Classification of intrinsically disordered regions and proteins

Proteome-wide assessment of human interactome as a source of capturing domain-motif and domain-domain interactions

Protein-protein interactions (PPIs) play a crucial role in various biological processes by establishing domain-motif (DMI) and domain-domain interactions (DDIs). While the existence of real DMIs/DDIs is generally assumed, it is rarely tested; therefore, this study extensively compared high-throughput methods and public PPI repositories as sources for DMI and DDI prediction based on the assumption that the human interactome provides sufficient data for the reliable identification of DMIs and DDIs. Different datasets from leading high-throughput methods (Yeast two-hybrid [Y2H], Affinity Purification coupled Mass Spectrometry [AP-MS], and Co-fractionation-coupled Mass Spectrometry) were assessed for their ability to capture DMIs and DDIs using known DMI/DDI information. High-throughput methods were not notably worse than PPI databases and, in some cases, appeared better. In conclusion, all PPI datasets demonstrated significant enrichment in DMIs and DDIs (p-value <0.001), establishing Y2H and AP-MS as reliable methods for predicting these interactions. This study provides valuable insights for biologists in selecting appropriate methods for predicting DMIs, ultimately aiding in SLiM discovery.

Disordered proteins interact with the chemical environment to tune their protective function during drying

The conformational ensemble and function of intrinsically disordered proteins (IDPs) are sensitive to their solution environment. The inherent malleability of disordered proteins combined with the exposure of their residues accounts for this sensitivity. One context in which IDPs play important roles that is concomitant with massive changes to the intracellular environment is during desiccation (extreme drying). The ability of organisms to survive desiccation has long been linked to the accumulation of high levels of cosolutes such as trehalose or sucrose as well as the enrichment of IDPs, such as late embryogenesis abundant (LEA) proteins or cytoplasmic abundant heat soluble (CAHS) proteins. Despite knowing that IDPs play important roles and are co-enriched alongside endogenous, species-specific cosolutes during desiccation, little is known mechanistically about how IDP-cosolute interactions influence desiccation tolerance. Here, we test the notion that the protective function of desiccation-related IDPs is enhanced through conformational changes induced by endogenous cosolutes. We find that desiccation-related IDPs derived from four different organisms spanning two LEA protein families and the CAHS protein family, synergize best with endogenous cosolutes during drying to promote desiccation protection. Yet the structural parameters of protective IDPs do not correlate with synergy for either CAHS or LEA proteins. We further demonstrate that for CAHS, but not LEA proteins, synergy is related to self-assembly and the formation of a gel. Our results demonstrate that functional synergy between IDPs and endogenous cosolutes is a convergent desiccation protection strategy seen among different IDP families and organisms, yet, the mechanisms underlying this synergy differ between IDP families.

The molecular basis for cellular function of intrinsically disordered protein regions

Intrinsically disordered protein regions exist in a collection of dynamic interconverting conformations that lack a stable 3D structure. These regions are structurally heterogeneous, ubiquitous and found across all kingdoms of life. Despite the absence of a defined 3D structure, disordered regions are essential for cellular processes ranging from transcriptional control and cell signalling to subcellular organization. Through their conformational malleability and adaptability, disordered regions extend the repertoire of macromolecular interactions and are readily tunable by their structural and chemical context, making them ideal responders to regulatory cues. Recent work has led to major advances in understanding the link between protein sequence and conformational behaviour in disordered regions, yet the link between sequence and molecular function is less well defined. Here we consider the biochemical and biophysical foundations that underlie how and why disordered regions can engage in productive cellular functions, provide examples of emerging concepts and discuss how protein disorder contributes to intracellular information processing and regulation of cellular function.

Amino acid pattern reveals multi-functionality of ORF3 protein from HEV

The smallest open reading frame (ORF) encoded protein ORF3 of hepatitis E virus (HEV), recently, has been demonstrated to perform multiple functions besides accessory roles. ORF3 could act as a target for vaccine against HEV infections. The IDR (intrinsically disordered region); IDP (ID protein)/IDPR (ID protein region), plays critical role in various regulatory functions of viruses. The dark proteome of HEV-ORF3 protein including its structure and function was systematically examined by computer predictors to explicate its role in viral pathogenesis and drug resistance beyond its functions as accessory viral protein. Amino acid distribution showed ORF3 enrichment with disorder-promoting residues (Ala, Pro, Ser, Gly) while deficiency in order-promoting residues (Asn, Ile, Phe, Tyr and Trp). Initial investigation revealed ORF3 as IDP (entirely disordered protein) or IDPR (proteins consisting of IDRs with structured globular domains). Structural examination revealed preponderance of disordered regions interpreting ORF3 as moderately/highly disordered protein. Further disorder predictors categorized ORF3 as highly disordered protein/IDP. Identified sites and associated-crucial molecular functions revealed ORF3 involvement in diverse biological processes, substantiating them as targets of regulation. As ORF3 functions are yet to completely explored, thus, data on its disorderness could help in elucidating its disorder related functions.

A Unified Description of Salt Effects on the Liquid-Liquid Phase Separation of Proteins

Protein aggregation via liquid-liquid phase separation (LLPS) is ubiquitous in nature and is intimately connected to many human diseases. Although it is widely known that the addition of salt has crucial impacts on the LLPS of proteins, full understanding of the salt effects remains an outstanding challenge. Here, we develop a molecular theory that systematically incorporates the self-consistent field theory for charged macromolecules into the solution thermodynamics. The electrostatic interaction, hydrophobicity, ion solvation, and translational entropy are included in a unified framework. Our theory fully captures the long-standing puzzles of the nonmonotonic salt concentration dependence and the specific ion effect. We find that proteins show salting-out at low salt concentrations due to ionic screening. The solubility follows the inverse Hofmeister series. In the high salt concentration regime, protein continues salting-out for small ions but turns to salting-in for larger ions, accompanied by the reversal of the Hofmeister series. We reveal that the solubility at high salt concentrations is determined by the competition between the solvation energy and translational entropy of the ion. Furthermore, we derive an analytical criterion for determining the boundary between the salting-in and salting-out regimes, which is in good agreement with experimental results for various proteins and salt ions.

Macromolecular Crowding, Phase Separation, and Homeostasis in the Orchestration of Bacterial Cellular Functions

Macromolecular crowding affects the activity of proteins and functional macromolecular complexes in all cells, including bacteria. Crowding, together with physicochemical parameters such as pH, ionic strength, and the energy status, influences the structure of the cytoplasm and thereby indirectly macromolecular function. Notably, crowding also promotes the formation of biomolecular condensates by phase separation, initially identified in eukaryotic cells but more recently discovered to play key functions in bacteria. Bacterial cells require a variety of mechanisms to maintain physicochemical homeostasis, in particular in environments with fluctuating conditions, and the formation of biomolecular condensates is emerging as one such mechanism. In this work, we connect physicochemical homeostasis and macromolecular crowding with the formation and function of biomolecular condensates in the bacterial cell and compare the supramolecular structures found in bacteria with those of eukaryotic cells. We focus on the effects of crowding and phase separation on the control of bacterial chromosome replication, segregation, and cell division, and we discuss the contribution of biomolecular condensates to bacterial cell fitness and adaptation to environmental stress.

The Conformational Contribution to Molecular Complexity and Its Implications for Information Processing in Living Beings and Chemical Artificial Intelligence

This work highlights the relevant contribution of conformational stereoisomers to the complexity and functions of any molecular compound. Conformers have the same molecular and structural formulas but different orientations of the atoms in the three-dimensional space. Moving from one conformer to another is possible without breaking covalent bonds. The interconversion is usually feasible through the thermal energy available in ordinary conditions. The behavior of most biopolymers, such as enzymes, antibodies, RNA, and DNA, is understandable if we consider that each exists as an ensemble of conformers. Each conformational collection confers multi-functionality and adaptability to the single biopolymers. The conformational distribution of any biopolymer has the features of a fuzzy set. Hence, every compound that exists as an ensemble of conformers allows the molecular implementation of a fuzzy set. Since proteins, DNA, and RNA work as fuzzy sets, it is fair to say that life's logic is fuzzy. The power of processing fuzzy logic makes living beings capable of swift decisions in environments dominated by uncertainty and vagueness. These performances can be implemented in chemical robots, which are confined molecular assemblies mimicking unicellular organisms: they are supposed to help humans "colonise" the molecular world to defeat diseases in living beings and fight pollution in the environment.

Charge-Patterned Disordered Peptides Tune Intracellular Phase Separation in Bacteria

Subcellular phase-separated compartments, known as biomolecular condensates, play an important role in the spatiotemporal organization of cells. To understand the sequence-determinants of phase separation in bacteria, we engineered protein-based condensates in Escherichia coli using electrostatic interactions as the main driving force. Minimal cationic disordered peptides were used to supercharge negative, neutral, and positive globular model proteins, enabling their phase separation with anionic biomacromolecules in the cell. The phase behavior was governed by the interaction strength between the cationic proteins and anionic biopolymers, in addition to the protein concentration. The interaction strength primarily depended on the overall net charge of the protein, but the distribution of charge between the globular and disordered domains also had an impact. Notably, the protein charge distribution between domains could tune mesoscale attributes such as the size, number, and subcellular localization of condensates within E. coli cells. The length and charge density of the disordered peptides had significant effects on protein expression levels, ultimately influencing the formation of condensates. Taken together, charge-patterned disordered peptides provide a platform for understanding the molecular grammar underlying phase separation in bacteria.

From isolated polyelectrolytes to star-like assemblies: the role of sequence heterogeneity on the statistical structure of the intrinsically disordered neurofilament-low tail domain

Intrinsically disordered proteins (IDPs) are a subset of proteins that lack stable secondary structure. Given their polymeric nature, previous mean-field approximations have been used to describe the statistical structure of IDPs. However, the amino-acid sequence heterogeneity and complex intermolecular interaction network have significantly impeded the ability to get proper approximations. One such case is the intrinsically disordered tail domain of neurofilament low (NFLt), which comprises a 50 residue-long uncharged domain followed by a 96 residue-long negatively charged domain. Here, we measure two NFLt variants to identify the impact of the NFLt two main subdomains on its complex interactions and statistical structure. Using synchrotron small-angle x-ray scattering, we find that the uncharged domain of the NFLt induces attractive interactions that cause it to self-assemble into star-like polymer brushes. On the other hand, when the uncharged domain is truncated, the remaining charged N-terminal domains remain isolated in solution with typical polyelectrolyte characteristics. We further discuss how competing long- and short-ranged interactions within the polymer brushes dominate their ensemble structure and, in turn, their implications on previously observed phenomena in NFL native and diseased states.

Exploring the Role of Globular Domain Locations on an Intrinsically Disordered Region of p53: A Molecular Dynamics Investigation

The pre-tetramerization loop (PTL) of the human tumor suppressor protein p53 is an intrinsically disordered region (IDR) necessary for the tetramerization process, and its flexibility contributes to the essential conformational changes needed. Although the IDR can be accurately simulated in the traditional manner of molecular dynamics (MD) with the end-to-end distance (EEdist) unhindered, we sought to explore the effects of restraining the EEdist to the values predicted by electron microscopy (EM) and other distances. Simulating the PTL trajectory with a restrained EEdist , we found an increased agreement of nuclear magnetic resonance (NMR) chemical shifts with experiments. Additionally, we observed a plethora of secondary structures and contacts that only appear when the trajectory is restrained. Our findings expand the understanding of the tetramerization of p53 and provide insight into how mutations could make the protein impotent. In particular, our findings demonstrate the importance of restraining the EEdist in studying IDRs and how their conformations change under different conditions. Our results provide a better understanding of the PTL and the conformational dynamics of IDRs in general, which are useful for further studies regarding mutations and their effects on the activity of p53.

Mesophiles vs. Thermophiles: Untangling the Hot Mess of Intrinsically Disordered Proteins and Growth Temperature of Bacteria

The dynamic structures and varying functions of intrinsically disordered proteins (IDPs) have made them fascinating subjects in molecular biology. Investigating IDP abundance in different bacterial species is crucial for understanding adaptive strategies in diverse environments. Notably, thermophilic bacteria have lower IDP abundance than mesophiles, and a negative correlation with optimal growth temperature (OGT) has been observed. However, the factors driving these trends are yet to be fully understood. We examined the types of IDPs present in both mesophiles and thermophiles alongside those unique to just mesophiles. The shared group of IDPs exhibits similar disorder levels in the two groups of species, suggesting that certain IDPs unique to mesophiles may contribute to the observed decrease in IDP abundance as OGT increases. Subsequently, we used quasi-independent contrasts to explore the relationship between OGT and IDP abundance evolution. Interestingly, we found no significant relationship between OGT and IDP abundance contrasts, suggesting that the evolution of lower IDP abundance in thermophiles may not be solely linked to OGT. This study provides a foundation for future research into the intricate relationship between IDP evolution and environmental adaptation. Our findings support further research on the adaptive significance of intrinsic disorder in bacterial species.

Magnetic tweezers characterization of the entropic elasticity of intrinsically disordered proteins and peptoids

Understanding the conformational behavior of biopolymers is essential to unlocking knowledge of their biophysical mechanisms and functional roles. Single-molecule force spectroscopy can provide a unique perspective on this by exploiting entropic elasticity to uncover key biopolymer structural parameters. A particularly powerful approach involves the use of magnetic tweezers, which can easily generate lower stretching forces (0.1-20 pN). For forces at the low end of this range, the elastic response of biopolymers is sensitive to excluded volume effects, and they can be described by Pincus blob elasticity model that allow robust extraction of the Flory polymer scaling exponent. Here, we detail protocols for the use of magnetic tweezers for force-extension measurements of intrinsically disordered proteins and peptoids. We also discuss procedures for fitting low-force elastic curves to the predictions of polymer physics models to extract key conformational parameters.

Folding-upon-binding pathways of an intrinsically disordered protein from a deep Markov state model

A central challenge in the study of intrinsically disordered proteins is the characterization of the mechanisms by which they bind their physiological interaction partners. Here, we utilize a deep learning-based Markov state modeling approach to characterize the folding-upon-binding pathways observed in a long timescale molecular dynamics simulation of a disordered region of the measles virus nucleoprotein NTAIL reversibly binding the X domain of the measles virus phosphoprotein complex. We find that folding-upon-binding predominantly occurs via two distinct encounter complexes that are differentiated by the binding orientation, helical content, and conformational heterogeneity of NTAIL. We observe that folding-upon-binding predominantly proceeds through a multi-step induced fit mechanism with several intermediates and do not find evidence for the existence of canonical conformational selection pathways. We observe four kinetically separated native-like bound states that interconvert on timescales of eighty to five hundred nanoseconds. These bound states share a core set of native intermolecular contacts and stable NTAIL helices and are differentiated by a sequential formation of native and non-native contacts and additional helical turns. Our analyses provide an atomic resolution structural description of intermediate states in a folding-upon-binding pathway and elucidate the nature of the kinetic barriers between metastable states in a dynamic and heterogenous, or "fuzzy", protein complex.

Determinants that enable disordered protein assembly into discrete condensed phases

Cells harbour numerous mesoscale membraneless compartments that house specific biochemical processes and perform distinct cellular functions. These protein- and RNA-rich bodies are thought to form through multivalent interactions among proteins and nucleic acids, resulting in demixing via liquid-liquid phase separation. Proteins harbouring intrinsically disordered regions (IDRs) predominate in membraneless organelles. However, it is not known whether IDR sequence alone can dictate the formation of distinct condensed phases. We identified a pair of IDRs capable of forming spatially distinct condensates when expressed in cells. When reconstituted in vitro, these model proteins do not co-partition, suggesting condensation specificity is encoded directly in the polypeptide sequences. Through computational modelling and mutagenesis, we identified the amino acids and chain properties governing homotypic and heterotypic interactions that direct selective condensation. These results form the basis of physicochemical principles that may direct subcellular organization of IDRs into specific condensates and reveal an IDR code that can guide construction of orthogonal membraneless compartments.

Tryptanthrin Analogs Substoichiometrically Inhibit Seeded and Unseeded Tau4RD Aggregation

Microtubule-associated protein tau is an intrinsically disordered protein (IDP) that forms characteristic fibrillar aggregates in several diseases, the most well-known of which is Alzheimer's disease (AD). Despite keen interest in disrupting or inhibiting tau aggregation to treat AD and related dementias, there are currently no FDA-approved tau-targeting drugs. This is due, in part, to the fact that tau and other IDPs do not exhibit a single well-defined conformation but instead populate a fluctuating conformational ensemble that precludes finding a stable "druggable" pocket. Despite this challenge, we previously reported the discovery of two novel families of tau ligands, including a class of aggregation inhibitors, identified through a protocol that combines molecular dynamics, structural analysis, and machine learning. Here we extend our exploration of tau druggability with the identification of tryptanthrin and its analogs as potent, substoichiometric aggregation inhibitors, with the best compounds showing potencies in the low nanomolar range even at a ~100-fold molar excess of tau4RD. Moreover, conservative changes in small molecule structure can have large impacts on inhibitory potency, demonstrating that similar structure-activity relationship (SAR) principles as used for traditional drug development also apply to tau and potentially to other IDPs.

Invariant BECN1 CXXC motifs bind Zn2+ and regulate structure and function of the BECN1 intrinsically disordered region

ABBREVIATIONS

AFM: aromatic finger mutant; BH3D: BCL2 homology 3 domain; CCD: coiled-coil domain; CD: circular dichroism spectroscopy; [CysDM1]: C18S and C21S double mutant; [CysDM2]: C137S, and C140S double mutant; [CysTM], C18S, C21S, C137S, and C140S tetrad mutant; Dmax: maximum particle diameter; dRI, differential refractive index; EFA: evolving factor analysis; FHD: flexible helical domain; FL: full length; GFP: green fluorescent protein; HDX-MS: hydrogen/deuterium exchange mass spectrometry; ICP-MS: inductively coupled plasma mass spectrometry; IDR: intrinsically disordered region; ITC, isothermal titration calorimetry; MALS, multi angle light scattering; MBP: maltose-binding protein; MoRFs: molecular recognition features; P(r): pairwise-distance distribution; PtdIns3K: class III phosphatidylinositol 3-kinase; Rg: radius of gyration; SASBDB: small angle scattering biological data bank; SEC: size-exclusion chromatography; SEC-SAXS: size-exclusion chromatography in tandem with small angle X-ray scattering; TEV: tobacco-etch virus; TFE: 2,2,2-trifluoroethanol; TPEN: N,N,N,N-tetrakis(2-pyridinylmethyl)-1,2-ethanediamine; Vc: volume of correlation; WT: wild-type.

Commonly asked questions about transcriptional activation domains

Eukaryotic transcription factors activate gene expression with their DNA-binding domains and activation domains. DNA-binding domains bind the genome by recognizing structurally related DNA sequences; they are structured, conserved, and predictable from protein sequences. Activation domains recruit chromatin modifiers, coactivator complexes, or basal transcriptional machinery via structurally diverse protein-protein interactions. Activation domains and DNA-binding domains have been called independent, modular units, but there are many departures from modularity, including interactions between these regions and overlap in function. Compared to DNA-binding domains, activation domains are poorly understood because they are poorly conserved, intrinsically disordered, and difficult to predict from protein sequences. This review, organized around commonly asked questions, describes recent progress that the field has made in understanding the sequence features that control activation domains and predicting them from sequence.

Relation between flexibility and intrinsically disorder regions in thermosensitive TRP channels reveal allosteric effects

How a protein propagates the conformational changes throughout its structure remains largely unknown. In thermosensitive TRP channels, this allosteric communication is triggered by ligand interaction or in response to temperature changes. Because dynamic allostery suggests a dynamic role of disordered regions, in this work we set out to thoroughly evaluate these regions in six thermosensitive TRP channels. Thus, by contrasting the intrinsic flexibility of the transmembrane region as a function of the degree of disorder in those proteins, we discovered several residues that do not show a direct correlation in both parameters. This kind of structural discrepancy revealed residues that are either reported to be dynamic, functionally relevant or are involved in signal propagation and probably part of allosteric networks. These discrepant, potentially dynamic regions are not exclusive of TRP channels, as this same correlation was found in the Kv Shaker channel.

Structural biases in disordered proteins are prevalent in the cell

Intrinsically disordered proteins and protein regions (IDPs) are prevalent in all proteomes and are essential to cellular function. Unlike folded proteins, IDPs exist in an ensemble of dissimilar conformations. Despite this structural plasticity, intramolecular interactions create sequence-specific structural biases that determine an IDP ensemble's three-dimensional shape. Such structural biases can be key to IDP function and are often measured in vitro, but whether those biases are preserved inside the cell is unclear. Here we show that structural biases in IDP ensembles found in vitro are recapitulated inside human-derived cells. We further reveal that structural biases can change in a sequence-dependent manner due to changes in the intracellular milieu, subcellular localization, and intramolecular interactions with tethered well-folded domains. We propose that the structural sensitivity of IDP ensembles can be leveraged for biological function, can be the underlying cause of IDP-driven pathology or can be used to design disorder-based biosensors and actuators.

Dynamics and interactions of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are widespread in eukaryotes and participate in a variety of important cellular processes. Numerous studies using state-of-the-art experimental and theoretical methods have advanced our understanding of IDPs and revealed that disordered regions engage in a large repertoire of intra- and intermolecular interactions through their conformational dynamics, thereby regulating many intracellular functions in concert with folded domains. The mechanisms by which IDPs interact with their partners are diverse, depending on their conformational propensities, and include induced fit, conformational selection, and their mixtures. In addition, IDPs are implicated in many diseases, and progress has been made in designing inhibitors of IDP-mediated interactions. Here we review these recent advances with a focus on the dynamics and interactions of IDPs.

Biological importance of arginine: A comprehensive review of the roles in structure, disorder, and functionality of peptides and proteins

Arginine shows Jekyll and Hyde behavior in several respects. It participates in protein folding via ionic and H-bonds and cation-pi interactions; the charge and hydrophobicity of its side chain make it a disorder-promoting amino acid. Its methylation in histones; RNA binding proteins; chaperones regulates several cellular processes. The arginine-centric modifications are important in oncogenesis and as biomarkers in several cardiovascular diseases. The cross-links involving arginine in collagen and cornea are involved in pathogenesis of tissues but have also been useful in tissue engineering and wound-dressing materials. Arginine is a part of active site of several enzymes such as GTPases, peroxidases, and sulfotransferases. Its metabolic importance is obvious as it is involved in production of urea, NO, ornithine and citrulline. It can form unusual functional structures such as molecular tweezers in vitro and sprockets which engage DNA chains as part of histones in vivo. It has been used in design of cell-penetrating peptides as drugs. Arginine has been used as an excipient in both solid and injectable drug formulations; its role in suppressing opalescence due to liquid-liquid phase separation is particularly very promising. It has been known as a suppressor of protein aggregation during protein refolding. It has proved its usefulness in protein bioseparation processes like ion-exchange, hydrophobic and affinity chromatographies. Arginine is an amino acid, whose importance in biological sciences and biotechnology continues to grow in diverse ways.

Searching for EGF Fragments Recreating the Outer Sphere of the Growth Factor Involved in Receptor Interactions

The aims of this study were to determine whether it is possible to use peptide microarrays obtained using the SPOT technique (immobilized on cellulose) and specific polyclonal antibodies to select fragments that reconstruct the outer sphere of proteins and to ascertain whether the selected peptide fragments can be useful in the study of their protein-protein and/or peptide-protein interactions. Using this approach, epidermal growth factor (EGF) fragments responsible for the interaction with the EGF receptor were searched. A library of EGF fragments immobilized on cellulose was obtained using triazine condensing reagents. Experiments on the interactions with EGFR confirmed the high affinity of the selected peptide fragments. Biological tests on cells showed the lack of cytotoxicity of the EGF fragments. Selected EGF fragments can be used in various areas of medicine.

Searching for Structure: Characterizing the Protein Conformational Landscape with Clustering-Based Algorithms

The identification and characterization of the main conformations from a protein population are a challenging and inherently high-dimensional problem. Here, we evaluate the performance of the Secondary sTructural Ensembles with machine LeArning (StELa) double-clustering method, which clusters protein structures based on the relationship between the φ and ψ dihedral angles in a protein backbone and the secondary structure of the protein, thus focusing on the local properties of protein structures. The classification of states as vectors composed of the clusters' indices arising naturally from the Ramachandran plot is followed by the hierarchical clustering of the vectors to allow for the identification of the main features of the corresponding free energy landscape (FEL). We compare the performance of StELa with the established root-mean-squared-deviation (RMSD)-based clustering algorithm, which focuses on global properties of protein structures and with Combinatorial Averaged Transient Structure (CATS), the combinatorial averaged transient structure clustering method based on distributions of the φ and ψ dihedral angle coordinates. Using ensembles of conformations from molecular dynamics simulations of intrinsically disordered proteins (IDPs) of various lengths (tau protein fragments) or short fragments from a globular protein, we show that StELa is the clustering method that identifies many of the minima and relevant energy states around the minima from the corresponding FELs. In contrast, the RMSD-based algorithm yields a large number of clusters that usually cover most of the FEL, thus being unable to distinguish between states, while CATS does not sample well the FELs for long IDPs and fragments from globular proteins.

Physiology and pharmacological targeting of phase separation

Liquid-liquid phase separation (LLPS) in biology describes a process by which proteins form membraneless condensates within a cellular compartment when conditions are met, including the concentration and posttranslational modifications of the protein components, the condition of the aqueous solution (pH, ionic strength, pressure, and temperature), and the existence of assisting factors (such as RNAs or other proteins). In these supramolecular liquid droplet-like inclusion bodies, molecules are held together through weak intermolecular and/or intramolecular interactions. With the aid of LLPS, cells can assemble functional sub-units within a given cellular compartment by enriching or excluding specific factors, modulating cellular function, and rapidly responding to environmental or physiological cues. Hence, LLPS is emerging as an important means to regulate biology and physiology. Yet, excessive inclusion body formation by, for instance, higher-than-normal concentrations or mutant forms of the protein components could result in the conversion from dynamic liquid condensates into more rigid gel- or solid-like aggregates, leading to the disruption of the organelle's function followed by the development of human disorders like neurodegenerative diseases. In summary, well-controlled formation and de-formation of LLPS is critical for normal biology and physiology from single cells to individual organisms, whereas abnormal LLPS is involved in the pathophysiology of human diseases. In turn, targeting these aggregates or their formation represents a promising approach in treating diseases driven by abnormal LLPS including those neurodegenerative diseases that lack effective therapies.

A novel fusion technology utilizing complex network and sequence information for FAD-binding site identification

Flavin adenine dinucleotide (FAD) binding sites play an increasingly important role as useful targets for inhibiting bacterial infections. To reveal protein topological structural information as a reasonable complement for the identification FAD-binding sites, we designed a novel fusion technology according to sequence and complex network. The specially designed feature vectors were combined and fed into CatBoost for model construction. Moreover, due to the minority class (positive samples) is more significant for biological researches, a random under-sampling technique was applied to solve the imbalance. Compared with the previous methods, our methods achieved the best results for two independent test datasets. Especially, the MCC obtained by FADsite and FADsite_seq were 14.37 %-53.37 % and 21.81 %-60.81 % higher than the results of existing methods on Test6; and they showed improvements ranging from 6.03 % to 21.96 % and 19.77 %-35.70 % on Test4. Meanwhile, statistical tests show that our methods significantly differ from the state-of-the-art methods and the cross-entropy loss shows that our methods have high certainty. The excellent results demonstrated the effectiveness of using sequence and complex network information in identifying FAD-binding sites. It may be complementary to other biological studies. The data and resource codes are available at https://github.com/Kangxiaoneuq/FADsite.

Single-cell transcriptomics analysis of zebrafish brain reveals adverse effects of manganese on neurogenesis

Manganese (Mn) is considered as an important environmental risk factor for Parkinson's disease. Excessive exposure to Mn can damage various neural cells and affect the neurogenesis, resulting in neurological dysfunction. However, the specific mechanisms of Mn exposure affecting neurogenesis have not been well understood, including compositional changes and heterogeneity of various neural cells. Zebrafish have been successfully used as a neurotoxicity model due to its homology with mammals in several key regions of the brain, as well as its advantages such as small size. We performed single-cell RNA sequencing of zebrafish brains from normal and Mn-exposed groups. Our results suggested that low levels of Mn exposure activated neurogenesis in the zebrafish brain, including promoting the proliferation of neural progenitor cells and differentiation to newborn neurons and oligodendrocytes, while high levels of Mn exposure inhibited neurogenesis and neural function. Mn could affect neurogenesis through specific molecular pathways. In addition, Mn regulated intercellular communication and affected cellular communication in neural cells through specific signaling pathways. Taken together, our study elucidates the cellular composition of the zebrafish brain and adds to the understanding of the mechanisms involved in Mn-induced neurogenesis damage.

Multi-eGO: Model Improvements toward the Study of Complex Self-Assembly Processes

Structure-based models have been instrumental in simulating protein folding and suggesting hypotheses about the mechanisms involved. Nowadays, at least for fast-folding proteins, folding can be simulated in explicit solvent using classical molecular dynamics. However, other self-assembly processes, such as protein aggregation, are still far from being accessible. Recently, we proposed that a hybrid multistate structure-based model, multi-eGO, could help to bridge the gap toward the simulation of out-of-equilibrium, concentration-dependent self-assembly processes. Here, we further improve the model and show how multi-eGO can effectively and accurately learn the conformational ensemble of the amyloid β42 intrinsically disordered peptide, reproduce the well-established folding mechanism of the B1 immunoglobulin-binding domain of streptococcal protein G, and reproduce the aggregation as a function of the concentration of the transthyretin 105-115 amyloidogenic peptide. We envision that by learning from the dynamics of a few minima, multi-eGO can become a platform for simulating processes inaccessible to other simulation techniques.

Fine structures of intrinsically disordered proteins

We report simulation studies of 33 single intrinsically disordered proteins (IDPs) using coarse-grained bead-spring models where interactions among different amino acids are introduced through a hydropathy matrix and additional screened Coulomb interaction for the charged amino acid beads. Our simulation studies of two different hydropathy scales (HPS1, HPS2) [Dignon et al., PLoS Comput. Biol. 14, e1005941 (2018); Tesei et al. Proc. Natl. Acad. Sci. U. S. A. 118, e2111696118 (2021)] and the comparison with the existing experimental data indicate an optimal interaction parameter ϵ = 0.1 and 0.2 kcal/mol for the HPS1 and HPS2 hydropathy scales. We use these best-fit parameters to investigate both the universal aspects as well as the fine structures of the individual IDPs by introducing additional characteristics. (i) First, we investigate the polymer-specific scaling relations of the IDPs in comparison to the universal scaling relations [Bair et al., J. Chem. Phys. 158, 204902 (2023)] for the homopolymers. By studying the scaled end-to-end distances ⟨RN2⟩/(2Lℓp) and the scaled transverse fluctuations l̃⊥2=⟨l⊥2⟩/L, we demonstrate that IDPs are broadly characterized with a Flory exponent of ν ≃ 0.56 with the conclusion that conformations of the IDPs interpolate between Gaussian and self-avoiding random walk chains. Then, we introduce (ii) Wilson charge index (W) that captures the essential features of charge interactions and distribution in the sequence space and (iii) a skewness index (S) that captures the finer shape variation of the gyration radii distributions as a function of the net charge per residue and charge asymmetry parameter. Finally, our study of the (iv) variation of ⟨Rg⟩ as a function of salt concentration provides another important metric to bring out finer characteristics of the IDPs, which may carry relevant information for the origin of life.

A syndromic neurodevelopmental disorder caused by rare variants in PPFIA3

PPFIA3 encodes the protein-tyrosine phosphatase, receptor-type, F-polypeptide-interacting-protein-alpha-3 (PPFIA3), which is a member of the LAR-protein-tyrosine phosphatase-interacting-protein (liprin) family involved in synapse formation and function, synaptic vesicle transport, and presynaptic active zone assembly. The protein structure and function are evolutionarily well conserved, but human diseases related to PPFIA3 dysfunction are not yet reported in OMIM. Here, we report 20 individuals with rare PPFIA3 variants (19 heterozygous and 1 compound heterozygous) presenting with developmental delay, intellectual disability, hypotonia, dysmorphisms, microcephaly or macrocephaly, autistic features, and epilepsy with reduced penetrance. Seventeen unique PPFIA3 variants were detected in 18 families. To determine the pathogenicity of PPFIA3 variants in vivo, we generated transgenic fruit flies producing either human wild-type (WT) PPFIA3 or five missense variants using GAL4-UAS targeted gene expression systems. In the fly overexpression assays, we found that the PPFIA3 variants in the region encoding the N-terminal coiled-coil domain exhibited stronger phenotypes compared to those affecting the C-terminal region. In the loss-of-function fly assay, we show that the homozygous loss of fly Liprin-α leads to embryonic lethality. This lethality is partially rescued by the expression of human PPFIA3 WT, suggesting human PPFIA3 function is partially conserved in the fly. However, two of the tested variants failed to rescue the lethality at the larval stage and one variant failed to rescue lethality at the adult stage. Altogether, the human and fruit fly data reveal that the rare PPFIA3 variants are dominant-negative loss-of-function alleles that perturb multiple developmental processes and synapse formation.

DisoFLAG: accurate prediction of protein intrinsic disorder and its functions using graph-based interaction protein language model

Intrinsically disordered proteins and regions (IDPs/IDRs) are functionally important proteins and regions that exist as highly dynamic conformations under natural physiological conditions. IDPs/IDRs exhibit a broad range of molecular functions, and their functions involve binding interactions with partners and remaining native structural flexibility. The rapid increase in the number of proteins in sequence databases and the diversity of disordered functions challenge existing computational methods for predicting protein intrinsic disorder and disordered functions. A disordered region interacts with different partners to perform multiple functions, and these disordered functions exhibit different dependencies and correlations. In this study, we introduce DisoFLAG, a computational method that leverages a graph-based interaction protein language model (GiPLM) for jointly predicting disorder and its multiple potential functions. GiPLM integrates protein semantic information based on pre-trained protein language models into graph-based interaction units to enhance the correlation of the semantic representation of multiple disordered functions. The DisoFLAG predictor takes amino acid sequences as the only inputs and provides predictions of intrinsic disorder and six disordered functions for proteins, including protein-binding, DNA-binding, RNA-binding, ion-binding, lipid-binding, and flexible linker. We evaluated the predictive performance of DisoFLAG following the Critical Assessment of protein Intrinsic Disorder (CAID) experiments, and the results demonstrated that DisoFLAG offers accurate and comprehensive predictions of disordered functions, extending the current coverage of computationally predicted disordered function categories. The standalone package and web server of DisoFLAG have been established to provide accurate prediction tools for intrinsic disorders and their associated functions.

Machine-learning-based methods to generate conformational ensembles of disordered proteins

Intrinsically disordered proteins are characterized by a conformational ensemble. While computational approaches such as molecular dynamics simulations have been used to generate such ensembles, their computational costs can be prohibitive. An alternative approach is to learn from data and train machine-learning models to generate conformational ensembles of disordered proteins. This has been a relatively unexplored approach, and in this work we demonstrate a proof-of-principle approach to do so. Specifically, we devised a two-stage computational pipeline: in the first stage, we employed supervised machine-learning models to predict ensemble-derived two-dimensional (2D) properties of a sequence, given the conformational ensemble of a closely related sequence. In the second stage, we used denoising diffusion models to generate three-dimensional (3D) coarse-grained conformational ensembles, given the two-dimensional predictions outputted by the first stage. We trained our models on a data set of coarse-grained molecular dynamics simulations of thousands of rationally designed synthetic sequences. The accuracy of our 2D and 3D predictions was validated across multiple metrics, and our work demonstrates the applicability of machine-learning techniques to predicting higher-dimensional properties of disordered proteins.

Allosteric control of dynamin-related protein 1 through a disordered C-terminal Short Linear Motif

The mechanochemical GTPase dynamin-related protein 1 (Drp1) catalyzes mitochondrial and peroxisomal fission, but the regulatory mechanisms remain ambiguous. Here we find that a conserved, intrinsically disordered, six-residue Short Linear Motif at the extreme Drp1 C-terminus, named CT-SLiM, constitutes a critical allosteric site that controls Drp1 structure and function in vitro and in vivo. Extension of the CT-SLiM by non-native residues, or its interaction with the protein partner GIPC-1, constrains Drp1 subunit conformational dynamics, alters self-assembly properties, and limits cooperative GTP hydrolysis, surprisingly leading to the fission of model membranes in vitro. In vivo, the involvement of the native CT-SLiM is critical for productive mitochondrial and peroxisomal fission, as both deletion and non-native extension of the CT-SLiM severely impair their progression. Thus, contrary to prevailing models, Drp1-catalyzed membrane fission relies on allosteric communication mediated by the CT-SLiM, deceleration of GTPase activity, and coupled changes in subunit architecture and assembly-disassembly dynamics.

Dynamic conformational changes of a tardigrade group-3 late embryogenesis abundant protein modulate membrane biophysical properties

A number of intrinsically disordered proteins (IDPs) encoded in stress-tolerant organisms, such as tardigrade, can confer fitness advantage and abiotic stress tolerance when heterologously expressed. Tardigrade-specific disordered proteins including the cytosolic-abundant heat-soluble proteins are proposed to confer stress tolerance through vitrification or gelation, whereas evolutionarily conserved IDPs in tardigrades may contribute to stress tolerance through other biophysical mechanisms. In this study, we characterized the mechanism of action of an evolutionarily conserved, tardigrade IDP, HeLEA1, which belongs to the group-3 late embryogenesis abundant (LEA) protein family. HeLEA1 homologs are found across different kingdoms of life. HeLEA1 is intrinsically disordered in solution but shows a propensity for helical structure across its entire sequence. HeLEA1 interacts with negatively charged membranes via dynamic disorder-to-helical transition, mainly driven by electrostatic interactions. Membrane interaction of HeLEA1 is shown to ameliorate excess surface tension and lipid packing defects. HeLEA1 localizes to the mitochondrial matrix when expressed in yeast and interacts with model membranes mimicking inner mitochondrial membrane. Yeast expressing HeLEA1 shows enhanced tolerance to hyperosmotic stress under nonfermentative growth and increased mitochondrial membrane potential. Evolutionary analysis suggests that although HeLEA1 homologs have diverged their sequences to localize to different subcellular organelles, all homologs maintain a weak hydrophobic moment that is characteristic of weak and reversible membrane interaction. We suggest that such dynamic and weak protein-membrane interaction buffering alterations in lipid packing could be a conserved strategy for regulating membrane properties and represent a general biophysical solution for stress tolerance across the domains of life.

Acetylation of nuclear receptors in health and disease: an update

Lysine acetylation is a common reversible post-translational modification of proteins that plays a key role in regulating gene expression. Nuclear receptors (NRs) include ligand-inducible transcription factors and orphan receptors for which the ligand is undetermined, which together regulate the expression of genes involved in development, metabolism, homeostasis, reproduction and human diseases including cancer. Since the original finding that the ERα, AR and HNF4 are acetylated, we now understand that the vast majority of NRs are acetylated and that this modification has profound effects on NR function. Acetylation sites are often conserved and involve both ordered and disordered regions of NRs. The acetylated residues function as part of an intramolecular signalling platform intersecting phosphorylation, methylation and other modifications. Acetylation of NR has been shown to impact recruitment into chromatin, co-repressor and coactivator complex formation, sensitivity and specificity of regulation by ligand and ligand antagonists, DNA binding, subcellular distribution and transcriptional activity. A growing body of evidence in mice indicates a vital role for NR acetylation in metabolism. Additionally, mutations of the NR acetylation site occur in human disease. This review focuses on the role of NR acetylation in coordinating signalling in normal physiology and disease.

Prediction of interface between regions of varying degrees of order or disorderness in intrinsically disordered proteins from dihedral angles

Intrinsically disordered proteins (IDPs) are proteins that do not form uniquely defined three-dimensional (3-D) structures. Experimental research on IDPs is difficult since they go against the traditional protein structure-function paradigm. Although there are several predictors of disorder based on amino acid sequences, but very limited based on the 3-D structures of proteins. Dihedral angles have a significant role in predicting protein structure because they establish a protein's backbone, which, coupled with its side chain, establishes its overall shape. Here, we have carried out atomistic Molecular Dynamics (MD) simulations on four different proteins: one ordered protein (Monellin), two partially disordered proteins (p53-TAD and Amyloid beta (Aβ1-42) peptide), and one completely disordered protein (Histatin 5). The MD simulation trajectories for the corresponding four proteins were used to conduct dihedral angle (ϕ and ѱ) analysis. Then, the average dihedral angles for each of the residues were calculated and plotted against the residue index. We noticed steep rises or falls in the average ϕ value at certain locations in the plot. These sudden shifts in the average ϕ value reflect the interface between regions of varying degrees of order or disorderness in intrinsically disordered proteins. Using this method, the probable conformer of a protein with a higher degree of disorder can be found among the ensembles of structures sampled during the MD simulations. The results of our study offer new understandings on precisely identifying regions of various degrees of disorder in intrinsically disordered proteins.Communicated by Ramaswamy H. Sarma.

Structural analysis and functional evaluation of the disordered ß-hexosyltransferase region from Hamamotoa (Sporobolomyces) singularis

Hamamotoa (Sporobolomyces) singularis codes for an industrially important membrane bound ß-hexosyltransferase (BHT), (BglA, UniprotKB: Q564N5) that has applications in the production of natural fibers such as galacto-oligosaccharides (GOS) and natural sugars found in human milk. When heterologously expressed by Komagataella phaffii GS115, BHT is found both membrane bound and soluble secreted into the culture medium. In silico structural predictions and crystal structures support a glycosylated homodimeric enzyme and the presence of an intrinsically disordered region (IDR) with membrane binding potential within its novel N-terminal region (1-110 amino acids). Additional in silico analysis showed that the IDR may not be essential for stable homodimerization. Thus, we performed progressive deletion analyses targeting segments within the suspected disordered region, to determine the N-terminal disorder region's impact on the ratio of membrane-bound to secreted soluble enzyme and its contribution to enzyme activity. The ratio of the soluble secreted to membrane-bound enzyme shifted from 40% to 53% after the disordered N-terminal region was completely removed, while the specific activity was unaffected. Furthermore, functional analysis of each glycosylation site found within the C-terminal domain revealed reduced total secreted protein activity by 58%-97% in both the presence and absence of the IDR, indicating that glycosylation at all four locations is required by the host for the secretion of active enzyme and independent of the removed disordered N-terminal region. Overall, the data provides evidence that the disordered region only partially influences the secretion and membrane localization of BHT.

Sequence-Tunable Phase Behavior and Intrinsic Fluorescence in Dynamically Interacting Peptides

A conceptual framework towards understanding biological condensed phases is emerging, derived from biological, biomimetic, and synthetic sequences. However, de novo peptide condensate design remains a challenge due to an incomplete understanding of the structural and interactive complexity. We designed peptide modules based on a simple repeat motif composed of tripeptide spacers (GSG, SGS, GLG) interspersed with adhesive amino acids (R/H and Y). We show, using sequence editing and a combination of computation and experiment, that n→π* interactions in GLG backbones are a dominant factor in providing sufficient backbone structure, which in turn regulates the water interface, collectively promoting liquid droplet formation. Moreover, these R(GLG)Y and H(GLG)Y condensates unexpectedly display sequence-dependent emission that is a consequence of their non-covalent network interactions, and readily observable by confocal microscopy.

Improved prediction of protein-protein interactions by a modified strategy using three conventional docking software in combination

Proteins play a crucial role in many biological processes, where their interaction with other proteins are integral. Abnormal protein-protein interactions (PPIs) have been linked to various diseases including cancer, and thus targeting PPIs holds promise for drug development. However, experimental confirmation of the peculiarities of PPIs is challenging due to their dynamic and transient nature. As a complement to experimental technologies, multiple computational molecular docking (MD) methods have been developed to predict the structures of protein-protein complexes and their dynamics, still requiring further improvements in several issues. Here, we report an improved MD method, namely three-software docking (3SD), by employing three popular protein-peptide docking software (CABS-dock, HPEPDOCK, and HADDOCK) in combination to ensure constant quality for most targets. We validated our 3SD performance in known protein-peptide interactions (PpIs). We also enhanced MD performance in proteins having intrinsically disordered regions (IDRs) by applying the modified 3SD strategy, the three-software docking after removing random coiled IDR (3SD-RR), to the comparable crystal PpI structures. At the end, we applied 3SD-RR to the AlphaFold2-predicted receptors, yielding an efficient prediction of PpI pose with high relevance to the experimental data regardless of the presence of IDRs or the availability of receptor structures. Our study provides an improved solution to the challenges in studying PPIs through computational docking and has the potential to contribute to PPIs-targeted drug discovery. SIGNIFICANCE STATEMENT: Protein-protein interactions (PPIs) are integral to life, and abnormal PPIs are associated with diseases such as cancer. Studying protein-peptide interactions (PpIs) is challenging due to their dynamic and transient nature. Here we developed improved docking methods (3SD and 3SD-RR) to predict the PpI poses, ensuring constant quality in most targets and also addressing issues like intrinsically disordered regions (IDRs) and artificial intelligence-predicted structures. Our study provides an improved solution to the challenges in studying PpIs through computational docking and has the potential to contribute to PPIs-targeted drug discovery.

Microproteins transitioning into a new Phase: Defining the undefined

Recent advancements in omics technologies have unveiled a hitherto unknown group of short polypeptides called microproteins (miPs). Despite their size, accumulating evidence has demonstrated that miPs exert varied and potent biological functions. They act in paracrine, juxtracrine, and endocrine fashion, maintaining cellular physiology and driving diseases. The present study focuses on biochemical and biophysical analysis and characterization of twenty-four human miPs using distinct computational methods, including RIDAO, AlphaFold2, D2P2, FuzDrop, STRING, and Emboss Pep wheel. miPs often lack well-defined tertiary structures and may harbor intrinsically disordered regions (IDRs) that play pivotal roles in cellular functions. Our analyses define the physicochemical properties of an essential subset of miPs, elucidating their structural characteristics and demonstrating their propensity for driving or participating in liquid-liquid phase separation (LLPS) and intracellular condensate formation. Notably, miPs such as NoBody and pTUNAR revealed a high propensity for LLPS, implicating their potential involvement in forming membrane-less organelles (MLOs) during intracellular LLPS and condensate formation. The results of our study indicate that miPs have functionally profound implications in cellular compartmentalization and signaling processes essential for regulating normal cellular functions. Taken together, our methodological approach explains and highlights the biological importance of these miPs, providing a deeper understanding of the unusual structural landscape and functionality of these newly defined small proteins. Understanding their functions and biological behavior will aid in developing targeted therapies for diseases that involve miPs.

Transcription factor condensates and signaling driven transcription

Transcription Factor (TF) condensates are a heterogenous mix of RNA, DNA, and multiple co-factor proteins capable of modulating the transcriptional response of the cell. The dynamic nature and the spatial location of TF-condensates in the 3D nuclear space is believed to provide a fast response, which is on the same pace as the signaling cascade and yet ever-so-specific in the crowded environment of the nucleus. However, the current understanding of how TF-condensates can achieve these feet so quickly and efficiently is still unclear. In this review, we draw parallels with other protein condensates and share our speculations on how the nucleus uses these TF-condensates to achieve high transcriptional specificity and fidelity. We discuss the various constituents of TF-condensates, their properties, and the known and unknown functions of TF-condensates with a particular focus on steroid signaling-induced transcriptional programs.

Intrinsically disordered regions are poised to act as sensors of cellular chemistry

Intrinsically disordered proteins and protein regions (IDRs) are abundant in eukaryotic proteomes and play a wide variety of essential roles. Instead of folding into a stable structure, IDRs exist in an ensemble of interconverting conformations whose structure is biased by sequence-dependent interactions. The absence of a stable 3D structure, combined with high solvent accessibility, means that IDR conformational biases are inherently sensitive to changes in their environment. Here, we argue that IDRs are ideally poised to act as sensors and actuators of cellular physicochemistry. We review the physical principles that underlie IDR sensitivity, the molecular mechanisms that translate this sensitivity to function, and recent studies where environmental sensing by IDRs may play a key role in their downstream function.

Non-canonical helical transitions and conformational switching are associated with characteristic flexibility and disorder indices in TRP and Kv channels

Structural evidence and much experimental data have demonstrated the presence of non-canonical helical substructures (π and 3₁₀) in regions of great functional relevance both in TRP as in Kv channels. Through an exhaustive compositional analysis of the sequences underlying these substructures, we find that each of them is associated with characteristic local flexibility profiles, which in turn are implicated in significant conformational rearrangements and interactions with specific ligands. We found that α-to-π helical transitions are associated with patterns of local rigidity whereas α-to-3₁₀ transitions are mainly leagued with high local flexibility profiles. We also study the relationship between flexibility and protein disorder in the transmembrane domain of these proteins. By contrasting these two parameters, we located regions showing a sort of structural discrepancy between these similar but not identical protein attributes. Notably, these regions are presumably implicated in important conformational rearrangements during the gating in those channels. In that sense, finding these regions where flexibility and disorder are not proportional allows us to detect regions with potential functional dynamism. From this point of view, we highlighted some conformational rearrangements that occur during ligand binding events, the compaction, and refolding of the outer pore loops in several TRP channels, as well as the well-known S4 motion in Kv channels.

The Functionality of Membrane-Inserting Proteins and Peptides: Curvature Sensing, Generation, and Pore Formation

Proteins and peptides with hydrophobic and amphiphilic segments are responsible for many biological functions. The sensing and generation of membrane curvature are the functions of several protein domains or motifs. While some specific membrane proteins play an essential role in controlling the curvature of distinct intracellular membranes, others participate in various cellular processes such as clathrin-mediated endocytosis, where several proteins sort themselves at the neck of the membrane bud. A few membrane-inserting proteins form nanopores that permeate selective ions and water to cross the membrane. In addition, many natural and synthetic small peptides and protein toxins disrupt the membrane by inducing nonspecific pores in the membrane. The pore formation causes cell death through the uncontrolled exchange between interior and exterior cellular contents. In this article, we discuss the insertion depth and orientation of protein/peptide helices, and their role as a sensor and inducer of membrane curvature as well as a pore former in the membrane. We anticipate that this extensive review will assist biophysicists to gain insight into curvature sensing, generation, and pore formation by membrane insertion.

Structure-function relationships in protein homorepeats

Homorepeats (or polyX), protein segments containing repetitions of the same amino acid, are abundant in proteomes from all kingdoms of life and are involved in crucial biological functions as well as several neurodegenerative and developmental diseases. Mainly inserted in disordered segments of proteins, the structure/function relationships of homorepeats remain largely unexplored. In this review, we summarize present knowledge for the most abundant homorepeats, highlighting the role of the inherent structure and the conformational influence exerted by their flanking regions. Recent experimental and computational methods enable residue-specific investigations of these regions and promise novel structural and dynamic information for this elusive group of proteins. This information should increase our knowledge about the structural bases of phenomena such as liquid-liquid phase separation and trinucleotide repeat disorders.

Microproteins-Discovery, structure, and function

Advances in proteogenomic technologies have revealed hundreds to thousands of translated small open reading frames (sORFs) that encode microproteins in genomes across evolutionary space. While many microproteins have now been shown to play critical roles in biology and human disease, a majority of recently identified microproteins have little or no experimental evidence regarding their functionality. Computational tools have some limitations for analysis of short, poorly conserved microprotein sequences, so additional approaches are needed to determine the role of each member of this recently discovered polypeptide class. A currently underexplored avenue in the study of microproteins is structure prediction and determination, which delivers a depth of functional information. In this review, we provide a brief overview of microprotein discovery methods, then examine examples of microprotein structures (and, conversely, intrinsic disorder) that have been experimentally determined using crystallography, cryo-electron microscopy, and NMR, which provide insight into their molecular functions and mechanisms. Additionally, we discuss examples of predicted microprotein structures that have provided insight or context regarding their function. Analysis of microprotein structure at the angstrom level, and confirmation of predicted structures, therefore, has potential to identify translated microproteins that are of biological importance and to provide molecular mechanism for their in vivo roles.

Conformational entropy in molecular recognition of intrinsically disordered proteins

Broad conformational ensembles make intrinsically disordered proteins or regions entropically intriguing. Although methodologically challenging and understudied, emerging studies into their changes in conformational entropy (ΔS°conf) upon complex formation have provided both quantitative and qualitative insight. Recent work based on thermodynamics from isothermal titration calorimetry and NMR spectroscopy uncovers an expanded repertoire of regulatory mechanisms, where ΔS°conf plays roles in partner selection, state behavior, functional buffering, allosteric regulation, and drug design. We highlight these mechanisms to display the large entropic reservoir of IDPs for the regulation of molecular communication. We call upon the field to make efforts to contribute to this insight as more studies are needed for forwarding mechanistic decoding of intrinsically disordered proteins and their complexes.

Programming co-assembled peptide nanofiber morphology via anionic amino acid type: Insights from molecular dynamics simulations

Co-assembling peptides can be crafted into supramolecular biomaterials for use in biotechnological applications, such as cell culture scaffolds, drug delivery, biosensors, and tissue engineering. Peptide co-assembly refers to the spontaneous organization of two different peptides into a supramolecular architecture. Here we use molecular dynamics simulations to quantify the effect of anionic amino acid type on co-assembly dynamics and nanofiber structure in binary CATCH(+/-) peptide systems. CATCH peptide sequences follow a general pattern: CQCFCFCFCQC, where all C's are either a positively charged or a negatively charged amino acid. Specifically, we investigate the effect of substituting aspartic acid residues for the glutamic acid residues in the established CATCH(6E-) molecule, while keeping CATCH(6K+) unchanged. Our results show that structures consisting of CATCH(6K+) and CATCH(6D-) form flatter β-sheets, have stronger interactions between charged residues on opposing β-sheet faces, and have slower co-assembly kinetics than structures consisting of CATCH(6K+) and CATCH(6E-). Knowledge of the effect of sidechain type on assembly dynamics and fibrillar structure can help guide the development of advanced biomaterials and grant insight into sequence-to-structure relationships.

Evolutionarily conserved protein motifs drive interactions between the plant nucleoskeleton and nuclear pores

The nucleoskeleton forms a filamentous meshwork under the nuclear envelope and contributes to the regulation of nuclear shape and gene expression. To understand how the Arabidopsis (Arabidopsis thaliana) nucleoskeleton physically connects to the nuclear periphery in plants, we investigated the Arabidopsis nucleoskeleton protein KAKU4 and sought for functional regions responsible for its localization at the nuclear periphery. We identified 3 conserved peptide motifs within the N-terminal region of KAKU4, which are required for intermolecular interactions of KAKU4 with itself, interaction with the nucleoskeleton protein CROWDED NUCLEI (CRWN), localization at the nuclear periphery, and nuclear elongation in differentiated tissues. Unexpectedly, we find these motifs to be present also in NUP82 and NUP136, 2 plant-specific nucleoporins from the nuclear pore basket. We further show that NUP82, NUP136, and KAKU4 have a common evolutionary history predating nonvascular land plants with KAKU4 mainly localizing outside the nuclear pore suggesting its divergence from an ancient nucleoporin into a new nucleoskeleton component. Finally, we demonstrate that both NUP82 and NUP136, through their shared N-terminal motifs, interact with CRWN and KAKU4 proteins revealing the existence of a physical continuum between the nuclear pore and the nucleoskeleton in plants.

Preserving condensate structure and composition by lowering sequence complexity

Biological condensates play a vital role in organizing cellular chemistry. They selectively partition biomolecules, preventing unwanted cross-talk and buffering against chemical noise. Intrinsically disordered proteins (IDPs) serve as primary components of these condensates due to their flexibility and ability to engage in multivalent, non-specific interactions, leading to spontaneous aggregation. Theoretical advancements are critical at connecting IDP sequences with condensate emergent properties to establish the so-called molecular grammar. We proposed an extension to the stickers and spacers model, incorporating non-specific pairwise interactions between spacers alongside specific interactions among stickers. Our investigation revealed that while spacer interactions contribute to phase separation and co-condensation, their non-specific nature leads to disorganized condensates. Specific sticker-sticker interactions drive the formation of condensates with well-defined structures and molecular composition. We discussed how evolutionary pressures might emerge to affect these interactions, leading to the prevalence of low complexity domains in IDP sequences. These domains suppress spurious interactions and facilitate the formation of biologically meaningful condensates.