Dynamic protein domains: identification, interdependence, and stability

Modeling coronavirus spike protein dynamics: implications for immunogenicity and immune escape

The ongoing COVID-19 pandemic is a global public health emergency requiring urgent development of efficacious vaccines. While concentrated research efforts have focused primarily on antibody-based vaccines that neutralize SARS-CoV-2, and several first-generation vaccines have either been approved or received emergency use authorization, it is forecasted that COVID-19 will become an endemic disease requiring updated second-generation vaccines. The SARS-CoV-2 surface spike (S) glycoprotein represents a prime target for vaccine development because antibodies that block viral attachment and entry, i.e., neutralizing antibodies, bind almost exclusively to the receptor-binding domain. Here, we develop computational models for a large subset of S proteins associated with SARS-CoV-2, implemented through coarse-grained elastic network models and normal mode analysis. We then analyze local protein domain dynamics of the S protein systems and their thermal stability to characterize structural and dynamical variability among them. These results are compared against existing experimental data and used to elucidate the impact and mechanisms of SARS-CoV-2 S protein mutations and their associated antibody binding behavior. We construct a SARS-CoV-2 antigenic map and offer predictions about the neutralization capabilities of antibody and S mutant combinations based on protein dynamic signatures. We then compare SARS-CoV-2 S protein dynamics to SARS-CoV and MERS-CoV S proteins to investigate differing antibody binding and cellular fusion mechanisms that may explain the high transmissibility of SARS-CoV-2. The outbreaks associated with SARS-CoV, MERS-CoV, and SARS-CoV-2 over the last two decades suggest that the threat presented by coronaviruses is ever-changing and long term. Our results provide insights into the dynamics-driven mechanisms of immunogenicity associated with coronavirus S proteins and present a new, to our knowledge, approach to characterize and screen potential mutant candidates for immunogen design, as well as to characterize emerging natural variants that may escape vaccine-induced antibody responses.

A Data-Driven Perspective on the Hierarchical Assembly of Molecular Structures

Macromolecular systems are composed of a very large number of atomic degrees of freedom. There is strong evidence suggesting that structural changes occurring in large biomolecular systems at long time scale dynamics may be captured by models coarser than atomistic, although a suitable or optimal coarse-graining is a priori unknown. Here we propose a systematic approach to learning a coarse representation of a macromolecule from microscopic simulation data. In particular, the definition of effective coarse variables is achieved by partitioning the degrees of freedom both in the structural (physical) space and in the conformational space. The identification of groups of microscopic particles forming dynamical coherent states in different metastable states leads to a multiscale description of the system, in space and time. The application of this approach to the folding dynamics of two proteins provides a revised view of the classical idea of prestructured regions (foldons) that combine during a protein-folding process and suggests a hierarchical characterization of the assembly process of folded structures.

Osmolyte-Like Stabilizing Effects of Low GdnHCl Concentrations on d-Glucose/d-Galactose-Binding Protein

The ability of d-glucose/d-galactose-binding protein (GGBP) to reversibly interact with its ligands, glucose and galactose, makes this protein an attractive candidate for sensing elements of glucose biosensors. This potential is largely responsible for attracting researchers to study the conformational properties of this protein. Previously, we showed that an increase in the fluorescence intensity of the fluorescent dye 6-bromoacetyl-2-dimetylaminonaphtalene (BADAN) is linked to the holo-form of the GGBP/H152C mutant in solutions containing sub-denaturing concentrations of guanidine hydrochloride (GdnHCl). It was hypothesized that low GdnHCl concentrations might lead to compaction of the protein, thereby facilitating ligand binding. In this work, we utilize BADAN fluorescence spectroscopy, intrinsic protein UV fluorescence spectroscopy, and isothermal titration calorimetry (ITC) to show that the sub-denaturing GdnHCl concentrations possess osmolyte-like stabilizing effects on the structural dynamics, conformational stability, and functional activity of GGBP/H152C and the wild type of this protein (wtGGBP). Our data are consistent with the model where low GdnHCl concentrations promote a shift in the dynamic distribution of the protein molecules toward a conformational ensemble enriched in molecules with a tighter structure and a more closed conformation. This promotes the increase in the configurational complementarity between the protein and glucose molecules that leads to the increase in glucose affinity in both GGBP/H152C and wtGGBP.

ResiCon: a method for the identification of dynamic domains, hinges and interfacial regions in proteins

MOTIVATION

Structure of most proteins is flexible. Identification and analysis of intramolecular motions is a complex problem. Breaking a structure into relatively rigid parts, the so-called dynamic domains, may help comprehend the complexity of protein's mobility. We propose a new approach called ResiCon (Residue Contacts analysis), which performs this task by applying a data-mining analysis of an ensemble of protein configurations and recognizes dynamic domains, hinges and interfacial regions, by considering contacts between residues.

RESULTS

Dynamic domains found by ResiCon are more compact than those identified by two other popular methods: PiSQRD and GeoStaS. The current analysis was carried out using a known reference set of 30 NMR protein structures, as well as molecular dynamics simulation data of flap opening events in HIV-1 protease. The more detailed analysis of HIV-1 protease dataset shows that ResiCon identified dynamic domains involved in structural changes of functional importance.

AVAILABILITY AND IMPLEMENTATION

The ResiCon server is available at URL: http://dworkowa.imdik.pan.pl/EP/ResiCon.

CONTACT

pawel@bioexploratorium.pl

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Systematic methods for defining coarse-grained maps in large biomolecules

Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.

Molecular mechanisms in the activation of abscisic acid receptor PYR1

The pyrabactin resistance 1 (PYR1)/PYR1-like (PYL)/regulatory component of abscisic acid (ABA) response (RCAR) proteins comprise a well characterized family of ABA receptors. Recent investigations have revealed two subsets of these receptors that, in the absence of ABA, either form inactive homodimers (PYR1 and PYLs 1–3) or mediate basal inhibition of downstream target type 2C protein phosphatases (PP2Cs; PYLs 4–10) respectively in vitro. Addition of ABA has been shown to release the apo-homodimers yielding ABA-bound monomeric holo-receptors that can interact with PP2Cs; highlighting a competitive-interaction process. Interaction selectivity has been shown to be mediated by subtle structural variations of primary sequence and ligand binding effects. Now, the dynamical contributions of ligand binding on interaction selectivity are investigated through extensive molecular dynamics (MD) simulations of apo and holo-PYR1 in monomeric and dimeric form as well as in complex with a PP2C, homology to ABA insensitive 1 (HAB1). Robust comparative interpretations were enabled by a novel essential collective dynamics approach. In agreement with recent experimental findings, our analysis indicates that ABA-bound PYR1 should efficiently bind to HAB1. However, both ABA-bound and ABA-extracted PYR1-HAB1 constructs have demonstrated notable similarities in their dynamics, suggesting that apo-PYR1 should also be able to make a substantial interaction with PP2Cs, albeit likely with slower complex formation kinetics. Further analysis indicates that both ABA-bound and ABA-free PYR1 in complex with HAB1 exhibit a higher intra-molecular structural stability and stronger inter-molecular dynamic correlations, in comparison with either holo- or apo-PYR1 dimers, supporting a model that includes apo-PYR1 in complex with HAB1. This possibility of a conditional functional apo-PYR1-PP2C complex was validated in vitro. These findings are generally consistent with the competitive-interaction model for PYR1 but highlight dynamical contributions of the PYR1 structure in mediating interaction selectivity suggesting added degrees of complexity in the regulation of the competitive-inhibition.

Protein pyrabactin resistance 1 (PYR1) belongs to a group of PYR1-like (PYL) proteins that regulate plant development and responses to conditions of drought and salinity. Recent studies have reported characterization of their molecular structures as well as elucidation of important aspects of their function; highlighting their roles as receptors for the stress responsive phytohormone, abscisic acid (ABA). However details of the molecular mechanisms regulating their receptor signalling remain enigmatic. In this work, we use molecular dynamics simulations complemented by a sophisticated statistical-mechanical analysis to investigate structural and dynamical properties of PYR1 protein and how its interaction with ABA modifies receptor-protein complex formation. Our results provide detailed insight into how the PYR1-mediated inactivation of its downstream phosphatase target is regulated by homodimer formation and yield new hypotheses, supported by in vitro experiments, for further investigation. Ultimately, this knowledge provides insight into how plants respond to stress, with potential applications in the development of crops with improved growth characteristics and higher stress tolerance.

Exploring the essential collective dynamics of interacting proteins: application to prion protein dimers

Essential collective dynamics is a promising and robust approach for analysing the slow motions of macromolecules from short molecular dynamics trajectories. In this study, an extension of the method to treat a collection of interacting protein molecules is presented. The extension is applied to investigate the effects of dimerization on the collective dynamics of ovine prion protein molecules in two different arrangements. Examination of the structural plasticity shows that aggregation has a restricting effect on the local mobility of the prion protein molecules in the interfacial regions. Domain motions of the two dimeric ovine prion protein conformations are distinctly different and can be related to interatomic correlations at the interface. Correlated motions are among the slow collective modes extensively analysed by considering both main-chain and side-chain atoms. Correlation maps reveal the existence of a vast network of dynamically correlated side groups, which extends beyond individual subunits via interfacial interconnections. The network is formed by a core of hydrophobic side chains surrounded by hydrophilic groups at the periphery. The relevance of these findings are discussed in the context of mutations associated with prion diseases. The binding free energy of the dimeric conformations is evaluated to probe their thermodynamic stability. The descriptions afforded by the analysis of the essential collective dynamics of the prion dimers are consistent with their binding free energies. The agreement validates the extension of the methodology and provides a means of interpreting the collective dynamics in terms of the thermodynamic stability of ovine prion proteins.

Density-cluster NMA: A new protein decomposition technique for coarse-grained normal mode analysis

Normal mode analysis has emerged as a useful technique for investigating protein motions on long time scales. This is largely due to the advent of coarse-graining techniques, particularly Hooke's Law-based potentials and the rotational-translational blocking (RTB) method for reducing the size of the force-constant matrix, the Hessian. Here we present a new method for domain decomposition for use in RTB that is based on hierarchical clustering of atomic density gradients, which we call Density-Cluster RTB (DCRTB). The method reduces the number of degrees of freedom by 85-90% compared with the standard blocking approaches. We compared the normal modes from DCRTB against standard RTB using 1-4 residues in sequence in a single block, with good agreement between the two methods. We also show that Density-Cluster RTB and standard RTB perform well in capturing the experimentally determined direction of conformational change. Significantly, we report superior correlation of DCRTB with B-factors compared with 1-4 residue per block RTB. Finally, we show significant reduction in computational cost for Density-Cluster RTB that is nearly 100-fold for many examples.

Stability of domain structures in multi-domain proteins

Multi-domain proteins have many advantages with respect to stability and folding inside cells. Here we attempt to understand the intricate relationship between the domain-domain interactions and the stability of domains in isolation. We provide quantitative treatment and proof for prevailing intuitive ideas on the strategies employed by nature to stabilize otherwise unstable domains. We find that domains incapable of independent stability are stabilized by favourable interactions with tethered domains in the multi-domain context. Stability of such folds to exist independently is optimized by evolution. Specific residue mutations in the sites equivalent to inter-domain interface enhance the overall solvation, thereby stabilizing these domain folds independently. A few naturally occurring variants at these sites alter communication between domains and affect stability leading to disease manifestation. Our analysis provides safe guidelines for mutagenesis which have attractive applications in obtaining stable fragments and domain constructs essential for structural studies by crystallography and NMR.

Comparative analysis of essential collective dynamics and NMR-derived flexibility profiles in evolutionarily diverse prion proteins

Collective motions on ns-μs time scales are known to have a major impact on protein folding, stability, binding and enzymatic efficiency. It is also believed that these motions may have an important role in the early stages of prion protein misfolding and prion disease. In an effort to accurately characterize these motions and their potential influence on the misfolding and prion disease transmissibility we have conducted a combined analysis of molecular dynamic simulations and NMR-derived flexibility measurements over a diverse range of prion proteins. Using a recently developed numerical formalism, we have analyzed the essential collective dynamics (ECD) for prion proteins from 8 different species including human, cow, elk, cat, hamster, chicken, turtle and frog. We also compared the numerical results with flexibility profiles generated by the random coil index (RCI) from NMR chemical shifts. Prion protein backbone flexibility derived from experimental NMR data and from theoretical computations show strong agreement with each other, demonstrating that it is possible to predict the observed RCI profiles employing the numerical ECD formalism. Interestingly, flexibility differences in the loop between second beta strand (S2) and the second alpha helix (HB) appear to distinguish prion proteins from species that are susceptible to prion disease and those that are resistant. Our results show that the different levels of flexibility in the S2-HB loop in various species are predictable via the ECD method, indicating that ECD may be used to identify disease resistant variants of prion proteins, as well as the influence of prion proteins mutations on disease susceptibility or misfolding propensity.

BlockMaster: partitioning protein kinase structures using normal-mode analysis

Protein kinases are key signaling enzymes which are dysregulated in many health disorders and therefore represent major targets of extensive drug discovery efforts. Their regulation in the cell is exerted via various mechanisms, including control of the 3D conformation of their catalytic domains. We developed a procedure, BlockMaster, for partitioning protein structures into semirigid blocks and flexible regions based on residue-residue correlations calculated from normal modes. BlockMaster provided correct partitioning into domains and subdomains of several test set proteins for which documented expert annotation of subdomains exists. When applied to representative structures of protein kinases, BlockMaster identified semirigid blocks within the traditional N-terminal and C-terminal lobes of the kinase domain. In general, the block regions had elevated helical content and reduced, but significant, coil content compared to the nonblock (flexible) regions. The specificity-determining regions, previously used to derive inhibitory peptides, were found to be more flexible in the tyrosine kinases than in serine/threonine kinases. Two blocks were identified which spanned both lobes. The first, which we termed the "pivot" block, included the alphaC-beta4 loop in the N-terminal lobe and part of the activation loop in the C-terminal lobe and appeared in both the active and inactive conformations of the kinases. The second, which we termed the "loop" block, differed between the active and inactive conformations. In the structures of active kinases, this block included part of the activation loop in the C-terminal lobe and the alphaC helix in the N-terminal lobe, representing a known interaction that stabilizes the active conformation. In the inactive structures, this block included G loop residues instead of the alphaC residues. This novel inactive "loop" block may stabilize the inactive conformation and thus downregulate kinase activity.

Fuzzy domains: new way of describing flexibility and interdependence of the protein domains

We proposed the innovative method of domain identification based on the concept of the fuzzy domains. In this method each residue of the protein can belong to several domains simultaneously with certain weights, which reflect to what extent this residue shares the motion pattern of the given domain. Our method allows describing the fuzzy boundaries between the domains and the gradual changes of the motion pattern from one domain to the other. It provides the reasonable compromise between the continuous change of the protein dynamics from one residue to the other and the discrete description of the structure in terms of small number of domains. We suggested quantitative criterion, which shows the overall degree of domain flexibility in the protein. The concept of the fuzzy domains provides an innovative way of visualization of domain flexibility, which makes the gradual transitions between the domains clearly visible and comparable to available experimental and structural data. In the future, the concept of the fuzzy domains can be used in the coarse-grained simulations of the domain dynamics in order to account for internal protein flexibility.

A systematic methodology for defining coarse-grained sites in large biomolecules

Coarse-grained (CG) models of biomolecules have recently attracted considerable interest because they enable the simulation of complex biological systems on length-scales and timescales that are inaccessible for atomistic molecular dynamics simulation. A CG model is defined by a map that transforms an atomically detailed configuration into a CG configuration. For CG models of relatively small biomolecules or in cases that the CG and all-atom models have similar resolution, the construction of this map is relatively straightforward and can be guided by chemical intuition. However, it is more challenging to construct a CG map when large and complex domains of biomolecules have to be represented by relatively few CG sites. This work introduces a new and systematic methodology called essential dynamics coarse-graining (ED-CG). This approach constructs a CG map of the primary sequence at a chosen resolution for an arbitrarily complex biomolecule. In particular, the resulting ED-CG method variationally determines the CG sites that reflect the essential dynamics characterized by principal component analysis of an atomistic molecular dynamics trajectory. Numerical calculations illustrate this approach for the HIV-1 CA protein dimer and ATP-bound G-actin. Importantly, since the CG sites are constructed from the primary sequence of the biomolecule, the resulting ED-CG model may be better suited to appropriately explore protein conformational space than those from other CG methods at the same degree of resolution.

GANDivAWeb: a web server for detecting early folding units ("foldons") from protein 3D structures

Background

It has long been known that small regions of proteins tend to fold independently and are then stabilized by interactions between these distinct subunits or modules. Such units, also known as autonomous folding units (AFUs) or"foldons" play a key role in protein folding. A knowledge of such early folding units has diverse applications in protein engineering as well as in developing an understanding of the protein folding process. Such AFUs can also be used as model systems in order to study the structural organization of proteins.

Results

In an earlier work, we had utilized a global network partitioning algorithm to identify modules in proteins. We had shown that these modules correlate well with AFUs. In this work, we have developed a webserver, GANDivAWeb, to identify early folding units or "foldons" in networks using the algorithm described earlier. The website has three functionalities: (a) It is able to display information on the modularity of a database of 1420 proteins used in the original work, (b) It can take as input an uploaded PDB file, identify the modules using the GANDivA algorithm and email the results back to the user and (c) It can take as input an uploaded PDB file and a results file (obtained from functionality (b)) and display the results using the embedded viewer. The results include the module decomposition of the protein, plots of cartoon representations of the protein colored by module identity and connectivity as well as contour plots of the hydrophobicity and relative accessible surface area (RASA) distributions.

Conclusion

We believe that the GANDivAWeb server, will be a useful tool for scientists interested in the phenomena of protein folding as well as in protein engineering. Our tool not only provides a knowledge of the AFUs through a natural graph partitioning approach but is also able to identify residues that are critical during folding. It is our intention to use this tool to study the topological determinants of protein folding by analyzing the topological changes in proteins over the unfolding/folding pathways.

Dynamics of essential collective motions in proteins: theory

A general theoretical background is introduced for characterization of conformational motions in protein molecules, and for building reduced coarse-grained models of proteins, based on the statistical analysis of their phase trajectories. Using the projection operator technique, a system of coupled generalized Langevin equations is derived for essential collective coordinates, which are generated by principal component analysis of molecular dynamic trajectories. The number of essential degrees of freedom is not limited in the theory. An explicit analytic relation is established between the generalized Langevin equation for essential collective coordinates and that for the all-atom phase trajectory projected onto the subspace of essential collective degrees of freedom. The theory introduced is applied to identify correlated dynamic domains in a macromolecule and to construct coarse-grained models representing the conformational motions in a protein through a few interacting domains embedded in a dissipative medium. A rigorous theoretical background is provided for identification of dynamic correlated domains in a macromolecule. Examples of domain identification in protein G are given and employed to interpret NMR experiments. Challenges and potential outcomes of the theory are discussed.

The change of protein intradomain mobility on ligand binding: is it a commonly observed phenomenon?

Analysis of changes in the dynamics of protein domains on ligand binding is important in several aspects: for the understanding of the hierarchical nature of protein folding and dynamics at equilibrium; for analysis of signal transduction mechanisms triggered by ligand binding, including allostery; for drug design; and for construction of biosensors reporting on the presence of target ligand in studied media. In this work we use the recently developed HCCP computational technique for the analysis of stabilities of dynamic domains in proteins, their intrinsic motions and of their changes on ligand binding. The work is based on comparative studies of 157 ligand binding proteins, for which several crystal structures (in ligand-free and ligand-bound forms) are available. We demonstrate that the domains of the proteins presented in the Protein DataBank are far more robust than it was thought before: in the majority of the studied proteins (152 out of 157), the ligand binding does not lead to significant change of domain stability. The exceptions from this rule are only four bacterial periplasmic transport proteins and calmodulin. Thus, as a rule, the pattern of correlated motions in dynamic domains, which determines their stability, is insensitive to ligand binding. This rule may be the general feature for a vast majority of proteins.