The advantages and limitations of protein crystal structures

Conformation-Selective Ultraviolet-Ultraviolet Hole Burning Spectra of Ubiquitin Ions in a Cryogenic Ion Trap

Understanding the structural variations of conformational isomers in proteins is crucial for elucidating protein folding mechanisms. Here, we present a novel method for obtaining conformation-selective ultraviolet (UV)-UV hole burning (HB) spectra of ubiquitin ions ((Ubi+zH)+z, z = 7-10) produced via electrospray ionization. Our approach involves binding multiple N2 molecules to ubiquitin ions ((Ubi+zH)+z(N2)m, m = 1-55) within a cryogenic ion trap. Upon exposure to UV irradiation, efficient fragmentation of (Ubi+zH)+z(N2)m occurs, primarily yielding bare (Ubi+zH)+z ions as fragments. The significant mass difference between the parent and fragment ions facilitates the acquisition of UV-UV HB spectra, which reveal the presence of at least two distinct conformers. Molecular dynamics simulations suggest that these conformers correspond to A-state structures, differing only in the interactions of a tyrosine residue with neighboring residues. Our findings underscore UV-UV HB spectroscopy of protein ions as a powerful tool for exploring diverse protein isomers.

An Ensemble Classifiers for Improved Prediction of Native-Non-Native Protein-Protein Interaction

In this study, we present an innovative approach to improve the prediction of protein-protein interactions (PPIs) through the utilization of an ensemble classifier, specifically focusing on distinguishing between native and non-native interactions. Leveraging the strengths of various base models, including random forest, gradient boosting, extreme gradient boosting, and light gradient boosting, our ensemble classifier integrates these diverse predictions using a logistic regression meta-classifier. Our model was evaluated using a comprehensive dataset generated from molecular dynamics simulations. While the gains in AUC and other metrics might seem modest, they contribute to a model that is more robust, consistent, and adaptable. To assess the effectiveness of various approaches, we compared the performance of logistic regression to four baseline models. Our results indicate that logistic regression consistently underperforms across all evaluated metrics. This suggests that it may not be well-suited to capture the complex relationships within this dataset. Tree-based models, on the other hand, appear to be more effective for problems involving molecular dynamics simulations. Extreme gradient boosting (XGBoost) and light gradient boosting (LightGBM) are optimized for performance and speed, handling datasets effectively and incorporating regularizations to avoid over-fitting. Our findings indicate that the ensemble method enhances the predictive capability of PPIs, offering a promising tool for computational biology and drug discovery by accurately identifying potential interaction sites and facilitating the understanding of complex protein functions within biological systems.

Solid-state vibrational circular dichroism: Methodology and application for amphetamine derivatives

Amphetamine derivatives are considered most seized substances worldwide. In this study, solid-state vibrational circular dichroism (VCD) measurements of enantiomerically pure substances were performed for spectroscopic discrimination between (S)- and (R)-enantiomers. First, we have developed a universal experimental approach to obtain reliable and reproducible solid-state VCD spectra. First, the samples were prepared as pellets composed of mixtures of camphor as a model compound and a crystalline matrix powder. In order to obtain the best results without artifacts and with a maximum signal-to-noise ratio, the following experimental conditions were optimized: pellet thickness and diameter and sample rotation speed. The optimized parameters were then used for the analysis of amphetamine and its derivatives (methamphetamine and 3,4-methylendioxymethamphetamine). Our high-quality spectra and results suggest that solid-state VCD spectroscopy represents a cost-effective and easy-to-use method for the analysis of conformation changes and molecular packing in solid-state with potential applications in pharmaceutical and forensic practice.

AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination

Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these predictions vary, however, and they do not take into account ligands, covalent modifications or other environmental factors. Here, we evaluate how well AlphaFold predictions can be expected to describe the structure of a protein by comparing predictions directly with experimental crystallographic maps. In many cases, AlphaFold predictions matched experimental maps remarkably closely. In other cases, even very high-confidence predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction.

Triboelectric Nanogenerators: Low-Cost Power Supplies for Improved Electrospray Ionization

Electrospray ionization (ESI) is one of the most popular methods to generate ions for mass spectrometry (MS). When compared with other ionization techniques, it can generate ions from liquid-phase samples without additives, retaining covalent and non-covalent interactions of the molecules of interest. When hyphenated to liquid chromatography, it greatly expands the versatility of MS analysis of complex mixtures. However, despite the extensive growth in the application of ESI, the technique still suffers from some drawbacks when powered by direct current (DC) power supplies. Triboelectric nanogenerators promise to be a new power source for the generation of ions by ESI, improving on the analytical capabilities of traditional DC ESI. In this review we highlight the fundamentals of ESI driven by DC power supplies, its contrasting qualities to triboelectric nanogenerator power supplies, and its applications to three distinct fields of research: forensics, metabolomics, and protein structure analysis.

Intelligent Protein Design and Molecular Characterization Techniques: A Comprehensive Review

In recent years, the widespread application of artificial intelligence algorithms in protein structure, function prediction, and de novo protein design has significantly accelerated the process of intelligent protein design and led to many noteworthy achievements. This advancement in protein intelligent design holds great potential to accelerate the development of new drugs, enhance the efficiency of biocatalysts, and even create entirely new biomaterials. Protein characterization is the key to the performance of intelligent protein design. However, there is no consensus on the most suitable characterization method for intelligent protein design tasks. This review describes the methods, characteristics, and representative applications of traditional descriptors, sequence-based and structure-based protein characterization. It discusses their advantages, disadvantages, and scope of application. It is hoped that this could help researchers to better understand the limitations and application scenarios of these methods, and provide valuable references for choosing appropriate protein characterization techniques for related research in the field, so as to better carry out protein research.

μMap Photoproximity Labeling Enables Small Molecule Binding Site Mapping

The characterization of ligand binding modes is a crucial step in the drug discovery process and is especially important in campaigns arising from phenotypic screening, where the protein target and binding mode are unknown at the outset. Elucidation of target binding regions is typically achieved by X-ray crystallography or photoaffinity labeling (PAL) approaches; yet, these methods present significant challenges. X-ray crystallography is a mainstay technique that has revolutionized drug discovery, but in many cases structural characterization is challenging or impossible. PAL has also enabled binding site mapping with peptide- and amino-acid-level resolution; however, the stoichiometric activation mode can lead to poor signal and coverage of the resident binding pocket. Additionally, each PAL probe can have its own fragmentation pattern, complicating the analysis by mass spectrometry. Here, we establish a robust and general photocatalytic approach toward the mapping of protein binding sites, which we define as identification of residues proximal to the ligand binding pocket. By utilizing a catalytic mode of activation, we obtain sets of labeled amino acids in the proximity of the target protein binding site. We use this methodology to map, in vitro, the binding sites of six protein targets, including several kinases and molecular glue targets, and furthermore to investigate the binding site of the STAT3 inhibitor MM-206, a ligand with no known crystal structure. Finally, we demonstrate the successful mapping of drug binding sites in live cells. These results establish μMap as a powerful method for the generation of amino-acid- and peptide-level target engagement data.

Toward the analysis of functional proteoforms using mass spectrometry-based stability proteomics

Functional proteomics aims to elucidate biological functions, mechanisms, and pathways of proteins and proteoforms at the molecular level to examine complex cellular systems and disease states. A series of stability proteomics methods have been developed to examine protein functionality by measuring the resistance of a protein to chemical or thermal denaturation or proteolysis. These methods can be applied to measure the thermal stability of thousands of proteins in complex biological samples such as cell lysate, intact cells, tissues, and other biological fluids to measure proteome stability. Stability proteomics methods have been popularly applied to observe stability shifts upon ligand binding for drug target identification. More recently, these methods have been applied to characterize the effect of structural changes in proteins such as those caused by post-translational modifications (PTMs) and mutations, which can affect protein structures or interactions and diversify protein functions. Here, we discussed the current application of a suite of stability proteomics methods, including thermal proteome profiling (TPP), stability of proteomics from rates of oxidation (SPROX), and limited proteolysis (LiP) methods, to observe PTM-induced structural changes on protein stability. We also discuss future perspectives highlighting the integration of top-down mass spectrometry and stability proteomics methods to characterize intact proteoform stability and understand the function of variable protein modifications.

A guide to studying protein aggregation

Disrupted protein folding or decreased protein stability can lead to the accumulation of (partially) un- or misfolded proteins, which ultimately cause the formation of protein aggregates. Much of the interest in protein aggregation is associated with its involvement in a wide range of human diseases and the challenges it poses for large-scale biopharmaceutical manufacturing and formulation of therapeutic proteins and peptides. On the other hand, protein aggregates can also be functional, as observed in nature, which triggered its use in the development of biomaterials or therapeutics as well as for the improvement of food characteristics. Thus, unmasking the various steps involved in protein aggregation is critical to obtain a better understanding of the underlying mechanism of amyloid formation. This knowledge will allow a more tailored development of diagnostic methods and treatments for amyloid-associated diseases, as well as applications in the fields of new (bio)materials, food technology and therapeutics. However, the complex and dynamic nature of the aggregation process makes the study of protein aggregation challenging. To provide guidance on how to analyse protein aggregation, in this review we summarize the most commonly investigated aspects of protein aggregation with some popular corresponding methods.

Exploring the Conformational Landscape and Stability of Aurora A Using Ion-Mobility Mass Spectrometry and Molecular Modeling

Protein kinase inhibitors are highly effective in treating diseases driven by aberrant kinase signaling and as chemical tools to help dissect the cellular roles of kinase signaling complexes. Evaluating the effects of binding of small molecule inhibitors on kinase conformational dynamics can assist in understanding both inhibition and resistance mechanisms. Using gas-phase ion-mobility mass spectrometry (IM-MS), we characterize changes in the conformational landscape and stability of the protein kinase Aurora A (Aur A) driven by binding of the physiological activator TPX2 or small molecule inhibition. Aided by molecular modeling, we establish three major conformations, the relative abundances of which were dependent on the Aur A activation status: one highly populated compact conformer similar to that observed in most crystal structures, a second highly populated conformer possessing a more open structure infrequently found in crystal structures, and an additional low-abundance conformer not currently represented in the protein databank. Notably, inhibitor binding induces more compact configurations of Aur A, as adopted by the unbound enzyme, with both IM-MS and modeling revealing inhibitor-mediated stabilization of active Aur A.

Recent advances in predicting protein-protein interactions with the aid of artificial intelligence algorithms

Protein-protein interactions (PPIs) are essential in the regulation of biological functions and cell events, therefore understanding PPIs have become a key issue to understanding the molecular mechanism and investigating the design of drugs. Here we highlight the major developments in computational methods developed for predicting PPIs by using types of artificial intelligence algorithms. The first part introduces the source of experimental PPI data. The second part is devoted to the PPI prediction methods based on sequential information. The third part covers representative methods using structural information as the input feature. The last part is methods designed by combining different types of features. For each part, the state-of-the-art computational PPI prediction methods are reviewed in an inclusive view. Finally, we discuss the flaws existing in this area and future directions of next-generation algorithms.

Cryo-EM as a powerful tool for drug discovery: recent structural based studies of SARS-CoV-2

The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has arisen as a global pandemic affecting the respiratory system showing acute respiratory distress syndrome (ARDS). However, there is no targeted therapeutic agent yet and due to the growing cases of infections and the rising death tolls, discovery of the possible drug is the need of the hour. In general, the study for discovering therapeutic agent for SARS-CoV-2 is largely focused on large-scale screening with fragment-based drug discovery (FBDD). With the recent advancement in cryo-electron microscopy (Cryo-EM), it has become one of the widely used tools in structural biology. It is effective in investigating the structure of numerous proteins in high-resolution and also had an intense influence on drug discovery, determining the binding reaction and regulation of known drugs as well as leading the design and development of new drug candidates. Here, we review the application of cryo-EM in a structure-based drug design (SBDD) and in silico screening of the recently acquired FBDD in SARS-CoV-2. Such insights will help deliver better understanding in the procurement of the effective remedial solution for this pandemic.

NMR Spectroscopy in the Conformational Analysis of Peptides: An Overview

BACKGROUND

NMR spectroscopy is one of the most powerful tools to study the structure and interaction properties of peptides and proteins from a dynamic perspective. Knowing the bioactive conformations of peptides is crucial in the drug discovery field to design more efficient analogue ligands and inhibitors of protein-protein interactions targeting therapeutically relevant systems.

OBJECTIVE

This review provides a toolkit to investigate peptide conformational properties by NMR.

METHODS

Articles cited herein, related to NMR studies of peptides and proteins were mainly searched through PubMed and the web. More recent and old books on NMR spectroscopy written by eminent scientists in the field were consulted as well.

RESULTS

The review is mainly focused on NMR tools to gain the 3D structure of small unlabeled peptides. It is more application-oriented as it is beyond its goal to deliver a profound theoretical background. However, the basic principles of 2D homonuclear and heteronuclear experiments are briefly described. Protocols to obtain isotopically labeled peptides and principal triple resonance experiments needed to study them, are discussed as well.

CONCLUSION

NMR is a leading technique in the study of conformational preferences of small flexible peptides whose structure can be often only described by an ensemble of conformations. Although NMR studies of peptides can be easily and fast performed by canonical protocols established a few decades ago, more recently we have assisted to tremendous improvements of NMR spectroscopy to investigate instead large systems and overcome its molecular weight limit.

Structural Characterization of Carbonic Anhydrase-Arylsulfonamide Complexes Using Ultraviolet Photodissociation Mass Spectrometry

Numerous mass spectrometry-based strategies ranging from hydrogen-deuterium exchange to ion mobility to native mass spectrometry have been developed to advance biophysical and structural characterization of protein conformations and determination of protein-ligand interactions. In this study, we focus on the use of ultraviolet photodissociation (UVPD) to examine the structure of human carbonic anhydrase II (hCAII) and its interactions with arylsulfonamide inhibitors. Carbonic anhydrase, which catalyzes the conversion of carbon dioxide to bicarbonate, has been the target of countless thermodynamic and kinetic studies owing to its well-characterized active site, binding cavity, and mechanism of inhibition by hundreds of ligands. Here, we showcase the application of UVPD for evaluating structural changes of hCAII upon ligand binding on the basis of variations in fragmentation of hCAII versus hCAII-arylsulfonamide complexes, particularly focusing on the hydrophobic pocket. To extend the coverage in the midregion of the protein sequence, a supercharging agent was added to the solutions to increase the charge states of the complexes. The three arylsulfonamides examined in this study largely shift the fragmentation patterns in similar ways, despite their differences in binding affinities.

Recent Insights into the Structure and Function of Mycobacterial Membrane Proteins Facilitated by Cryo-EM

Mycobacterium tuberculosis (Mtb) is one of the deadliest pathogens encountered by humanity. Over the decades, its characteristic membrane organization and composition have been understood. However, there is still limited structural information and mechanistic understanding of the constituent membrane proteins critical for drug discovery pipelines. Recent advances in single-particle cryo-electron microscopy and cryo-electron tomography have provided the much-needed impetus towards structure determination of several vital Mtb membrane proteins whose structures were inaccessible via X-ray crystallography and NMR. Important insights into membrane composition and organization have been gained via a combination of electron tomography and biochemical and biophysical assays. In addition, till the time of writing this review, 75 new structures of various Mtb proteins have been reported via single-particle cryo-EM. The information obtained from these structures has improved our understanding of the mechanisms of action of these proteins and the physiological pathways they are associated with. These structures have opened avenues for structure-based drug design and vaccine discovery programs that might help achieve global-TB control. This review describes the structural features of selected membrane proteins (type VII secretion systems, Rv1819c, Arabinosyltransferase, Fatty Acid Synthase, F-type ATP synthase, respiratory supercomplex, ClpP1P2 protease, ClpB disaggregase and SAM riboswitch), their involvement in physiological pathways, and possible use as a drug target. Tuberculosis is a deadly disease caused by Mycobacterium tuberculosis. The Cryo-EM and tomography have simplified the understanding of the mycobacterial membrane organization. Some proteins are located in the plasma membrane; some span the entire envelope, while some, like MspA, are located in the mycomembrane. Cryo-EM has made the study of such membrane proteins feasible.

Deconstructing Noncovalent Kelch-like ECH-Associated Protein 1 (Keap1) Inhibitors into Fragments to Reconstruct New Potent Compounds

Targeting the protein-protein interaction (PPI) between nuclear factor erythroid 2-related factor 2 (Nrf2) and Kelch-like ECH-associated protein 1 (Keap1) is a potential therapeutic strategy to control diseases involving oxidative stress. Here, six classes of known small-molecule Keap1-Nrf2 PPI inhibitors were dissected into 77 fragments in a fragment-based deconstruction reconstruction (FBDR) study and tested in four orthogonal assays. This gave 17 fragment hits of which six were shown by X-ray crystallography to bind in the Keap1 Kelch binding pocket. Two hits were merged into compound 8 with a 220-380-fold stronger affinity (K_i = 16 μM) relative to the parent fragments. Systematic optimization resulted in several novel analogues with K_i values of 0.04-0.5 μM, binding modes determined by X-ray crystallography, and enhanced microsomal stability. This demonstrates how FBDR can be used to find new fragment hits, elucidate important ligand-protein interactions, and identify new potent inhibitors of the Keap1-Nrf2 PPI.

Probing Structural Dynamics of Membrane Proteins Using Electron Paramagnetic Resonance Spectroscopic Techniques

Membrane proteins are essential for the survival of living organisms. They are involved in important biological functions including transportation of ions and molecules across the cell membrane and triggering the signaling pathways. They are targets of more than half of the modern medical drugs. Despite their biological significance, information about the structural dynamics of membrane proteins is lagging when compared to that of globular proteins. The major challenges with these systems are low expression yields and lack of appropriate solubilizing medium required for biophysical techniques. Electron paramagnetic resonance (EPR) spectroscopy coupled with site directed spin labeling (SDSL) is a rapidly growing powerful biophysical technique that can be used to obtain pertinent structural and dynamic information on membrane proteins. In this brief review, we will focus on the overview of the widely used EPR approaches and their emerging applications to answer structural and conformational dynamics related questions on important membrane protein systems.

Recombinant expression of HIV-1 protease using soluble fusion tags in Escherichia coli: A vital tool for functional characterization of HIV-1 protease

HIV-1 protease expression in the laboratory is demanding because of its high cytotoxicity, making it difficult to express in bacterial expression systems such as Escherichia coli. To overcome these challenges, HIV-1 protease fusion with solubility enhancing tags helps to mitigate its cytotoxic effect and drive its expression as a soluble protein. Therefore, this review focuses on the expression of bioactive HIV-1 protease using solubility-enhancing fusion tags in Escherichia coli and summarises the characteristic features of the different common fusion tags that have been used in the expression of HIV-1 protease. This review will assist researchers with their choice of protein fusion tag for HIV-1 protease expression.

Conformational Differences Are Observed for the Active and Inactive Forms of Pinholin S21 Using DEER Spectroscopy

Bacteriophages have evolved with an efficient host cell lysis mechanism to terminate the infection cycle and release the new progeny virions at the optimum time, allowing adaptation with the changing host and environment. Among the lytic proteins, holin controls the first and rate-limiting step of host cell lysis by permeabilizing the inner membrane at an allele-specific time known as "holin triggering". Pinholin S²¹ is a prototype holin of phage Φ21 which makes many nanoscale holes and destroys the proton motive force, which in turn activates the signal anchor release (SAR) endolysin system to degrade the peptidoglycan layer of the host cell and destruction of the outer membrane by the spanin complex. Like many others, phage Φ21 has two holin proteins: active pinholin and antipinholin. The antipinholin form differs only by three extra amino acids at the N-terminus; however, it has a different structural topology and conformation with respect to the membrane. Predefined combinations of active pinholin and antipinholin fine-tune the lysis timing through structural dynamics and conformational changes. Previously, the dynamics and topology of active pinholin and antipinholin were investigated (Ahammad et al. JPCB 2019, 2020) using continuous wave electron paramagnetic resonance (CW-EPR) spectroscopy. However, detailed structural studies and direct comparison of these two forms of pinholin S²¹ are absent in the literature. In this study, the structural topology and conformations of active pinholin (S²¹68) and inactive antipinholin (S²¹68_IRS) in DMPC (1,2-dimyristoyl-sn-glycero-3-phosphocholine) proteoliposomes were investigated using the four-pulse double electron-electron resonance (DEER) EPR spectroscopic technique to measure distances between transmembrane domains 1 and 2 (TMD1 and TMD2). Five sets of interlabel distances were measured via DEER spectroscopy for both the active and inactive forms of pinholin S²¹. Structural models of the active pinholin and inactive antipinholin forms in DMPC proteoliposomes were obtained using the experimental DEER distances coupled with the simulated annealing software package Xplor-NIH. TMD2 of S²¹68 remains in the lipid bilayer, and TMD1 is partially externalized from the bilayer with some residues located on the surface. However, both TMDs remain incorporated in the lipid bilayer for the inactive S²¹68_IRS form. This study demonstrates, for the first time, clear structural topology and conformational differences between the two forms of pinholin S²¹. This work will pave the way for further studies of other holin systems using the DEER spectroscopic technique and will give structural insight into these biological clocks in molecular detail.

Structural Dynamics and Topology of the Inactive Form of S21 Holin in a Lipid Bilayer Using Continuous-Wave Electron Paramagnetic Resonance Spectroscopy

The bacteriophage infection cycle plays a crucial role in recycling the world's biomass. Bacteriophages devise various cell lysis systems to strictly control the length of the infection cycle for an efficient phage life cycle. Phages evolved with lysis protein systems, which can control and fine-tune the length of this infection cycle depending on the host and growing environment. Among these lysis proteins, holin controls the first and rate-limiting step of host cell lysis by permeabilizing the inner membrane at an allele-specific time and concentration hence known as the simplest molecular clock. Pinholin S²¹ is the holin from phage Φ21, which defines the cell lysis time through a predefined ratio of active pinholin and antipinholin (inactive form of pinholin). Active pinholin and antipinholin fine-tune the lysis timing through structural dynamics and conformational changes. Previously we reported the structural dynamics and topology of active pinholin S²¹68. Currently, there is no detailed structural study of the antipinholin using biophysical techniques. In this study, the structural dynamics and topology of antipinholin S²¹68_IRS in DMPC proteoliposomes is investigated using electron paramagnetic resonance (EPR) spectroscopic techniques. Continuous-wave (CW) EPR line shape analysis experiments of 35 different R1 side chains of S²¹68_IRS indicated restricted mobility of the transmembrane domains (TMDs), which were predicted to be inside the lipid bilayer when compared to the N- and C-termini R1 side chains. In addition, the R1 accessibility test performed on 24 residues using the CW-EPR power saturation experiment indicated that TMD1 and TMD2 of S²¹68_IRS were incorporated into the lipid bilayer where N- and C-termini were located outside of the lipid bilayer. Based on this study, a tentative model of S²¹68_IRS is proposed where both TMDs remain incorporated into the lipid bilayer and N- and C-termini are located outside of the lipid bilayer. This work will pave the way for the further studies of other holins using biophysical techniques and will give structural insights into these biological clocks in molecular detail.

The analysis of living systems can generate both knowledge and illusions

Life relies on phenomena that range from changes in molecules that occur within nanoseconds to changes in populations that occur over millions of years. Researchers have developed a vast range of experimental techniques to analyze living systems, but a given technique usually only works over a limited range of length or time scales. Therefore, gaining a full understanding of a living system usually requires the integration of information obtained at multiple different scales by two or more techniques. This approach has undoubtedly led to a much better understanding of living systems but, equally, the staggering complexity of these systems, the sophistication and limitations of the techniques available in modern biology, and the need to use two or more techniques, can lead to persistent illusions of knowledge. Here, in an effort to make better use of the experimental techniques we have at our disposal, I propose a broad classification of techniques into six complementary approaches: perturbation, visualization, substitution, characterization, reconstitution, and simulation. Such a taxonomy might also help increase the reproducibility of inferences and improve peer review.

Use of Multiple Ion Fragmentation Methods to Identify Protein Cross-Links and Facilitate Comparison of Data Interpretation Algorithms

Multiple ion fragmentation methods involving collision-induced dissociation (CID), higher-energy collisional dissociation (HCD) with regular and very high energy settings, and electron-transfer dissociation with supplementary HCD (EThcD) are implemented to improve the confidence of cross-link identifications. Three different S. cerevisiae proteasome samples cross-linked by diethyl suberthioimidate (DEST) or bis(sulfosuccinimidyl)suberate (BS³) are analyzed. Two approaches are introduced to combine interpretations from the above four methods. Working with cleavable cross-linkers such as DEST, the first approach searches for cross-link diagnostic ions and consistency among the best interpretations derived from all four MS² spectra associated with each precursor ion. Better agreement leads to a more definitive identification. Compatible with both cleavable and noncleavable cross-linkers such as BS³, the second approach multiplies scoring metrics from a number of fragmentation experiments to derive an overall best match. This significantly increases the scoring gap between the target and decoy matches. The validity of cross-links fragmented by HCD alone and identified by Kojak, MeroX, pLink, and Xi was evaluated using multiple fragmentation data. Possible ways to improve the identification credibility are discussed. Data are available via ProteomeXchange with identifier PXD018310.

Electron Paramagnetic Resonance as a Tool for Studying Membrane Proteins

Membrane proteins possess a variety of functions essential to the survival of organisms. However, due to their inherent hydrophobic nature, it is extremely difficult to probe the structure and dynamic properties of membrane proteins using traditional biophysical techniques, particularly in their native environments. Electron paramagnetic resonance (EPR) spectroscopy in combination with site-directed spin labeling (SDSL) is a very powerful and rapidly growing biophysical technique to study pertinent structural and dynamic properties of membrane proteins with no size restrictions. In this review, we will briefly discuss the most commonly used EPR techniques and their recent applications for answering structure and conformational dynamics related questions of important membrane protein systems.

Structural dynamics of the GluK3-kainate receptor neurotransmitter binding domains revealed by cryo-EM

Kainate receptors belong to the ionotropic glutamate receptor family and play critical roles in the regulation of synaptic networks. The kainate receptor subunit GluK3 has unique functional properties and contributes to presynaptic facilitation at the hippocampal mossy fiber synapses along with roles at the post-synapses. To gain structural insights into the unique functional properties and dynamics of GluK3 receptor, we imaged them via electron microscopy in the apo-state and in complex with either agonist kainate or antagonist UBP301. Our analysis of all the GluK3 full-length structures not only provides insights into the receptor transitions between desensitized and closed states but also reveals a "non-classical" conformation of neurotransmitter binding domain in the closed-state distinct from that observed in AMPA and other kainate receptor structures. We show by molecular dynamics simulations that Asp759 influences the stability of the LBD dimers and hence could be responsible for the observed conformational variability and dynamics of the GluK3 via electron microscopy. Lower dimer stability could explain faster desensitization and low agonist sensitivity of GluK3. In overview, our work helps to associate biochemistry and physiology of GluK3 receptors with their structural biology and offers structural insights into the unique functional properties of these atypical receptors.

Opposites Attract: Escherichia coli Heptosyltransferase I Conformational Changes Induced by Interactions between the Substrate and Positively Charged Residues

Gram-negative bacterial viability is greatly reduced by the disruption of heptose sugar addition during the biosynthesis of lipopolysaccharide (LPS), an important bacterial outer membrane component. Heptosyltransferase I (HepI), a member of the GT-B structural subclass of glycosyltransferases, is therefore an essential enzyme for the biosynthesis of the LPS. The disruption of HepI also increases the susceptibility of bacteria to hydrophobic antibiotics, making HepI a potential target for drug development. In this work, the structural and dynamic properties of the catalytic cycle of HepI are explored. Previously, substrate-induced stabilization of HepI was observed and hypothesized to be assisted by interactions between the substrate and residues located on dynamic loops. Herein, positively charged amino acids were probed to identify binding partners of the negatively charged phosphates and carboxylates of Kdo₂-lipid A and its analogues. Mutant enzymes were characterized to explore changes in enzymatic activities and protein stability. Molecular modeling of HepI in the presence and absence of ligands was then performed with the wild type and mutant enzyme to allow determination of the relative change in substrate binding affinity resulting from each mutation. Together, these studies suggest that multiple residues are involved in mediating substrate binding, and a lack of additivity of these effects illustrates the functional redundancy of these binding interactions. The redundancy of residues mediating conformational transitions in HepI illustrates the evolutionary importance of these structural rearrangements for catalysis. This work enhances the understanding of HepI's protein dynamics and mechanism and is a model for improving our understanding of glycosyltransferase enzymes.

In Situ Proteolysis Condition-Induced Crystallization of the XcpVWX Complex in Different Lattices

Although prevalent in the determination of protein structures; crystallography always has the bottleneck of obtaining high-quality protein crystals for characterizing a wide range of proteins; especially large protein complexes. Stable fragments or domains of proteins are more readily to crystallize; which prompts the use of in situ proteolysis to remove flexible or unstable structures for improving crystallization and crystal quality. In this work; we investigated the effects of in situ proteolysis by chymotrypsin on the crystallization of the XcpVWX complex from the Type II secretion system of Pseudomonas aeruginosa. Different proteolysis conditions were found to result in two distinct lattices in the same crystallization solution. With a shorter chymotrypsin digestion at a lower concentration; the crystals exhibited a P3 hexagonal lattice that accommodates three complex molecules in one asymmetric unit. By contrast; a longer digestion with chymotrypsin of a 10-fold higher concentration facilitated the formation of a compact P2₁2₁2₁ orthorhombic lattice with only one complex molecule in each asymmetric unit. The molecules in the hexagonal lattice have shown high atomic displacement parameter values compared with the ones in the orthorhombic lattice. Taken together; our results clearly demonstrate that different proteolysis conditions can result in the generation of distinct lattices in the same crystallization solution; which can be exploited in order to obtain different crystal forms of a better quality

In Situ Structural Restraints from Cross-Linking Mass Spectrometry in Human Mitochondria

The field of structural biology is increasingly focusing on studying proteins in situ, i.e., in their greater biological context. Cross-linking mass spectrometry (CLMS) is contributing to this effort, typically through the use of mass spectrometry (MS)-cleavable cross-linkers. Here, we apply the popular noncleavable cross-linker disuccinimidyl suberate (DSS) to human mitochondria and identify 5518 distance restraints between protein residues. Each distance restraint on proteins or their interactions provides structural information within mitochondria. Comparing these restraints to protein data bank (PDB)-deposited structures and comparative models reveals novel protein conformations. Our data suggest, among others, substrates and protein flexibility of mitochondrial heat shock proteins. Through this study, we bring forward two central points for the progression of CLMS towards large-scale in situ structural biology: First, clustered conflicts of cross-link data reveal in situ protein conformation states in contrast to error-rich individual conflicts. Second, noncleavable cross-linkers are compatible with proteome-wide studies.

A New Look at the Structures of Old Sepsis Actors by Exploratory Data Analysis Tools

Sepsis is a life-threatening condition that accounts for numerous deaths worldwide, usually complications of common community infections (i.e., pneumonia, etc), or infections acquired during the hospital stay. Sepsis and septic shock, its most severe evolution, involve the whole organism, recruiting and producing a lot of molecules, mostly proteins. Proteins are dynamic entities, and a large number of techniques and studies have been devoted to elucidating the relationship between the conformations adopted by proteins and what is their function. Although molecular dynamics has a key role in understanding these relationships, the number of protein structures available in the databases is so high that it is currently possible to build data sets obtained from experimentally determined structures. Techniques for dimensionality reduction and clustering can be applied in exploratory data analysis in order to obtain information on the function of these molecules, and this may be very useful in immunology to better understand the structure-activity relationship of the numerous proteins involved in host defense, moreover in septic patients. The large number of degrees of freedom that characterize the biomolecules requires special techniques which are able to analyze this kind of data sets (with a small number of entries respect to the number of degrees of freedom). In this work we analyzed the ability of two different types of algorithms to provide information on the structures present in three data sets built using the experimental structures of allosteric proteins involved in sepsis. The results obtained by means of a principal component analysis algorithm and those obtained by a random projection algorithm are largely comparable, proving the effectiveness of random projection methods in structural bioinformatics. The usefulness of random projection in exploratory data analysis is discussed, including validation of the obtained clusters. We have chosen these proteins because of their involvement in sepsis and septic shock, aimed to highlight the potentiality of bioinformatics to point out new diagnostic and prognostic tools for the patients.

Fine Mapping of Glutamate Decarboxylase 65 Epitopes Reveals Dependency on Hydrophobic Amino Acids for Specific Interactions

Characterization of multiple antibody epitopes has revealed the necessity of specific groups of amino acid residues for reactivity. This applies to the majority of antibody-antigen interactions, where especially charged and hydrophilic amino acids have been reported to be essential for antibody reactivity. This study describes thorough characterization of glutamic acid decarboxylase (GAD) 65 antigenic epitopes, an immunodominant autoantigen in type 1 diabetes (T1D). As linear epitopes are sparsely described for GAD65 in T1D, we aimed to identify and thoroughly characterize two GAD65 antibodies using immunoassays. A monoclonal antibody recognized an epitope in the N-terminal domain of GAD65, ⁸FWSFGSE¹⁴, whereas a polyclonal antibody recognized two continuous epitopes in the C-terminal domain, corresponding to amino acids ⁵¹⁴RTLED⁵¹⁸ and ⁵⁴⁹PLGDKVNF⁵⁵⁶. Hydrophobic amino acids were essential for antibody reactivity, which was verified by competitive inhibition assays. Moreover, the epitopes were located in flexible linker regions and turn structures. These findings confirm the versatile nature of antibody-antigen interactions and describe potential continuous epitopes related to T1D, which predominantly have been proposed to be of discontinuous nature.

Impact of charge state on 193 nm ultraviolet photodissociation of protein complexes

As applications in mass spectrometry continue to expand into the field of structural biology, there have been an increasing number of studies on noncovalent biological assemblies. Ensuring that protein complexes maintain native-like conformations and architectures during the transition from solution to the gas phase is a key aim. Probing composition and arrangement of subunits of multi-charged complexes via tandem mass spectrometry (MS/MS) may lead to protein unfolding and the redistribution of charges on the constituent subunits, leading to asymmetric charge partitioning and ejection of a high-charged monomer. Additionally, the overall dissociation efficiency of many ion activation methods is often suppressed for low charge states, hindering the effectiveness of MS/MS for complexes that have low charge density. Ultraviolet photodissociation (UVPD) of proteins using 193 nm photons is a high-energy alternative to collisional activation and demonstrates little to no charge state dependence. Here the symmetry of charge partitioning upon UVPD is evaluated for an array of multimeric protein complexes as a function of initial charge state. The results demonstrate that high laser energies (3 mJ) for UVPD induces more symmetric charge partitioning and ejection of low-charged, presumably compact monomers than higher-energy collisional dissociation (HCD).

Equilibrium versus Nonequilibrium Peptide Dynamics: Insights into Transient 2D IR Spectroscopy

Over the past two decades, two-dimensional infrared (2D IR) spectroscopy has evolved from the theoretical underpinnings of nonlinear spectroscopy as a means of investigating detailed molecular structure on an ultrafast time scale. The combined time and spectral resolution over which spectra can be collected on complex molecular systems has led to the precise structural resolution of dynamic species that have previously been impossible to directly observe through traditional methods. The adoption of 2D IR spectroscopy for the study of protein folding and peptide interactions has provided key details of how small changes in conformations can exert major influences on the activities of these complex molecular systems. Traditional 2D IR experiments are limited to molecules under equilibrium conditions, where small motions and fluctuations of these larger molecules often still lead to functionality. Utilizing techniques that allow the rapid initiation of chemical or structural changes in conjunction with 2D IR spectroscopy, i.e., transient 2D IR, a vast dynamic range becomes available to the spectroscopist uncovering structural content far from equilibrium. Furthermore, this allows the observation of reaction pathways of these macromolecules under quasi- and nonequilibrium conditions.

Use of designed sequences in protein structure recognition

Background

Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure.

Results

We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation.

Conclusion

The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as ‘linkers’, where natural linkers between distant proteins are unavailable.

Reviewers

This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.

Electronic supplementary material

The online version of this article (10.1186/s13062-018-0209-6) contains supplementary material, which is available to authorized users.

Sixty-five years of the long march in protein secondary structure prediction: the final stretch?

Protein secondary structure prediction began in 1951 when Pauling and Corey predicted helical and sheet conformations for protein polypeptide backbone even before the first protein structure was determined. Sixty-five years later, powerful new methods breathe new life into this field. The highest three-state accuracy without relying on structure templates is now at 82-84%, a number unthinkable just a few years ago. These improvements came from increasingly larger databases of protein sequences and structures for training, the use of template secondary structure information and more powerful deep learning techniques. As we are approaching to the theoretical limit of three-state prediction (88-90%), alternative to secondary structure prediction (prediction of backbone torsion angles and Cα-atom-based angles and torsion angles) not only has more room for further improvement but also allows direct prediction of three-dimensional fragment structures with constantly improved accuracy. About 20% of all 40-residue fragments in a database of 1199 non-redundant proteins have <6 Å root-mean-squared distance from the native conformations by SPIDER2. More powerful deep learning methods with improved capability of capturing long-range interactions begin to emerge as the next generation of techniques for secondary structure prediction. The time has come to finish off the final stretch of the long march towards protein secondary structure prediction.

Site-Directed Spin Labeling EPR for Studying Membrane Proteins

Site-directed spin labeling (SDSL) in combination with electron paramagnetic resonance (EPR) spectroscopy is a rapidly expanding powerful biophysical technique to study the structural and dynamic properties of membrane proteins in a native environment. Membrane proteins are responsible for performing important functions in a wide variety of complicated biological systems that are responsible for the survival of living organisms. In this review, a brief introduction of the most popular SDSL EPR techniques and illustrations of recent applications for studying pertinent structural and dynamic properties on membrane proteins will be discussed.

Orthogonal Mass Spectrometry-Based Footprinting for Epitope Mapping and Structural Characterization: The IL-6 Receptor upon Binding of Protein Therapeutics

Higher-order structure (HOS) is a crucial determinant for the biological functions and quality attributes of protein therapeutics. Mass spectrometry (MS)-based protein footprinting approaches play an important role in elucidating the relationship between protein biophysical properties and structure. Here, we describe the use of a combined method including hydrogen-deuterium exchange (HDX), fast photochemical oxidation of proteins (FPOP), and site-specific carboxyl group footprinting to investigate the HOS of protein and protein complexes. The work focuses on implementing complementary solution-phase footprinting approaches that differ in time scale, specificity for protein residue side chains vs backbone as well as selectivity for different residue types to map integratively the epitope of human interleukin-6 receptor (IL-6R) for two adnectins with distinct affinities (Kd, Adnectin1 ∼ 6.2 pM vs Kd, Adnectin2 ∼ 46 nM). Furthermore, the study evaluates the resultant conformation/dynamic change of IL-6R. The suggested epitope, which is conserved for adnectin1 and adnectin2 binding, is a flexible loop that connects two β-strands in the cytokine-binding domain (DII) of IL-6R. We also found that adnectin1, the more strongly binding ligand, induces structural perturbations on two unstructured loops that are distally located beyond the epitope. Those changes are either attenuated or not detected for the case of adnectin2 binding. In addition to providing credibility in epitope determination, utilization of those combined approaches reveals the structural effects that can differentiate protein therapeutics with apparently similar biophysical properties.

Conformational modulation of the farnesoid X receptor by prenylflavonoids: Insights from hydrogen deuterium exchange mass spectrometry (HDX-MS), fluorescence titration and molecular docking studies

We report on the molecular interactions of the farnesoid X receptor (FXR) with prenylflavonoids, an emerging class of FXR modulators. FXR is an attractive therapeutic target for mitigating metabolic syndromes (MetS) because FXR activates the inhibitory nuclear receptor, small heterodimer partner (SHP), thereby inhibiting both gluconeogenesis and de novo lipogenesis. We and others have shown that xanthohumol (XN), the principal prenylflavonoid of the hop plant (Humulus lupulus L.), is a FXR agonist based on its ability to affect lipid and glucose metabolism in vivo and to induces FXR target genes in biliary carcinoma cells and HEK293 cells. However, studies are currently lacking to rationalize the molecular mechanisms of FXR modulation by prenylflavonoids. We addressed this deficiency and report the first systematic study of FXR prenylflavonoid interactions. We combined hydrogen deuterium exchange mass spectrometry (HDX-MS) with computational studies for dissecting molecular recognition and conformational impact of prenylflavonoid interactions on the ligand binding domain (LBD) of human FXR. Four prenylflavonoids were tested: xanthohumol, a prenylated chalcone, two prenylated flavonones, namely isoxanthohumol (IX) and 8-prenylnaringenin (8PN), and a semisynthetic prenylflavonoid derivative, tetrahydroxanthohumol (TX). Enhancement of the HDX protection profile data by in silico predicted models of FXR prenylflavonoid complexes resulted in mapping of the prenylflavonoid interactions within the canonical ligand binding pocket. Our findings provide a foundation for the exploration of the chemical scaffolds of prenylated chalcones and flavanones as leads for future structure activity studies of this important nuclear receptor with potential relevance for ameliorating lipid metabolic disorders associated with obesity and MetS.

Gene Prioritization by Integrated Analysis of Protein Structural and Network Topological Properties for the Protein-Protein Interaction Network of Neurological Disorders

Neurological disorders are known to show similar phenotypic manifestations like anxiety, depression, and cognitive impairment. There is a need to identify shared genetic markers and molecular pathways in these diseases, which lead to such comorbid conditions. Our study aims to prioritize novel genetic markers that might increase the susceptibility of patients affected with one neurological disorder to other diseases with similar manifestations. Identification of pathways involving common candidate markers will help in the development of improved diagnosis and treatments strategies for patients affected with neurological disorders. This systems biology study for the first time integratively uses 3D-structural protein interface descriptors and network topological properties that characterize proteins in a neurological protein interaction network, to aid the identification of genes that are previously not known to be shared between these diseases. Results of protein prioritization by machine learning have identified known as well as new genetic markers which might have direct or indirect involvement in several neurological disorders. Important gene hubs have also been identified that provide an evidence for shared molecular pathways in the neurological disease network.

Ras Conformational Ensembles, Allostery, and Signaling

Ras proteins are classical members of small GTPases that function as molecular switches by alternating between inactive GDP-bound and active GTP-bound states. Ras activation is regulated by guanine nucleotide exchange factors that catalyze the exchange of GDP by GTP, and inactivation is terminated by GTPase-activating proteins that accelerate the intrinsic GTP hydrolysis rate by orders of magnitude. In this review, we focus on data that have accumulated over the past few years pertaining to the conformational ensembles and the allosteric regulation of Ras proteins and their interpretation from our conformational landscape standpoint. The Ras ensemble embodies all states, including the ligand-bound conformations, the activated (or inactivated) allosteric modulated states, post-translationally modified states, mutational states, transition states, and nonfunctional states serving as a reservoir for emerging functions. The ensemble is shifted by distinct mutational events, cofactors, post-translational modifications, and different membrane compositions. A better understanding of Ras biology can contribute to therapeutic strategies.

Mapping of Fab-1:VEGF Interface Using Carboxyl Group Footprinting Mass Spectrometry

A proof-of-concept study was performed to demonstrate that carboxyl group footprinting, a relatively simple, bench-top method, has utility for first-pass analysis to determine epitope regions of therapeutic mAb:antigen complexes. The binding interface of vascular endothelial growth factor (VEGF) and the Fab portion of a neutralizing antibody (Fab-1) was analyzed using carboxyl group footprinting with glycine ethyl ester (GEE) labeling. Tryptic peptides involved in the binding interface between VEGF and Fab-1 were identified by determining the specific GEE-labeled residues that exhibited a reduction in the rate of labeling after complex formation. A significant reduction in the rate of GEE labeling was observed for E93 in the VEGF tryptic peptide V5, and D28 and E57 in the Fab-1 tryptic peptides HC2 and HC4, respectively. Results from the carboxyl group footprinting were compared with the binding interface identified from a previously characterized crystal structure (PDB: 1BJ1). All of these residues are located at the Fab-1:VEGF interface according to the crystal structure, demonstrating the potential utility of carboxyl group footprinting with GEE labeling for mapping epitopes. Graphical Abstract ᅟ.

Phospholipase C zeta (PLCζ) and male infertility: Clinical update and topical developments

The development of a mammalian embryo is initiated by a sequence of molecular events collectively referred to as 'oocyte activation' and regulated by the release of intracellular calcium in the ooplasm. Over the last decade, phospholipase C zeta (PLCζ), a sperm protein introduced into the oocyte upon gamete fusion, has gained almost universal acceptance as the protein factor responsible for initiating oocyte activation. A large body of consistent and reproducible evidence, from both biochemical and clinical settings, confers support for the role of PLCζ in this fundamental biological context, which has significant ramifications for the management of human male infertility. Oocyte activation deficiency (OAD) and total fertilisation failure (TFF) are known causes of infertility and have both been linked to abnormalities in the structure, expression, and localisation pattern of PLCζ in human sperm. Assisted oocyte activators (AOAs) represent the only therapeutic option available for OAD at present, although these agents have been the source of much debate recently, particularly with regard to their potential epigenetic effects upon the embryo. Consequently, there is much interest in the deployment of sensitive PLCζ assays as prognostic/diagnostic tests and human recombinant PLCζ protein as an alternative form of therapy. Although PLCζ deficiency has been directly linked to a cohort of infertile cases, we have yet to identify the specific causal mechanisms involved. While two genetic mutations have been identified which link defective PLCζ protein to an infertile phenotype, both were observed in the same patient, and have yet to be described in other patients. Consequently, some researchers are investigating the possibility that genetic variations in the form of single nucleotide polymorphisms (SNPs) could provide some explanation, especially since >6000 SNPs have been identified in the PLCζ gene. As yet, however, there is no consistent data to suggest that any of these SNPs influence the functional ability of PLCζ. Other laboratories appear to be focussing upon the PLCζ promoter, which is bi-directional and shared with the actin filament capping muscle Z-line alpha 3 gene (CAPZA3), or seeking to identify interacting proteins within the ooplasm. The aim of this review is to provide a synopsis of recent progress in the application of PLCζ in diagnostic and therapeutic medicine, to discuss our current understanding of how the functional ability of PLCζ might be controlled, and thus how PLCζ deficiency might arise, and finally, to consider the potential implications of alternative sperm protein candidates, such as post-acrosomal WW-domain binding protein (PAWP), which has caused much debate and confusion in the field over the last few years.

Biophysical EPR Studies Applied to Membrane Proteins

Membrane proteins are very important in controlling bioenergetics, functional activity, and initializing signal pathways in a wide variety of complicated biological systems. They also represent approximately 50% of the potential drug targets. EPR spectroscopy is a very popular and powerful biophysical tool that is used to study the structural and dynamic properties of membrane proteins. In this article, a basic overview of the most commonly used EPR techniques and examples of recent applications to answer pertinent structural and dynamic related questions on membrane protein systems will be presented.

Structural characterization of holo- and apo-myoglobin in the gas phase by ultraviolet photodissociation mass spectrometry

Ultraviolet photodissociation (UVPD) mass spectrometry is employed to investigate the structure of holo-myoglobin as well as its apo form transferred to the gas phase by native electrospray. UVPD provided insight into the stability of native structural elements of holo-myoglobin. The fragmentation yields from UVPD showed the greatest overall correlation with B-factors generated from the crystal structure of apo-myoglobin, particularly for the more disordered loop regions. Solvent accessibility measurements also showed some correlation with the UVPD fragmentation of holo-myoglobin. Comparison of UVPD of holo- and apo-myoglobin revealed similarities in fragmentation yields, particularly for the lower charge states (8 and 9+). Both holo- and apo-myoglobin exhibited low fragmentation yields for the AGH helical core, whereas regions known to interact with the heme show suppressed fragmentation for holo-myoglobin. The fragment yields from HCD showed the lowest correlation with B-factor values and rather reflected preferential charge-directed backbone cleavages.

The s2D method: simultaneous sequence-based prediction of the statistical populations of ordered and disordered regions in proteins

Extensive amounts of information about protein sequences are becoming available, as demonstrated by the over 79 million entries in the UniProt database. Yet, it is still challenging to obtain proteome-wide experimental information on the structural properties associated with these sequences. Fast computational predictors of secondary structure and of intrinsic disorder of proteins have been developed in order to bridge this gap. These two types of predictions, however, have remained largely separated, often preventing a clear characterization of the structure and dynamics of proteins. Here, we introduce a computational method to predict secondary-structure populations from amino acid sequences, which simultaneously characterizes structure and disorder in a unified statistical mechanics framework. To develop this method, called s2D, we exploited recent advances made in the analysis of NMR chemical shifts that provide quantitative information about the probability distributions of secondary-structure elements in disordered states. The results that we discuss show that the s2D method predicts secondary-structure populations with an average error of about 14%. A validation on three datasets of mostly disordered, mostly structured and partly structured proteins, respectively, shows that its performance is comparable to or better than that of existing predictors of intrinsic disorder and of secondary structure. These results indicate that it is possible to perform rapid and quantitative sequence-based characterizations of the structure and dynamics of proteins through the predictions of the statistical distributions of their ordered and disordered regions.

Combining ion mobility spectrometry with hydrogen-deuterium exchange and top-down MS for peptide ion structure analysis

The gas-phase conformations of electrosprayed ions of the model peptide KKDDDDIIKIIK have been examined by ion mobility spectrometry (IMS) and hydrogen deuterium exchange (HDX)-tandem mass spectrometry (MS/MS) techniques. [M+4H](4+) ions exhibit two conformers with collision cross sections of 418 Å(2) and 471 Å(2). [M+3H](3+) ions exhibit a predominant conformer with a collision cross section of 340 Å(2) as well as an unresolved conformer (shoulder) with a collision cross section of ~367 Å(2). Maximum HDX levels for the more compact [M+4H](4+) ions and the compact and partially-folded [M+3H](3+) ions are ~12.9, ~15.5, and ~14.9, respectively. Ion structures obtained from molecular dynamics simulations (MDS) suggest that this ordering of HDX level results from increased charge-site/exchange-site density for the more compact ions of lower charge. Additionally, a new model that includes two distance calculations (charge site to carbonyl group and carbonyl group to exchange site) for the computer-generated structures is shown to better correlate to the experimentally determined per-residue deuterium uptake. Future comparisons of IMS-HDX-MS data with structures obtained from MDS are discussed with respect to novel experiments that will reveal the HDX rates of individual residues.