Prediction of Residue Status to Be Protected or Not Protected From Hy-drogen Exchange Using Amino Acid Sequence Only

Exploring Compactness and Dynamics of Apomyoglobin

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) approach has become a valuable analytical complement to traditional methods. HDX-MS allows the identification of dynamic surfaces in proteins. We have shown that the introduction of various mutations into the amino acid sequence of whale apomyoglobin (apoMb) leads to a change in the number of exchangeable hydrogen atoms, which is associated with a change in its compactness in the native-like condition. Thus, amino acid substitutions V10A, A15S, P120G, and M131A result in an increase in the number of exchangeable hydrogen atoms at the native-like condition, while the mutant form A144S leads to a decrease in the number of exchangeable hydrogen atoms. This may be due to a decrease and increase in the compactness of apoMb structure compared to the wild-type apoMb, respectively. The L9F and L9E mutations did not affect the compactness of the molecule compared to the wild type. We have demonstrated that V10A and M131A substitutions lead to the maximum and large increase correspondently in the average number of exchangeable hydrogen atoms for deuterium, since these substitutions lead to the loss of contacts between important parts of myoglobin structure: helices A, G, and H, which are structured at the early stage of folding.

Computational Structure Prediction for Antibody-Antigen Complexes From Hydrogen-Deuterium Exchange Mass Spectrometry: Challenges and Outlook

Although computational structure prediction has had great successes in recent years, it regularly fails to predict the interactions of large protein complexes with residue-level accuracy, or even the correct orientation of the protein partners. The performance of computational docking can be notably enhanced by incorporating experimental data from structural biology techniques. A rapid method to probe protein-protein interactions is hydrogen-deuterium exchange mass spectrometry (HDX-MS). HDX-MS has been increasingly used for epitope-mapping of antibodies (Abs) to their respective antigens (Ags) in the past few years. In this paper, we review the current state of HDX-MS in studying protein interactions, specifically Ab-Ag interactions, and how it has been used to inform computational structure prediction calculations. Particularly, we address the limitations of HDX-MS in epitope mapping and techniques and protocols applied to overcome these barriers. Furthermore, we explore computational methods that leverage HDX-MS to aid structure prediction, including the computational simulation of HDX-MS data and the combination of HDX-MS and protein docking. We point out challenges in interpreting and incorporating HDX-MS data into Ab-Ag complex docking and highlight the opportunities they provide to build towards a more optimized hybrid method, allowing for more reliable, high throughput epitope identification.

Computational Modeling of Molecular Structures Guided by Hydrogen-Exchange Data

Data produced by hydrogen-exchange monitoring experiments have been used in structural studies of molecules for several decades. Despite uncertainties about the structural determinants of hydrogen exchange itself, such data have successfully helped guide the structural modeling of challenging molecular systems, such as membrane proteins or large macromolecular complexes. As hydrogen-exchange monitoring provides information on the dynamics of molecules in solution, it can complement other experimental techniques in so-called integrative modeling approaches. However, hydrogen-exchange data have often only been used to qualitatively assess molecular structures produced by computational modeling tools. In this paper, we look beyond qualitative approaches and survey the various paradigms under which hydrogen-exchange data have been used to quantitatively guide the computational modeling of molecular structures. Although numerous prediction models have been proposed to link molecular structure and hydrogen exchange, none of them has been widely accepted by the structural biology community. Here, we present as many hydrogen-exchange prediction models as we could find in the literature, with the aim of providing the first exhaustive list of its kind. From purely structure-based models to so-called fractional-population models or knowledge-based models, the field is quite vast. We aspire for this paper to become a resource for practitioners to gain a broader perspective on the field and guide research toward the definition of better prediction models. This will eventually improve synergies between hydrogen-exchange monitoring and molecular modeling.

POPPeT: a New Method to Predict the Protection Factor of Backbone Amide Hydrogens

Hydrogen exchange (HX) has become an important tool to monitor protein structure and dynamics. The interpretation of HX data with respect to protein structure requires understanding of the factors that influence exchange. Simulated protein structures can be validated by comparing experimental deuteration profiles with the profiles derived from the modeled protein structure. To do this, we propose here a new method, POPPeT, for protection factor prediction based on protein motions that enable HX. By comparing POPPeT with two existing methods, the phenomenological approximation and COREX, we show enhanced predictability measured at both protection factor and deuteration level. This method can be subsequently used by modeling strategies for protein structure prediction. Graphical Abstract ᅟ.

Probing protein ensemble rigidity and hydrogen-deuterium exchange

Protein rigidity and flexibility can be analyzed accurately and efficiently using the program floppy inclusion and rigid substructure topography (FIRST). Previous studies using FIRST were designed to analyze the rigidity and flexibility of proteins using a single static (snapshot) structure. It is however well known that proteins can undergo spontaneous sub-molecular unfolding and refolding, or conformational dynamics, even under conditions that strongly favor a well-defined native structure. These (local) unfolding events result in a large number of conformers that differ from each other very slightly. In this context, proteins are better represented as a thermodynamic ensemble of 'native-like' structures, and not just as a single static low-energy structure. Working with this notion, we introduce a novel FIRST-based approach for predicting rigidity/flexibility of the protein ensemble by (i) averaging the hydrogen bonding strengths from the entire ensemble and (ii) by refining the mathematical model of hydrogen bonds. Furthermore, we combine our FIRST-ensemble rigidity predictions with the ensemble solvent accessibility data of the backbone amides and propose a novel computational method which uses both rigidity and solvent accessibility for predicting hydrogen-deuterium exchange (HDX). To validate our predictions, we report a novel site specific HDX experiment which characterizes the native structural ensemble of Acylphosphatase from hyperthermophile Sulfolobus solfataricus (Sso AcP). The sub-structural conformational dynamics that is observed by HDX data, is closely matched with the FIRST-ensemble rigidity predictions, which could not be attained using the traditional single 'snapshot' rigidity analysis. Moreover, the computational predictions of regions that are protected from HDX and those that undergo exchange are in very good agreement with the experimental HDX profile of Sso AcP.

Stability and rigidity/flexibility-two sides of the same coin?

Protein molecules require both flexibility and rigidity for functioning. The fast and accurate prediction of protein rigidity/flexibility is one of the important problems in protein science. We have determined flexible regions for four homologous pairs from thermophilic and mesophilic organisms by two methods: the fast FoldUnfold which uses amino acid sequence and the time consuming MDFirst which uses three-dimensional structures. We demonstrate that both methods allow determining flexible regions in protein structure. For three of the four thermophile-mesophile pairs of proteins, FoldUnfold predicts practically the same flexible regions which have been found by the MD/First method. As expected, molecular dynamics simulations show that thermophilic proteins are more rigid in comparison to their mesophilic homologues. Analysis of rigid clusters and their decomposition provides new insights into protein stability. It has been found that the local networks of salt bridges and hydrogen bonds in thermophiles render their structure more stable with respect to fluctuations of individual contacts. Such network includes salt bridge triads Agr-Glu-Lys and Arg-Glu-Arg, or salt bridges (such as Arg-Glu) connected with hydrogen bonds. This ionic network connects alpha helices and rigidifies the structure. Mesophiles can be characterized by stand alone salt bridges and hydrogen bonds or small ionic clusters. Such difference in the network of salt bridges results in different flexibility of homologous proteins. Combining both approaches allows characterizing structural features in atomic detail that determine the rigidity/flexibility of a protein structure. This article is a part of a Special Issue entitled: The emerging dynamic view of proteins: Protein plasticity in allostery, evolution and self-assembly.

Structure fluctuations and conformational changes in protein binding

Structure fluctuations and conformational changes accompany all biological processes involving macromolecules. The paper presents a classification of protein residues based on the normalized equilibrium fluctuations of the residue centers of mass in proteins and a statistical analysis of conformation changes in the side-chains upon binding. Normal mode analysis and an elastic network model were applied to a set of protein complexes to calculate the residue fluctuations and develop the residue classification. Comparison with a classification based on normalized B-factors suggests that the B-factors may underestimate protein flexibility in solvent. Our classification shows that protein loops and disordered fragments are enriched with highly fluctuating residues and depleted with weakly fluctuating residues. Strategies for engineering thermostable proteins are discussed. To calculate the dihedral angles distribution functions, the configuration space was divided into cells by a cubic grid. The effect of protein association on the distribution functions depends on the amino acid type and a grid step in the dihedral angles space. The changes in the dihedral angles increase from the near-backbone dihedral angle to the most distant one, for most residues. On average, one fifth of the interface residues change the rotamer state upon binding, whereas the rest of the interface residues undergo local readjustments within the same rotamer.

Flexibility and mobility in mesophilic and thermophilic homologous proteins from molecular dynamics and FoldUnfold method

To function properly protein molecules require both flexibility and rigidity, therefore fast and accurate prediction of protein rigidity/flexibility is one of the important problems in protein science. In this work we used two theoretical approaches to determine flexible regions in four homologous pairs of proteins from thermophilic and mesophilic organisms. Protein pairs chosen in this study were selected to represent four typical folding classes. Our first approach, FoldUnfold, uses amino acid sequence and statistical information on the density of contacts of amino acids in tertiary structures of known globular proteins. The main advantages of such knowledge-based methodology are its computational speed and ability to make predictions in the absence of three-dimensional (3D) structure of a protein. The second approach uses a graph theory-based rigid cluster decomposition termed FIRST, applied together with Molecular Dynamics (MD) simulations of proteins with known structure. While MD simulations are time-consuming, they are the most direct way of studying physical properties of proteins, including their rigidity/flexibility. Flexible regions predicted by both methods in this work were in good agreement with each other. We also showed that high mobility of a site is not necessarily indicative of its high flexibility and vice versa. In our simulations thermophile proteins were less flexible than their mesophilic homologues. Longer flexible loops were found in mesophilic proteins of all classes.