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MOTIVATION: Sidechain rotamer libraries of the common amino acids of a protein are useful for folded protein structure determination and for generating ensembles of intrinsically disordered proteins (IDPs). However, much of protein function is modulated beyond the translated sequence through the introduction of post-translational modifications (PTMs). RESULTS: In this work, we have provided a curated set of side chain rotamers for the most common PTMs derived from the RCSB PDB database, including phosphorylated, methylated, and acetylated sidechains. Our rotamer libraries improve upon existing methods such as SIDEpro, Rosetta, and AlphaFold3 in predicting the experimental structures for PTMs in folded proteins. In addition, we showcase our PTM libraries in full use by generating ensembles with the Monte Carlo Side Chain Entropy (MCSCE) for folded proteins, and combining MCSCE with the Local Disordered Region Sampling algorithms within IDPConformerGenerator for proteins with intrinsically disordered regions. AVAILABILITY AND IMPLEMENTATION: The codes for dihedral angle computations and library creation are available at https://github.com/THGLab/ptm_sc.git.

Tardigrades are microscopic animals that survive desiccation by inducing biostasis. To survive drying tardigrades rely on intrinsically disordered CAHS proteins, which also function to prevent perturbations induced by drying in vitro and in heterologous systems. CAHS proteins have been shown to form gels both in vitro and in vivo, which has been speculated to be linked to their protective capacity. However, the sequence features and mechanisms underlying gel formation and the necessity of gelation for protection have not been demonstrated. Here we report a mechanism of fibrillization and gelation for CAHS D similar to that of intermediate filament assembly. We show that in vitro, gelation restricts molecular motion, immobilizing and protecting labile material from the harmful effects of drying. In vivo, we observe that CAHS D forms fibrillar networks during osmotic stress. Fibrillar networking of CAHS D improves survival of osmotically shocked cells. We observe two emergent properties associated with fibrillization; (i) prevention of cell volume change and (ii) reduction of metabolic activity during osmotic shock. We find that there is no significant correlation between maintenance of cell volume and survival, while there is a significant correlation between reduced metabolism and survival. Importantly, CAHS Ds fibrillar network formation is reversible and metabolic rates return to control levels after CAHS fibers are resolved. This work provides insights into how tardigrades induce reversible biostasis through the self-assembly of labile CAHS gels.

Numerous biological systems contain vesicle-like biomolecular compartments without membranes, which contribute to diverse functions including gene regulation, stress response, signaling, and skin barrier formation. Coacervation, as a form of liquid-liquid phase separation (LLPS), is recognized as a representative precursor to the formation and assembly of membrane-less vesicle-like structures, although their formation mechanism remains unclear. In this study, a coacervation-driven membrane-less vesicle-like structure is constructed using two proteins, GG1234 (an anionic intrinsically disordered protein) and bhBMP-2 (a bioengineered human bone morphogenetic protein 2). GG1234 formed both simple coacervates by itself and complex coacervates with the relatively cationic bhBMP-2 under acidic conditions. Upon addition of dissolved bhBMP-2 to the simple coacervates of GG1234, a phase transition from spherical simple coacervates to vesicular condensates occurred via the interactions between GG1234 and bhBMP-2 on the surface of the highly viscoelastic GG1234 simple coacervates. Furthermore, the shell structure in the outer region of the GG1234/bhBMP-2 vesicular condensates exhibited gel-like properties, leading to the formation of multiphasic vesicle-like compartments. A potential mechanism is proposed for the formation of the membrane-less GG1234/bhBMP-2 vesicle-like compartments. This study provides a dynamic process underlying the formation of biomolecular multiphasic condensates, thereby enhancing the understanding of these biomolecular structures.

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.

The Protein Ensemble Database (PED) (URL: https://proteinensemble.org) is the primary resource for depositing structural ensembles of intrinsically disordered proteins. This updated version of PED reflects advancements in the field, denoting a continual expansion with a total of 461 entries and 538 ensembles, including those generated without explicit experimental data through novel machine learning (ML) techniques. With this significant increment in the number of ensembles, a few yet-unprecedented new entries entered the database, including those also determined or refined by electron paramagnetic resonance or circular dichroism data. In addition, PED was enriched with several new features, including a novel deposition service, improved user interface, new database cross-referencing options and integration with the 3D-Beacons network-all representing efforts to improve the FAIRness of the database. Foreseeably, PED will keep growing in size and expanding with new types of ensembles generated by accurate and fast ML-based generative models and coarse-grained simulations. Therefore, among future efforts, priority will be given to further develop the database to be compatible with ensembles modeled at a coarse-grained level.

Proteins with intrinsically disordered regions (IDRs) often undergo phase separation to control their functions spatiotemporally. Changing the pH alters the protonation levels of charged sidechains, which in turn affects the attractive or repulsive force for phase separation. In a cell, the rupture of membrane‐bound compartments, such as lysosomes, creates an abrupt change in pH. However, how proteins' phase separation reacts to different pH environments remains largely unexplored. Here, using extensive mutagenesis, NMR spectroscopy, and biophysical techniques, it is shown that the assembly of galectin‐3, a widely studied lysosomal damage marker, is driven by cation‐π interactions between positively charged residues in its folded domain with aromatic residues in the IDR in addition to π–π interaction between IDRs. It is also found that the sole two negatively charged residues in its IDR sense pH changes for tuning the condensation tendency. Also, these two residues may prevent this prion‐like IDR domain from forming rapid and extensive aggregates. These results demonstrate how cation‐π, π–π, and electrostatic interactions can regulate protein condensation between disordered and structured domains and highlight the importance of sparse negatively charged residues in prion‐like IDRs. [ABSTRACT FROM AUTHOR]

During seed maturation, plants may experience severe desiccation, leading to the accumulation of late embryogenesis abundant (LEA) proteins. These intrinsically disordered proteins also accumulate in plant tissues under water deficit. Functional roles of LEA proteins have been proposed based on in vitro studies, where monomers are considered as the functional units. However, the potential formation of homo‐oligomers has been little explored. In this work, we investigated the potential self‐association of Arabidopsis thaliana group 4 LEA proteins (AtLEA4) using in vitro and in vivo approaches. LEA4 proteins represent a compelling case of study due to their high conservation throughout the plant kingdom. This protein family is characterized by a conserved N‐terminal region, with a high alpha‐helix propensity and invitro protective activity, as compared to the highly disordered and low‐conserved C‐terminal region. Our findings revealed that full‐length AtLEA4 proteins oligomerize and that both terminal regions are sufficient for self‐association in vitro. However, the ability of both amino and carboxy regions of AtLEA4‐5 to self‐associate invivo is significantly lower than that of the entire protein. Using high‐resolution and quantitative fluorescence microscopy, we were able to disclose the unreported ability of LEA proteins to form high‐order oligomers in planta. Additionally, we found that high‐order complexes require the simultaneous engagement of both terminal regions, indicating that the entire protein is needed to attain such structural organization. This research provides valuable insights into the self‐association of LEA proteins in plants and emphasizes the role of protein oligomer formation. [ABSTRACT FROM AUTHOR]

Casein kinase 1δ (CK1δ) controls essential biological processes including circadian rhythms and wingless-related integration site (Wnt) signaling, but how its activity is regulated is not well understood. CK1δ is inhibited by autophosphorylation of its intrinsically disordered C-terminal tail. Two CK1 splice variants, δ1 and δ2, are known to have very different effects on circadian rhythms. These variants differ only in the last 16 residues of the tail, referred to as the extreme C termini (XCT), but with marked changes in potential phosphorylation sites. Here, we test whether the XCT of these variants have different effects in autoinhibition of the kinase. Using NMR and hydrogen/deuterium exchange mass spectrometry, we show that the δ1 XCT is preferentially phosphorylated by the kinase and the δ1 tail makes more extensive interactions across the kinase domain. Mutation of δ1-specific XCT phosphorylation sites increases kinase activity both in vitro and in cells and leads to changes in the circadian period, similar to what is reported in vivo. Mechanistically, loss of the phosphorylation sites in XCT disrupts tail interaction with the kinase domain. δ1 autoinhibition relies on conserved anion-binding sites around the CK1 active site, demonstrating a common mode of product inhibition of CK1δ. These findings demonstrate how a phosphorylation cycle controls the activity of this essential kinase. [ABSTRACT FROM AUTHOR]

Obviously, the discussion of different factors that could have contributed to the origin of life and evolution is clear speculation, since there is no way of checking the validity of most of the related hypotheses in practice, as the corresponding events not only already happened, but took place in a very distant past. However, there are a few undisputable facts that are present at the moment, such as the existence of a wide variety of living forms and the abundant presence of intrinsically disordered proteins (IDPs) or hybrid proteins containing ordered domains and intrinsically disordered regions (IDRs) in all living forms. Since it seems that the currently existing living forms originated from a common ancestor, their variety is a result of evolution. Therefore, one could ask a logical question of what role(s) the structureless and highly dynamic but vastly abundant and multifunctional IDPs/IDRs might have in evolution. This study represents an attempt to consider various ideas pertaining to the potential roles of protein intrinsic disorder in the origin of life and evolution. [ABSTRACT FROM AUTHOR]

Studies of proteins, found in one of the most stress-resistant animals tardigrade Ramazzottius varieornatus, aim to reveal molecular principles of extreme tolerance to various types of stress and developing applications based on them for medicine, biotechnology, pharmacy, and space research. Tardigrade DNA/RNA-binding damage suppressor protein (Dsup) reduces DNA damage caused by reactive oxygen spices (ROS) produced upon irradiation and oxidative stresses in Dsup-expressing transgenic organisms. This work is focused on the determination of structural features of Dsup protein and Dsup-DNA complex, which refines details of protective mechanism. For the first time, intrinsically disordered nature of Dsup protein with highly flexible structure was experimentally proven and characterized by the combination of small angle X-ray scattering (SAXS) technique, circular dichroism spectroscopy, and computational methods. Low resolution models of Dsup protein and an ensemble of conformations were presented. In addition, we have shown that Dsup forms fuzzy complex with DNA. [ABSTRACT FROM AUTHOR]

We apply methods of Artificial Intelligence and Machine Learning to protein dynamic bioinformatics. We rewrite the sequences of a large protein data set, containing both folded and intrinsically disordered molecules, using a representation developed previously, which encodes the intrinsic dynamic properties of the naturally occurring amino acids. We Fourier analyze the resulting sequences. It is demonstrated that classification models built using several different supervised learning methods are able to successfully distinguish folded from intrinsically disordered proteins from sequence alone. It is further shown that the most important sequence property for this discrimination is the sequence mobility, which is the sequence averaged value of the residue‐specific average alpha carbon B factor. This is in agreement with previous work, in which we have demonstrated the central role played by the sequence mobility in protein dynamic bioinformatics and biophysics. This finding opens a path to the application of dynamic bioinformatics, in combination with machine learning algorithms, to a range of significant biomedical problems. [ABSTRACT FROM AUTHOR]

Structures at serine‐proline sites in proteins were analyzed using a combination of peptide synthesis with structural methods and bioinformatics analysis of the PDB. Dipeptides were synthesized with the proline derivative (2S,4S)‐(4‐iodophenyl)hydroxyproline [hyp(4‐I‐Ph)]. The crystal structure of Boc‐Ser‐hyp(4‐I‐Ph)‐OMe had two molecules in the unit cell. One molecule exhibited cis‐proline and a type VIa2 β‐turn (BcisD). The cis‐proline conformation was stabilized by a C–H/O interaction between Pro C–Hα and the Ser side‐chain oxygen. NMR data were consistent with stabilization of cis‐proline by a C–H/O interaction in solution. The other crystallographically observed molecule had trans‐Pro and both residues in the PPII conformation. Two conformations were observed in the crystal structure of Ac‐Ser‐hyp(4‐I‐Ph)‐OMe, with Ser adopting PPII in one and the β conformation in the other, each with Pro in the δ conformation and trans‐Pro. Structures at Ser‐Pro sequences were further examined via bioinformatics analysis of the PDB and via DFT calculations. Ser‐Pro versus Ala–Pro sequences were compared to identify bases for Ser stabilization of local structures. C–H/O interactions between the Ser side‐chain Oγ and Pro C–Hα were observed in 45% of structures with Ser‐cis‐Pro in the PDB, with nearly all Ser‐cis‐Pro structures adopting a type VI β‐turn. 53% of Ser‐trans‐Pro sequences exhibited main‐chain COi•••HNi+3 or COi•••HNi+4 hydrogen bonds, with Ser as the i residue and Pro as the i + 1 residue. These structures were overwhelmingly either type I β‐turns or N‐terminal capping motifs on α‐helices or 310‐helices. These results indicate that Ser‐Pro sequences are particularly potent in favoring these structures. In each, Ser is in either the PPII or β conformation, with the Ser Oγ capable of engaging in a hydrogen bond with the amide N–H of the i + 2 (type I β‐turn or 310‐helix; Ser χ1t) or i + 3 (α‐helix; Ser χ1g+) residue. Non‐proline cis amide bonds can also be stabilized by C–H/O interactions. [ABSTRACT FROM AUTHOR]

The coacervation of alpha‐synuclein (αSyn) into cytotoxic oligomers and amyloid fibrils are considered pathological hallmarks of Parkinson's disease. While aggregation is central to amyloid diseases, liquid–liquid phase separation (LLPS) and its interplay with aggregation have gained increasing interest. Previous work shows that factors promoting or inhibiting aggregation have similar effects on LLPS. This study provides a detailed scanning of a wide range of parameters, including protein, salt and crowding concentrations at multiple pH values, revealing different salt dependencies of aggregation and LLPS. The influence of salt on aggregation under crowding conditions follows a non‐monotonic pattern, showing increased effects at medium salt concentrations. This behavior can be elucidated through a combination of electrostatic screening and salting‐out effects on the intramolecular interactions between the N‐terminal and C‐terminal regions of αSyn. By contrast, this study finds a monotonic salt dependence of LLPS due to intermolecular interactions. Furthermore, it observes time evolution of the two distinct assembly states, with macroscopic fibrillar‐like bundles initially forming at medium salt concentration but subsequently converting into droplets after prolonged incubation. The droplet state is therefore capable of inhibiting aggregation or even dissolving aggregates through heterotypic interactions, thus preventing αSyn from its dynamically arrested state. [ABSTRACT FROM AUTHOR]

Circular dichroism (CD) spectroscopy is an analytical technique that measures the wavelength-dependent differential absorbance of circularly polarized light and is applicable to most biologically important macromolecules, such as proteins, nucleic acids, and carbohydrates. It serves to characterize the secondary structure composition of proteins, including intrinsically disordered proteins, by analyzing their recorded spectra. Several computational tools have been developed to interpret protein CD spectra. These methods have been calibrated and tested mostly on globular proteins with well-defined structures, mainly due to the lack of reliable reference structures for disordered proteins. It is therefore still largely unclear how accurately these computational methods can determine the secondary structure composition of disordered proteins. Here, we provide such a required reference data set consisting of model structural ensembles and matching CD spectra for eight intrinsically disordered proteins. Using this set of data, we have assessed the accuracy of several published CD prediction and secondary structure estimation tools, including our own CD analysis package, SESCA. Our results show that for most of the tested methods, their accuracy for disordered proteins is generally lower than for globular proteins. In contrast, SESCA, which was developed using globular reference proteins, but was designed to be applicable to disordered proteins as well, performs similarly well for both classes of proteins. The new reference data set for disordered proteins should allow for further improvement of all published methods. [ABSTRACT FROM AUTHOR]

SUMMARY: The Local Disordered Region Sampling (LDRS, pronounced loaders) tool is a new module developed for IDPConformerGenerator, a previously validated approach to model intrinsically disordered proteins (IDPs). The IDPConformerGenerator LDRS module provides a method for generating all-atom conformations of intrinsically disordered protein regions at N- and C-termini of and in loops or linkers between folded regions of an existing protein structure. These disordered elements often lead to missing coordinates in experimental structures or low confidence in predicted structures. Requiring only a pre-existing PDB or mmCIF formatted structural template of the protein with missing coordinates or with predicted confidence scores and its full-length primary sequence, LDRS will automatically generate physically meaningful conformational ensembles of the missing flexible regions to complete the full-length protein. The capabilities of the LDRS tool of IDPConformerGenerator include modeling phosphorylation sites using enhanced Monte Carlo-Side Chain Entropy, transmembrane proteins within an all-atom bilayer, and multi-chain complexes. The modeling capacity of LDRS capitalizes on the modularity, the ability to be used as a library and via command-line, and the computational speed of the IDPConformerGenerator platform. AVAILABILITY AND IMPLEMENTATION: The LDRS module is part of the IDPConformerGenerator modeling suite, which can be downloaded from GitHub at https://github.com/julie-forman-kay-lab/IDPConformerGenerator. IDPConformerGenerator is written in Python3 and works on Linux, Microsoft Windows, and Mac OS versions that support DSSP. Users can utilize LDRSs Python API for scripting the same way they can use any part of IDPConformerGenerators API, by importing functions from the idpconfgen.ldrs_helper library. Otherwise, LDRS can be used as a command line interface application within IDPConformerGenerator. Full documentation is available within the command-line interface as well as on IDPConformerGenerators official documentation pages (https://idpconformergenerator.readthedocs.io/en/latest/).

Abstract Studies of proteins, found in one of the most stress-resistant animals tardigrade Ramazzottius varieornatus, aim to reveal molecular principles of extreme tolerance to various types of stress and developing applications based on them for medicine, biotechnology, pharmacy, and space research. Tardigrade DNA/RNA-binding damage suppressor protein (Dsup) reduces DNA damage caused by reactive oxygen spices (ROS) produced upon irradiation and oxidative stresses in Dsup-expressing transgenic organisms. This work is focused on the determination of structural features of Dsup protein and Dsup-DNA complex, which refines details of protective mechanism. For the first time, intrinsically disordered nature of Dsup protein with highly flexible structure was experimentally proven and characterized by the combination of small angle X-ray scattering (SAXS) technique, circular dichroism spectroscopy, and computational methods. Low resolution models of Dsup protein and an ensemble of conformations were presented. In addition, we have shown that Dsup forms fuzzy complex with DNA.

Aggregated and hyperphosphorylated Tau is one of the pathological hallmarks of Alzheimer's disease. Tau is a polyampholytic and intrinsically disordered protein (IDP). In this paper, we present for the first time experimental results on the ionic strength dependence of the radius of gyration (Rg) of human Tau 4RS and 4RL isoforms. Synchrotron X-ray scattering revealed that 4RS Rg is regulated from 65.4 to 58.5 Å and 4RL Rg is regulated from 70.9 to 57.9 Å by varying ionic strength from 0.01 to 0.592 M. The Rg of 4RL Tau is larger than 4RS at lower ionic strength. This result provides an insight into the ion-responsive nature of intrinsically disordered and polyampholytic Tau, and can be implicated to the further study of Tau-Tau and Tau-tubulin intermolecular structure in ionic environments.

Reflectin is a cationic, block copolymeric protein that mediates the dynamic fine-tuning of color and brightness of light reflected from nanostructured Bragg reflectors in iridocyte skin cells of squids. In vivo, the neuronally activated phosphorylation of reflectin triggers its assembly, driving osmotic dehydration of the membrane-bounded Bragg lamellae containing the protein to simultaneously shrink the lamellar thickness and spacing while increasing their refractive index contrast, thus tuning the wavelength and increasing the brightness of reflectance. In vitro, we show that the reduction in repulsive net charge of the purified, recombinant reflectin—either (for the first time) by generalized anionic screening with salt or by pH titration—drives a finely tuned, precisely calibrated increase in the size of the resulting multimeric assemblies. The calculated effects of phosphorylation in vivo are consistent with these effects observed in vitro. The precise proportionality between the assembly size and charge neutralization is enabled by the demonstrated rapid dynamic arrest of multimer growth by a continual, equilibrium tuning of the balance between the protein's Coulombic repulsion and short-range interactive forces. The resulting stability of reflectin assemblies with time ensures a reciprocally precise control of the particle number concentration, encoding a precise calibration between the extent of neuronal signaling, osmotic pressure, and the resulting optical changes. The charge regulation of reflectin assembly precisely fine-tunes a colligative property-based nanostructured biological machine. A physical mechanism is proposed. [ABSTRACT FROM AUTHOR]

Actin is present in the cytoplasm and nucleus of every eukaryotic cell. In the cytoplasm, framework and motor functions of actin are associated with its ability to polymerize to form F-actin. In the nucleus, globular actin plays a significant functional role. For a globular protein, actin has a uniquely large number of proteins with which it interacts. Bioinformatics analysis of the actin interactome showed that only a part of actin-binding proteins are both cytoplasmic and nuclear. There are proteins that interact only with cytoplasmic, or only with nuclear actin. The first pool includes proteins associated with the formation, regulation, and functioning of the actin cytoskeleton predominate, while nuclear actin-binding proteins are involved in the majority of key nuclear processes, from regulation of transcription to DNA damage response. Bioinformatics analysis of the structure of actin-binding proteins showed that these are mainly intrinsically disordered proteins, many of which are part of membrane-less organelles. Interestingly, although the number of intrinsically disordered actin-binding proteins in the nucleus is greater than in the cytoplasm, the drivers for the formation of the membrane-less organelles in the cytoplasm are significantly (four times) greater than in the nucleus. [ABSTRACT FROM AUTHOR]

The formation of amyloid fibrils is a common feature of many protein systems. It has implications in both health, as amyloid fibrils are implicated in over 30 degenerative diseases, and in the biological functions of proteins. Surfaces have long been known to affect the formation of fibrils but the specific effect depends on the details of both the surface and protein. Fully understanding the role of surfaces in fibrillization requires microscopic information on protein conformation on surfaces. In this paper replica exchange molecular dynamics simulation is used to investigate the model fibril forming protein, A β (10–40) (a 31-residue segment of the amyloid-beta protein) on surfaces of different hydrophobicity. Similar to other proteins A β (10–40) is found to adsorb strongly onto hydrophobic surfaces. It also adopts significantly different sets of conformations on hydrophobic and polar surfaces, as well as in bulk solution. On hydrophobic surfaces, it adopts partially helical structures, with the helices overlapping with beta-strand regions in the mature fibril. These may be helical intermediates on the fibril formation pathway, suggesting a mechanism for the enhanced fibril formation seen on hydrophobic surfaces. [ABSTRACT FROM AUTHOR]

In eukaryotes, pre‐mRNA splicing is vital for RNA processing and orchestrated by the spliceosome, whose assembly starts with the interaction between U1‐70K and SR proteins. Despite the significance of the U1‐70K/SR interaction, the dynamic nature of the complex and the challenges in obtaining soluble U1‐70K have impeded a comprehensive understanding of the interaction at the structural level for decades. We overcome the U1‐70K solubility issues, enabling us to characterize the interaction between U1‐70K and SRSF1, a representative SR protein. We unveil specific interactions: phosphorylated SRSF1 RS with U1‐70K BAD1, and SRSF1 RRM1 with U1‐70K RRM. The RS/BAD1 interaction plays a dominant role, whereas the interaction between the RRM domains further enhances the stability of the U1‐70K/SRSF1 complex. The RRM interaction involves the C‐terminal extension of U1‐70K RRM and the conserved acid patches on SRSF1 RRM1 that is involved in SRSF1 phase separation. Our circular dichroism spectra reveal that BAD1 adapts an α‐helical conformation and RS is intrinsically disordered. Intriguingly, BAD1 undergoes a conformation switch from α‐helix to β‐strand and random coil upon RS binding. In addition to the regulatory mechanism via SRSF1 phosphorylation, the U1‐70K/SRSF1 interaction is also regulated by U1‐70K BAD1 phosphorylation. We find that U1‐70K phosphorylation inhibits the U1‐70K and SRSF1 interaction. Our structural findings are validated through in vitro splicing assays and in‐cell saturated domain scanning using the CRISPR method, providing new insights into the intricate regulatory mechanisms of pre‐mRNA splicing. [ABSTRACT FROM AUTHOR]

Intrinsically disordered proteins (IDPs) pose challenges to conventional experimental techniques due to their large-scale conformational fluctuations and transient structural elements. This work presents computational methods for studying IDPs at various resolutions using the Amber and Gromacs packages with both all-atom (Amber ff19SB with the OPC water model) and coarse-grained (Martini 3 and SIRAH) approaches. The effectiveness of these methodologies is demonstrated by examining the monomeric form of amyloid-β (Aβ42), an IDP, with and without disulfide bonds at different resolutions. Our results clearly show that the addition of a disulfide bond decreases the β-content of Aβ42; however, it increases the tendency of the monomeric Aβ42 to form fibril-like conformations, explaining the various aggregation rates observed in experiments. Moreover, analysis of the monomeric Aβ42 compactness, secondary structure content, and comparison between calculated and experimental chemical shifts demonstrates that all three methods provide a reasonable choice to study IDPs; however, coarse-grained approaches may lack some atomistic details, such as secondary structure recognition, due to the simplifications used. In general, this study not only explains the role of disulfide bonds in Aβ42 but also provides a step-by-step protocol for setting up, conducting, and analyzing molecular dynamics (MD) simulations, which is adaptable for studying other biomacromolecules, including folded and disordered proteins and peptides. [ABSTRACT FROM AUTHOR]

A proteomics analysis of purified rabies virus (RABV) revealed 47 entrapped host proteins within the viral particles. Out of these, 11 proteins were highly disordered. Our study was particularly focused on five of the RABV-entrapped mouse proteins with the highest levels of disorder: Neuromodulin, Chmp4b, DnaJB6, Vps37B, and Wasl. We extensively utilized bioinformatics tools, such as FuzDrop, D2P2, UniProt, RIDAO, STRING, AlphaFold, and ELM, for a comprehensive analysis of the intrinsic disorder propensity of these proteins. Our analysis suggested that these disordered host proteins might play a significant role in facilitating the rabies virus pathogenicity, immune system evasion, and the development of antiviral drug resistance. Our study highlighted the complex interaction of the virus with its host, with a focus on how the intrinsic disorder can play a crucial role in virus pathogenic processes, and suggested that these intrinsically disordered proteins (IDPs) and disorder-related host interactions can also be a potential target for therapeutic strategies. [ABSTRACT FROM AUTHOR]

We present in this article the PACSAB server, which is designed to provide information about the structural ensemble and interactions of both stable and disordered proteins to researchers in the field of molecular biology. The use of this tool does not require any computational skills as the user just needs to upload the structure of the protein to be studied; the server runs a simulation with the PACSAB model, a highly accurate coarse-grained model that is much more efficient than standard molecular dynamics for the exploration of the conformational space of multiprotein systems. The trajectories generated by the simulations based on this model reveal the propensity of the protein under study for aggregation, identify the residues playing a central role in the aggregation process, and reproduce the whole conformational space of disordered proteins. All of this information is shown and can be downloaded from the web page. [ABSTRACT FROM AUTHOR]

A high level of disorder in many viral proteins is a direct consequence of their small genomes, which makes interaction with multiple binding partners a necessity for infection and pathogenicity. A segment of the flaviviral capsid protein (C), also known as the molecular recognition feature (MoRF), undergoes a disorder-to-order transition upon binding to several protein partners. To understand their role in pathogenesis, MoRFs were identified and their occurrence across different flaviviral capsids were studied. Despite lack of sequence similarities, docking studies of Cs with the host proteins indicate conserved interactions involving MoRFs across members of phylogenetic subclades. Additionally, it was observed from the protein–protein networks that some MoRFs preferentially bind proteins that are involved in specialized functions such as ribosome biogenesis. The findings point to the importance of MoRFs in the flaviviral life cycle, with important consequences for disease progression and suppression of the host immune system. Potentially, they might have impacted the way flaviviruses evolved to infect varied hosts using multiple vectors. [ABSTRACT FROM AUTHOR]

AF9 (MLLT3) and its paralog ENL(MLLT1) are members of the YEATS family of proteins with important role in transcriptional and epigenetic regulatory complexes. These proteins are two common MLL fusion partners in MLL‐rearranged leukemias. The oncofusion proteins MLL‐AF9/ENL recruit multiple binding partners, including the histone methyltransferase DOT1L, leading to aberrant transcriptional activation and enhancing the expression of a characteristic set of genes that drive leukemogenesis. The interaction between AF9 and DOT1L is mediated by an intrinsically disordered C‐terminal ANC1 homology domain (AHD) in AF9, which undergoes folding upon binding of DOT1L and other partner proteins. We have recently reported peptidomimetics that disrupt the recruitment of DOT1L by AF9 and ENL, providing a proof‐of‐concept for targeting AHD and assessing its druggability. Intrinsically disordered proteins, such as AF9 AHD, are difficult to study and characterize experimentally on a structural level. In this study, we present a successful protein engineering strategy to facilitate structural investigation of the intrinsically disordered AF9 AHD domain in complex with peptidomimetic inhibitors by using maltose binding protein (MBP) as a crystallization chaperone connected with linkers of varying flexibility and length. The strategic incorporation of disulfide bonds provided diffraction‐quality crystals of the two disulfide‐bridged MBP–AF9 AHD fusion proteins in complex with the peptidomimetics. These successfully determined first series of 2.1–2.6 Å crystal complex structures provide high‐resolution insights into the interactions between AHD and its inhibitors, shedding light on the role of AHD in recruiting various binding partner proteins. We show that the overall complex structures closely resemble the reported NMR structure of AF9 AHD/DOT1L with notable difference in the conformation of the β‐hairpin region, stabilized through conserved hydrogen bonds network. These first series of AF9 AHD/peptidomimetics complex structures are providing insights of the protein–inhibitor interactions and will facilitate further development of novel inhibitors targeting the AF9/ENL AHD domain. [ABSTRACT FROM AUTHOR]

Membrane curvature is essential to diverse cellular functions. While classically attributed to structured domains, recent work illustrates that intrinsically disordered proteins are also potent drivers of membrane bending. Specifically, repulsive interactions among disordered domains drive convex bending, while attractive interactions drive concave bending, creating membrane-bound, liquid-like condensates. How might disordered domains that contain both repulsive and attractive domains affect curvature? Here, we examined chimeras that combined attractive and repulsive interactions. When the attractive domain was closer to the membrane, its condensation amplified steric pressure among repulsive domains, leading to convex curvature. In contrast, when the repulsive domain was closer to the membrane, attractive interactions dominated, resulting in concave curvature. Further, a transition from convex to concave curvature occurred with increasing ionic strength, which reduced repulsion while enhancing condensation. In agreement with a simple mechanical model, these results illustrate a set of design rules for membrane bending by disordered proteins.

Abstract Proteins with intrinsically disordered regions (IDRs) often undergo phase separation to control their functions spatiotemporally. Changing the pH alters the protonation levels of charged sidechains, which in turn affects the attractive or repulsive force for phase separation. In a cell, the rupture of membrane‐bound compartments, such as lysosomes, creates an abrupt change in pH. However, how proteins’ phase separation reacts to different pH environments remains largely unexplored. Here, using extensive mutagenesis, NMR spectroscopy, and biophysical techniques, it is shown that the assembly of galectin‐3, a widely studied lysosomal damage marker, is driven by cation‐π interactions between positively charged residues in its folded domain with aromatic residues in the IDR in addition to π–π interaction between IDRs. It is also found that the sole two negatively charged residues in its IDR sense pH changes for tuning the condensation tendency. Also, these two residues may prevent this prion‐like IDR domain from forming rapid and extensive aggregates. These results demonstrate how cation‐π, π–π, and electrostatic interactions can regulate protein condensation between disordered and structured domains and highlight the importance of sparse negatively charged residues in prion‐like IDRs.

How the sequences of intrinsically disordered proteins (IDPs) code for functions is still an enigma. Dynamics, in particular residue-specific dynamics, holds crucial clues. Enormous efforts have been spent to characterize residue-specific dynamics of IDPs, mainly through NMR spin relaxation experiments. Here, we present a sequence-based method, SeqDYN, for predicting residue-specific backbone dynamics of IDPs. SeqDYN employs a mathematical model with 21 parameters: one is a correlation length and 20 are the contributions of the amino acids to slow dynamics. Training on a set of 45 IDPs reveals aromatic, Arg, and long-branched aliphatic amino acids as the most active in slow dynamics whereas Gly and short polar amino acids as the least active. SeqDYN predictions not only provide an accurate and insightful characterization of sequence-dependent IDP dynamics but may also serve as indicators in a host of biophysical processes, including the propensities of IDP sequences to undergo phase separation.

Abstract The coacervation of alpha‐synuclein (αSyn) into cytotoxic oligomers and amyloid fibrils are considered pathological hallmarks of Parkinson's disease. While aggregation is central to amyloid diseases, liquid–liquid phase separation (LLPS) and its interplay with aggregation have gained increasing interest. Previous work shows that factors promoting or inhibiting aggregation have similar effects on LLPS. This study provides a detailed scanning of a wide range of parameters, including protein, salt and crowding concentrations at multiple pH values, revealing different salt dependencies of aggregation and LLPS. The influence of salt on aggregation under crowding conditions follows a non‐monotonic pattern, showing increased effects at medium salt concentrations. This behavior can be elucidated through a combination of electrostatic screening and salting‐out effects on the intramolecular interactions between the N‐terminal and C‐terminal regions of αSyn. By contrast, this study finds a monotonic salt dependence of LLPS due to intermolecular interactions. Furthermore, it observes time evolution of the two distinct assembly states, with macroscopic fibrillar‐like bundles initially forming at medium salt concentration but subsequently converting into droplets after prolonged incubation. The droplet state is therefore capable of inhibiting aggregation or even dissolving aggregates through heterotypic interactions, thus preventing αSyn from its dynamically arrested state.

Intrinsically disordered protein regions (IDRs) make up over 30% of the human proteome and exist in a dynamic conformational ensemble instead of a native, well-folded structure. Tethering IDRs to a surface (for example, the surface of a well-folded region of the same protein) can reduce the number of accessible conformations in these ensembles. This reduces the ensemble's conformational entropy, generating an effective entropic force that pulls away from the point of tethering. Recent experimental work has shown that this entropic force causes measurable, physiologically relevant changes to protein function. But how the magnitude of this force depends on IDR sequence remains unexplored. Here, we use all-atom simulations to analyze how structural preferences in IDR ensembles contribute to the entropic force they exert upon tethering. We show that sequence-encoded structural preferences play an important role in determining the magnitude of this force: compact, spherical ensembles generate an entropic force that can be several times higher than more extended ensembles. We further show that changes in the surrounding solution's chemistry can modulate the IDR entropic force strength. We propose that the entropic force is a sequence-dependent, environmentally tunable property of terminal IDR sequences.

The structural characterization of proteins with a disorder requires a computational approach backed by experiments to model their diverse and dynamic structural ensembles. The selection of conformational ensembles consistent with solution experiments of disordered proteins highly depends on the initial pool of conformers, with currently available tools limited by conformational sampling. We have developed a Generative Recurrent Neural Network (GRNN) that uses supervised learning to bias the probability distributions of torsions to take advantage of experimental data types such as nuclear magnetic resonance J-couplings, nuclear Overhauser effects, and paramagnetic resonance enhancements. We show that updating the generative model parameters according to the reward feedback on the basis of the agreement between experimental data and probabilistic selection of torsions from learned distributions provides an alternative to existing approaches that simply reweight conformers of a static structural pool for disordered proteins. Instead, the biased GRNN, DynamICE, learns to physically change the conformations of the underlying pool of the disordered protein to those that better agree with experiments.

Toxoplasma gondii oocysts, which are shed in large quantities in the feces from infected felines, are very stable in the environment, resistant to most inactivation procedures, and highly infectious. The oocyst wall provides an important physical barrier for sporozoites contained inside oocysts, protecting them from many chemical and physical stressors, including most inactivation procedures. Furthermore, sporozoites can withstand large temperature changes, even freeze-thawing, as well as desiccation, high salinity, and other environmental insults; however, the genetic basis for this environmental resistance is unknown. Here, we show that a cluster of four genes encoding Late Embryogenesis Abundant (LEA)-related proteins are required to provide Toxoplasma sporozoites resistance to environmental stresses. Toxoplasma LEA-like genes (TgLEAs) exhibit the characteristic features of intrinsically disordered proteins, explaining some of their properties. Our in vitro biochemical experiments using recombinant TgLEA proteins show that they have cryoprotective effects on the oocyst-resident lactate dehydrogenase enzyme and that induced expression in E. coli of two of them leads to better survival after cold stress. Oocysts from a strain in which the four LEA genes were knocked out en bloc were significantly more susceptible to high salinity, freezing, and desiccation compared to wild-type oocysts. We discuss the evolutionary acquisition of LEA-like genes in Toxoplasma and other oocyst-producing apicomplexan parasites of the Sarcocystidae family and discuss how this has likely contributed to the ability of sporozoites within oocysts to survive outside the host for extended periods. Collectively, our data provide a first molecular detailed view on a mechanism that contributes to the remarkable resilience of oocysts against environmental stresses. IMPORTANCE Toxoplasma gondii oocysts are highly infectious and may survive in the environment for years. Their resistance against disinfectants and irradiation has been attributed to the oocyst and sporocyst walls by acting as physical and permeability barriers. However, the genetic basis for their resistance against stressors like changes in temperature, salinity, or humidity, is unknown. We show that a cluster of four genes encoding Toxoplasma Late Embryogenesis Abundant (TgLEA)-related proteins are important for this resistance to environmental stresses. TgLEAs have features of intrinsically disordered proteins, explaining some of their properties. Recombinant TgLEA proteins show cryoprotective effects on the parasite's lactate dehydrogenase, an abundant enzyme in oocysts, and expression in E. coli of two TgLEAs has a beneficial effect on growth after cold stress. Moreover, oocysts from a strain lacking all four TgLEA genes were more susceptible to high salinity, freezing, and desiccation compared to wild-type oocysts, highlighting the importance of the four TgLEAs for oocyst resilience.

The nuclear pore complex (NPC) is a critical gateway regulating molecular transport between the nucleus and cytoplasm. It allows small molecules to pass freely, while larger molecules require nuclear transport receptors to traverse the barrier. This selective permeability is maintained by phenylalanine-glycine-rich nucleoporins (FG-Nups), intrinsically disordered proteins that fill the NPC’s central channel. The disordered and flexible nature of FG-Nups complicates their spatial characterization with conventional structural biology techniques. To address this challenge, polymer physics offers a valuable framework for describing FG-Nup behavior, reducing their complex structures to a few key parameters. In this review, we explore how polymer physics models FG-Nups using these parameters and discuss experimental efforts to quantify them in various contexts, providing insights into the conformational properties of FG-Nups.

Network Hamiltonian models (NHMs) are a framework for topological coarse-graining of protein-protein interactions, in which each node corresponds to a protein, and edges are drawn between nodes representing proteins that are noncovalently bound. Here, this framework is applied to aggregates of γD-crystallin, a structural protein of the eye lens implicated in cataract disease. The NHMs in this study are generated from atomistic simulations of equilibrium distributions of wild-type and the cataract-causing variant W42R in solution, performed by Wong, E. K.; Prytkova, V.; Freites, J. A.; Butts, C. T.; Tobias, D. J. Molecular Mechanism of Aggregation of the Cataract-Related γD-Crystallin W42R Variant from Multiscale Atomistic Simulations. Biochemistry2019, 58 (35), 3691-3699. Network models are shown to successfully reproduce the aggregate size and structure observed in the atomistic simulation, and provide information about the transient protein-protein interactions therein. The system size is scaled from the original 375 monomers to a system of 10000 monomers, revealing a lowering of the upper tail of the aggregate size distribution of the W42R variant. Extrapolation to higher and lower concentrations is also performed. These results provide an example of the utility of NHMs for coarse-grained simulation of protein systems, as well as their ability to scale to large system sizes and high concentrations, reducing computational costs while retaining topological information about the system.

Advances in quantitative biophysical techniques have allowed researchers to probe deeply into the mechanisms behind complex membrane remodeling phenomena. Despite their lack of structure, intrinsically disordered proteins have become widely recognized for their various biophysical functions over the past several years. These functions include membrane curvature sensing and membrane bending. The combination of nanofabricated substrates and live-cell systems has created a new avenue for biomimetic research that will vastly expand our ability to study protein interactions with curved membranes. Biological membranes are integral cellular structures that can be curved into various geometries. These curved structures are abundant in cells as they are essential for various physiological processes. However, curved membranes are inherently unstable, especially on nanometer length scales. To stabilize curved membranes, cells can utilize proteins that sense and generate membrane curvature. In this review, we summarize recent research that has advanced our understanding of interactions between proteins and curved membrane surfaces, as well as work that has expanded our ability to study curvature sensing and generation. Additionally, we look at specific examples of cellular processes that require membrane curvature, such as neurotransmission, clathrin-mediated endocytosis (CME), and organelle biogenesis. [ABSTRACT FROM AUTHOR]

Biomolecular phase separation is a vital mechanism for orchestrating biomolecules within living cells. This crucial role has spurred an intense pursuit to comprehend the molecular underpinnings governing and regulating these processes. Computational methodologies offer a unique perspective, augmenting experimental techniques by providing detailed information that cannot be obtained otherwise. In this review, we briefly overview the theoretical and computational approaches to investigate biomolecular phase separation. As a short primer, we explain the factors driving and affecting phase separation of biomolecules, and then we delve into analytical and simulation methods used to study phase separation. We explain how analytical methods like the Flory–Huggins theory, random phase approximation, and graph‐based methods have been used to study phase behaviors of various proteins. We also discuss principles and applications of all‐atom simulations, coarse‐grained simulations, and field‐theoretical approaches. Additionally, we explore the recent advances in machine learning approach to predict phase separation of biomolecules. [ABSTRACT FROM AUTHOR]

For years, proteasomal degradation was predominantly attributed to the ubiquitin-26S proteasome pathway. However, it is now evident that the core 20S proteasome can independently target proteins for degradation. With approximately half of the cellular proteasomes comprising free 20S complexes, this degradation mechanism is not rare. Identifying 20S-specific substrates is challenging due to the dual-targeting of some proteins to either 20S or 26S proteasomes and the non-specificity of proteasome inhibitors. Consequently, knowledge of 20S proteasome substrates relies on limited hypothesis-driven studies. To comprehensively explore 20S proteasome substrates, we employed advanced mass spectrometry, along with biochemical and cellular analyses. This systematic approach revealed hundreds of 20S proteasome substrates, including proteins undergoing specific N- or C-terminal cleavage, possibly for regulation. Notably, these substrates were enriched in RNA- and DNA-binding proteins with intrinsically disordered regions, often found in the nucleus and stress granules. Under cellular stress, we observed reduced proteolytic activity in oxidized proteasomes, with oxidized protein substrates exhibiting higher structural disorder compared to unmodified proteins. Overall, our study illuminates the nature of 20S substrates, offering crucial insights into 20S proteasome biology. Synopsis: A systematic investigation of the repertoire of protein substrates degraded by the 20S proteasome under basal and oxidized conditions reveals hundreds of substrates and differential functionality of naïve and oxidized 20S proteasome complexes. 20S proteasome substrates are primarily RNA- and DNA-binding proteins with intrinsically disordered regions. The 20S proteasome not only fully degrades substrates but also cleaves proteins at their N- and C-termini, indicating regulatory actions. Oxidized proteasomes show lower proteolytic activity in comparison to naïve proteasomes. Oxidized protein substrates display higher structural disorder than naïve substrates. A systematic investigation of the repertoire of protein substrates degraded by the 20S proteasome under basal and oxidized conditions reveals hundreds of substrates and differential functionality of naïve and oxidized 20S proteasome complexes. [ABSTRACT FROM AUTHOR]

The power of structural information for informing biological mechanisms is clear for stable folded macromolecules, but similar structure-function insight is more difficult to obtain for highly dynamic systems such as intrinsically disordered proteins (IDPs) which must be described as structural ensembles. Here, we present IDPConformerGenerator, a flexible, modular open-source software platform for generating large and diverse ensembles of disordered protein states that builds conformers that obey geometric, steric, and other physical restraints on the input sequence. IDPConformerGenerator samples backbone phi (φ), psi (ψ), and omega (ω) torsion angles of relevant sequence fragments from loops and secondary structure elements extracted from folded protein structures in the RCSB Protein Data Bank and builds side chains from robust Monte Carlo algorithms using expanded rotamer libraries. IDPConformerGenerator has many user-defined options enabling variable fractional sampling of secondary structures, supports Bayesian models for assessing the agreement of IDP ensembles for consistency with experimental data, and introduces a machine learning approach to transform between internal and Cartesian coordinates with reduced error. IDPConformerGenerator will facilitate the characterization of disordered proteins to ultimately provide structural insights into these states that have key biological functions.

Abstract For years, proteasomal degradation was predominantly attributed to the ubiquitin-26S proteasome pathway. However, it is now evident that the core 20S proteasome can independently target proteins for degradation. With approximately half of the cellular proteasomes comprising free 20S complexes, this degradation mechanism is not rare. Identifying 20S-specific substrates is challenging due to the dual-targeting of some proteins to either 20S or 26S proteasomes and the non-specificity of proteasome inhibitors. Consequently, knowledge of 20S proteasome substrates relies on limited hypothesis-driven studies. To comprehensively explore 20S proteasome substrates, we employed advanced mass spectrometry, along with biochemical and cellular analyses. This systematic approach revealed hundreds of 20S proteasome substrates, including proteins undergoing specific N- or C-terminal cleavage, possibly for regulation. Notably, these substrates were enriched in RNA- and DNA-binding proteins with intrinsically disordered regions, often found in the nucleus and stress granules. Under cellular stress, we observed reduced proteolytic activity in oxidized proteasomes, with oxidized protein substrates exhibiting higher structural disorder compared to unmodified proteins. Overall, our study illuminates the nature of 20S substrates, offering crucial insights into 20S proteasome biology.

Obviously, the discussion of different factors that could have contributed to the origin of life and evolution is clear speculation, since there is no way of checking the validity of most of the related hypotheses in practice, as the corresponding events not only already happened, but took place in a very distant past. However, there are a few undisputable facts that are present at the moment, such as the existence of a wide variety of living forms and the abundant presence of intrinsically disordered proteins (IDPs) or hybrid proteins containing ordered domains and intrinsically disordered regions (IDRs) in all living forms. Since it seems that the currently existing living forms originated from a common ancestor, their variety is a result of evolution. Therefore, one could ask a logical question of what role(s) the structureless and highly dynamic but vastly abundant and multifunctional IDPs/IDRs might have in evolution. This study represents an attempt to consider various ideas pertaining to the potential roles of protein intrinsic disorder in the origin of life and evolution.

It became clear more than 20 years ago that the nucleolus not only performs the most important biological function of assembling ribonucleic particles but is also a key controller of many cellular processes, participating in cellular adaptation to stress. The nucleolus’s multifunctionality is due to the peculiarities of its biogenesis. The nucleolus is a multilayered biomolecular condensate formed by liquid–liquid phase separation (LLPS). In this review, we focus on changes occurring in the nucleolus during cellular stress, molecular features of the nucleolar response to abnormal and stressful conditions, and the role of long non-coding RNAs transcribed from the intergenic spacer region of ribosomal DNA (IGS rDNA).

Intrinsically disordered proteins (IDPs) fold upon binding to select/recruit multiple partners, morph around the partner's structure, and exhibit allostery. However, we do not know whether these properties emerge passively from disorder, or rather are encoded into the IDP's folding mechanisms. A main reason for this gap is the lack of suitable methods to dissect the energetics of IDP conformational landscapes without partners. Here we introduce such an approach that we term molecular LEGO, and apply it to NCBD, a helical, molten globule–like IDP, as proof of concept. The approach entails the experimental and computational characterization of the protein, its separate secondary structure elements (LEGO building blocks), and their supersecondary combinations. Comparative analysis uncovers specific, yet inconspicuous, energetic biases in the conformational/folding landscape of NCBD, including 1) strong local signals that define the three native helices, 2) stabilization of helix–helix interfaces via soft pairwise tertiary interactions, 3) cooperative stabilization of a heterogeneous three-helix bundle fold, and 4) a dynamic exchange between sets of tertiary interactions (native and nonnative) that recapitulate the different structures NCBD adopts in complex with various partners. Crucially, a tug of war between sets of interactions makes NCBD gradually shift between structural subensembles as a conformational rheostat. Such conformational rheostatic behavior provides a built-in mechanism to modulate binding and switch/recruit partners that is likely at the core of NCBD's function as transcriptional coactivator. Hence, the molecular LEGO approach emerges as a powerful tool to dissect the conformational landscapes of unbound IDPs and rationalize their functional mechanisms.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]