyclopeptides displaying different affinity for integrin αIIbß3. We rationalised the conformational effects induced by N-methylation and its interplay with receptor affinity, obtaining good agreement with experimental data. This approach can be exploited before entering time-consuming and expensive synthesis and binding experiments.

Iterative derivation of effective potentials to sample the conformational space of proteins at atomistic scale.

The current capacity of computers makes it possible to perform simulations of small systems with portable, explicit-solvent potentials achieving high degree of accuracy. However, simplified models must be employed to exploit the behavior of large systems or to perform systematic scans of smaller systems. While powerful algorithms are available to facilitate the sampling of the conformational space, successful applications of such models are hindered by the availability of simple enough potentials able to satisfactorily reproduce known properties of the system. We develop an interatomic potential to account for a number of properties of proteins in a computationally economic way. The potential is defined within an all-atom, implicit solvent model by contact functions between the different atom types. The associated numerical values can be optimized by an iterative Monte Carlo scheme on any available experimental data, provided that they are expressible as thermal averages of some conformational properties. We test this model on three different proteins, for which we also perform a scan of all possible point mutations with explicit conformational sampling. The resulting models, optimized solely on a subset of native distances, not only reproduce the native conformations within a few Angstroms from the experimental ones, but show the cooperative transition between native and denatured state and correctly predict the measured free-energy changes associated with point mutations. Moreover, differently from other structure-based models, our method leaves a residual degree of frustration, which is known to be present in protein molecules.