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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.

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- e GO, 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- e GO 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- e GO 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- e GO, 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.

The stabilization of native states of proteins is a powerful drug discovery strategy. It is still unclear, however, whether this approach can be applied to intrinsically disordered proteins. Here, we report a small molecule that stabilizes the native state of the Aβ42 peptide, an intrinsically disordered protein fragment associated with Alzheimer's disease. We show that this stabilization takes place by a disordered binding mechanism, in which both the small molecule and the Aβ42 peptide remain disordered. This disordered binding mechanism involves enthalpically favorable local π-stacking interactions coupled with entropically advantageous global effects. These results indicate that small molecules can stabilize disordered proteins in their native states through transient non-specific interactions that provide enthalpic gain while simultaneously increasing the conformational entropy of the proteins.

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.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Protein aggregation into amyloid fibrils is the archetype of aberrant biomolecular self-assembly processes, with more than 50 diseases associated that are mostly uncurable. Understanding aggregation mechanisms is thus of fundamental importance and goes in parallel with the characterization of the structures of the transient oligomers formed in 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, so far, the use of computational methods. To surmount these limitations, we introduce here multi-eGO, an atomistic, hybrid structure-based model, which leveraging on the knowledge of monomers conformational dynamics and of fibril structures, can efficiently capture 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 on an amyloidogenic peptide of Transthyretin, a protein responsible for one of the most common cardiac amyloidosis. Multi-eGO simulations allow to observe in time and at atomic resolution the formation of primary nuclei in a sea of transient lower order oligomers, to follow their growth and the subsequent secondary nucleation events, till the maturation of multiple fibrils. 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.Significance StatementAlzheimer’s and Parkinson’s diseases are uncurable pathologies associated to the aberrant aggregation of specific proteins into amyloid fibrils. Understanding the mechanism leading to protein aggregation, by characterizing the structures of the oligomeric species populated in the process, would have a tremendous impact on the design of therapeutic molecules. We propose that a structure-based approach to molecular dynamics simulations can allow following at high resolution the aggregation kinetics of thousands of monomers. Having shown that simulations can describe the aggregation of a Transthyretin amyloidogenic peptide, we demonstrate how their efficiency allows acquiring a wealth of structural information. We foresee that integrating the latter with the many techniques developed to study protein aggregation will support the design of molecules to modulate amyloidogenesis.

In Crohn's disease (CD) patients, the adherent-invasive

Presentation of pathogen-derived epitopes by major histocompatibility complex I (MHC-I) can lead to the activation and expansion of specific CD8

The stabilisation of native states of proteins is a powerful drug discovery strategy. It is still unclear, however, whether this approach can be applied to intrinsically disordered proteins. Here we report a small molecule that stabilises the native state of the Aβ42 peptide, an intrinsically disordered protein fragment associated with Alzheimer’s disease. We show that this stabilisation takes place by a dynamic binding mechanism, in which both the small molecule and the Aβ42 peptide remain disordered. This disordered binding mechanism involves enthalpically favourable local π-stacking interactions coupled with entropically advantageous global effects. These results indicate that small molecules can stabilise disordered proteins in their native states through transient non-specific interactions that provide enthalpic gain while simultaneously increasing the conformational entropy of the proteins.

Bacterial NADPH-dependent glutamate synthase (GltS) is a complex iron-sulfur flavoprotein that catalyzes the reductive synthesis of two L-Glu molecules from L-Gln and 2-oxo-glutarate. GltS functional unit hosts an α-subunit (αGltS) and a β-subunit (βGltS) that assemble in different αβ oligomers in solution. Here, we present the cryo-electron microscopy structures of Azospirillum brasilense GltS in four different oligomeric states (α4β3, α4β4, α6β4 and α6β6, in the 3.5- to 4.1-A resolution range). Our study provides a comprehensive GltS model that details the inter-protomeric assemblies and allows unequivocal location of the FAD cofactor and of two electron transfer [4Fe-4S]+1,+2 clusters within βGltS.

Frontiers in molecular biosciences 8, 654333 (1-13) (2021). doi:10.3389/fmolb.2021.654333, The inherent flexibility of intrinsically disordered proteins (IDPs) makes it difficult to interpret experimental data using structural models. On the other hand, molecular dynamics simulations of IDPs often suffer from force-field inaccuracies, and long simulation times or enhanced sampling methods are needed to obtain converged ensembles. Here, we apply metainference and Bayesian/Maximum Entropy reweighting approaches to integrate prior knowledge of the system with experimental data, while also dealing with various sources of errors and the inherent conformational heterogeneity of IDPs. We have measured new SAXS data on the protein ��-synuclein, and integrate this with simulations performed using different force fields. We find that if the force field gives rise to ensembles that are much more compact than what is implied by the SAXS data it is difficult to recover a reasonable ensemble. On the other hand, we show that when the simulated ensemble is reasonable, we can obtain an ensemble that is consistent with the SAXS data, but also with NMR diffusion and paramagnetic relaxation enhancement data., Published by Frontiers, Lausanne

MJ0366 from Methanocaldococcus jannaschii is the smallest topologically knotted protein known to date. 92 residues in length, MJ0366 ties a trefoil (3(1)) 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.

NF-Y is a transcription factor (TF) comprising three subunits (NF-YA, NF-YB, NF-YC) that binds with high specificity to the CCAAT sequence, a widespread regulatory element in gene promoters of prosurvival, cell-cycle-promoting, and metabolic genes. Tumor cells undergo &ldquo, metabolic rewiring&rdquo, through overexpression of genes involved in such pathways, many of which are under NF-Y control. In addition, NF-YA appears to be overexpressed in many tumor types. Thus, limiting NF-Y activity may represent a desirable anti-cancer strategy, which is an ongoing field of research. With virtual-screening docking simulations on a library of pharmacologically active compounds, we identified suramin as a potential NF-Y inhibitor. We focused on suramin given its high water-solubility that is an important factor for in vitro testing, since NF-Y is sensitive to DMSO. By electrophoretic mobility shift assays (EMSA), isothermal titration calorimetry (ITC), STD NMR, X-ray crystallography, and molecular dynamics (MD) simulations, we showed that suramin binds to the histone fold domains (HFDs) of NF-Y, preventing DNA-binding. Our analyses, provide atomic-level detail on the interaction between suramin and NF-Y and reveal a region of the protein, nearby the suramin-binding site and poorly conserved in other HFD-containing TFs, that may represent a promising starting point for rational design of more specific and potent inhibitors with potential therapeutic applications.

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.

The use of small-angle X-ray scattering (SAXS) in combination with molecular dynamics simulation is hampered by its heavy computational cost. The calculation of SAXS from atomic structures can be speeded up by using a coarse-grain representation of the structure. Following the work of Niebling, Björling & Westenhoff [J. Appl. Cryst. (2014), 47, 1190–1198], the Martini bead form factors for nucleic acids have been derived and then implemented, together with those previously determined for proteins, in the publicly available PLUMED library. A hybrid multi-resolution strategy has also been implemented to perform SAXS restrained simulations at atomic resolution by calculating the virtual positions of the Martini beads on the fly and using them for the calculation of SAXS. The accuracy and efficiency of the method are demonstrated by refining the structure of two protein–nucleic acid complexes. Instrumental for this result is the use of metainference, which allows the consideration and alleviation of the approximations at play in the present SAXS calculations.

The discovery that disordered proteins are widespread in the human proteome has prompted the quest for methods to characterize the conformational properties that determine their functional and dysfunctional behaviour. It has become customary to describe these proteins in terms of structural ensembles and free energy landscapes, which offer conformational and thermodynamic insight. However, a current major challenge is to generalize this description to ‘kinetic ensembles’, thereby also providing information on transition rates between states. Approaches based on the theory of stochastic processes can be particularly suitable for this purpose. Here, we develop a Markov state model and illustrate its application by determining a kinetic ensemble of the 42-residue form of the amyloid-β peptide (Aβ42), whose aggregation is associated with Alzheimer’s disease. Using the Google Compute Engine, we generated 315 μs all-atom, explicit solvent molecular dynamics trajectories, validated with experimental data from nuclear magnetic resonance spectroscopy. Using a probabilistic-based definition of conformational states in a neural network approach, we found that Aβ42 is characterized by inter-state transitions no longer than the microsecond timescale, exhibiting only fully unfolded or short-lived, partially-folded states. We contextualize our findings by performing additional simulations of the oxidized form of Aβ42. Our results illustrate how the use of kinetic ensembles offers an effective means to provide information about the structure, thermodynamics, and kinetics of disordered proteins towards an understanding of these ubiquitous biomolecules.

Poly-ubiquitin chains are flexible multidomain proteins, whose conformational dynamics enable their molecular recognition by a large number of partners in multiple biological pathways. By using alternative linkage, it is possible to obtain poly-ubiquitin molecules with different dynamical properties. This flexibility is further increased by the possibility to tune the length of poly-ubiquitin chains. Characterizing the dynamics of poly-ubiquitins as a function of their length is thus relevant to understand their biology. Structural characterization of poly-ubiquitin conformational dynamics is challenging both experimentally and computationally due to increasing system size and conformational variability. Here, by developing highly efficient and accurate small-angle X-ray scattering driven Martini coarse-grain simulations, we characterize the dynamics of linear M1-linked di-, tri- and tetra-ubiquitin chains. Our data show that the behavior of the di-ubiquitin subunits is independent of the presence of additional ubiquitin modules. We propose that the conformational space sampled by linear poly-ubiquitins, in general, may follow a simple self-avoiding polymer model. These results, combined with experimental data from small angle X-ray scattering, biophysical techniques and additional simulations show that binding of NEMO, a central regulator in the NF-κB pathway, to linear poly-ubiquitin obeys a 2:1 (NEMO:poly-ubiquitin) stoichiometry in solution, even in the context of four ubiquitin units. Eventually, we show how the conformational properties of long poly-ubiquitins may modulate the binding with their partners in a length-dependent manner.SignificanceProtein conformational dynamics plays an essential role in molecular recognition mechanisms. The characterization of conformational dynamics is hampered by the conformational averaging of observable in experimental structural biology techniques and by the limitations in the accuracy of computational methods. By developing an efficient and accurate approach to combine small-angle X-ray scattering solution experiments and coarse-grain Martini simulations, we show that the conformational dynamics of linear poly-ubiquitins can be efficiently determined and to rationalize the role of poly-ubiquitin dynamic in the molecular recognition of the UBAN domain upon binding to the signaling regulator NEMO. The analysis of the conformational ensembles allows us to propose a general model of the dynamics of linear poly-ubiquitin chains where they can be described as a self-avoiding polymer with a characteristic length associated with their specific linkage.

Significance Efficient synthesis and folding of proteins, avoiding misfolded states, are central to cell function. As folding may be initiated in parallel with translation, key experimental challenges are to map changes that occur in folding free energy landscapes as translation proceeds and to understand how these landscapes might be modulated by the ribosome and auxiliary factors. Here, we study the length-dependent folding of a domain from a tandem repeat protein and solve the structure of a stable folding intermediate. Although destabilized by the ribosome at equilibrium, modeling of the nonequilibrium folding pathway nevertheless indicates a significant role for proline isomerization during translation. We develop a simple model to explore the impact of cotranslational folding kinetics on misfolding hazards., Cotranslational folding (CTF) is a fundamental molecular process that ensures efficient protein biosynthesis and minimizes the formation of misfolded states. However, the complexity of this process makes it extremely challenging to obtain structural characterizations of CTF pathways. Here, we correlate observations of translationally arrested nascent chains with those of a systematic C-terminal truncation strategy. We create a detailed description of chain length-dependent free energy landscapes associated with folding of the FLN5 filamin domain, in isolation and on the ribosome, and thus, quantify a substantial destabilization of the native structure on the ribosome. We identify and characterize two folding intermediates formed in isolation, including a partially folded intermediate associated with the isomerization of a conserved cis proline residue. The slow folding associated with this process raises the prospect that neighboring unfolded domains might accumulate and misfold during biosynthesis. We develop a simple model to quantify the risk of misfolding in this situation and show that catalysis of folding by peptidyl-prolyl isomerases is sufficient to eliminate this hazard.

Proteins employ the information stored in the genetic code and translated into their sequences to carry out well-defined functions in the cellular environment. The possibility to encode for such functions is controlled by the balance between the amount of information supplied by the sequence and that left after that the protein has folded into its structure. We developed a computational algorithm to evaluate the amount of information necessary to specify the protein structure, keeping into account the thermodynamic properties of protein folding. We thus show that the information remaining in the protein sequence after encoding for its structure (the 'information gap') is very close to what needed to encode for its function and interactions. Then, by predicting the information gap directly from the protein sequence, we show that it may be possible to use these insights from information theory to discriminate between ordered and disordered proteins, to identify unknown functions, and to optimize designed proteins sequences.

Small molecules with rotatable bonds can occupy different conformational states in solution as a consequence of their thermal fluctuations. The accurate determination of the structures of such states, as well as of their statistical weights, has been challenging because of the technical difficulties in extracting information from experimental measurements, which are normally averaged over the conformational space available. Here, to achieve this objective, we present an approach based on a recently proposed tensor-free method for incorporating NMR residual dipolar couplings as structural restraints in replica-averaged molecular dynamics simulations. This approach enables the information provided by the experimental data to be used in the spirit of the maximum entropy principle to determine the structural ensembles of small molecules. Furthermore, in order to enhance the sampling of the conformational space we incorporated the metadynamics method in the simulations. We illustrate the method in the case of strychnine, determining the three major conformational states of this small molecule and their associated occupation probabilities.

The PLUMED consortium unifies developers and contributors to PLUMED, an open-source library for enhanced-sampling, free-energy calculations and the analysis of molecular dynamics simulations. Here, we outline our efforts to promote transparency and reproducibility by disseminating protocols for enhanced-sampling molecular simulations.

The nucleation-condensation mechanism represents a major paradigm to understand the folding process of many small globular proteins. Although substantial evidence has been acquired for this mechanism, it has remained very challenging to characterize the initial events leading to the formation of a folding nucleus. To achieve this goal, we used a combination of relaxation dispersion NMR spectroscopy and molecular dynamics simulations to determine ensembles of conformations corresponding to the denatured, transition, and native states in the folding of the activation domain of human procarboxypeptidase A2 (ADA2h). We found that the residues making up the folding nucleus tend to interact in the denatured state in a transient manner and not simultaneously, thereby forming incomplete and distorted versions of the folding nucleus. Only when all the contacts between these key residues are eventually formed can the protein reach the transition state and continue folding. Overall, our results elucidate the mechanism of formation of the folding nucleus of a protein and provide insights into how its folding rate can be modified during evolution by mutations that modulate the strength of the interactions between the residues forming the folding nucleus.

SAXS experiments provide low-resolution but valuable information about the dynamics of biomolecular systems, which could be ideally integrated into 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.

Designed peptides derived from the islet amyloid polypeptide (IAPP) cross‐amyloid interaction surface with Aβ (termed interaction surface mimics or ISMs) have been shown to be highly potent inhibitors of Aβ amyloid self‐assembly. However, the molecular mechanism of their function is not well understood. Using solution‐state and solid‐state NMR spectroscopy in combination with ensemble‐averaged dynamics simulations and other biophysical methods including TEM, fluorescence spectroscopy and microscopy, and DLS, we characterize ISM structural preferences and interactions. We find that the ISM peptide R3‐GI is highly dynamic, can adopt a β‐like structure, and oligomerizes into colloid‐like assemblies in a process that is reminiscent of liquid–liquid phase separation (LLPS). Our results suggest that such assemblies yield multivalent surfaces for interactions with Aβ40. Sequestration of substrates into these colloid‐like structures provides a mechanistic basis for ISM function and the design of novel potent anti‐amyloid molecules., ISM inhibitors are highly dynamic assemblies and exchange between monomeric and high‐molecular‐weight states. In both states, the ISM peptide adopts a β‐loop‐like structure that provides a suitable surface for sequestration of Aβ40 in the colloidal state. ISM inhibitors thus exploit multivalency by self‐association to yield high substrate avidity.

Accurate protein structural ensembles can be determined with metainference, a Bayesian inference method that integrates experimental information with prior knowledge of the system and deals with all sources of uncertainty and errors as well as with system heterogeneity. Furthermore, metainference can be implemented using the metadynamics approach, which enables the computational study of complex biological systems requiring extensive conformational sampling. In this chapter, we provide a step-by-step guide to perform and analyse metadynamic metainference simulations using the ISDB module of the open-source PLUMED library, as well as a series of practical tips to avoid common mistakes. Specifically, we will guide the reader in the process of learning how to model the structural ensemble of a small disordered peptide by combining state-of-the-art molecular mechanics force fields with nuclear magnetic resonance data, including chemical shifts, scalar couplings and residual dipolar couplings.

Many protein systems rely on coupled dynamic networks to allosterically regulate function. However, the broad conformational space sampled by non-coherently dynamic systems has precluded detailed analysis of their communication mechanisms. Here, we have developed a methodology that combines the high sensitivity afforded by nuclear magnetic resonance relaxation techniques and single-site multiple mutations, termed RASSMM, to identify two allosterically coupled dynamic networks within the non-coherently dynamic enzyme cyclophilin A. Using this methodology, we discovered two key hotspot residues, Val6 and Val29, that communicate through these networks, the mutation of which altered active-site dynamics, modulating enzymatic turnover of multiple substrates. Finally, we utilized molecular dynamics simulations to identify the mechanism by which one of these hotspots is coupled to the larger dynamic networks. These studies confirm a link between enzyme dynamics and the catalytic cycle of cyclophilin A and demonstrate how dynamic allostery may be engineered to tune enzyme function.

The interaction of the HIV-1 protein transactivator of transcription (Tat) and its cognate transactivation response element (TAR) RNA transactivates viral transcription and represents a paradigm for the widespread occurrence of conformational rearrangements in protein-RNA recognition. Although the structures of free and bound forms of TAR are well characterized, the conformations of the intermediates in the binding process are still unknown. By determining the free energy landscape of the complex using NMR residual dipolar couplings in replica-averaged metadynamics simulations, we observe two low-population intermediates. We then rationally design two mutants, one in the protein and another in the RNA, that weaken specific nonnative interactions that stabilize one of the intermediates. By using surface plasmon resonance, we show that these mutations lower the release rate of Tat, as predicted. These results identify the structure of an intermediate for RNA-protein binding and illustrate a general strategy to achieve this goal with high resolution.

The ribosome is increasingly becoming recognized as a key hub for integrating quality control processes associated with protein biosynthesis and cotranslational folding (CTF). The molecular mechanisms by which these processes take place, however, remain largely unknown, in particular in the case of intrinsically disordered proteins (IDPs). To address this question, we studied at a residue-specific level the structure and dynamics of ribosome-nascent chain complexes (RNCs) of α-synuclein (αSyn), an IDP associated with Parkinson's disease (PD). Using solution-state nuclear magnetic resonance (NMR) spectroscopy and coarse-grained molecular dynamics (MD) simulations, we find that, although the nascent chain (NC) has a highly disordered conformation, its N-terminal region shows resonance broadening consistent with interactions involving specific regions of the ribosome surface. We also investigated the effects of the ribosome-associated molecular chaperone trigger factor (TF) on αSyn structure and dynamics using resonance broadening to define a footprint of the TF-RNC interactions. We have used these data to construct structural models that suggest specific ways by which emerging NCs can interact with the biosynthesis and quality control machinery.

Here a differential geometry (DG) representation of protein backbone is explored on the analyses of protein conformational ensembles. The protein backbone is described by curvature, κ, and torsion, τ, values per residue and we propose 1) a new dissimilarity and protein flexibility measurement and 2) a local conformational clustering method. The methods were applied to Ubiquitin and c-Myb-KIX protein conformational ensembles and results show that κ\τ metric space allows to properly judge protein flexibility by avoiding the superposition problem. The dmax measurement presents equally good or superior results when compared to RMSF, especially for the intrinsically unstructured protein. The clustering method is unique as it relates protein global to local dynamics by providing a global clustering solutions per residue. The methods proposed can be especially useful to the analyses of highly flexible proteins. The software written for the analyses presented here is available at https://github.com/AMarinhoSN/FleXgeo for academic usage only.

The molecular bases of amyloid aggregation propensity are still poorly understood, especially for proteins that display a stable folded native structure. A prototypic example is human beta-2 microglobulin (β2m), which, when accumulated in patients, gives rise to dialysis-related amyloidosis. Interestingly, although the physiologic concentration of β2m in mice is five times higher than that found in human patients, no amyloid deposits are observed in mice. Moreover, murine β2m (mβ2m) not only displays a lower amyloid propensity both invivo and invitro but also inhibits the aggregation of human β2m invitro. Here, we compared human and mβ2m for their aggregation propensity, ability to form soluble oligomers, stability, three-dimensional structure and dynamics. Our results indicate that mβ2m low-aggregation propensity is due to two concomitant aspects: the low-aggregation propensity of its primary sequence combined with the absence of high-energy amyloid-competent conformations under native conditions. The identification of the specific properties determining the low-aggregation propensity of mouse β2m will help delineate the molecular risk factors which cause a folded protein to aggregate.

Nuclear magnetic resonance (NMR) spectroscopy provides detailed information about the structure and dynamics of proteins by exploiting the conformational dependence of the magnetic properties of certain atomic nuclei. The mapping between NMR measurements and molecular structures, however, often requires approximated descriptions based on the fitting of a number of parameters, thus reducing the quality of the information available from the experiments. To improve on this limitation, we show here that it is possible to use pseudocontact shifts and residual dipolar couplings as "exact" NMR restraints. We implement this strategy by using a replica-averaging method and illustrate its application by calculating an ensemble of structures representing the dynamics of the two-domain protein calmodulin.

Co-translational folding is a fundamental molecular process that ensures efficient protein biosynthesis and minimizes the wasteful or hazardous formation of misfolded states. However, the complexity of this process makes it extremely challenging to obtain structural characterizations of co-translational folding pathways. Here we contrast observations in translationally-arrested nascent chains with those of a systematic C-terminal truncation strategy. We create a detailed description of chain length-dependent free energy landscapes associated with folding of the FLN5 filamin domain, in isolation and on the ribosome. By using this approach we identify and characterize two folding intermediates, including a partially folded intermediate associated with the isomerization of a conserved proline residue, which, together with measurements of folding kinetics, raises the prospect that neighboring unfolded domains might accumulate during biosynthesis. We develop a simple model to quantify the risk of misfolding in this situation, and show that catalysis of folding by peptidyl-prolyl isomerases is essential to eliminate this hazard.

Metadynamic metainference has been recently introduced as a theoretical framework to determine structural ensembles by combining and weighting their noise multiple sources of experimental data with molecular mechanics force fields and metadynamics simulations. Here we build upon these initial developments to further extend and streamline the computational approach. We also show that metadynamic metainference can actually determine a structural ensemble for a disordered peptide that is essentially independent from the employed force field. We further show that it is possible to use a very computationally efficient implicit solvent force field in the place of very expensive state-of-the-art explicit solvent ones without a significant loss in accuracy.

Lymphocyte function-associated antigen-1 (LFA-1) is an integrin protein that transmits information across the plasma membrane through the so-called inside-out and outside-in signaling mechanisms. To investigate these mechanisms, we carried out an NMR analysis of the dynamics of the LFA-1 I-domain, which has enabled us to characterize the motions of this domain on a broad range of timescales. We studied first the internal motions on the nanosecond timescale by spin relaxation measurements and model-free analysis. We then extended this analysis to the millisecond timescale motions by measuring 15N-1H residual dipolar couplings of the backbone amide groups. We analyzed these results in the context of the three major conformational states of the I-domain using their corresponding X-ray crystallographic structures. Our results highlight the importance of the low-frequency motions of the LFA-1 I-domain in the inactive apo-state. We found in particular that α-helix 7 is in a position in the apo-closed state that cannot be fully described by any of the existing X-ray structures, as it appears to be in dynamic exchange between different conformations. This type of motion seems to represent an inherent property of the LFA-1 I-domain and might be relevant for controlling the access to the allosteric binding pocket, as well as for the downward displacement of α-helix 7 that is required for the activation of LFA-1.

The characterization of denatured states of proteins is challenging because the lack of permanent structure in these states makes it difficult to apply to them standard methods of structural biology. In this work we use all-atom replica-averaged metadynamics (RAM) simulations with NMR chemical shift restraints to determine an ensemble of structures representing an acid-denatured state of the 86-residue protein ACBP. This approach has enabled us to reach convergence in the free energy landscape calculations, obtaining an ensemble of structures in relatively accurate agreement with independent experimental data used for validation. By observing at atomistic resolution the transient formation of native and non-native structures in this acid-denatured state of ACBP, we rationalize the effects of single-point mutations on the folding rate, stability, and transition-state structures of this protein, thus characterizing the role of the unfolded state in determining the folding process.

Residual dipolar couplings (RDCs) are parameters measured in nuclear magnetic resonance spectroscopy that can provide exquisitely detailed information about the structure and dynamics of biological macromolecules. We describe here a method of using RDCs for the structural and dynamical refinement of proteins that is based on the observation that the RDC between two atomic nuclei depends directly on the angle ϑ between the internuclear vector and the external magnetic field. For every pair of nuclei for which an RDC is available experimentally, we introduce a structural restraint to minimize the deviation from the value of the angle ϑ derived from the measured RDC and that calculated in the refinement protocol. As each restraint involves only the calculation of the angle ϑ of the corresponding internuclear vector, the method does not require the definition of an overall alignment tensor to describe the preferred orientation of the protein with respect to the alignment medium. Application to the case of ubiquitin demonstrates that this method enables an accurate refinement of the structure and dynamics of this protein to be obtained.

Interleukin-8 (CXCL8, IL-8) is a proinflammatory chemokine important for the regulation of inflammatory and immune responses via its interaction with G-protein coupled receptors, including CXC receptor 1 (CXCR1). CXCL8 exists as both a monomer and as a dimer at physiological concentrations, yet the molecular basis of CXCL8 interaction with its receptor as well as the importance of CXCL8 dimer formation remain poorly characterized. Although several biological studies have indicated that both the CXCL8 monomer and dimer are active, biophysical studies have reported conflicting results regarding the binding of CXCL8 to CXCR1. To clarify this problem, we expressed and purified a peptide (hCXCR1pep) corresponding to the N-terminal region of human CXCR1 (hCXCR1) and utilized nuclear magnetic resonance (NMR) spectroscopy to interrogate the binding of wild-type CXCL8 and a previously reported mutant (CXCL8M) that stabilizes the monomeric form. Our data reveal that the CXCL8 monomer engages hCXCR1pep with a slightly higher affinity than the CXCL8 dimer, but that the CXCL8 dimer does not dissociate upon binding hCXCR1pep. These investigations also showed that CXCL8 is dynamic on multiple timescales, which may help explain the versatility in this interleukin for engaging its target receptors.

Recent improvements in the accuracy of structure-based methods for the prediction of nuclear magnetic resonance chemical shifts have inspired numerous approaches for determining the secondary and tertiary structures of proteins. Such advances also suggest the possibility of using chemical shifts to characterize the conformational fluctuations of these molecules. Here we describe a method of using methyl chemical shifts as restraints in replica-averaged molecular dynamics (MD) simulations, which enables us to determine the conformational ensemble of the HU dimer and characterize the range of motions accessible to its flexible β-arms. Our analysis suggests that the bending action of HU on DNA is mediated by a mechanical clamping mechanism, in which metastable structural intermediates sampled during the hinge motions of the β-arms in the free state are presculpted to bind DNA. These results illustrate that using side-chain chemical shift data in conjunction with MD simulations can provide quantitative information about the free energy landscapes of proteins and yield detailed insights into their functional mechanisms.

Residual dipolar couplings (RDCs) can provide exquisitely detailed information about the structure and dynamics of proteins. It is challenging, however, to extract such information from RDC measurements in conformationally heterogeneous states of proteins because of the complex relationship between RDCs and protein structures. To obtain new insights into this problem, we discuss methods of calculating the RDCs that do not require the definition of an alignment tensor. These methods can help in particular in the search of effective ways to use RDCs to characterise disordered or partially disordered states of proteins. © 2014 Springer Science+Business Media Dordrecht.

Almost (all atom molecular simulation toolkit) is an open source computational package for structure determination and analysis of complex molecular systems including proteins, and nucleic acids. Almost has been designed with two primary goals: to provide tools for molecular structure determination using various types of experimental measurements as conformational restraints, and to provide methods for the analysis and assessment of structural and dynamical properties of complex molecular systems. The methods incorporated in Almost include the determination of structural and dynamical features of proteins using distance restraints derived from nuclear Overhauser effect measurements, orientational restraints obtained from residual dipolar couplings and the structural restraints from chemical shifts. Here, we present the first public release of Almost, highlight the key aspects of its computational design and discuss the main features currently implemented. Almost is available for the most common Unix-based operating systems, including Linux and Mac OS X. Almost is distributed free of charge under the GNU Public License, and is available both as a source code and as a binary executable from the project web site at http://www.open-almost.org. Interested users can follow and contribute to the further development of Almost on http://sourceforge.net/ projects/almost. © 2014 Wiley Periodicals, Inc. "Almost" (all atom molecular simulation toolkit) is an open source computational package for the structure determination and analysis of biomolecules. Almost provides tools for the molecular structure determination using various types of experimental measurements as conformational restraints and methods for the analysis of structural and dynamical properties of complex molecular systems. Copyright © 2014 Wiley Periodicals, Inc.

A statistical mechanics description of complex molecular systems involves the determination of ensembles of conformations that represent their Boltzmann distributions. The observable properties of these systems can be then predicted by calculating averages over such ensembles. In principle, given accurate energy functions and efficient sampling methods, these ensembles can be generated by molecular dynamics simulations. In practice, however, often the energy functions are known only approximately and the sampling can be carried out only in a limited manner. We describe here a method that enables to increase simultaneously both the quality of the energy functions and of the extent of the sampling in a system-dependent manner. The method is based on the incorporation of experimental data as replica-averaged structural restraints in molecular dynamics simulations and exploits the metadynamics framework to enhance the sampling. The application to the case of α-conotoxin SI, a 13-residue peptide that has been characterized extensively by experimental measurements, shows that the approach that we describe enables accurate free energy landscapes to be generated. The analysis of these landscapes indicates the presence of a low population state in equilibrium with the native state in which the only aromatic residue of α-conotoxin SI is exposed to the solvent, which is a feature that may predispose the peptide to interact with its partners.

Intrinsically disordered proteins constitute a significant part of the human proteome and carry out a wide range of different functions, including in particular signaling and regulation. Several of these proteins are vulnerable to aggregation, and their aberrant assemblies have been associated with a variety of neurodegenerative and systemic diseases. It remains unclear, however, the extent to which the conformational properties of intrinsically disordered proteins in their monomeric states influence the aggregation behavior of these molecules. Here we report a relationship between aggregation rates and secondary structure populations in the soluble monomeric states of a series of mutational variants of α-synuclein. Overall, we found a correlation of over 90% between the changes in β-sheet populations calculated from NMR chemical shift data and the changes in aggregation rates for eight human-to-mouse chimeric mutants. These results provide support to the idea of investigating therapeutic strategies based on the stabilization of the monomeric form of intrinsically disordered proteins through the alteration of their conformational properties.

The description of the dynamics of a complex, high-dimensional system in terms of a low-dimensional set of collective variables $Y$ can be fruitful if the low-dimensional representation satisfies a Langevin equation with drift and diffusion coefficients that depend only on $Y$. We present a computational scheme to evaluate whether a given collective variable provides a faithful low-dimensional representation of the dynamics of a high-dimensional system. The scheme is based on the framework of a finite-difference Langevin equation, similar to that used for molecular-dynamics simulations. This allows one to calculate the drift and diffusion coefficients in any point of the full-dimensional system. The width of the distribution of drift and diffusion coefficients in an ensemble of microscopic points at the same value of $Y$ indicates to what extent the dynamics of $Y$ is described by a simple Langevin equation. Using a simple protein model, we show that collective variables often used to describe biopolymers display a non-negligible width both in the drift and in the diffusion coefficients. We also show that the associated effective force is compatible with the equilibrium free energy calculated from a microscopic sampling, but it results in markedly different dynamical properties.

The mechanical properties of proteins and their force-induced structural changes play key roles in many biological processes. Previous studies have shown that natively folded proteins are brittle under tension, unfolding after small mechanical deformations, while partially folded intermediate states, such as molten globules, are compliant and can deform elastically a great amount before crossing the transition state barrier. Moreover, under tension proteins appear to unfold through a different sequence of events than during spontaneous unfolding. Here, we describe the response to force of the four-α-helix acyl-CoA binding protein (ACBP) in the low-force regime using optical tweezers and ratcheted molecular dynamics simulations. The results of our studies reveal an unprecedented mechanical behavior of a natively folded protein. ACBP displays an atypical compliance along two nearly orthogonal pulling axes, with transition states located almost halfway between the unfolded and folded states. Surprisingly, the deformability of ACBP is greater than that observed for the highly pliant molten globule intermediate states. Furthermore, when manipulated from the N- and C-termini, ACBP unfolds by populating a transition state that resembles that observed during chemical denaturation, both for structure and position along the reaction coordinate. Our data provide the first experimental evidence of a spontaneous-like mechanical unfolding pathway of a protein. The mechanical behavior of ACBP is discussed in terms of topology and helix propensity.

The characterization of the structural dynamics of proteins, including those that present a substantial degree of disorder, is currently a major scientific challenge. These dynamics are biologically relevant and govern the majority of functional and pathological processes. We exploited a combination of enhanced molecular simulations of metadynamics and NMR measurements to study heterogeneous states of proteins and peptides. In this way, we determined the structural ensemble and free-energy landscape of the highly dynamic helix 1 of the prion protein (PrP-H1), whose misfolding and aggregation are intimately connected to a group of neurodegenerative disorders known as transmissible spongiform encephalopathies. Our combined approach allowed us to dissect the factors that govern the conformational states of PrP-H1 in solution, and the implications of these factors for prion protein misfolding and aggregation. The results underline the importance of adopting novel integrated approaches that take advantage of experiments and theory to achieve a comprehensive characterization of the structure and dynamics of biological macromolecules. © 2012 Biophysical Society.

Many proteins display complex dynamical properties that are often intimately linked to their biological functions. As the native state of a protein is best described as an ensemble of confor-mations, it is important to be able to generate models of native state ensembles with high accuracy. Due to limitations in sampling efficiency and force field accuracy it is, however, challenging to obtain accurate ensembles of protein conformations by the use of molecular simulations alone. Here we show that dynamic ensemble refinement, which combines an accurate atomistic force field with commonly available nuclear magnetic resonance (NMR) chemical shifts and NOEs, can provide a detailed and accurate description of the conformational ensemble of the native state of a highly dynamic protein. As both NOEs and chemical shifts are averaged on timescales up to milliseconds, the resulting ensembles reflect the structural heterogeneity that goes beyond that probed e.g. by NMR relaxation order parameters. We selected the small protein domain NCBD as object of our study since this protein, which has been characterized experimentally in substantial detail, displays a rich and complex dynamical behaviour. In particular, the protein has been described as having a molten-globule like structure, but with a relatively rigid core. Our approach allowed us to describe the conformational dynamics of NCBD in solution, and to probe the structural heterogeneity resulting from both short- and long-time-scale dynamics by the calculation of order parameters on different time scales. These results illustrate the usefulness of our approach since they show that NCBD is rather rigid on the nanosecond timescale, but interconverts within a broader ensemble on longer timescales, thus enabling the derivation of a coherent set of conclusions from various NMR experiments on this protein, which could otherwise appear in contradiction with each other.