An allosteric conduit facilitates dynamic multisite substrate recognition by the SCFCdc4 ubiquitin ligase

The role of intrinsic protein disorder in regulation of cyclin-dependent kinases

While the structure/function paradigm for folded domains was established decades ago, our understanding of how intrinsically disordered regions (IDRs) contribute to biological function is still evolving. IDRs exist as conformational ensembles that can range from highly compact to highly extended depending on their sequence composition. IDR sequences are less conserved than those of folded domains, but often display short, conserved segments termed short linear motifs (SLiMs), that often mediate protein-protein interactions and are often regulated by posttranslational modifications, giving rise to complex functionality when multiple, differently regulated SLiMs are combined. This combinatorial functionality was associated with signaling and regulation soon after IDRs were first recognized as functional elements within proteins. Here, we discuss roles for disorder in proteins that regulate cyclin-dependent kinases, the master timekeepers of the eukaryotic cell cycle. We illustrate the importance of intrinsic flexibility in the transmission of regulatory signals by these entirely disordered proteins.

Biomolecular NMR spectroscopy in the era of artificial intelligence

Biomolecular nuclear magnetic resonance (NMR) spectroscopy and artificial intelligence (AI) have a burgeoning synergy. Deep learning-based structural predictors have forever changed structural biology, yet these tools currently face limitations in accurately characterizing protein dynamics, allostery, and conformational heterogeneity. We begin by highlighting the unique abilities of biomolecular NMR spectroscopy to complement AI-based structural predictions toward addressing these knowledge gaps. We then highlight the direct integration of deep learning approaches into biomolecular NMR methods. AI-based tools can dramatically improve the acquisition and analysis of NMR spectra, enhancing the accuracy and reliability of NMR measurements, thus streamlining experimental processes. Additionally, deep learning enables the development of novel types of NMR experiments that were previously unattainable, expanding the scope and potential of biomolecular NMR spectroscopy. Ultimately, a combination of AI and NMR promises to further revolutionize structural biology on several levels, advance our understanding of complex biomolecular systems, and accelerate drug discovery efforts.

Machine Learning Generation of Dynamic Protein Conformational Ensembles

Machine learning has achieved remarkable success across a broad range of scientific and engineering disciplines, particularly its use for predicting native protein structures from sequence information alone. However, biomolecules are inherently dynamic, and there is a pressing need for accurate predictions of dynamic structural ensembles across multiple functional levels. These problems range from the relatively well-defined task of predicting conformational dynamics around the native state of a protein, which traditional molecular dynamics (MD) simulations are particularly adept at handling, to generating large-scale conformational transitions connecting distinct functional states of structured proteins or numerous marginally stable states within the dynamic ensembles of intrinsically disordered proteins. Machine learning has been increasingly applied to learn low-dimensional representations of protein conformational spaces, which can then be used to drive additional MD sampling or directly generate novel conformations. These methods promise to greatly reduce the computational cost of generating dynamic protein ensembles, compared to traditional MD simulations. In this review, we examine recent progress in machine learning approaches towards generative modeling of dynamic protein ensembles and emphasize the crucial importance of integrating advances in machine learning, structural data, and physical principles to achieve these ambitious goals.

NMR insights into dynamic, multivalent interactions of intrinsically disordered regions: from discrete complexes to condensates

The spatial and temporal organization of interactions between proteins underlie the regulation of most cellular processes. The requirement for such interactions to be specific predisposes a view that protein-protein interactions are relatively static and are formed through the stable complementarity of the interacting partners. A growing body of reports indicate, however, that many interactions lead to fuzzy complexes with an ensemble of conformations in dynamic exchange accounting for the observed binding. Here, we discuss how NMR has facilitated the characterization of these discrete, dynamic complexes and how such characterization has aided the understanding of dynamic, condensed phases of phase-separating proteins with exchanging multivalent interactions.

Toward Accurate Coarse-Grained Simulations of Disordered Proteins and Their Dynamic Interactions

Intrinsically disordered proteins (IDPs) play crucial roles in cellular regulatory networks and are now recognized to often remain highly dynamic even in specific interactions and assemblies. Accurate description of these dynamic interactions is extremely challenging using atomistic simulations because of the prohibitive computational cost. Efficient coarse-grained approaches could offer an effective solution to overcome this bottleneck if they could provide an accurate description of key local and global properties of IDPs in both unbound and bound states. The recently developed hybrid-resolution (HyRes) protein model has been shown to be capable of providing a semiquantitative description of the secondary structure propensities of IDPs. Here, we show that greatly improved description of global structures and transient interactions can be achieved by introducing a solvent-accessible surface area-based implicit solvent term followed by reoptimization of effective interaction strengths. The new model, termed HyRes II, can semiquantitatively reproduce a wide range of local and global structural properties of a set of IDPs of various lengths and complexities. It can also distinguish the level of compaction between folded proteins and IDPs. In particular, applied to the disordered N-terminal transactivation domain (TAD) of tumor suppressor p53, HyRes II is able to recapitulate various nontrivial structural properties compared to experimental results, some of them to a level of accuracy that is almost comparable to results from atomistic explicit solvent simulations. Furthermore, we demonstrate that HyRes II can be used to simulate the dynamic interactions of TAD with the DNA-binding domain of p53, generating structural ensembles that are highly consistent with existing NMR data. We anticipate that HyRes II will provide an efficient and relatively reliable tool toward accurate coarse-grained simulations of dynamic protein interactions.

Counting Degrons: Lessons From Multivalent Substrates for Targeted Protein Degradation

E3s comprise a structurally diverse group of at least 800 members, most of which target multiple substrates through specific and regulated protein-protein interactions. These interactions typically rely on short linear motifs (SLiMs), called "degrons", in an intrinsically disordered region (IDR) of the substrate, with variable rules of engagement governing different E3-docking events. These rules of engagement are of importance to the field of targeted protein degradation (TPD), where substrate ubiquitination and destruction require tools to effectively harness ubiquitin ligases (E3s). Substrates are often found to contain multiple degrons, or multiple copies of a degron, contributing to the affinity and selectivity of the substrate for its E3. One important paradigm for E3-substrate docking is presented by the Anaphase-Promoting Complex/Cyclosome (APC/C), a multi-subunit E3 ligase that targets hundreds of proteins for destruction during mitotic exit. APC/C substrate targeting takes place in an ordered manner thought to depend on tightly regulated interactions of substrates, with docking sites provided by the substoichiometric APC/C substrate adaptors and coactivators, Cdc20 or Cdh1/FZR1. Both structural and functional studies of individual APC/C substrates indicate that productive ubiquitination usually requires more than one degron, and that degrons are of different types docking to distinct sites on the coactivators. However, the dynamic nature of APC/C substrate recruitment, and the influence of multiple degrons, remains poorly understood. Here we review the significance of multiple degrons in a number of E3-substrate interactions that have been studied in detail, illustrating distinct kinetic effects of multivalency and allovalency, before addressing the role of multiple degrons in APC/C substrates, key to understanding ordered substrate destruction by APC/C. Lastly, we consider how lessons learnt from these studies can be applied in the design of TPD tools.

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.

Advanced Sampling Methods for Multiscale Simulation of Disordered Proteins and Dynamic Interactions

Intrinsically disordered proteins (IDPs) are highly prevalent and play important roles in biology and human diseases. It is now also recognized that many IDPs remain dynamic even in specific complexes and functional assemblies. Computer simulations are essential for deriving a molecular description of the disordered protein ensembles and dynamic interactions for a mechanistic understanding of IDPs in biology, diseases, and therapeutics. Here, we provide an in-depth review of recent advances in the multi-scale simulation of disordered protein states, with a particular emphasis on the development and application of advanced sampling techniques for studying IDPs. These techniques are critical for adequate sampling of the manifold functionally relevant conformational spaces of IDPs. Together with dramatically improved protein force fields, these advanced simulation approaches have achieved substantial success and demonstrated significant promise towards the quantitative and predictive modeling of IDPs and their dynamic interactions. We will also discuss important challenges remaining in the atomistic simulation of larger systems and how various coarse-grained approaches may help to bridge the remaining gaps in the accessible time- and length-scales of IDP simulations.

Small-Angle X-ray Scattering Signatures of Conformational Heterogeneity and Homogeneity of Disordered Protein Ensembles

An accurate account of disordered protein conformations is of central importance to deciphering the physicochemical basis of biological functions of intrinsically disordered proteins and the folding-unfolding energetics of globular proteins. Physically, disordered ensembles of nonhomopolymeric polypeptides are expected to be heterogeneous, i.e., they should differ from those homogeneous ensembles of homopolymers that harbor an essentially unique relationship between average values of end-to-end distance R_EE and radius of gyration R_g. It was posited recently, however, that small-angle X-ray scattering (SAXS) data on conformational dimensions of disordered proteins can be rationalized almost exclusively by homopolymer ensembles. Assessing this perspective, chain-model simulations are used to evaluate the discriminatory power of SAXS-determined molecular form factors (MFFs) with regard to homogeneous versus heterogeneous ensembles. The general approach adopted here is not bound by any assumption about ensemble encodability, in that the postulated heterogeneous ensembles we evaluated are not restricted to those entailed by simple interaction schemes. Our analysis of MFFs for certain heterogeneous ensembles with more narrowly distributed R_EE and R_g indicates that while they deviate from MFFs of homogeneous ensembles, the differences can be rather small. Remarkably, some heterogeneous ensembles with asphericity and R_EE drastically different from those of homogeneous ensembles can nonetheless exhibit practically identical MFFs, demonstrating that SAXS MFFs do not afford unique characterizations of basic properties of conformational ensembles in general. In other words, the ensemble to MFF mapping is practically many-to-one and likely nonsmooth. Heteropolymeric variations of the R_EE-R_g relationship were further showcased using an analytical perturbation theory developed here for flexible heteropolymers. Ramifications of our findings for interpretation of experimental data are discussed.

An E3 ligase guide to the galaxy of small-molecule-induced protein degradation

Induced protein degradation accomplishes elimination, rather than inhibition, of pathological proteins. Key to the success of this novel therapeutic modality is the modification of proteins with ubiquitin chains, which is brought about by molecular glues or bivalent compounds that induce proximity between the target protein and an E3 ligase. The human genome encodes ∼600 E3 ligases that differ widely in their structures, catalytic mechanisms, modes of regulation, and physiological roles. While many of these enzymes hold great promise for drug discovery, few have been successfully engaged by small-molecule degraders. Here, we review E3 ligases that are being used for induced protein degradation. Based on these prior successes and our growing understanding of the biology and biochemistry of E3 ligases, we propose new ubiquitylation enzymes that can be harnessed for drug discovery to firmly establish induced protein degradation as a specific and efficient therapeutic approach.

Conformational Ensembles of an Intrinsically Disordered Protein Consistent with NMR, SAXS, and Single-Molecule FRET

Intrinsically disordered proteins (IDPs) have fluctuating heterogeneous conformations, which makes their structural characterization challenging. Although challenging, characterization of the conformational ensembles of IDPs is of great interest, since their conformational ensembles are the link between their sequences and functions. An accurate description of IDP conformational ensembles depends crucially on the amount and quality of the experimental data, how it is integrated, and if it supports a consistent structural picture. We used integrative modeling and validation to apply conformational restraints and assess agreement with the most common structural techniques for IDPs: Nuclear Magnetic Resonance (NMR) spectroscopy, Small-angle X-ray Scattering (SAXS), and single-molecule Förster Resonance Energy Transfer (smFRET). Agreement with such a diverse set of experimental data suggests that details of the generated ensembles can now be examined with a high degree of confidence. Using the disordered N-terminal region of the Sic1 protein as a test case, we examined relationships between average global polymeric descriptions and higher-moments of their distributions. To resolve apparent discrepancies between smFRET and SAXS inferences, we integrated SAXS data with NMR data and reserved the smFRET data for independent validation. Consistency with smFRET, which was not guaranteed a priori, indicates that, globally, the perturbative effects of NMR or smFRET labels on the Sic1 ensemble are minimal. Analysis of the ensembles revealed distinguishing features of Sic1, such as overall compactness and large end-to-end distance fluctuations, which are consistent with biophysical models of Sic1's ultrasensitive binding to its partner Cdc4. Our results underscore the importance of integrative modeling and validation in generating and drawing conclusions from IDP conformational ensembles.

Analytical Theory for Sequence-Specific Binary Fuzzy Complexes of Charged Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) are important for biological functions. In contrast to folded proteins, molecular recognition among certain IDPs is "fuzzy" in that their binding and/or phase separation are stochastically governed by the interacting IDPs' amino acid sequences, while their assembled conformations remain largely disordered. To help elucidate a basic aspect of this fascinating yet poorly understood phenomenon, the binding of a homo or heterodimeric pair of polyampholytic IDPs is modeled statistical mechanically using cluster expansion. We find that the binding affinities of binary fuzzy complexes in the model correlate strongly with a newly derived simple "joint sequence charge decoration" parameter readily calculable from the pair of IDPs' sequence charge patterns. Predictions by our analytical theory are in essential agreement with coarse-grained explicit-chain simulations. This computationally efficient theoretical framework is expected to be broadly applicable to rationalizing and predicting sequence-specific IDP-IDP polyelectrostatic interactions.

Modes of allosteric regulation of the ubiquitination machinery

Ubiquitination is a post-translational modification crucial for cellular signaling. A diverse range of enzymes constitute the machinery that mediates attachment of ubiquitin onto target proteins. This diversity allows the targeting of various proteins in a highly regulated fashion. Many of the enzymes have multiple domains or subunits that bind allosteric effectors and exhibit large conformational rearrangements to facilitate regulation. Here we consider recent examples of ubiquitin itself as an allosteric effector of RING and RBR E3 ligases, as well as advances in the understanding of allosteric regulatory elements within HECT E3 ligases.

Surface charge of Merkel cell polyomavirus small T antigen determines cell transformation through allosteric FBW7 WD40 domain targeting

Merkel cell polyomavirus (MCV) small T (sT) is the main oncoprotein in Merkel cell carcinoma (MCC) development. A unique domain of sT, LT stabilization domain (LSD), has been reported to bind and inactivate multiple SCF (Skp1-Cullin-F-box) E3 ligases. These interactions impede the turnover of MCV large T (LT) antigen and cellular oncoproteins such as c-Myc and cyclin E, thereby promoting viral replication and cell transformation. However, it is currently unclear how this LSD region contributes to multiple transforming activities of sT. Structural docking simulation of sT and F-box and WD repeat domain-containing 7 (FBW7) revealed a novel allosteric interaction between sT and FBW7 WD40 domain. This model is supported by experimental evidence confirming that charge engineering in the LSD alters sT-WD40 binding. Specifically, loss of net positive charge in the LSD prevents sT-FBW7 binding by abrogating the electrostatic interaction, thus impeding inhibition of FBW7 by sT. Furthermore, positively charged mutations in the LSD significantly restored the sT function and its ability to transform rodent fibroblast cells. We infer that the surface charge of sT is a major determinant for targeting E3 ligases, which leads to sT-induced cell transformation, an observation that could be used to develop targeted therapeutics for MCC.

Flexibility of intrinsically disordered degrons in AUX/IAA proteins reinforces auxin co-receptor assemblies

Cullin RING-type E3 ubiquitin ligases SCF^TIR1/AFB1-5 and their AUX/IAA targets perceive the phytohormone auxin. The F-box protein TIR1 binds a surface-exposed degron in AUX/IAAs promoting their ubiquitylation and rapid auxin-regulated proteasomal degradation. Here, by adopting biochemical, structural proteomics and in vivo approaches we unveil how flexibility in AUX/IAAs and regions in TIR1 affect their conformational ensemble allowing surface accessibility of degrons. We resolve TIR1·auxin·IAA7 and TIR1·auxin·IAA12 complex topology, and show that flexible intrinsically disordered regions (IDRs) in the degron’s vicinity, cooperatively position AUX/IAAs on TIR1. We identify essential residues at the TIR1 N- and C-termini, which provide non-native interaction interfaces with IDRs and the folded PB1 domain of AUX/IAAs. We thereby establish a role for IDRs in modulating auxin receptor assemblies. By securing AUX/IAAs on two opposite surfaces of TIR1, IDR diversity supports locally tailored positioning for targeted ubiquitylation, and might provide conformational flexibility for a multiplicity of functional states.

Auxin-mediated recruitment of AUX/IAAs by the F-box protein TIR1 prompts rapid AUX/IAA ubiquitylation and degradation. By resolving auxin receptor topology, the authors show that intrinsically disordered regions near the degrons of two Aux/IAA proteins reinforce complex assembly and position Aux/IAAs for ubiquitylation.

'Nonlinear' Biochemistry of Nucleosome Detergents

The transcriptional activation domains (TADs) are critical for life, yet intrinsically disordered polypeptides with no specific consensus sequence, interacting with multiple targets via low-specificity fuzzy contacts. The recent integration of machine learning approaches in biochemistry allows analysis of large experimental datasets of functional TADs as a whole and clear observation of TAD features. The emerging picture describes TADs as sequences without consensus but with a variety of detergent-like mini-motifs enriched in negatively charged and aromatic amino acids. Comparison of the canonical direct coactivator recruitment model and a new model describing TADs as nucleosome detergents that trigger chromatin remodeling during gene activation helps solve a fundamental enigma of molecular biology spanning 30 years.

Multisite dependency of an E3 ligase controls monoubiquitylation-dependent cell fate decisions

Metazoan development depends on tightly regulated gene expression programs that instruct progenitor cells to adopt specialized fates. Recent work found that posttranslational modifications, such as monoubiquitylation, can determine cell fate also independently of effects on transcription, yet how monoubiquitylation is implemented during development is poorly understood. Here, we have identified a regulatory circuit that controls monoubiquitylation-dependent neural crest specification by the E3 ligase CUL3 and its substrate adaptor KBTBD8. We found that CUL3^KBTBD8 monoubiquitylates its essential targets only after these have been phosphorylated in multiple motifs by CK2, a kinase whose levels gradually increase during embryogenesis. Its dependency on multisite phosphorylation allows CUL3^KBTBD8 to convert the slow rise in embryonic CK2 into decisive recognition of ubiquitylation substrates, which in turn is essential for neural crest specification. We conclude that multisite dependency of an E3 ligase provides a powerful mechanism for switch-like cell fate transitions controlled by monoubiquitylation.

Expanding the Paradigm: Intrinsically Disordered Proteins and Allosteric Regulation

Allosteric regulatory processes are implicated at all levels of biological function. Recent advances in our understanding of the diverse and functionally significant class of intrinsically disordered proteins have identified a multitude of ways in which disordered proteins function within the confines of the allosteric paradigm. Allostery within or mediated by intrinsically disordered proteins ensures robust and efficient signal integration through mechanisms that would be extremely unfavorable or even impossible for globular protein interaction partners. Here, we highlight recent examples that indicate the breadth of biological outcomes that can be achieved through allosteric regulation by intrinsically disordered proteins. Ongoing and future work in this rapidly evolving area of research will expand our appreciation of the central role of intrinsically disordered proteins in ensuring the fidelity and efficiency of cellular regulation.

Multivalent Interactions with Fbw7 and Pin1 Facilitate Recognition of c-Jun by the SCFFbw7 Ubiquitin Ligase

Many regulatory proteins, including the transcription factor c-Jun, are highly enriched in disordered protein regions that govern growth, division, survival, differentiation, and response to signals. The stability of c-Jun is controlled by poorly understood regulatory interactions of its disordered region with both the E3 ubiquitin ligase SCF^Fbw7 and prolyl cis-trans isomerase Pin1. We use nuclear magnetic resonance and fluorescence studies of c-Jun to demonstrate that multisite c-Jun phosphorylation is required for high-affinity interaction with Fbw7. We show that the Pin1 WW and PPIase domains interact in a dynamic complex with multiply phosphorylated c-Jun. Importantly, Pin1 isomerizes a pSer-Pro peptide bond at the c-Jun N terminus that affects binding to Fbw7 and thus modulates the ubiquitin-mediated degradation of c-Jun. Our findings support the general principle that multiple weak binding motifs within disordered regions can synergize to yield high-affinity interactions and provide rapidly evolvable means to build and fine-tune regulatory events.

Conformational Heterogeneity and FRET Data Interpretation for Dimensions of Unfolded Proteins

A mathematico-physically valid formulation is required to infer properties of disordered protein conformations from single-molecule Förster resonance energy transfer (smFRET). Conformational dimensions inferred by conventional approaches that presume a homogeneous conformational ensemble can be unphysical. When all possible-heterogeneous as well as homogeneous-conformational distributions are taken into account without prejudgment, a single value of average transfer efficiency 〈E〉 between dyes at two chain ends is generally consistent with highly diverse, multiple values of the average radius of gyration 〈R_g〉. Here we utilize unbiased conformational statistics from a coarse-grained explicit-chain model to establish a general logical framework to quantify this fundamental ambiguity in smFRET inference. As an application, we address the long-standing controversy regarding the denaturant dependence of 〈R_g〉 of unfolded proteins, focusing on Protein L as an example. Conventional smFRET inference concluded that 〈R_g〉 of unfolded Protein L is highly sensitive to [GuHCl], but data from SAXS suggested a near-constant 〈R_g〉 irrespective of [GuHCl]. Strikingly, our analysis indicates that although the reported 〈E〉 values for Protein L at [GuHCl] = 1 and 7 M are very different at 0.75 and 0.45, respectively, the Bayesian R_g² distributions consistent with these two 〈E〉 values overlap by as much as 75%. Our findings suggest, in general, that the smFRET-SAXS discrepancy regarding unfolded protein dimensions likely arise from highly heterogeneous conformational ensembles at low or zero denaturant, and that additional experimental probes are needed to ascertain the nature of this heterogeneity.

WD40 repeat domain proteins: a novel target class?

Antagonism of protein-protein interactions (PPIs) with small molecules is becoming more feasible as a therapeutic approach. Successful PPI inhibitors tend to target proteins containing deep peptide-binding grooves or pockets rather than the more common large, flat protein interaction surfaces. Here, we review one of the most abundant PPI domains in the human proteome, the WD40 repeat (WDR) domain, which has a central peptide-binding pocket and is a member of the β-propeller domain-containing protein family. Recently, two WDR domain-containing proteins, WDR5 and EED, as well as other β-propeller domains have been successfully targeted by potent, specific, cell-active, drug-like chemical probes. Could WDR domains be a novel target class for drug discovery? Although the research is at an early stage and therefore not clinically validated, cautious optimism is justified, as WDR domain-containing proteins are involved in multiple disease-associated pathways. The druggability and structural diversity of WDR domain binding pockets suggest that understanding how to target this prevalent domain class will open up areas of disease biology that have so far resisted drug discovery efforts.

Genetic code asymmetry supports diversity through experimentation with posttranslational modifications

Protein N-glycosylation has been identified in all three domains of life presumably conserved for its early role in glycoprotein folding. However, the N-glycans added to proteins in the secretory pathway of multicellular organisms are remodeling in the Golgi, increasing structural diversity exponentially and adding new layers of functionality in immunity, metabolism and other systems. The branching and elongation of N-glycan chains found on cell surface receptors generates a gradation of affinities for carbohydrate-binding proteins, the galectin, selectin and siglec families. These interactions adapt cellular responsiveness to environmental conditions, but their complexity presents a daunting challenge to drug design. To gain further insight, I review how N-glycans biosynthesis and biophysical properties provide a selective advantage in the form of tunable and ultrasensitive stimulus-response relationships. In addition, the N-glycosylation motif favors step-wise mutational experimentation with sites. Glycoproteins display accelerated evolution during vertebrate radiation, and the encoding asymmetry of NXS/T(X≠P) has left behind phylogenetic evidence suggesting that the genetic code may have been selected to optimize diversity in part through emerging posttranslational modifications.

Complementary uses of small angle X-ray scattering and X-ray crystallography

Most proteins function within networks and, therefore, protein interactions are central to protein function. Although stable macromolecular machines have been extensively studied, dynamic protein interactions remain poorly understood. Small-angle X-ray scattering probes the size, shape and dynamics of proteins in solution at low resolution and can be used to study samples in a large range of molecular weights. Therefore, it has emerged as a powerful technique to study the structure and dynamics of biomolecular systems and bridge fragmented information obtained using high-resolution techniques. Here we review how small-angle X-ray scattering can be combined with other structural biology techniques to study protein dynamics. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

Phase Separation and Single-Chain Compactness of Charged Disordered Proteins Are Strongly Correlated

Liquid-liquid phase separation of intrinsically disordered proteins (IDPs) is a major undergirding factor in the regulated formation of membraneless organelles in the cell. The phase behavior of an IDP is sensitive to its amino acid sequence. Here we apply a recent random-phase-approximation polymer theory to investigate how the tendency for multiple chains of a protein to phase-separate, as characterized by the critical temperature T^∗_cr, is related to the protein's single-chain average radius of gyration 〈R_g〉. For a set of sequences containing different permutations of an equal number of positively and negatively charged residues, we found a striking correlation T^∗_cr ∼ 〈R_g〉^-γ with γ as large as ∼6.0, indicating that electrostatic effects have similarly significant impact on promoting single-chain conformational compactness and phase separation. Moreover, T^∗_cr ∝ -SCD, where SCD is a recently proposed "sequence charge decoration" parameter determined solely by sequence information. Ramifications of our findings for deciphering the sequence dependence of IDP phase separation are discussed.