Fold stability during endolysosomal acidification is a key factor for allergenicity and immunogenicity of the major birch pollen allergen.

BACKGROUND: The search for intrinsic factors, which account for a protein's capability to act as an allergen, is ongoing. Fold stability has been identified as a molecular feature that affects processing and presentation, thereby influencing an antigen's immunologic properties. OBJECTIVE: We assessed how changes in fold stability modulate the immunogenicity and sensitization capacity of the major birch pollen allergen Bet v 1. METHODS: By exploiting an exhaustive virtual mutation screening, we generated mutants of the prototype allergen Bet v 1 with enhanced thermal and chemical stability and rigidity. Structural changes were analyzed by means of x-ray crystallography, nuclear magnetic resonance, and molecular dynamics simulations. Stability was monitored by using differential scanning calorimetry, circular dichroism, and Fourier transform infrared spectroscopy. Endolysosomal degradation was simulated in vitro by using the microsomal fraction of JAWS II cells, followed by liquid chromatography coupled to mass spectrometry. Immunologic properties were characterized in vitro by using a human T-cell line specific for the immunodominant epitope of Bet v 1 and in vivo in an adjuvant-free BALB/c mouse model. RESULTS: Fold stabilization of Bet v 1 was pH dependent and resulted in resistance to endosomal degradation at a pH of 5 or greater, affecting presentation of the immunodominant T-cell epitope in vitro. These properties translated in vivo into a strong allergy-promoting TH2-type immune response. Efficient TH2 cell activation required both an increased stability at the pH of the early endosome and efficient degradation at lower pH in the late endosomal/lysosomal compartment. CONCLUSIONS: Our data indicate that differential pH-dependent fold stability along endosomal maturation is an essential protein-inherent determinant of allergenicity.

Specificity of a protein-protein interface: local dynamics direct substrate recognition of effector caspases.

Proteases are prototypes of multispecific protein-protein interfaces. Proteases recognize and cleave protein and peptide substrates at a well-defined position in a substrate binding groove and a plethora of experimental techniques provide insights into their substrate recognition. We investigate the caspase family of cysteine proteases playing a key role in programmed cell death and inflammation, turning caspases into interesting drug targets. Specific ligand binding to one particular caspase is difficult to achieve, as substrate specificities of caspase isoforms are highly similar. In an effort to rationalize substrate specificity of two closely related caspases, we investigate the substrate promiscuity of the effector Caspases 3 and 7 by data mining (cleavage entropy) and by molecular dynamics simulations. We find a strong correlation between binding site rigidity and substrate readout for individual caspase subpockets explaining more stringent substrate readout of Caspase 7 via its narrower conformational space. Caspase 3 subpockets S3 and S4 show elevated local flexibility explaining the more unspecific substrate readout of that isoform in comparison to Caspase 7. We show by in silico exchange mutations in the S3 pocket of the proteases that a proline residue in Caspase 7 contributes to the narrowed conformational space of the binding site. These findings explain the substrate specificities of caspases via a mechanism of conformational selection and highlight the crucial importance of binding site local dynamics in substrate recognition of proteases. Proteins 2014; 82:546-555. © 2013 Wiley Periodicals, Inc.

Cleavage entropy as quantitative measure of protease specificity.

A purely information theory-guided approach to quantitatively characterize protease specificity is established. We calculate an entropy value for each protease subpocket based on sequences of cleaved substrates extracted from the MEROPS database. We compare our results with known subpocket specificity profiles for individual proteases and protease groups (e.g. serine proteases, metallo proteases) and reflect them quantitatively. Summation of subpocket-wise cleavage entropy contributions yields a measure for overall protease substrate specificity. This total cleavage entropy allows ranking of different proteases with respect to their specificity, separating unspecific digestive enzymes showing high total cleavage entropy from specific proteases involved in signaling cascades. The development of a quantitative cleavage entropy score allows an unbiased comparison of subpocket-wise and overall protease specificity. Thus, it enables assessment of relative importance of physicochemical and structural descriptors in protease recognition. We present an exemplary application of cleavage entropy in tracing substrate specificity in protease evolution. This highlights the wide range of substrate promiscuity within homologue proteases and hence the heavy impact of a limited number of mutations on individual substrate specificity.

A challenging system: free energy prediction for factor Xa.

Factor Xa (fXa) is a promising target for antithrombotic drugs. Recently, we presented a molecular dynamics study on fXa, which highlighted the need for a careful system setup to obtain stable simulations. Here, we show that these simulations can be used to predict the free energy of binding of several fXa inhibitors. We tested molecular mechanics/Poisson-Boltzmann surface area, molecular mechanics/Generalized Born surface area, and linear interaction energy (LIE) on a small data set of fXa ligands. The continuum solvent approaches only yield satisfying correlations to the experimental results if some of the water molecules are explicitly included in the free energy calculations. LIE gave reasonable results if a sufficiently large data set is used. In general, our procedure of setting up the fXa simulation system enabled MD simulations, which produce adequate ensembles for free energy calculations.

A GRID-derived water network stabilizes molecular dynamics computer simulations of a protease.

Structural water molecules are crucial for the stability and function of proteins. Recently, we presented a molecular dynamics (MD) study on blood coagulation factor Xa (fXa) to investigate the effect of water molecules on the flexibility of the protein structure. We showed that neglecting important water positions at the outset of the simulation leads to severe structural distortions during the MD simulations: A stable trajectory was obtained with a water set that was derived from all 73 X-ray structures of the protein. However, for many proteins of interest, only limited structural data is available, which precludes the merging of information from many X-ray structures. Here, we show that an in silico assembled water network, derived from molecular interaction fields generated with the GRID program, is a viable alternative to X-ray data. MD simulations with the GRID water set show a significantly improved stability over alternative setups without water or the X-ray resolved water molecules in the starting structure. The performance is comparable to a water setup derived from a recently presented clustering approach.

Backbone flexibility controls the activity and specificity of a protein-protein interface: specificity in snake venom metalloproteases.

Protein-protein interfaces have crucial functions in many biological processes. The large interaction areas of such interfaces show complex interaction motifs. Even more challenging is the understanding of (multi)specificity in protein-protein binding. Many proteins can bind several partners to mediate their function. A perfect paradigm to study such multispecific protein-protein interfaces are snake venom metalloproteases (SVMPs). Inherently, they bind to a variety of basement membrane proteins of capillaries, hydrolyze them, and induce profuse bleeding. However, despite having a high sequence homology, some SVMPs show a strong hemorrhagic activity, while others are (almost) inactive. We present computer simulations indicating that the activity to induce hemorrhage, and thus the capability to bind the potential reaction partners, is related to the backbone flexibility in a certain surface region. A subtle interplay between flexibility and rigidity of two loops seems to be the prerequisite for the proteins to carry out their damaging function. Presumably, a significant alteration in the backbone dynamics makes the difference between SVMPs that induce hemorrhage and the inactive ones.

Dispersion dominated halogen-π interactions: energies and locations of minima.

The interactions of halogen atoms with aromatic π-systems can be crucial for structural stability and ligand binding. However, many aspects of the nature and energetics of these interactions remain elusive. Therefore, we designed model systems mimicking the T-shaped complex of chloro- and bromobenzene with tyrosine as found, e.g., in serine protease-inhibitor complexes. Three dimensional potential energy surfaces (3D-PES) were calculated at a high level of theory, up to CCSD(T). On these 3D-PES the exact location of the minima and, even more important, the shape of favorable interaction regions were determined. We show that the height of the halogen atom above the tyrosine-ring is decisive, while the lateral position is of minor influence. Finally, a truncated harmonic potential is developed to modify the Amber/GAFF force field to shift the locations of the minima to the correct regions.

Interface dynamics explain assembly dependency of influenza neuraminidase catalytic activity.

Influenza virus neuraminidase (iNA) is a homotetrameric surface protein of the influenza virus and an established target for antiviral drugs. In contrast to neuraminidases (NAs) of other biological systems (non-iNAs), enzymatic activity of iNA is only observed in a quaternary assembly and iNA needs the tetramerization to mediate enzymatic activity. Obviously, differences on a molecular level between iNA and non-iNAs are responsible for this intriguing observation. Comparison between protein structures and multiple sequence alignment allow the identification of differences in amino acid composition in crucial regions of the enzyme, such as next to the conserved D151 and the 150-loop. These differences in amino acid sequence and protein tetramerization are likely to alter the dynamics of the system. Therefore, we performed molecular dynamics simulations to investigate differences in the molecular flexibility of monomers, dimers, and tetramers of iNAs of subtype N1 (avian 2004, pandemic 1918 and pandemic 2009 iNA) and as comparison the non-iNA monomer from Clostridium perfringens. We show that conformational transitions of iNA are crucially influenced by its assembly state. The protein-protein interface induces a complex hydrogen-bonding network between the 110-helix and the 150-loop, which consequently stabilizes the structural arrangement of the binding site. Therefore, we claim that these altered dynamics are responsible for the dependence of iNA's catalytic activity on the tetrameric assembly. Only the tetramerization-induced balance between stabilization and altered local flexibility in the binding site provides the appropriate arrangement of key residues for iNA's catalytic activity.

Entropy from state probabilities: hydration entropy of cations.

Entropy is an important energetic quantity determining the progression of chemical processes. We propose a new approach to obtain hydration entropy directly from probability density functions in state space. We demonstrate the validity of our approach for a series of cations in aqueous solution. Extensive validation of simulation results was performed. Our approach does not make prior assumptions about the shape of the potential energy landscape and is capable of calculating accurate hydration entropy values. Sampling times in the low nanosecond range are sufficient for the investigated ionic systems. Although the presented strategy is at the moment limited to systems for which a scalar order parameter can be derived, this is not a principal limitation of the method. The strategy presented is applicable to any chemical system where sufficient sampling of conformational space is accessible, for example, by computer simulations.

Dynamic regulation of phenylalanine hydroxylase by simulated redox manipulation.

Recent clinical studies revealed increased phenylalanine levels and phenylalanine to tyrosine ratios in patients suffering from infection, inflammation and general immune activity. These data implicated down-regulation of activity of phenylalanine hydroxylase by oxidative stress upon in vivo immune activation. Though the structural damage of oxidative stress is expected to be comparably small, a structural rationale for this experimental finding was lacking. Hence, we investigated the impact of side chain oxidation at two vicinal cysteine residues on local conformational flexibility in the protein by comparative molecular dynamics simulations. Analysis of backbone dynamics revealed a highly flexible loop region (Tyr138-loop) in proximity to the active center of phenylalanine hydroxylase. We observed elevated loop dynamics in connection with a loop movement towards the active site in the oxidized state, thereby partially blocking access for the substrate phenylalanine. These findings were confirmed by extensive replica exchange molecular dynamics simulations and serve as a first structural explanation for decreased enzyme turnover in situations of oxidative stress.

First Principles-Based Calculations of Free Energy of Binding: Application to Ligand Binding in a Self-Assembling Superstructure.

The accurate prediction of ligand binding affinities to a protein remains a desirable goal of computational biochemistry. Many available methods use molecular mechanics (MM) to describe the system, however, MM force fields cannot fully describe the complex interactions involved in binding, specifically electron transfer and polarization. First principles approaches can fully account for these interactions, and with the development of linear-scaling first principles programs, it is now viable to apply first principles calculations to systems containing tens of thousands of atoms. In this paper, a quantum mechanical Poisson-Boltzmann surface area approach is applied to a model of a protein-ligand binding cavity, the "tennis ball" dimer. Results obtained from this approach demonstrate considerable improvement over conventional molecular mechanics Poisson-Boltzmann surface area due to the more accurate description of the interactions in the system. For the first principles calculations in this study, the linear-scaling density functional theory program ONETEP is used, allowing the approach to be applied to receptor-ligand complexes of pharmaceutical interest that typically include thousands of atoms.

Stabilizing of a globular protein by a highly complex water network: a molecular dynamics simulation study on factor Xa.

The role of water molecules is increasingly attracting attention in structural biology, and many studies have demonstrated their crucial contribution to the stability and function of proteins. Here, we present molecular dynamics studies on factor Xa (fXa) to investigate the effect of water molecules in this serine protease. fXa is a key enzyme in the blood coagulation cascade, and thus, an important target for antithrombotic drugs. A reasonable representation of the structure is crucial for an investigation at the molecular level and, thus, a prerequisite for structure-based drug design. Simulations of well-resolved fXa X-ray structures with different sets of water molecules show the importance of a well-determined water set for the simulation. We discuss implications of different water sets on the structure and dynamics of fXa.