Residue-level Resolution Research Articles

A Protocol to Depict the Proteolytic Processes Using a Combination of Metal-Organic Materials (MOMs), Electron Paramagnetic Resonance (EPR), and Mass Spectrometry (MS).

Proteolysis is a critical biochemical process yet a challenging field to study experimentally due to the self-degradation of a protease and the complex, dynamic degradation steps of a substrate. Mass spectrometry (MS) is the traditional way for proteolytic studies, yet it is challenging when time-resolved, step-by-step details of the degradation process are needed. We recently found a way to resolve the cleavage site, preference/selectivity of cleavage regions, and proteolytic kinetics by combining site-directed spin labeling (SDSL) of protein substrate, time-resolved two-dimensional (2D) electron paramagnetic resonance (EPR) spectroscopy, protease immobilization via metal-organic materials (MOMs), and MS. The method has been demonstrated on a model substrate and protease, yet there is a lack of details on the practical operations to carry out our strategy. Thus, this protocol summarizes the key steps and considerations when carrying out the EPR/MS study on proteolytic processes, which can be generalized to study other protein/polypeptide substrates in proteolysis. Details for the experimental operation and cautions of each step are reported with figures illustrating the concepts. This protocol provides an effective approach to understanding the proteolytic process with the advantages of offering time-resolved, residue-level resolution of structural basis underlying the process. Such information is important for revealing the cleavage site and proteolytic mechanisms of unknown proteases. The advantage of EPR, probing the target substrate regardless of the complexities caused by the proteases and their self-degradation, offers a practically effective, rapid, and easy-to-operate approach to studying proteolysis. Key features • Combining protease immobilization, EPR, spin labeling, and MS experimental methods allows for the analysis of proteolysis process in real time. • Reveals cleavage site, kinetics of product generation, and preference of cleavage regions via time-resolved SDSL-EPR. • MS confirms EPR findings and helps depict the sequences and populations of the cleaved segments in real time. • The demonstrated method can be generalized to other proteins or polypeptide substrates upon proteolysis by other proteases.

IDPpred: a new sequence-based predictor for identification of intrinsically disordered protein with enhanced accuracy

Discovery of intrinsically disordered proteins (IDPs) and protein hybrids that contain both intrinsically disordered protein regions (IDPRs) along with ordered regions has changed the sequence–structure–function paradigm of protein. These proteins with lack of persistently fixed structure are often found in all organisms and play vital roles in various biological processes. Some of them are considered as potential drug targets due to their overrepresentation in pathophysiological processes. The major bottlenecks for characterizing such proteins are their occasional overexpression, difficulty in getting purified homogeneous form and the challenge of investigating them experimentally. Sequence-based prediction of intrinsic disorder remains a useful strategy especially for many large-scale proteomic investigations. However, worst accuracy still occurs for short disordered regions with less than ten residues, for the residues close to order–disorder boundaries, for regions that undergo coupled folding and binding in presence of partner, and for prediction of fully disordered proteins. Annotation of fully disordered proteins mostly relies on the far-UV circular dichroism experiment which gives overall secondary structure composition without residue-level resolution. Current methods including that using secondary structure information failed to predict half of target IDPs correctly in the recent Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment. This study utilized profiles of random sequential appearance of physicochemical properties of amino acids and random sequential appearance of order and disorder promoting amino acids in protein together with the existing CIDER feature for the prediction of IDP from sequence input. Our method was found to significantly outperform the existing predictors across different datasets.Communicated by Ramaswamy H. Sarma

Myristoyl's dual role in allosterically regulating and localizing Abl kinase.

c-Abl kinase, a key signalling hub in many biological processes ranging from cell development to proliferation, is tightly regulated by two inhibitory Src homology domains. An N-terminal myristoyl-modification can bind to a hydrophobic pocket in the kinase C-lobe, which stabilizes the auto-inhibitory assembly. Activation is triggered by myristoyl release. We used molecular dynamics simulations to show how both myristoyl and the Src homology domains are required to impose the full inhibitory effect on the kinase domain, and reveal the allosteric transmission pathway at residue-level resolution. Importantly, we find myristoyl insertion into a membrane to thermodynamically compete with binding to c-Abl. Myristoyl thus not only localizes the protein to the cellular membrane, but membrane attachment at the same time enhances activation of c-Abl by stabilizing its pre-activated state. Our data put forward a model in which lipidation tightly couples kinase localization and regulation, a scheme that currently appears to be unique for this non-receptor tyrosine kinase.

Progress toward Proteome-Wide Photo-Cross-Linking to Enable Residue-Level Visualization of Protein Structures and Networks In Vivo.

Cross-linking mass spectrometry (XL-MS) is emerging as a method at the crossroads of structural and cellular biology, uniquely capable of identifying protein-protein interactions with residue-level resolution and on the proteome-wide scale. With the development of cross-linkers that can form linkages inside cells and easily cleave during fragmentation on the mass spectrometer (MS-cleavable cross-links), it has become increasingly facile to identify contacts between any two proteins in complex samples, including in live cells or tissues. Photo-cross-linkers possess the advantages of high temporal resolution and high reactivity, thereby engaging all residue-types (rather than just lysine); nevertheless, photo-cross-linkers have not enjoyed widespread use and are yet to be employed for proteome-wide studies because their products are challenging to identify. Here, we demonstrate the synthesis and application of two heterobifunctional photo-cross-linkers that feature diazirines and N-hydroxy-succinimidyl carbamate groups, the latter of which unveil doubly fissile MS-cleavable linkages upon acyl transfer to protein targets. Moreover, these cross-linkers demonstrate high water-solubility and cell-permeability. Using these compounds, we demonstrate the feasibility of proteome-wide photo-cross-linking in cellulo. These studies elucidate a small portion of Escherichia coli's interaction network, albeit with residue-level resolution. With further optimization, these methods will enable the detection of protein quinary interaction networks in their native environment at residue-level resolution, and we expect that they will prove useful toward the effort to explore the molecular sociology of the cell.

A complete allosteric map of a GTPase switch in its native cellular network.

Allosteric regulation is central to protein function in cellular networks. A fundamental open question is whether cellular regulation of allosteric proteins occurs only at a few defined positions or at many sites distributed throughout the structure. Here, we probe the regulation of GTPases-protein switches that control signaling through regulated conformational cycling-at residue-level resolution by deep mutagenesis in the native biological network. For the GTPase Gsp1/Ran, we find that 28% of the 4,315 assayed mutations show pronounced gain-of-function responses. Twenty of the sixty positions enriched for gain-of-function mutations are outside the canonical GTPase active site switch regions. Kinetic analysis shows that these distal sites are allosterically coupled to the active site. We conclude that the GTPase switch mechanism is broadly sensitive to cellular allosteric regulation. Our systematic discovery of new regulatory sites provides a functional map to interrogate and target GTPases controlling many essential biological processes.

Covalent Labeling with Diethylpyrocarbonate for Studying Protein Higher-Order Structure by Mass Spectrometry.

Characterizing a protein's higher-order structure is essential for understanding its function. Mass spectrometry (MS) has emerged as a powerful tool for this purpose, especially for protein systems that are difficult to study by traditional methods. To study a protein's structure by MS, specific chemical reactions are performed in solution that encode a protein's structural information into its mass. One particularly effective approach is to use reagents that covalently modify solvent accessible amino acid side chains. These reactions lead to mass increases that can be localized with residue-level resolution when combined with proteolytic digestion and tandem mass spectrometry. Here, we describe the protocols associated with use of diethylpyrocarbonate (DEPC) as a covalent labeling reagent together with MS detection. DEPC is a highly electrophilic molecule capable of labeling up to 30% of the residues in the average protein, thereby providing excellent structural resolution. DEPC has been successfully used together with MS to obtain structural information for small single-domain proteins, such as β2-microglobulin, to large multi-domain proteins, such as monoclonal antibodies.

NMR Reporter Assays for the Quantification of Weak-Affinity Receptor-Ligand Interactions.

Biophysical methods are widely employed in academia and the pharmaceutical industry to detect and quantify weak molecular interactions. Such methods find broad application in fragment-based drug discovery (FBDD). In an FBDD campaign, a suitable affinity determination method is key to advancing a project beyond the initial screening phase. Protein-observed (PO) nuclear magnetic resonance (NMR) finds widespread use due to its ability to sensitively detect very weak interactions at residue-level resolution. When there are issues precluding the use of PO-NMR, ligand-observed (LO) NMR reporter assays can be a useful alternative. Such assays can measure affinities in a similar range to PO-NMR while offering some distinct advantages, especially with regard to protein consumption and compound throughput. In this paper, we take a closer look at setting up such assays for routine use, with the aim of getting high-quality, accurate data and good throughput. We assess some of the key characteristics of these assays in the mathematical framework established for fluorescence polarization assays with which the readers may be more familiar. We also provide guidance on setting up such assays and compare their performance with other affinity determination methods that are commonly used in drug discovery.

Combining High-Pressure Perturbation with NMR Spectroscopy for a Structural and Dynamical Characterization of Protein Folding Pathways.

High-hydrostatic pressure is an alternative perturbation method that can be used to destabilize globular proteins. Generally perfectly reversible, pressure exerts local effects on regions or domains of a protein containing internal voids, contrary to heat or chemical denaturant that destabilize protein structures uniformly. When combined with NMR spectroscopy, high pressure (HP) allows one to monitor at a residue-level resolution the structural transitions occurring upon unfolding and to determine the kinetic properties of the process. The use of HP-NMR has long been hampered by technical difficulties. Owing to the recent development of commercially available high-pressure sample cells, HP-NMR experiments can now be routinely performed. This review summarizes recent advances of HP-NMR techniques for the characterization at a quasi-atomic resolution of the protein folding energy landscape.

Quantitative Cooperative Binding Model for Intrinsically Disordered Proteins Interacting with Nanomaterials.

Intrinsically disordered proteins (IDPs) can display a broad spectrum of binding modes and highly variable binding affinities when interacting with both biological and nonbiological materials. A quantitative model of such behavior is important for the better understanding of the function of IDPs when encountering inorganic nanomaterials with the potential to control their behavior in vivo and in vitro. Depending on their amino acid composition and chain length, binding properties can vary strongly between different IDPs. Moreover, due to differences in the physical chemical properties of clusters of amino acid residues along the IDP primary sequence, individual residues can adopt a wide range of bound state populations. Quantitative experimental binding affinities with synthetic silica nanoparticles (SNPs) at residue-level resolution, which were obtained for a set of IDPs by solution NMR relaxation experiments, are explained here by a first-principle analytical statistical mechanical model termed SILC. SILC quantitatively predicts residue-specific binding affinities to nanoparticles and it expresses binding cooperativity as the cumulative result of pairwise residue effects. The model, which was parametrized for anionic SNPs and applied to experimental data of four IDP systems with distinctive binding behavior, successfully predicts differences in overall binding affinities, fine details of IDP-SNP affinity profiles, and site-directed mutagenesis effects with a spatial resolution at the individual residue level. The SILC model provides an analytical description of such types of fuzzy IDP-SNP complexes and may help advance understanding nanotoxicity and in vivo targeting of IDPs by specifically designed nanomaterials.

Investigating the Residue-Level Dynamics of the Thrombin-Thrombomodulin Interaction

The serine protease, thrombin catalyzes the final step in the blood clotting cascade by cleaving, and thereby activating, proteins in the blood that consequently form a blood clot. However, thrombin has also demonstrated an anticoagulative role as well, which is initiated by the binding of the cofactor thrombomodulin to thrombin, and is characterized by a change in thrombin substrate affinity away from procoagulative substrates and towards activation of protein C instead. Despite decades of study, the mechanism behind this shift in the substrate preference of thrombin remains unclear. However, evidence from previous studies suggests that this change in activity results from changes in the intermolecular protein dynamics of thrombin that are induced by the binding of thrombomodulin. As a result, the thrombin-thrombomodulin interaction has been suggested to undergo dynamic allostery. Hydrogen-Deuterium Exchange Mass Spectrometry (HDX-MS) experiments have been used to identify the solvent-exposed regions of thrombin that undergo changes in protein dynamics when thrombomodulin is present, yet the limits of the HDX-MS technique prevent the identification of changes at residue-level resolution, as well as any changes in motion of residues buried in the protein core of thrombin. In order to supplement the HDX-MS data collected, Curr-Purcell-Meibloom-Gill (CPMG) NMR experiments have been conducted on S195M mutant thrombin in the presence of thrombomodulin. The results of these experiments will be compared to previous CPMG results published on S195M Mutant thrombin in the absence of thrombomodulin in order to identify which residues are affected by the binding of thrombomodulin to thrombin. Thus, by comparing the rates of transitions to rare states determined from the CPMG experiments, new insights regarding the allosteric transition between thrombin's procoagulative and anticoagulative states will be obtained.

Folding of the Ig-Like Domain of the Dengue Virus Envelope Protein Analyzed by High-Hydrostatic-Pressure NMR at a Residue-Level Resolution.

Dengue fever is a mosquito-borne endemic disease in tropical and subtropical regions, causing a significant public health problem in Southeast Asia. Domain III (ED3) of the viral envelope protein contains the two dominant putative epitopes and part of the heparin sulfate receptor binding region that drives the dengue virus (DENV)’s fusion with the host cell. Here, we used high-hydrostatic-pressure nuclear magnetic resonance (HHP-NMR) to obtain residue-specific information on the folding process of domain III from serotype 4 dengue virus (DEN4-ED3), which adopts the classical three-dimensional (3D) ß-sandwich structure known as the Ig-like fold. Interestingly, the folding pathway of DEN4-ED3 shares similarities with that of the Titin I27 module, which also adopts an Ig-like fold, but is functionally unrelated to ED3. For both proteins, the unfolding process starts by the disruption of the N- and C-terminal strands on one edge of the ß-sandwich, yielding a folding intermediate stable over a substantial pressure range (from 600 to 1000 bar). In contrast to this similarity, pressure-jump kinetics indicated that the folding transition state is considerably more hydrated in DEN4-ED3 than in Titin I27.

ExMS2: An Integrated Solution for Hydrogen-Deuterium Exchange Mass Spectrometry Data Analysis.

Hydrogen-deuterium exchange mass spectrometry (HDX MS) has become an important technique for the analysis of protein structure and dynamics. Data analysis remains a bottleneck in the workflow. Sophisticated computer analysis is required to scan through the voluminous MS output in order to find, identify, and validate many partially deuterated peptides, elicit the HDX information, and extend the results to higher structural resolution. We previously made available two software suites, ExMS for identification and analysis of peptide isotopic envelopes in the HDX MS raw data and HDsite for residue-level resolution. Further experience has led to advances in the usability and performance of both programs. Also, newly added modules deal with ETD/ECD analysis, multimodal mass spectra analysis, and presentation options. These advances have been integrated into a stand-alone software solution named ExMS2. The package has been successfully tested by many workers in fine scale epitope mapping, in protein folding studies, and in dissecting structure and structure change of large protein complexes. A description and tutorial for this major upgrade are given here.

Enhanced H/D exchange unravels sequential structural excursions in G57W variant of human γS-crystallin with pro-cataractogenic conformations

Our two recent reports on the high resolution NMR structure and conformational dynamics of G57W variant of human γS-crystallin (abbreviated as γS-G57W) causing severe infantile cataracts, revealed slackening of its N-terminal domain with enhanced local conformational dynamics attributed to mutation. Exploring the biochemistry of infantile cataracts in detail, here we studied structural unfolding in both human γS-WT and γS-G57W at residue level resolution using solution NMR spectroscopy and chemical kinetics and characterized the molecular intermediates with functional consequences. We report, for the first time, that human γS-crystallin unfolds sequentially under H/D exchange. This communication forms the first experimental evidence for non-concerted destabilization of structural foldon units in human γS-G57W. Residues contributing to the compact fold and structural stability exchanged their amide protons with deuterons more readily in γS-G57W compared to γS-WT, displaying differential free energies of exchange. Overall, our results establish a direct conformational link between the structure, dynamics, design and function in human γS-crystallin such that the G57W cataract variant promotes enhanced structural excursions concomitant with increased instability, elucidating very crucial molecular details of cataract formation affecting infants across the globe.

Backmapping from Multiresolution Coarse-Grained Models to Atomic Structures of Large Biomolecules by Restrained Molecular Dynamics Simulations Using Bayesian Inference.

Coarse-grained (CG) simulations have allowed access to larger length scales and longer time scales in the study of the dynamic processes of large biomolecules than all-atom (AA) molecular dynamics (MD) simulations. Backmapping from CG models to AA structures has long been studied because it enables us to gain detailed structure insights from CG simulations. Many methods first construct an AA structure from the CG model by fragments, random placement, or geometrical rules and subsequently optimize the solution via energy minimization, simulated annealing or position-restrained simulations. However, such methods may only work well on residue-level CG models and cannot consider the deviations of CG models. In this work, we describe, to the best of our knowledge, a new backmapping method based on Bayesian inference and restrained MD simulations. Restraints with log harmonic energy terms are defined according to the target CG model using the Bayesian inference in which the CG deviations can be estimated. From an initial AA structure obtained from either high-resolution experiments or homology modeling, a MD simulation with the aforementioned restraints is performed to obtain a final AA structure that is a backmapping of the target CG model. The method was validated using multiresolution CG models of the soluble extracellular region of the human epidermal growth factor receptor and was further applied to construct AA structures from CG simulations of the nucleosome core particle. The results demonstrate that our method can generate accurate AA structures of different types of biomolecules from multiple CG models with either residue-level resolution or much lower resolution than one-site-per-residue.

Mass spectrometric approaches for profiling protein folding and stability.

Protein stability reports on protein homeostasis, function, and binding interactions, such as to other proteins, metabolites and drugs. As such, there is a pressing need for technologies that can report on protein stability. The ideal technique could be applied in vitro or in vivo systems, proteome-wide, independently of matrix, under native conditions, with residue-level resolution, and on protein at endogenous levels. Mass spectrometry has rapidly become a preferred technology for identifying and quantifying proteins. As such, it has been increasingly incorporated into methodologies for interrogating protein stability and folding. Although no single technology can satisfy all desired applications, several emerging approaches have shown outstanding success at providing biological insight into the stability of the proteome. This chapter outlines some of these recent emerging technologies.

Protein-Ligand Interaction by Ligand Titration, Fast Photochemical Oxidation of Proteins and Mass Spectrometry: LITPOMS.

We report a novel method named LITPOMS (ligand titration, fast photochemical oxidation of proteins and mass spectrometry) to characterize protein-ligand binding stoichiometry, binding sites, and site-specific binding constants. The system used to test the method is melittin-calmodulin, in which the peptide melittin binds to calcium-bound calmodulin. Global-level measurements reveal the binding stoichiometry of 1:1 whereas peptide-level data coupled with fitting reveal the binding sites and the site-specific binding affinity. Moreover, we extended the analysis to the residue level and identified six critical binding residues. The results show that melittin binds to the N-terminal, central linker, and C-terminal regions of holo-calmodulin with an affinity of 4.6nM, in agreement with results of previous studies. LITPOMS, for the first time, brings high residue-level resolution to affinity measurements, providing simultaneously qualitative and quantitative understanding of protein-ligand binding. The approach can be expanded to other binding systems without tagging the protein to give high spatial resolution. Graphical Abstract.

Abstract 2262: Inference of kinase activity for cancer phosphoproteomics using substrate prediction scores

Abstract Background: Quantification of global protein phosphorylation abundance levels with residue-level resolution is feasible with mass spectrometry and phosphopeptide enrichment methods. Researchers have inferred kinase activity from phosphoproteomics data using a variety of methods to extract interpretable and biologically relevant information, but analysis of phosphoproteomics data is limited by the fact that detected phosphorylation sites often have unknown function and relevance. Methods: We developed a novel method for aggregating and interpreting phosphoproteomics data that combines kinase prediction scores from NetworKIN with experimental summary statistics to estimate abundance changes in predicted kinase substrates. By weighting student t-statistic scores by kinase prediction scores and summing cumulative scores across all phosphopeptides detected in a given screen, we generated kinase activity scores that reflect the overall direction, magnitude and significance of observed changes in predicted kinase substrates. These kinase scores were assessed using permutation testing to determine their significance versus changes that would be expected from random chance. To evaluate our method, we applied it to a shotgun phosphoproteomic dataset generated to study phosphorylation responses to rapamycin, dasatinib and combination treatment in MDA-MB-231 breast cancer cells. Results: We were able to confirm phosphoproteomic perturbations in expected “hallmark” kinase activities using prediction-based kinase activity inference scores, including decreased phosphorylation of Src and Abl substrates in response to dasatinib treatment, as well as decreases in p70S6K substrate phosphorylation in response to rapamycin. Compared to KSEA, we identified changes in substrate abundance for a variety of potential downstream kinases including DNAPK, PAK2, CDK3, and multiple members of the MAPK family that were observed to be downregulated in single-agent and in combination treatment. Conclusions: Our novel method provides a representation of phosphoproteomic changes based on abundance of predicted kinase substrates. Using predicted substrates allows for a global view of phosphoproteomic changes that extends beyond the relatively small number of known kinase-substrate relationships. Using a drug combination with potential application in breast cancer as an example, we demonstrate that this method can be used to identify phosphoproteomic changes and can potentially be used to rationally design and investigate novel drug combinations. Citation Format: Peter Liao, Jennifer Yori, Ruth Keri, Mehmet Koyuturk, Jill Barnholtz-Sloan. Inference of kinase activity for cancer phosphoproteomics using substrate prediction scores [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2262.

Structurally Guided In Vivo Crosslinking.

The focus of modern molecular biology on protein structure and function has reached unparalleled levels. Whether interacting with nucleic acids or other proteins, protein contacts are the basis for fine-tuning all cellular processes. It is for this reason imperative that protein interactions are studied in ways that reflect actual events taking place inside living cells.Here, we describe in detail a method that combines the residue-level resolution provided by structural biology with physiological studies inside living cells, with the overall goal of explaining the contribution of protein-protein interactions in cellular processes. We use as a powerful example our experience with the DNA exit gate interface of the chromosomal cohesin complex, and we argue that this methodology may be followed to address similar questions within any protein complex and in various model systems.

Molecular mechanism of G\u03b1i activation by non-GPCR proteins with a G\u03b1-Binding and Activating motif

Heterotrimeric G proteins are quintessential signalling switches activated by nucleotide exchange on Gα. Although activation is predominantly carried out by G-protein-coupled receptors (GPCRs), non-receptor guanine-nucleotide exchange factors (GEFs) have emerged as critical signalling molecules and therapeutic targets. Here we characterize the molecular mechanism of G-protein activation by a family of non-receptor GEFs containing a Gα-binding and -activating (GBA) motif. We combine NMR spectroscopy, computational modelling and biochemistry to map changes in Gα caused by binding of GBA proteins with residue-level resolution. We find that the GBA motif binds to the SwitchII/α3 cleft of Gα and induces changes in the G-1/P-loop and G-2 boxes (involved in phosphate binding), but not in the G-4/G-5 boxes (guanine binding). Our findings reveal that G-protein-binding and activation mechanisms are fundamentally different between GBA proteins and GPCRs, and that GEF-mediated perturbation of nucleotide phosphate binding is sufficient for Gα activation.

Stability and orientation of cecropin P1 on maleimide self-assembled monolayer (SAM) surfaces and suggested functional mutations

One of the main challenges of biosensor design is to understand the protein or peptide stability on the chip in high resolution structural detail. Since conventional experimental methods are limited by the resolution for their applications on surface tethered peptides/proteins, a recently developed coarse grained simulation method is employed to explore the peptide/surface interaction in residue-level resolution. This work shows how the coarse grained model successfully describes peptide–surface interactions by evaluating thermal stability of the peptide cecropin P1 in bulk solution and on surfaces by physical adsorption and chemical tethering. The simulation also reproduces observations of peptide orientations on the self-assembled monolayer surface from earlier experimental work. Additionally, using knowledge obtained from the simulations, specific mutations are suggested and the desired structure and pose on the surface is obtained. In summary, this work sheds a light on the reasonable biosensor design that is guided by simulations.