Theoretical modeling of multiprotein complexes by iSPOT: Integration of small-angle X-ray scattering, hydroxyl radical footprinting, and computational docking

Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery

Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.

Protein complex prediction using Rosetta, AlphaFold, and mass spectrometry covalent labeling

Covalent labeling (CL) in combination with mass spectrometry can be used as an analytical tool to study and determine structural properties of protein-protein complexes. However, data from these experiments is sparse and does not unambiguously elucidate protein structure. Thus, computational algorithms are needed to deduce structure from the CL data. In this work, we present a hybrid method that combines models of protein complex subunits generated with AlphaFold with differential CL data via a CL-guided protein-protein docking in Rosetta. In a benchmark set, the RMSD (root-mean-square deviation) of the best-scoring models was below 3.6 Å for 5/5 complexes with inclusion of CL data, whereas the same quality was only achieved for 1/5 complexes without CL data. This study suggests that our integrated approach can successfully use data obtained from CL experiments to distinguish between nativelike and non-nativelike models.

Incorporation of D2O-Induced Fluorine Chemical Shift Perturbations into Ensemble-Structure Characterization of the ERalpha Disordered Region

Structural characterization of intrinsically disordered proteins (IDPs) requires a concerted effort between experiments and computations by accounting for their conformational heterogeneity. Given the diversity of experimental tools providing local and global structural information, constructing an experimental restraint-satisfying structural ensemble remains challenging. Here, we use the disordered N-terminal domain (NTD) of the estrogen receptor alpha (ERalpha) as a model system to combine existing small-angle X-ray scattering (SAXS) and hydroxyl radical protein footprinting (HRPF) data and newly acquired solvent accessibility data via D2O-induced fluorine chemical shifting (DFCS) measurements. A new set of DFCS data for the solvent exposure of a set of 12 amino acid positions were added to complement previously acquired HRPF measurements for the solvent exposure of the other 16 nonoverlapping amino acids, thereby improving the NTD ensemble characterization considerably. We also found that while choosing an initial ensemble of structures generated from a different atomic-level force field or sampling/modeling method can lead to distinct contact maps even when the same sets of experimental measurements were used for ensemble-fitting, comparative analyses from these initial ensembles reveal commonly recurring structural features in their ensemble-averaged contact map. Specifically, nonlocal or long-range transient interactions were found consistently between the N-terminal segments and the central region, sufficient to mediate the conformational ensemble and regulate how the NTD interacts with its coactivator proteins.

Recent advances in structural characterization of biomacromolecules in foods via small-angle X-ray scattering

Small-angle X-ray scattering (SAXS) is a method for examining the solution structure, oligomeric state, conformational changes, and flexibility of biomacromolecules at a scale ranging from a few Angstroms to hundreds of nanometers. Wide time scales ranging from real time (milliseconds) to minutes can be also covered by SAXS. With many advantages, SAXS has been extensively used, it is widely used in the structural characterization of biomacromolecules in food science and technology. However, the application of SAXS in charactering the structure of food biomacromolecules has not been reviewed so far. In the current review, the principle, theoretical calculations and modeling programs are summarized, technical advances in the experimental setups and corresponding applications of in situ capabilities: combination of chromatography, time-resolved, temperature, pressure, flow-through are elaborated. Recent applications of SAXS for monitoring structural properties of biomacromolecules in food including protein, carbohydrate and lipid are also highlighted, and limitations and prospects for developing SAXS based on facility upgraded and artificial intelligence to study the structural properties of biomacromolecules are finally discussed. Future research should focus on extending machine time, simplifying SAXS data treatment, optimizing modeling methods in order to achieve an integrated structural biology based on SAXS as a practical tool for investigating the structure-function relationship of biomacromolecules in food industry.

New system for archiving integrative structures

Structures of many complex biological assemblies are increasingly determined using integrative approaches, in which data from multiple experimental methods are combined. A standalone system, called PDB-Dev, has been developed for archiving integrative structures and making them publicly available. Here, the data standards and software tools that support PDB-Dev are described along with the new and updated components of the PDB-Dev data-collection, processing and archiving infrastructure. Following the FAIR (Findable, Accessible, Interoperable and Reusable) principles, PDB-Dev ensures that the results of integrative structure determinations are freely accessible to everyone.

Hydroxyl Radical Protein Footprinting: A Mass Spectrometry-Based Structural Method for Studying the Higher Order Structure of Proteins

Hydroxyl radical protein footprinting (HRPF) coupled to mass spectrometry has been successfully used to investigate a plethora of protein-related questions. The method, which utilizes hydroxyl radicals to oxidatively modify solvent-accessible amino acids, can inform on protein interaction sites and regions of conformational change. Hydroxyl radical-based footprinting was originally developed to study nucleic acids, but coupling the method with mass spectrometry has enabled the study of proteins. The method has undergone several advancements since its inception that have increased its utility for more varied applications such as protein folding and the study of biotherapeutics. In addition, recent innovations have led to the study of increasingly complex systems including cell lysates and intact cells. Technological advances have also increased throughput and allowed for better control of experimental conditions. In this review, we provide a brief history of the field of HRPF and detail recent innovations and applications in the field.

Small-angle X-ray scattering for the proteomics community: current overview and future potential

Introduction: Proteins are biological nanoparticles. For structural proteomics and hybrid structural biology, complementary methods are required that allow both high throughput and accurate automated data analysis. Small-angle X-ray scattering (SAXS) is a method for observing the size and shape of particles, such as proteins and complexes, in solution. SAXS data can be used to model both the structure, oligomeric state, conformational changes, and flexibility of biomolecular samples.Areas covered: The key principles of SAXS, its sample requirements, and its current and future applications for structural proteomics are briefly reviewed. Recent technical developments in SAXS experiments are discussed, and future potential of the method in structural proteomics is evaluated.Expert opinion: SAXS is a method suitable for several aspects of integrative structural proteomics, with current technical developments allowing for higher throughput and time-resolved studies, as well as the analysis of complex samples, such as membrane proteins. Increasing automation and streamlined data analysis are expected to equip SAXS for structure-based screening workflows. Originally, structural genomics had a heavy focus on folded, crystallizable proteins and complexes - SAXS is a method allowing an expansion of this focus to flexible and disordered systems.

Structural Proteomics Methods to Interrogate the Conformations and Dynamics of Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) and regions of intrinsic disorder (IDRs) are abundant in proteomes and are essential for many biological processes. Thus, they are often implicated in disease mechanisms, including neurodegeneration and cancer. The flexible nature of IDPs and IDRs provides many advantages, including (but not limited to) overcoming steric restrictions in binding, facilitating posttranslational modifications, and achieving high binding specificity with low affinity. IDPs adopt a heterogeneous structural ensemble, in contrast to typical folded proteins, making it challenging to interrogate their structure using conventional tools. Structural mass spectrometry (MS) methods are playing an increasingly important role in characterizing the structure and function of IDPs and IDRs, enabled by advances in the design of instrumentation and the development of new workflows, including in native MS, ion mobility MS, top-down MS, hydrogen-deuterium exchange MS, crosslinking MS, and covalent labeling. Here, we describe the advantages of these methods that make them ideal to study IDPs and highlight recent applications where these tools have underpinned new insights into IDP structure and function that would be difficult to elucidate using other methods.

Hybrid methods for combined experimental and computational determination of protein structure

Knowledge of protein structure is paramount to the understanding of biological function, developing new therapeutics, and making detailed mechanistic hypotheses. Therefore, methods to accurately elucidate three-dimensional structures of proteins are in high demand. While there are a few experimental techniques that can routinely provide high-resolution structures, such as x-ray crystallography, nuclear magnetic resonance (NMR), and cryo-EM, which have been developed to determine the structures of proteins, these techniques each have shortcomings and thus cannot be used in all cases. However, additionally, a large number of experimental techniques that provide some structural information, but not enough to assign atomic positions with high certainty have been developed. These methods offer sparse experimental data, which can also be noisy and inaccurate in some instances. In cases where it is not possible to determine the structure of a protein experimentally, computational structure prediction methods can be used as an alternative. Although computational methods can be performed without any experimental data in a large number of studies, inclusion of sparse experimental data into these prediction methods has yielded significant improvement. In this Perspective, we cover many of the successes of integrative modeling, computational modeling with experimental data, specifically for protein folding, protein-protein docking, and molecular dynamics simulations. We describe methods that incorporate sparse data from cryo-EM, NMR, mass spectrometry, electron paramagnetic resonance, small-angle x-ray scattering, Förster resonance energy transfer, and genetic sequence covariation. Finally, we highlight some of the major challenges in the field as well as possible future directions.

Integrative structural modeling of a multidomain polo-like kinase

Polo-like kinase 1 (PLK1) is a key regulator and coordinator for mitotic signaling that contains two major functional units of a kinase domain (KD) and a polo-box domain (PBD). While individual domain structures of the KD and the PBD are known, how they interact and assemble into a functional complex remains an open question. The structural model from the KD-PBD-Map205PBM heterotrimeric crystal structure of zebrafish PLK1 represents a major step in understanding the KD and the PBD interactions. However, how these two domains interact when connected by a linker in the full length PLK1 needs further investigation. By integrating different sources of structural data from small-angle X-ray scattering, hydroxyl radical protein footprinting, and computational sampling, here we report an overall architecture for PLK1 multidomain assembly between the KD and the PBD. Our model revealed that the KD uses its C-lobe to interact with the PBD via the site near the phosphopeptide binding site in its auto-inhibitory state in solution. Disruption of this auto-inhibition via site-directed mutagenesis at the KD-PBD interface increases its kinase activity, supporting the functional role of KD-PBD interactions predicted for regulating the PLK1 kinase function. Our results indicate that the full length human PLK1 takes dynamic structures with a variety of domain-domain interfaces in solution.

Mass Spectrometry-Based Protein Footprinting for Higher-Order Structure Analysis: Fundamentals and Applications

Proteins adopt different higher-order structures (HOS) to enable their unique biological functions. Understanding the complexities of protein higher-order structures and dynamics requires integrated approaches, where mass spectrometry (MS) is now positioned to play a key role. One of those approaches is protein footprinting. Although the initial demonstration of footprinting was for the HOS determination of protein/nucleic acid binding, the concept was later adapted to MS-based protein HOS analysis, through which different covalent labeling approaches "mark" the solvent accessible surface area (SASA) of proteins to reflect protein HOS. Hydrogen-deuterium exchange (HDX), where deuterium in D2O replaces hydrogen of the backbone amides, is the most common example of footprinting. Its advantage is that the footprint reflects SASA and hydrogen bonding, whereas one drawback is the labeling is reversible. Another example of footprinting is slow irreversible labeling of functional groups on amino acid side chains by targeted reagents with high specificity, probing structural changes at selected sites. A third footprinting approach is by reactions with fast, irreversible labeling species that are highly reactive and footprint broadly several amino acid residue side chains on the time scale of submilliseconds. All of these covalent labeling approaches combine to constitute a problem-solving toolbox that enables mass spectrometry as a valuable tool for HOS elucidation. As there has been a growing need for MS-based protein footprinting in both academia and industry owing to its high throughput capability, prompt availability, and high spatial resolution, we present a summary of the history, descriptions, principles, mechanisms, and applications of these covalent labeling approaches. Moreover, their applications are highlighted according to the biological questions they can answer. This review is intended as a tutorial for MS-based protein HOS elucidation and as a reference for investigators seeking a MS-based tool to address structural questions in protein science.

Protein Footprinting: Auxiliary Engine to Power the Structural Biology Revolution

Structural biology is entering an exciting time where many new high-resolution structures of large complexes and membrane proteins are determined regularly. These advances have been driven by over fifteen years of technology advancements, first in macromolecular crystallography, and recently in Cryo-electron microscopy. These structures are allowing detailed questions about functional mechanisms of the structures, and the biology enabled by these structures, to be addressed for the first time. At the same time, mass spectrometry technologies for protein structure analysis, "footprinting" studies, have improved their sensitivity and resolution dramatically and can provide detailed sub-peptide and residue level information for validating structures and interactions or understanding the dynamics of structures in the context of ligand binding or assembly. In this perspective, we review the use of protein footprinting to extend our understanding of macromolecular systems, particularly for systems challenging for analysis by other techniques, such as intrinsically disordered proteins, amyloidogenic proteins, and other proteins/complexes so far recalcitrant to existing methods. We also illustrate how the availability of high-resolution structural information can be a foundation for a suite of hybrid approaches to divine structure-function relationships beyond what individual techniques can deliver.

Zinc-finger protein CNBP alters the 3-D structure of lncRNA Braveheart in solution

Long non-coding RNAs (lncRNAs) constitute a significant fraction of the transcriptome, playing important roles in development and disease. However, our understanding of structure-function relationships for this emerging class of RNAs has been limited to secondary structures. Here, we report the 3-D atomistic structural study of epigenetic lncRNA, Braveheart (Bvht), and its complex with CNBP (Cellular Nucleic acid Binding Protein). Using small angle X-ray scattering (SAXS), we elucidate the ensemble of Bvht RNA conformations in solution, revealing that Bvht lncRNA has a well-defined, albeit flexible 3-D structure that is remodeled upon CNBP binding. Our study suggests that CNBP binding requires multiple domains of Bvht and the RHT/AGIL RNA motif. We show that RHT/AGIL, previously shown to interact with CNBP, contains a highly flexible loop surrounded by more ordered helices. As one of the largest RNA-only 3-D studies, the work lays the foundation for future structural studies of lncRNA-protein complexes.

Reporting on the future of integrative structural biology ORAU workshop

Integrative and hybrid methods have the potential to bridge long-standing knowledge gaps in structural biology. These methods will have a prominent role in the future of the field as we make advances toward a complete, unified representation of biology that spans the molecular and cellular scales. The Department of Physics and Astronomy at Clemson University hosted The Future of Integrative Structural Biology workshop on April 29, 2017 and partially sponsored by partially sponsored by a program of the Oak Ridge Associated Universities (ORAU). The workshop brought experts from multiple structural biology disciplines together to discuss near-term steps toward the goal of a molecular atlas of the cell. The discussion focused on the types of structural data that should be represented, how this data should be represented, and how the time domain might be incorporated into such an atlas. The consensus was that an explorable, map-like Virtual Cell, containing both spatial and temporal data bridging the atomic and cellular length scales obtained by multiple experimental methods, represents the best path toward a complete atlas of the cell.

Federating Structural Models and Data: Outcomes from A Workshop on Archiving Integrative Structures

Structures of biomolecular systems are increasingly computed by integrative modeling. In this approach, a structural model is constructed by combining information from multiple sources, including varied experimental methods and prior models. In 2019, a Workshop was held as a Biophysical Society Satellite Meeting to assess progress and discuss further requirements for archiving integrative structures. The primary goal of the Workshop was to build consensus for addressing the challenges involved in creating common data standards, building methods for federated data exchange, and developing mechanisms for validating integrative structures. The summary of the Workshop and the recommendations that emerged are presented here.

Molecular Dissection of the Intrinsically Disordered Estrogen Receptor Alpha-NTD

In this issue of Structure, Peng et al. (2019) use a combination of computational modeling and solution-based experimental methods to characterize the intrinsically disordered N-terminal transactivation domain of estrogen receptor alpha. A long-range contact (I33-S118) was identified and was demonstrated to affect the protein conformation and coactivator binding.

Reconstruction of low-resolution molecular structures from simulated atomic force microscopy images

BACKGROUND

Atomic Force Microscopy (AFM) is an experimental technique to study structure-function relationship of biomolecules. AFM provides images of biomolecules at nanometer resolution. High-speed AFM experiments produce a series of images following dynamics of biomolecules. To further understand biomolecular functions, information on three-dimensional (3D) structures is beneficial.

METHOD

We aim to recover 3D information from an AFM image by computational modeling. The AFM image includes only low-resolution representation of a molecule; therefore we represent the structures by a coarse grained model (Gaussian mixture model). Using Monte-Carlo sampling, candidate models are generated to increase similarity between AFM images simulated from the models and target AFM image.

RESULTS

The algorithm was tested on two proteins to model their conformational transitions. Using a simulated AFM image as reference, the algorithm can produce a low-resolution 3D model of the target molecule. Effect of molecular orientations captured in AFM images on the 3D modeling performance was also examined and it is shown that similar accuracy can be obtained for many orientations.

CONCLUSIONS

The proposed algorithm can generate 3D low-resolution protein models, from which conformational transitions observed in AFM images can be interpreted in more detail.

GENERAL SIGNIFICANCE

High-speed AFM experiments allow us to directly observe biomolecules in action, which provides insights on biomolecular function through dynamics. However, as only partial structural information can be obtained from AFM data, this new AFM based hybrid modeling method would be useful to retrieve 3D information of the entire biomolecule.

Large-scale simulations of nucleoprotein complexes: ribosomes, nucleosomes, chromatin, chromosomes and CRISPR

Recent advances in biotechnology such as Hi-C, CRISPR/Cas9 and ribosome display have placed nucleoprotein complexes at center stage. Understanding the structural dynamics of these complexes aids in optimizing protocols and interpreting data for these new technologies. The integration of simulation and experiment has helped advance mechanistic understanding of these systems. Coarse-grained simulations, reduced-description models, and explicit solvent molecular dynamics simulations yield useful complementary perspectives on nucleoprotein complex structural dynamics. When combined with Hi-C, cryo-EM, and single molecule measurements, these simulations integrate disparate forms of experimental data into a coherent mechanism.

Fast Photochemical Oxidation of Proteins Coupled with Mass Spectrometry

BACKGROUND

Determination of the composition and some structural features of macromolecules can be achieved by using structural proteomics approaches coupled with mass spectrometry (MS). One approach is hydroxyl radical protein footprinting whereby amino-acid side chains are modified with reactive reagents to modify irreversibly a protein side chain. The outcomes, when deciphered with mass-spectrometry-based proteomics, can increase our knowledge of structure, assembly, and conformational dynamics of macromolecules in solution. Generating the hydroxyl radicals by laser irradiation, Hambly and Gross developed the approach of Fast Photochemical Oxidation of Proteins (FPOP), which labels proteins on the sub millisecond time scale and provides, with MS analysis, deeper understanding of protein structure and protein-ligand and protein- protein interactions. This review highlights the fundamentals of FPOP and provides descriptions of hydroxyl-radical and other radical and carbene generation, of the hydroxyl labeling of proteins, and of determination of protein modification sites. We also summarize some recent applications of FPOP coupled with MS in protein footprinting.

CONCLUSION

We survey results that show the capability of FPOP for qualitatively measuring protein solvent accessibility on the residue level. To make these approaches more valuable, we describe recent method developments that increase FPOP's quantitative capacity and increase the spatial protein sequence coverage. To improve FPOP further, several new labeling reagents including carbenes and other radicals have been developed. These growing improvements will allow oxidative- footprinting methods coupled with MS to play an increasingly significant role in determining the structure and dynamics of macromolecules and their assemblies.

Tracking Higher Order Protein Structure by Hydrogen-Deuterium Exchange Mass Spectrometry

BACKGROUND

Structural biology has provided a fundamental understanding of protein structure and mechanistic insight into their function. However, high-resolution structures alone are insufficient for a complete understanding of protein behavior. Higher energy conformations, conformational changes, and subtle structural fluctuations that underlie the proper function of proteins are often difficult to probe using traditional structural approaches. Hydrogen/Deuterium Exchange with Mass Spectrometry (HDX-MS) provides a way to probe the accessibility of backbone amide protons under native conditions, which reports on local structural dynamics of solution protein structure that can be used to track complex structural rearrangements that occur in the course of a protein's function.

CONCLUSION

In the last 20 years the advances in labeling techniques, sample preparation, instrumentation, and data analysis have enabled HDX to gain insights into very complex biological systems. Analysis of challenging targets such as membrane protein complexes is now feasible and the field is paving the way to the analysis of more and more complex systems.

A Metastable Contact and Structural Disorder in the Estrogen Receptor Transactivation Domain

The N-terminal transactivation domain (NTD) of estrogen receptor alpha, a well-known member of the family of intrinsically disordered proteins, mediates the receptor's transactivation function. However, an accurate molecular dissection of NTD's structure-function relationships remains elusive. Here, we show that the NTD adopts a mostly disordered, unexpectedly compact conformation that undergoes structural expansion on chemical denaturation. By combining small-angle X-ray scattering, hydroxyl radical protein footprinting, and computational modeling, we derive the ensemble-structures of the NTD and determine its ensemble-contact map revealing metastable long-range contacts, e.g., between residues I33 and S118. We show that mutation at S118, a known phosphorylation site, promotes conformational changes and increases coactivator binding. We further demonstrate via fluorine-19 (¹⁹F) nuclear magnetic resonance that mutations near I33 alter ¹⁹F chemical shifts at S118, confirming the proposed I33-S118 contact in the ensemble of structural disorder. These findings extend our understanding of how specific contact metastability mediates critical functions of disordered proteins.

Targeting intrinsically disordered proteins at the edge of chaos

Intrinsically disordered proteins or intrinsically disordered regions (IDPs or IDRs) are those that do not fold into defined tertiary structures under physiological conditions. Given their prevalence in various diseases, IDPs are attractive therapeutic targets. However, because of the dynamic nature of the IDP structure, conventional structure-based drug design methods cannot be directly applied. Thanks to recent progress in understanding the mechanisms underlying IDP and ligand interactions, computational strategies for IDP-targeted rational drug discovery are emerging. Here, we summarize recent developments in computational IDP drug design strategies and their successful applications, analyze the typical properties of reported IDP-binding compounds (iIDPs), and discuss the major challenges ahead as well as possible solutions.

Multidomain architecture of estrogen receptor reveals interfacial cross-talk between its DNA-binding and ligand-binding domains

Human estrogen receptor alpha (hERα) is a hormone-responsive nuclear receptor (NR) involved in cell growth and survival that contains both a DNA-binding domain (DBD) and a ligand-binding domain (LBD). Functionally relevant inter-domain interactions between the DBD and LBD have been observed in several other NRs, but for hERα, the detailed structural architecture of the complex is unknown. By utilizing integrated complementary techniques of small-angle X-ray scattering, hydroxyl radical protein footprinting and computational modeling, here we report an asymmetric L-shaped “boot” structure of the multidomain hERα and identify the specific sites on each domain at the domain interface involved in DBD–LBD interactions. We demonstrate the functional role of the proposed DBD–LBD domain interface through site-specific mutagenesis altering the hERα interfacial structure and allosteric signaling. The L-shaped structure of hERα is a distinctive DBD–LBD organization of NR complexes and more importantly, reveals a signaling mechanism mediated by inter-domain crosstalk that regulates this receptor’s allosteric function.

The human estrogen receptor alpha (hERα) is a hormone-responsive transcription factor. Here the authors combine small-angle X-ray scattering, hydroxyl radical protein footprinting and computational modeling and show that multidomain hERα adopts an L-shaped boot-like architecture revealing a cross-talk between its DNA-binding domain and Ligand-binding domain.

Covalent labeling-mass spectrometry with non-specific reagents for studying protein structure and interactions

Using mass spectrometry (MS) to obtain information about a higher order structure of protein requires that a protein's structural properties are encoded into the mass of that protein. Covalent labeling (CL) with reagents that can irreversibly modify solvent accessible amino acid side chains is an effective way to encode structural information into the mass of a protein, as this information can be read-out in a straightforward manner using standard MS-based proteomics techniques. The differential reactivity of proteins under two or more conditions can be used to distinguish protein topologies, conformations, and/or binding sites. CL-MS methods have been effectively used for the structural analysis of proteins and protein complexes, particularly for systems that are difficult to study by other more traditional biochemical techniques. This review provides an overview of the non-specific CL approaches that have been combined with MS with a particular emphasis on the reagents that are commonly used, including hydroxyl radicals, carbenes, and diethylpyrocarbonate. We describe the reagent and protein factors that affect the reactivity of amino acid side chains. We also include details about experimental design and workflow, data analysis, recent applications, and some future prospects of CL-MS methods.

Rosetta Protein Structure Prediction from Hydroxyl Radical Protein Footprinting Mass Spectrometry Data

In recent years mass spectrometry-based covalent labeling techniques such as hydroxyl radical footprinting (HRF) have emerged as valuable structural biology techniques, yielding information on protein tertiary structure. These data, however, are not sufficient to predict protein structure unambiguously, as they provide information only on the relative solvent exposure of certain residues. Despite some recent advances, no software currently exists that can utilize covalent labeling mass spectrometry data to predict protein tertiary structure. We have developed the first such tool, which incorporates mass spectrometry derived protection factors from HRF labeling as a new centroid score term for the Rosetta scoring function to improve the prediction of protein tertiary structures. We tested our method on a set of four soluble benchmark proteins with known crystal structures and either published HRF experimental results or internally acquired data. Using the HRF labeling data, we rescored large decoy sets of structures predicted with Rosetta for each of the four benchmark proteins. As a result, the model quality improved for all benchmark proteins as compared to when scored with Rosetta alone. For two of the four proteins we were even able to identify atomic resolution models with the addition of HRF data.

Implementing fast photochemical oxidation of proteins (FPOP) as a footprinting approach to solve diverse problems in structural biology

Fast photochemical oxidation of proteins (FPOP) is a footprinting technique used in mass spectrometry-based structural proteomics. It has been applied to solve a variety of problems in different areas of biology. A FPOP platform requires a laser, optics, and sample flow path properly assembled to enable fast footprinting. Sample preparation, buffer conditions, and reagent concentrations are essential to obtain reasonable oxidations on proteins. FPOP samples can be analyzed by LC-MS methods to measure the modification extent, which is a function of the solvent-accessible surface area of the protein. The platform can be expanded to accommodate several new approaches, including dose-response studies, new footprinting reagents, and two-laser pump-probe experiments. Here, we briefly review FPOP applications and in a detailed manner describe the procedures to set up an FPOP protein footprinting platform.

High-Resolution Hydroxyl Radical Protein Footprinting: Biophysics Tool for Drug Discovery

Hydroxyl radical footprinting (HRF) of proteins with mass spectrometry (MS) is a widespread approach for assessing protein structure. Hydroxyl radicals react with a wide variety of protein side chains, and the ease with which radicals can be generated (by radiolysis or photolysis) has made the approach popular with many laboratories. As some side chains are less reactive and thus cannot be probed, additional specific and nonspecific labeling reagents have been introduced to extend the approach. At the same time, advances in liquid chromatography and MS approaches permit an examination of the labeling of individual residues, transforming the approach to high resolution. Lastly, advances in understanding of the chemistry of the approach have led to the determination of absolute protein topologies from HRF data. Overall, the technology can provide precise and accurate measures of side-chain solvent accessibility in a wide range of interesting and useful contexts for the study of protein structure and dynamics in both academia and industry.

A Practical Guide to iSPOT Modeling: An Integrative Structural Biology Platform

Integrative structure modeling is an emerging method for structural determination of protein-protein complexes that are challenging for conventional structural techniques. Here, we provide a practical protocol for implementing our integrated iSPOT platform by integrating three different biophysical techniques: small-angle X-ray scattering (SAXS), hydroxyl radical footprinting, and computational docking simulations. Specifically, individual techniques are described from experimental and/or computational perspectives, and complementary structural information from these different techniques are integrated for accurate characterization of the structures of large protein-protein complexes.