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

Transient Non-local Interactions Dominate the Dynamics of Measles Virus NTAIL

The RNA genome of measles virus is encapsidated by the nucleoprotein within a helical nucleocapsid that serves as template for both transcription and replication. The intrinsically disordered domain of the nucleoprotein (NTAIL), partly protruding outward from the nucleocapsid, is essential for binding the polymerase complex responsible for viral transcription and replication. As for many IDPs, binding of NTAIL occurs through a short molecular recognition element (MoRE) that folds upon binding, with the majority of NTAIL remaining disordered. Though NTAIL regions far from the MoRE influence the binding affinity, interactions between them and the MoRE have not been investigated in depth. Using an integrated approach, relying on photo-induced electron transfer (PET) experiments between tryptophan and cysteine pairs placed at different positions in the protein under varying salt and pH conditions, combined with simulations and analytical models, we identified transient interactions between two disordered regions distant in sequence, which dominate NTAIL dynamics, and regulate the conformational preferences of both the MoRE and the entire NTAIL domain. Co-evolutionary analysis corroborates our findings, and suggests an important functional role for the same intramolecular interactions. We propose mechanisms by which these non-local interactions may regulate binding to the phosphoprotein, polymerase recruitment, and ultimately viral transcription and replication. Our findings may be extended to other IDPs, where non-local intra-protein interactions affect the conformational preferences of intermolecular binding sites.

Clusters of acidic and hydrophobic residues can predict acidic transcriptional activation domains from protein sequence

Transcription factors activate gene expression in development, homeostasis, and stress with DNA binding domains and activation domains. Although there exist excellent computational models for predicting DNA binding domains from protein sequence, models for predicting activation domains from protein sequence have lagged, particularly in metazoans. We recently developed a simple and accurate predictor of acidic activation domains on human transcription factors. Here, we show how the accuracy of this human predictor arises from the clustering of aromatic, leucine, and acidic residues, which together are necessary for acidic activation domain function. When we combine our predictor with the predictions of convolutional neural network (CNN) models trained in yeast, the intersection is more accurate than individual models, emphasizing that each approach carries orthogonal information. We synthesize these findings into a new set of activation domain predictions on human transcription factors.

The Sherpa hypothesis: Phenotype-Preserving Disordered Proteins stabilize the phenotypes of neurons and oligodendrocytes

Intrinsically disordered proteins (IDPs), which can interact with many partner proteins, are central to many physiological functions and to various pathologies that include neurodegeneration. Here, we introduce the Sherpa hypothesis, according to which a subset of stable IDPs that we term Phenotype-Preserving Disordered Proteins (PPDP) play a central role in protecting cell phenotypes from perturbations. To illustrate and test this hypothesis, we computer-simulate some salient features of how cells evolve and differentiate in the presence of either a single PPDP or two incompatible PPDPs. We relate this virtual experiment to the pathological interactions between two PPDPs, α-synuclein and Tubulin Polymerization Promoting Protein/p25, in neurodegenerative disorders. Finally, we discuss the implications of the Sherpa hypothesis for aptamer-based therapies of such disorders.

Interpreting Transient Interactions of Intrinsically Disordered Proteins

The flexible nature of intrinsically disordered proteins (IDPs) gives rise to a conformational ensemble with a diverse set of conformations. The simplest way to describe this ensemble is through a homopolymer model without any specific interactions. However, there has been growing evidence that the conformational properties of IDPs and their relevant functions can be affected by transient interactions between specific and even nonlocal pairs of amino acids. Interpreting these interactions from experimental methods, each of which is most sensitive to a different distance regime referred to as probing length, remains a challenging and unsolved problem. Here, we first show that transient interactions can be realized between short fragments of charged amino acids by generating conformational ensembles using model disordered peptides and coarse-grained simulations. Using these ensembles, we investigate how sensitive different types of experimental measurements are to the presence of transient interactions. We find methods with shorter probing lengths to be more appropriate for detecting these transient interactions, but one experimental method is not sufficient due to the existence of other weak interactions typically seen in IDPs. Finally, we develop an adjusted polymer model with an additional short-distance peak which can robustly reproduce the distance distribution function from two experimental measurements with complementary short and long probing lengths. This new model can suggest whether a homopolymer model is insufficient for describing a specific IDP and meets the challenge of quantitatively identifying specific, transient interactions from a background of nonspecific, weak interactions.

Estrogen Receptor Alpha Splice Variants, Post-Translational Modifications, and Their Physiological Functions

The importance of estrogenic signaling for a broad spectrum of biological processes, including reproduction, cancer development, energy metabolism, memory and learning, and so on, has been well documented. Among reported estrogen receptors, estrogen receptor alpha (ERα) has been known to be a major mediator of cellular estrogenic signaling. Accumulating evidence has shown that the regulations of ERα gene transcription, splicing, and expression across the tissues are highly complex. The ERα promoter region is composed of multiple leader exons and 5′-untranslated region (5′-UTR) exons. Differential splicing results in multiple ERα proteins with different molecular weights and functional domains. Furthermore, various post-translational modifications (PTMs) further impact ERα cellular localization, ligand affinity, and therefore functionality. These splicing isoforms and PTMs are differentially expressed in a tissue-specific manner, mediate certain aspects of ERα signaling, and may work even antagonistically against the full-length ERα. The fundamental understanding of the ERα splicing isoforms in normal physiology is limited and association studies of the splicing isoforms and the PTMs are scarce. This review aims to summarize the functional diversity of these ERα variants and the PTMs in normal physiological processes, particularly as studied in transgenic mouse models.

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.

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.

Estrogen receptor α revised: Expression, structure, function, and stability

Estrogen receptor α (ERα) is a ligand-dependent transcription factor that regulates the expression of estrogen-responsive genes. Approximately 70% of patients with breast cancer are ERα positive. Estrogen stimulates cancer cell proliferation and contributes to tumor progression. Endocrine therapies, which suppress the ERα signaling pathway, significantly improve the prognosis of patients with breast cancer. However, the development of de novo or acquired endocrine therapy resistance remains a barrier to breast cancer treatment. Therefore, understanding the regulatory mechanisms of ERα is essential to overcome the resistance to treatment. This review focuses on the regulation of ERα expression, including copy number variation, epigenetic regulation, transcriptional regulation, and stability, as well as functions from the point of view post-translational modifications.

Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma

Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.

Intrinsically disordered proteins play diverse roles in cell signaling

Signaling pathways allow cells to detect and respond to a wide variety of chemical (e.g. Ca2+ or chemokine proteins) and physical stimuli (e.g., sheer stress, light). Together, these pathways form an extensive communication network that regulates basic cell activities and coordinates the function of multiple cells or tissues. The process of cell signaling imposes many demands on the proteins that comprise these pathways, including the abilities to form active and inactive states, and to engage in multiple protein interactions. Furthermore, successful signaling often requires amplifying the signal, regulating or tuning the response to the signal, combining information sourced from multiple pathways, all while ensuring fidelity of the process. This sensitivity, adaptability, and tunability are possible, in part, due to the inclusion of intrinsically disordered regions in many proteins involved in cell signaling. The goal of this collection is to highlight the many roles of intrinsic disorder in cell signaling. Following an overview of resources that can be used to study intrinsically disordered proteins, this review highlights the critical role of intrinsically disordered proteins for signaling in widely diverse organisms (animals, plants, bacteria, fungi), in every category of cell signaling pathway (autocrine, juxtacrine, intracrine, paracrine, and endocrine) and at each stage (ligand, receptor, transducer, effector, terminator) in the cell signaling process. Thus, a cell signaling pathway cannot be fully described without understanding how intrinsically disordered protein regions contribute to its function. The ubiquitous presence of intrinsic disorder in different stages of diverse cell signaling pathways suggest that more mechanisms by which disorder modulates intra- and inter-cell signals remain to be discovered.

Fusion-Associated Carcinomas of the Breast: Diagnostic, Prognostic, and Therapeutic Significance

Recurrent gene fusions comprise a class of viable genetic targets in solid tumors that have culminated several recent break-through cancer therapies. Their role in breast cancer, however, remains largely underappreciated due to the complexity of genomic rearrangements in breast malignancy. Just recently, we and others have identified several recurrent gene fusions in breast cancer with important clinical and biological implications. Examples of the most significant recurrent gene fusions to date include 1) ESR1-CCDC170 gene fusions in luminal B and endocrine resistant breast cancer that exert oncogenic function via modulating the HER2/HER3/SRC complex, 2) ESR1 exon 6 fusions in metastatic disease that drive estrogen-independent ER transcriptional activity, 3) BCL2L14-ETV6 fusions in a more aggressive form of the triple negative subtype that prime epithelial-mesenchymal transition and endow paclitaxel resistance, 4) the ETV6-NTRK3 fusion in secretory breast carcinoma that constitutively activates NTRK3 kinase, 5) the oncogenic MYB-NFIB fusion as a genetic driver underpinning adenoid cystic carcinomas of the breast that activates MYB pathway, and 6) the NOTCH/MAST kinase gene fusions that activate NOTCH and MAST signaling. Importantly, these fusions are enriched in more aggressive and lethal breast cancer presentations and appear to confer therapeutic resistance. Thus, these gene fusions could be utilized as genetic biomarkers to identify patients that require more intensive treatment and surveillance. In addition, kinase fusions are currently being evaluated in breast cancer clinical trials and on-going mechanistic investigation is exposing therapeutic vulnerabilities in patients with fusion positive disease. This article is protected by copyright. All rights reserved.

Allosteric binding on nuclear receptors: Insights on screening of non-competitive endocrine-disrupting chemicals

Endocrine-disrupting chemicals (EDCs) can compete with endogenous hormones and bind to the orthosteric site of nuclear receptors (NRs), affecting normal endocrine system function and causing severe symptoms. Recently, a series of pharmaceuticals and personal care products (PPCPs) have been discovered to bind to the allosteric sites of NRs and induce similar effects. However, it remains unclear how diverse EDCs work in this new way. Therefore, we have systematically summarized the allosteric sites and underlying mechanisms based on existing studies, mainly regarding drugs belonging to the PPCP class. Advanced methods, classified as structural biology, biochemistry and computational simulation, together with their advantages and hurdles for allosteric site recognition and mechanism insight have also been described. Furthermore, we have highlighted two available strategies for virtual screening of numerous EDCs, relying on the structural features of allosteric sites and lead compounds, respectively. We aim to provide reliable theoretical and technical support for a broader view of various allosteric interactions between EDCs and NRs, and to drive high-throughput and accurate screening of potential EDCs with non-competitive effects.

Small, but powerful and attractive: 19F in biomolecular NMR

Nuclear magnetic resonance (NMR) spectroscopy is a versatile tool for probing structure, dynamics, folding, and interactions at atomic resolution. While naturally occurring magnetically active isotopes, such as ¹H, ¹³C, or ¹⁵N, are most commonly used in biomolecular NMR, with ¹⁵N and ¹³C isotopic labeling routinely employed at the present time, ¹⁹F is a very attractive and sensitive alternative nucleus, which offers rich information on biomolecules in solution and in the solid state. This perspective summarizes the unique benefits of solution and solid-state ¹⁹F NMR spectroscopy for the study of biological systems. Particular focus is on the most recent studies and on future unique and important potential applications of fluorine NMR methodology.

Recent advances in small-angle scattering and its expanding impact in structural biology

Applications of small-angle scattering (SAS) in structural biology have benefited from continuing developments in instrumentation, tools for data analysis, modeling capabilities, standards for data and model presentation, and data archiving. The interplay of these capabilities has enabled SAS to contribute to advances in structural biology as the field pushes the boundaries in studies of biomolecular complexes and assemblies as large as whole cells, membrane proteins in lipid environments, and dynamic systems on time scales ranging from femtoseconds to hours. This review covers some of the important advances in biomolecular SAS capabilities for structural biology focused on over the last 5 years and presents highlights of recent applications that demonstrate how the technique is exploring new territories.

Poly-glutamine-dependent self-association as a potential mechanism for regulation of androgen receptor activity

The androgen receptor (AR) plays a central role in prostate cancer. Development of castration resistant prostate cancer (CRPC) requires androgen-independent activation of AR, which involves its large N-terminal domain (NTD) and entails extensive epigenetic changes depending in part on histone lysine demethylases (KDMs) that interact with AR. The AR-NTD is rich in low-complexity sequences, including a polyQ repeat. Longer polyQ sequences were reported to decrease transcriptional activity and to protect against prostate cancer, although they can lead to muscular atrophy. However, the molecular mechanisms underlying these observations are unclear. Using NMR spectroscopy, here we identify weak interactions between the AR-NTD and the KDM4A catalytic domain, and between the AR ligand-binding domain and a central KDM4A region that also contains low-complexity sequences. We also show that the AR-NTD can undergo liquid-liquid phase separation in vitro, with longer polyQ sequences phase separating more readily. Moreover, longer polyQ sequences hinder nuclear localization in the absence of hormone and increase the propensity for formation of AR-containing puncta in the nucleus of cells treated with dihydrotestosterone. These results lead us to hypothesize that polyQ-dependent liquid-liquid phase separation may provide a mechanism to decrease the transcriptional activity of AR, potentially opening new opportunities to design effective therapies against CRPC and muscular atrophy.

Mechanism of RNA recognition by a Musashi RNA-binding protein

The Musashi RNA-binding proteins (RBPs) regulate translation of target mRNAs and maintenance of cell stemness and tumorigenesis. Musashi-1 (MSI1), long considered as an intestinal and neural stem cell marker, has been more recently found to be over expressed in many cancers. It has served as an important drug target for treating acute myeloid leukemia and solid tumors such as ovarian, colorectal and bladder cancer. One of the reported binding targets of MSI1 is Numb, a negative regulator of the Notch signaling. However, the dynamic mechanism of Numb RNA binding to MSI1 remains unknown, largely hindering effective drug design targeting this critical interaction. Here, we have performed extensive all-atom microsecond-timescale simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method, which successfully captured multiple times of spontaneous and highly accurate binding of the Numb RNA from bulk solvent to the MSI1 protein target site. GaMD simulations revealed that Numb RNA binding to MSI1 involved largely induced fit in both the RNA and protein. The simulations also identified important low-energy intermediate conformational states during RNA binding, in which Numb interacted mainly with the β2-β3 loop and C terminus of MSI1. The mechanistic understanding of RNA binding obtained from our GaMD simulations is expected to facilitate rational structure-based drug design targeting MSI1 and other RBPs.

Gaussian accelerated molecular dynamics (GaMD): principles and applications

Gaussian accelerated molecular dynamics (GaMD) is a robust computational method for simultaneous unconstrained enhanced sampling and free energy calculations of biomolecules. It works by adding a harmonic boost potential to smooth biomolecular potential energy surface and reduce energy barriers. GaMD greatly accelerates biomolecular simulations by orders of magnitude. Without the need to set predefined reaction coordinates or collective variables, GaMD provides unconstrained enhanced sampling and is advantageous for simulating complex biological processes. The GaMD boost potential exhibits a Gaussian distribution, thereby allowing for energetic reweighting via cumulant expansion to the second order (i.e., "Gaussian approximation"). This leads to accurate reconstruction of free energy landscapes of biomolecules. Hybrid schemes with other enhanced sampling methods, such as the replica exchange GaMD (rex-GaMD) and replica exchange umbrella sampling GaMD (GaREUS), have also been introduced, further improving sampling and free energy calculations. Recently, new "selective GaMD" algorithms including the ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD) enabled microsecond simulations to capture repetitive dissociation and binding of small-molecule ligands and highly flexible peptides. The simulations then allowed highly efficient quantitative characterization of the ligand/peptide binding thermodynamics and kinetics. Taken together, GaMD and its innovative variants are applicable to simulate a wide variety of biomolecular dynamics, including protein folding, conformational changes and allostery, ligand binding, peptide binding, protein-protein/nucleic acid/carbohydrate interactions, and carbohydrate/nucleic acid interactions. In this review, we present principles of the GaMD algorithms and recent applications in biomolecular simulations and drug design.

Structural basis for the hyperthermostability of an archaeal enzyme induced by succinimide formation

Stability of proteins from hyperthermophiles (organisms existing under boiling water conditions) enabled by a reduction of conformational flexibility is realized through various mechanisms. A succinimide (SNN) arising from the post-translational cyclization of the side chains of aspartyl/asparaginyl residues with the backbone amide -NH of the succeeding residue would restrain the torsion angle Ψ and can serve as a new route for hyperthermostability. However, such a succinimide is typically prone to hydrolysis, transforming to either an aspartyl or β-isoaspartyl residue. Here, we present the crystal structure of Methanocaldococcus jannaschii glutamine amidotransferase and, using enhanced sampling molecular dynamics simulations, address the mechanism of its increased thermostability, up to 100°C, imparted by an unexpectedly stable succinimidyl residue at position 109. The stability of SNN109 to hydrolysis is seen to arise from its electrostatic shielding by the side-chain carboxylate group of its succeeding residue Asp110, as well as through n → π^∗ interactions between SNN109 and its preceding residue Glu108, both of which prevent water access to SNN. The stable succinimidyl residue induces the formation of an α-turn structure involving 13-atom hydrogen bonding, which locks the local conformation, reducing protein flexibility. The destabilization of the protein upon replacement of SNN with a Φ-restricted prolyl residue highlights the specificity of the succinimidyl residue in imparting hyperthermostability to the enzyme. The conservation of the succinimide-forming tripeptide sequence (E(N/D)(E/D)) in several archaeal GATases strongly suggests an adaptation of this otherwise detrimental post-translational modification as a harbinger of thermostability.

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.

Beyond history and "on a roll": The list of the most well-studied human protein structures and overall trends in the protein data bank

Of the roughly 20,000 canonical human protein sequences, as of January 20, 2021, 7,077 proteins have had their full or partial, medium- to high-resolution structures determined by x-ray crystallography or other methods. Which of these proteins dominate the protein data bank (the PDB) and why? In this paper, we list the 273 top human protein structures based on the number of their PDB entries. This set of proteins accounts for more than 40% of all available human PDB entries and represent past trends as well as current status for protein structural biology. We briefly discuss the relationship which some of the prominent protein structures have with protein research as a whole and mention their relevance to human diseases. The top-10 soluble and membrane proteins are all well-known (most of their first structures being deposited more than 30 years ago). Overall, there is no dramatic change in recent trends in the PDB. Remarkably, the number of structure depositions has grown nearly exponentially over the last 10 or more years (with a doubling time of 7 years for proteins, obtained from any organism). Growth in human protein structures is slightly faster (at 5.9 years). The information in this paper may be informative to senior scientists but also inspire researchers who are new to protein science, providing the year 2021 snap-shot for the state of protein structural biology.

Quantitative comparison between sub-millisecond time resolution single-molecule FRET measurements and 10-second molecular simulations of a biosensor protein

Molecular Dynamics (MD) simulations seek to provide atomic-level insights into conformationally dynamic biological systems at experimentally relevant time resolutions, such as those afforded by single-molecule fluorescence measurements. However, limitations in the time scales of MD simulations and the time resolution of single-molecule measurements have challenged efforts to obtain overlapping temporal regimes required for close quantitative comparisons. Achieving such overlap has the potential to provide novel theories, hypotheses, and interpretations that can inform idealized experimental designs that maximize the detection of the desired reaction coordinate. Here, we report MD simulations at time scales overlapping with in vitro single-molecule Förster (fluorescence) resonance energy transfer (smFRET) measurements of the amino acid binding protein LIV-BP^SS at sub-millisecond resolution. Computationally efficient all-atom structure-based simulations, calibrated against explicit solvent simulations, were employed for sampling multiple cycles of LIV-BP^SS clamshell-like conformational changes on the time scale of seconds, examining the relationship between these events and those observed by smFRET. The MD simulations agree with the smFRET measurements and provide valuable information on local dynamics of fluorophores at their sites of attachment on LIV-BP^SS and the correlations between fluorophore motions and large-scale conformational changes between LIV-BP^SS domains. We further utilize the MD simulations to inform the interpretation of smFRET data, including Förster radius (R₀) and fluorophore orientation factor (κ²) determinations. The approach we describe can be readily extended to distinct biochemical systems, allowing for the interpretation of any FRET system conjugated to protein or ribonucleoprotein complexes, including those with more conformational processes, as well as those implementing multi-color smFRET.

Förster (fluorescence) resonance energy transfer (FRET) has been used extensively by biophysicists as a molecular-scale ruler that yields fundamental structural and kinetic insights into transient processes including complex formation and conformational rearrangements required for biological function. FRET techniques require the identification of informative fluorophore labeling sites, spaced at defined distances to inform on a reaction coordinate of interest and consideration of noise sources that have the potential to obscure quantitative interpretations. Here, we describe an approach to leverage advancements in computationally efficient all-atom structure-based molecular dynamics simulations in which structural dynamics observed via FRET can be interpreted in full atomistic detail on commensurate time scales. We demonstrate the potential of this approach using a model FRET system, the amino acid binding protein LIV-BP^SS conjugated to self-healing organic fluorophores. LIV-BP^SS exhibits large scale, sub-millisecond clamshell-like conformational changes between open and closed conformations associated with ligand unbinding and binding, respectively. Our findings inform on the molecular basis of the dynamics observed by smFRET and on strategies to optimize fluorophore labeling sites, the manner of fluorophore attachment, and fluorophore composition.

Agonist Binding and G Protein Coupling in Histamine H2 Receptor: A Molecular Dynamics Study

The histamine H2 receptor (H₂R) plays an important role in the regulation of gastric acid secretion. Therefore, it is a main drug target for the treatment of gastroesophageal reflux or peptic ulcer disease. However, there is as of yet no 3D-structural information available hampering a mechanistic understanding of H₂R. Therefore, we created a model of the histamine-H₂R-G_s complex based on the structure of the ternary complex of the β2-adrenoceptor and investigated the conformational stability of this active GPCR conformation. Since the physiologically relevant motions with respect to ligand binding and conformational changes of GPCRs can only partly be assessed on the timescale of conventional MD (cMD) simulations, we also applied metadynamics and Gaussian accelerated molecular dynamics (GaMD) simulations. A multiple walker metadynamics simulation in combination with cMD was applied for the determination of the histamine binding mode. The preferential binding pose detected is in good agreement with previous data from site directed mutagenesis and provides a basis for rational ligand design. Inspection of the H₂R-G_s interface reveals a network of polar interactions that may contribute to H₂R coupling selectivity. The cMD and GaMD simulations demonstrate that the active conformation is retained on a μs-timescale in the ternary histamine-H₂R-G_s complex and in a truncated complex that contains only G_s helix α5 instead of the entire G protein. In contrast, histamine alone is unable to stabilize the active conformation, which is in line with previous studies of other GPCRs.

Emerging Role of Mass Spectrometry-Based Structural Proteomics in Elucidating Intrinsic Disorder in Proteins

Inherent disorder is an integral part of all proteomes, represented as fully or partially unfolded proteins. The lack of order in intrinsically disordered proteins (IDPs) results in an incredibly flexible, floppy, and heterogeneous ensemble, contrary to the well-structured and unique organization of folded proteins. Despite such unusual demeanor, IDPs are crucial for numerous cellular processes and are increasingly being associated with disease-causing pathologies. These warrant more intensive investigation of this atypical class of protein. Traditional biophysical tools, however, fall short of analyzing IDPs, thus making their structure-function characterization challenging. Mass spectrometry (MS) in recent years has evolved as a valuable tool for elucidating the unusual conformational facets of IDPs. In this review, the features of advanced MS techniques such as Hydrogen-deuterium exchange (HDX)-MS, native MS, limited proteolysis (LiP)-MS, chemical cross-linking (XL)-MS, and Fast photochemical oxidation of proteins (FPOP)-MS are briefly discussed. Recent MS studies on IDPs and the unique advantages/shortfalls associated with the above methods while evaluating structural proteomics of IDPs, are illustrated. Eventually the future scope of the MS methods in further decoding the unexplored landscapes of IDPs is presented.

The metastable states of proteins

The intriguing process of protein folding comprises discrete steps that stabilize the protein molecules in different conformations. The metastable state of protein is represented by specific conformational characteristics, which place the protein in a local free energy minimum state of the energy landscape. The native-to-metastable structural transitions are governed by transient or long-lived thermodynamic and kinetic fluctuations of the intrinsic interactions of the protein molecules. Depiction of the structural and functional properties of metastable proteins is not only required to understand the complexity of folding patterns but also to comprehend the mechanisms of anomalous aggregation of different proteins. In this article, we review the properties of metastable proteins in context of their stability and capability of undergoing atypical aggregation in physiological conditions.

Hydropathy Patterning Complements Charge Patterning to Describe Conformational Preferences of Disordered Proteins

Understanding the conformational ensemble of an intrinsically disordered protein (IDP) is of great interest due to its relevance to critical intracellular functions and diseases. It is now well established that the polymer scaling behavior can provide a great deal of information about the conformational properties as well as liquid-liquid phase separation of an IDP. It is, therefore, extremely desirable to be able to predict an IDP's scaling behavior from the protein sequence itself. The work in this direction so far has focused on highly charged proteins and how charge patterning can perturb their structural properties. As naturally occurring IDPs are composed of a significant fraction of uncharged amino acids, the rules based on charge content and patterning are only partially helpful in solving the problem. Here, we propose a new order parameter, sequence hydropathy decoration, which can provide a near-quantitative understanding of scaling and structural properties of IDPs devoid of charged residues. We combine this with a charge patterning parameter, sequence charge decoration, to obtain a general equation, parametrized from extensive coarse-grained simulation data, for predicting protein dimensions from the sequence. We finally test this equation against available experimental data and find a semiquantitative match in predicting the scaling behavior. We also provide guidance on how to extend this approach to experimental data, which should be feasible in the near future.

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.

19F NMR as a versatile tool to study membrane protein structure and dynamics

To elucidate the structures and dynamics of membrane proteins, highly advanced biophysical methods have been developed that often require significant resources, both for sample preparation and experimental analyses. For very complex systems, such as membrane transporters, ion channels or G-protein coupled receptors (GPCRs), the incorporation of a single reporter at a select site can significantly simplify the observables and the measurement/analysis requirements. Here we present examples using 19F nuclear magnetic resonance (NMR) spectroscopy as a powerful, yet relatively straightforward tool to study (membrane) protein structure, dynamics and ligand interactions. We summarize methods to incorporate 19F labels into proteins and discuss the type of information that can be readily obtained for membrane proteins already from relatively simple NMR spectra with a focus on GPCRs as the membrane protein family most extensively studied by this technique. In the future, these approaches may be of particular interest also for many proteins that undergo complex functional dynamics and/or contain unstructured regions and thus are not amenable to X-ray crystallography or cryo electron microscopy (cryoEM) studies.

Predicting Conformational Properties of Intrinsically Disordered Proteins from Sequence

Intrinsically disordered proteins (IDPs) can adopt a range of conformations from globules to swollen coils. This large range of conformational preferences for different IDPs raises the question of how conformational preferences are encoded by sequence. Global compositional features of a sequence such as the fraction of charged residues and the net charge per residue engender certain conformational biases. However, more specific sequence features such as the patterning of oppositely charged residues, expansion driving residues, or residues that can undergo posttranslational modifications can also influence the conformational ensembles of an IDP. Here, we outline how to calculate important global compositional features and patterning metrics that can be used to classify IDPs into different conformational classes and predict relative changes in conformation for sequences with the same amino acid composition. Although increased effort has been devoted to determining conformational properties of IDPs in recent years, quantitative predictions of conformation directly from sequence remain difficult and often inaccurate. Thus, if quantitative predictions of conformational properties are desired, then sequence-specific simulations must be performed.

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.

An intrinsically disordered proteins community for ELIXIR

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) are now recognised as major determinants in cellular regulation. This white paper presents a roadmap for future e-infrastructure developments in the field of IDP research within the ELIXIR framework. The goal of these developments is to drive the creation of high-quality tools and resources to support the identification, analysis and functional characterisation of IDPs. The roadmap is the result of a workshop titled “An intrinsically disordered protein user community proposal for ELIXIR” held at the University of Padua. The workshop, and further consultation with the members of the wider IDP community, identified the key priority areas for the roadmap including the development of standards for data annotation, storage and dissemination; integration of IDP data into the ELIXIR Core Data Resources; and the creation of benchmarking criteria for IDP-related software. Here, we discuss these areas of priority, how they can be implemented in cooperation with the ELIXIR platforms, and their connections to existing ELIXIR Communities and international consortia. The article provides a preliminary blueprint for an IDP Community in ELIXIR and is an appeal to identify and involve new stakeholders.