Intrinsically disordered proteins and intrinsically disordered protein regions

Regulation and function of endoplasmic reticulum autophagy in neurodegenerative diseases

The endoplasmic reticulum, a key cellular organelle, regulates a wide variety of cellular activities. Endoplasmic reticulum autophagy, one of the quality control systems of the endoplasmic reticulum, plays a pivotal role in maintaining endoplasmic reticulum homeostasis by controlling endoplasmic reticulum turnover, remodeling, and proteostasis. In this review, we briefly describe the endoplasmic reticulum quality control system, and subsequently focus on the role of endoplasmic reticulum autophagy, emphasizing the spatial and temporal mechanisms underlying the regulation of endoplasmic reticulum autophagy according to cellular requirements. We also summarize the evidence relating to how defective or abnormal endoplasmic reticulum autophagy contributes to the pathogenesis of neurodegenerative diseases. In summary, this review highlights the mechanisms associated with the regulation of endoplasmic reticulum autophagy and how they influence the pathophysiology of degenerative nerve disorders. This review would help researchers to understand the roles and regulatory mechanisms of endoplasmic reticulum-phagy in neurodegenerative disorders.

Enhancing prediction of short linear protein motifs with Wregex 3.0

Short linear motifs (SLiMs) play an important role in protein-protein interactions. However, SLiM patterns are intrinsically permissive and result into many matches that occur just by chance, specially when targeting large datasets. To prioritize these matches as candidates for functional testing, we developed Wregex (Weighted regular expression), which uses a position-specific scoring matrix (PSSM) to order a list of regular expression matches according to a PSSM-derived score. Here we present Wregex 3.0, an improved version with new functionalities such as the support for a second auxiliary motif to help refining prediction of a primary SLiM, and post-translational modifications (PTMs) enrichment taking into account that many regulatory SLiM-mediated interactions are modulated by one or more PTMs. This version also incorporates a number of new features such as a convenient use of subproteomes, showing UniProt annotations such as disordered regions, searching for all known motifs and generating decoy databases for enrichment analysis. We provide case studies to illustrate how these new Wregex functionalities enhance prediction of short linear protein motifs. The Wregex 3.0 server is freely accessible at https://ehubio.ehu.eus/wregex3/.

Weighted families of contact maps to characterize conformational ensembles of (highly-)flexible proteins

MOTIVATION

Characterizing the structure of flexible proteins, particularly within the realm of intrinsic disorder, presents a formidable challenge due to their high conformational variability. Currently, their structural representation relies on (possibly large) conformational ensembles derived from a combination of experimental and computational methods. The detailed structural analysis of these ensembles is a difficult task, for which existing tools have limited effectiveness.

RESULTS

This study proposes an innovative extension of the concept of contact maps to the ensemble framework, incorporating the intrinsic probabilistic nature of disordered proteins. Within this framework, a conformational ensemble is characterized through a weighted family of contact maps. To achieve this, conformations are first described using a refined definition of contact that appropriately accounts for the geometry of the inter-residue interactions and the sequence context. Representative structural features of the ensemble naturally emerge from the subsequent clustering of the resulting contact-based descriptors. Importantly, transiently populated structural features are readily identified within large ensembles. The performance of the method is illustrated by several use cases and compared with other existing approaches, highlighting its superiority in capturing relevant structural features of highly flexible proteins.

AVAILABILITY AND IMPLEMENTATION

An open-source implementation of the method is provided together with an easy-to-use Jupyter notebook, available at https://gitlab.laas.fr/moma/WARIO.

Clr4SUV39H1 ubiquitination and non-coding RNA mediate transcriptional silencing of heterochromatin via Swi6 phase separation

Transcriptional silencing by RNAi paradoxically relies on transcription, but how the transition from transcription to silencing is achieved has remained unclear. The Cryptic Loci Regulator complex (CLRC) in Schizosaccharomyces pombe is a cullin-ring E3 ligase required for silencing that is recruited by RNAi. We found that the E2 ubiquitin conjugating enzyme Ubc4 interacts with CLRC and mono-ubiquitinates the histone H3K9 methyltransferase Clr4SUV39H1, promoting the transition from co-transcriptional gene silencing (H3K9me2) to transcriptional gene silencing (H3K9me3). Ubiquitination of Clr4 occurs in an intrinsically disordered region (Clr4IDR), which undergoes liquid droplet formation in vitro, along with Swi6HP1 the effector of transcriptional gene silencing. Our data suggests that phase separation is exquisitely sensitive to non-coding RNA (ncRNA) which promotes self-association of Clr4, chromatin association, and di-, but not tri- methylation instead. Ubc4-CLRC also targets the transcriptional co-activator Bdf2BRD4, down-regulating centromeric transcription and small RNA (sRNA) production. The deubiquitinase Ubp3 counteracts both activities.

AlphaFold-Multimer accurately captures interactions and dynamics of intrinsically disordered protein regions

Interactions mediated by intrinsically disordered protein regions (IDRs) pose formidable challenges in structural characterization. IDRs are highly versatile, capable of adopting diverse structures and engagement modes. Motivated by recent strides in protein structure prediction, we embarked on exploring the extent to which AlphaFold-Multimer can faithfully reproduce the intricacies of interactions involving IDRs. To this end, we gathered multiple datasets covering the versatile spectrum of IDR binding modes and used them to probe AlphaFold-Multimer's prediction of IDR interactions and their dynamics. Our analyses revealed that AlphaFold-Multimer is not only capable of predicting various types of bound IDR structures with high success rate, but that distinguishing true interactions from decoys, and unreliable predictions from accurate ones is achievable by appropriate use of AlphaFold-Multimer's intrinsic scores. We found that the quality of predictions drops for more heterogeneous, fuzzy interaction types, most likely due to lower interface hydrophobicity and higher coil content. Notably though, certain AlphaFold-Multimer scores, such as the Predicted Aligned Error and residue-ipTM, are highly correlated with structural heterogeneity of the bound IDR, enabling clear distinctions between predictions of fuzzy and more homogeneous binding modes. Finally, our benchmarking revealed that predictions of IDR interactions can also be successful when using full-length proteins, but not as accurate as with cognate IDRs. To facilitate identification of the cognate IDR of a given partner, we established "minD," which pinpoints potential interaction sites in a full-length protein. Our study demonstrates that AlphaFold-Multimer can correctly identify interacting IDRs and predict their mode of engagement with a given partner.

Homologous Peptide Foldamer Promotes FUS Aggregation and Triggers Cancer Cell Death

Fused in sarcoma (FUS), a multifunctional deoxyribonucleic acid (DNA)/ribonucleic acid (RNA)-binding protein, has been implicated in various cancer types, including sarcoma and leukemia. Despite its association with these diseases, there has been limited exploration of FUS as a cancer therapy target, primarily because its dynamic nature makes it difficult to target specifically. In this study, we explored a kind of β-sheet peptide foldamer, named β4-TAT, to influence FUS aggregation by targeting its RNA recognition motifs (RRM). This approach leverages the noncovalent interaction characteristics of peptide self-assembly processes. The β4 sequence, derived from the FUS RRM β-sheet, in combination with TAT, a peptide known for its nuclear targeting capability, enables β4-TAT to bind specifically to the analogous β4 sequence within FUS. Notably, β4-TAT effectively induces FUS aggregation within cells, leading to the death of cancer cells. Our work developed a novel peptide foldamer-based strategy for inducing protein aggregation, paving the way for innovative therapeutic approaches in targeting FUS-associated cancers.

iDLB-Pred: identification of disordered lipid binding residues in protein sequences using convolutional neural network

Proteins, nucleic acids, and lipids all interact with intrinsically disordered protein areas. Lipid-binding regions are involved in a variety of biological processes as well as a number of human illnesses. The expanding body of experimental evidence for these interactions and the dearth of techniques to anticipate them from the protein sequence serve as driving forces. Although large-scale laboratory techniques are considered to be essential for equipment for studying binding residues, they are time consuming and costly, making it challenging for researchers to predict lipid binding residues. As a result, computational techniques are being looked at as a different strategy to overcome this difficulty. To predict disordered lipid-binding residues (DLBRs), we proposed iDLB-Pred predictor utilizing benchmark dataset to compute feature through extraction techniques to identify relevant patterns and information. Various classification techniques, including deep learning methods such as Convolutional Neural Networks (CNNs), Deep Neural Networks (DNNs), Multilayer Perceptrons (MLPs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) networks, and Gated Recurrent Units (GRUs), were employed for model training. The proposed model, iDLB-Pred, was rigorously validated using metrics such as accuracy, sensitivity, specificity, and Matthew's correlation coefficient. The results demonstrate the predictor's exceptional performance, achieving accuracy rates of 81% on an independent dataset and 86% in 10-fold cross-validation.

How fingers affect folding of a thumb: Inter-subdomain cooperation in the folding of SARS-CoV-2 RdRp protein

The RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 is a critical enzyme essential for the virus's replication and transcription, making it a key therapeutic target. The RdRp protein exhibits a characteristic cupped right-hand shaped structure with two vital subdomains: the fingers and the thumb. Despite being distinct, biophysical experiments suggest that these subdomains cooperate to facilitate RNA accommodation, ensuring RdRp functionality. To investigate the structure-based mechanisms underlying the fingers-thumb interaction in both apo and RNA-bound RdRp, we constructed a coarse-grained structure-based model based on recent cryo-electron microscopy data. The simulations reveal frequent open-to-closed conformational transitions in apo RdRp, akin to a breathing-like motion. These conformational changes are regulated by the fingers-thumb association and the folding dynamics of the thumb subdomain. The thumb adopts a stable fold only when tethered by the fingers-thumb interface; when these subdomains are disconnected, the thumb transitions into an open state. A significant number of open-to-closed transition events were analyzed to generate a transition contact probability map, which highlights a few specific residues at the thumb-fingers interface, distant from the RNA accommodation sites, as essential for inducing the thumb's folding process. Given that thumb subdomain folding is critical for RNA binding and viral replication, the study proposes that these interfacial residues may function as remote regulatory switches and could be targeted for the development of allosteric drugs against SARS-CoV-2 and similar RNA viruses.

Biomolecular condensates in plant cells: Mediating and integrating environmental signals and development

In response to the spatiotemporal coordination of various biochemical reactions and membrane-encapsulated organelles, plants appear to provide another effective mechanism for cellular organization by phase separation that allows the internal compartmentalization of cells to form a variety of membrane-less organelles. Most of the research on phase separation has centralized in various non-plant systems, such as yeast and animal systems. Recent studies have shown a remarkable correlation between the formation of condensates in plant systems and the formation of condensates in these systems. Moreover, the last decade has made new advances in phase separation research in the context of plant biology. Here, we provide an overview of the physicochemical forces and molecular factors that drive liquid-liquid phase separation in plant cells and the biochemical characterization of condensates. We then explore new developments in phase separation research specific to plants, discussing examples of condensates found in green plants and detailing their role in plant growth and development. We propose that phase separation may be a conserved organizational mechanism in plant evolution to help plants respond rapidly and effectively to various environmental stresses as sessile organisms.

Molecular Mechanisms of Phase Separation and Amyloidosis of ALS/FTD-linked FUS and TDP-43

FUS and TDP-43, two RNA-binding proteins from the heterogeneous nuclear ribonucleoprotein family, have gained significant attention in the field of neurodegenerative diseases due to their association with amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). They possess folded domains for binding ATP and various nucleic acids including DNA and RNA, as well as substantial intrinsically disordered regions (IDRs) including prion-like domains (PLDs) and RG-/RGG-rich regions. They play vital roles in various cellular processes, including transcription, splicing, microRNA maturation, RNA stability and transport and DNA repair. In particular, they are key components for forming ribonucleoprotein granules and stress granules (SGs) through homotypic or heterotypic liquid-liquid phase separation (LLPS). Strikingly, liquid-like droplets formed by FUS and TDP-43 may undergo aging to transform into less dynamic assemblies such as hydrogels, inclusions, and amyloid fibrils, which are the pathological hallmarks of ALS and FTD. This review aims to synthesize and consolidate the biophysical knowledge of the sequences, structures, stability, dynamics, and inter-domain interactions of FUS and TDP-43 domains, so as to shed light on the molecular mechanisms underlying their liquid-liquid phase separation (LLPS) and amyloidosis. The review further delves into the mechanisms through which ALS-causing mutants of the well-folded hPFN1 disrupt the dynamics of LLPS of FUS prion-like domain, providing key insights into a potential mechanism for misfolding/aggregation-prone proteins to cause neurodegenerative diseases and aging by gain of functions. With better understanding of different biophysical aspects of FUS and TDP-43, the ultimate goal is to develop drugs targeting LLPS and amyloidosis, which could mediate protein homeostasis within cells and lead to new treatments for currently intractable diseases, particularly neurodegenerative diseases such as ALS, FTD and aging. However, the study of membrane-less organelles and condensates is still in its infancy and therefore the review also highlights key questions that require future investigation.

Ensembles of interconverting protein complexes with multiple interaction domains

Many critical biological processes depend on protein complexes that exist as ensembles of subcomplexes rather than a discrete complex. The subcomplexes dynamically interconvert with one another, and the ability to accurately resolve the composition of the diverse molecular species in the ensemble is crucial for understanding the contribution of each subcomplex to the overall function of the protein complex. Advances in computational programs have made it possible to predict the various molecular species in these ensembles, but experimental approaches to identify the pool of subcomplexes and associated stoichiometries are often challenging. This review highlights some experimental approaches that can be used to resolve the diverse molecular species in protein complexes that exist as ensembles of sub complexes.

CDK phosphorylation of Sfr1 downregulates Rad51 function in late-meiotic homolog invasions

Meiosis is the developmental program that generates gametes. To produce healthy gametes, meiotic recombination creates reciprocal exchanges between each pair of homologous chromosomes that facilitate faithful chromosome segregation. Using fission yeast and biochemical, genetic, and cytological approaches, we have studied the role of CDK (cyclin-dependent kinase) in the control of Swi5-Sfr1, a Rad51-recombinase auxiliary factor involved in homolog invasion during recombination. We show that Sfr1 is a CDK target, and its phosphorylation downregulates Swi5-Sfr1 function in the meiotic prophase. Expression of a phospho-mimetic sfr1-7D mutant inhibits Rad51 binding, its robust chromosome loading, and subsequently decreases interhomolog recombination. On the other hand, the non-phosphorylatable sfr1-7A mutant alters Rad51 dynamics at late prophase, and exacerbates chromatin segregation defects and Rad51 retention observed in dbl2 deletion mutants when combined with them. We propose Sfr1 phospho-inhibition as a novel cell-cycle-dependent mechanism, which ensures timely resolution of recombination intermediates and successful chromosome distribution into the gametes. Furthermore, the N-terminal disordered part of Sfr1, an evolutionarily conserved feature, serves as a regulatory platform coordinating this phospho-regulation, protein localization and stability, with several CDK sites and regulatory sequences being conserved.

Prediction and design of transcriptional repressor domains with large-scale mutational scans and deep learning

Regulatory proteins have evolved diverse repressor domains (RDs) to enable precise context-specific repression of transcription. However, our understanding of how sequence variation impacts the functional activity of RDs is limited. To address this gap, we generated a high-throughput mutational scanning dataset measuring the repressor activity of 115,000 variant sequences spanning more than 50 RDs in human cells. We identified thousands of clinical variants with loss or gain of repressor function, including TWIST1 HLH variants associated with Saethre-Chotzen syndrome and MECP2 domain variants associated with Rett syndrome. We also leveraged these data to annotate short linear interacting motifs (SLiMs) that are critical for repression in disordered RDs. Then, we designed a deep learning model called TENet ( T ranscriptional E ffector Net work) that integrates sequence, structure and biochemical representations of sequence variants to accurately predict repressor activity. We systematically tested generalization within and across domains with varying homology using the mutational scanning dataset. Finally, we employed TENet within a directed evolution sequence editing framework to tune the activity of both structured and disordered RDs and experimentally test thousands of designs. Our work highlights critical considerations for future dataset design and model training strategies to improve functional variant prioritization and precision design of synthetic regulatory proteins.

Systematic discovery of DNA-binding tandem repeat proteins

Tandem repeat proteins (TRPs) are widely distributed and bind to a wide variety of ligands. DNA-binding TRPs such as zinc finger (ZNF) and transcription activator-like effector (TALE) play important roles in biology and biotechnology. In this study, we first conducted an extensive analysis of TRPs in public databases, and found that the enormous diversity of TRPs is largely unexplored. We then focused our efforts on identifying novel TRPs possessing DNA-binding capabilities. We established a protein language model for DNA-binding protein prediction (PLM-DBPPred), and predicted a large number of DNA-binding TRPs. A subset was then selected for experimental screening, leading to the identification of 11 novel DNA-binding TRPs, with six showing sequence specificity. Notably, members of the STAR (Short TALE-like Repeat proteins) family can be programmed to target specific 9 bp DNA sequences with high affinity. Leveraging this property, we generated artificial transcription factors using reprogrammed STAR proteins and achieved targeted activation of endogenous gene sets. Furthermore, the members of novel families such as MOON (Marine Organism-Originated DNA binding protein) and pTERF (prokaryotic mTERF-like protein) exhibit unique features and distinct DNA-binding characteristics, revealing interesting biological clues. Our study expands the diversity of DNA-binding TRPs, and demonstrates that a systematic approach greatly enhances the discovery of new biological insights and tools.

Detection of Intrinsically Disordered Peptides by Biological Nanopore

Intrinsically disordered protein regions (IDPRs) are pivotal in regulation of transcription and facilitation of signal transduction. Because of their multiple conformational states of structure, characterizing the highly flexible structures of IDPRs becomes challenging. Herein, we employed the wild-type (WT) aerolysin nanopore as a real-time biosensor for identification and monitoring of long peptides containing IDPRs. This sensor successfully identified three intrinsically disordered peptides, with the lengths up to 43 amino acids, by distinguishing the unique signatures of blockade current and duration time. The analysis of the binding constant revealed that interactions between the nanopore and peptides are critical for peptide translocation, which suggests that mechanisms beyond mere volume exclusion. Furthermore, we were able to compare the conformational stabilities of various IDPRs by examining the detailed current traces of blockade events. Our approach can detect the conformational changes of IDPR in a confined nanopore space. These insights broaden the understanding of peptide structural changes. The nanopore biosensor showed the potential to study the conformations change of IDPRs, IDPRs transmembrane interactions, and protein drug discovery.

Predicting the Dynamic Interaction of Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) participate in various biological processes. Interactions involving IDPs are usually dynamic and are affected by their inherent conformation fluctuations. Comprehensive characterization of these interactions based on current techniques is challenging. Here, we present GSALIDP, a GraphSAGE-embedded LSTM network, to capture the dynamic nature of IDP-involved interactions and predict their behaviors. This framework models multiple conformations of IDP as a dynamic graph, which can effectively describe the fluctuation of its flexible conformation. The dynamic interaction between IDPs is studied, and the data sets of IDP conformations and their interactions are obtained through atomistic molecular dynamic (MD) simulations. Residues of IDP are encoded through a series of features including their frustration. GSALIDP can effectively predict the interaction sites of IDP and the contact residue pairs between IDPs. Its performance in predicting IDP interactions is on par with or even better than the conventional models in predicting the interaction of structural proteins. To the best of our knowledge, this is the first model to extend the protein interaction prediction to IDP-involved interactions.

PDFll: Predictors of Disorder and Function of Proteins from the Language of Life

The identification of intrinsically disordered proteins and their functional roles is largely dependent on the performance of computational predictors, necessitating a high standard of accuracy in these tools. In this context, we introduce a novel series of computational predictors, termed PDFll (Predictors of Disorder and Function of proteins from the Language of Life), which are designed to offer precise predictions of protein disorder and associated functional roles based on protein sequences. PDFll is developed through a two-step process. Initially, it leverages large-scale protein language models (pLMs), trained on an extensive dataset comprising billions of protein sequences. Subsequently, the embeddings derived from pLMs are integrated into streamlined, yet sophisticated, deep-learning models to generate predictions. These predictions notably surpass the performance of existing state-of-the-art predictors, particularly those that forecast disorder and function without utilizing evolutionary information.

The H1/H5 domain contributes to OsTRBF2 phase separation and gene repression during rice development

Transcription factors (TFs) tightly control plant development by regulating gene expression. The phase separation of TFs plays a vital role in gene regulation. Many plant TFs have the potential to form phase-separated protein condensates; however, little is known about which TFs are regulated by phase separation and how it affects their roles in plant development. Here, we report that the rice (Oryza sativa) single Myb TF TELOMERE REPEAT-BINDING FACTOR 2 (TRBF2) is highly expressed in fast-growing tissues at the seedling stage. TRBF2 is a transcriptional repressor that binds to the transcriptional start site of thousands of genes. Mutation of TRBF2 leads to pleiotropic developmental defects and misexpression of many genes. TRBF2 displays characteristics consistent with phase separation in vivo and forms phase-separated condensates in vitro. The H1/H5 domain of TRBF2 plays a crucial role in phase separation, chromatin targeting, and gene repression. Replacing the H1/H5 domain by a phase-separated intrinsically disordered region from Arabidopsis (Arabidopsis thaliana) AtSERRATE partially recovers the function of TRBF2 in gene repression in vitro and in transgenic plants. We also found that TRBF2 is required for trimethylation of histone H3 Lys27 (H3K27me3) deposition at specific genes and genome wide. Our findings reveal that phase separation of TRBF2 facilitates gene repression in rice development.

The Enigma of Transcriptional Activation Domains

Activation domains (ADs) of eukaryotic gene activators remain enigmatic for decades as short, extremely variable sequences which often are intrinsically disordered in structure and interact with an uncertain number of targets. The general absence of specificity increasingly complicates the utilization of the widely accepted mechanism of AD function by recruitment of coactivators. The long-standing enigma at the heart of molecular biology demands a fundamental rethinking of established concepts. Here, we review the experimental evidence supporting a novel mechanistic model of gene activation, based on ADs functioning via surfactant-like near-stochastic interactions with gene promoter nucleosomes. This new model is consistent with recent information-rich experimental data obtained using high-throughput synthetic biology and bioinformatics analysis methods, including machine learning. We clarify why the conventional biochemical principle of specificity for sequence, structures, and interactions fails to explain activation domain function. This perspective provides connections to the liquid-liquid phase separation model, signifies near-stochastic interactions as fundamental for the biochemical function, and can be generalized to other cellular functions.

StrIDR: a database of intrinsically disordered regions of proteins with experimentally resolved structures

Motivation

Intrinsically disordered regions (IDRs) of proteins exist as an ensemble of conformations, and not as a single structure. Existing databases contain extensive, experimentally derived annotations of intrinsic disorder for millions of proteins at the sequence level. However, only a tiny fraction of these IDRs are associated with an experimentally determined protein structure. Moreover, even if a structure exists, parts of the disordered regions may still be unresolved.

Results

Here we organize Structures of Intrinsically Disordered Regions (StrIDR), a database of IDRs confirmed via experimental or homology-based evidence, resolved in experimentally determined structures. The database can provide useful insights into the dynamics, folding, and interactions of IDRs. It can also facilitate computational studies on IDRs, such as those using molecular dynamics simulations and/or machine learning.

Availability

StrIDR is available at https://isblab.ncbs.res.in/stridr. The web UI allows for downloading PDB structures and SIFTS mappings of individual entries. Additionally, the entire database can be downloaded in a JSON format. The source code for creating and updating the database is available at https://github.com/isblab/stridr.

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics.

Deeper Insight of the Conformational Ensemble of Intrinsically Disordered Proteins

It is generally known that, unlike structured proteins, intrinsically disordered proteins, IDPs, exhibit various structures and conformers, the so-called conformational ensemble, CoE. This study aims to better understand the conformers that make up the IDP ensemble by decomposing the CoE into groups separated by their radius of gyration, Rg. A common approach to studying CoE for IDPs is to use low-resolution techniques, such as small-angle scattering, and combine those with computer simulations on different length scales. Herein, the well-studied antimicrobial saliva protein histatin 5 was utilized as a model peptide for an IDP; the average intensity curves were obtained from small-angle X-ray scattering; and compared with fully atomistic, explicit water, molecular dynamics simulations; then, the intensity curve was decomposed with respect to the different Rg values; and their secondary structure propensities were investigated. We foresee that this approach can provide important information on the CoE and the individual conformers within; in that case, it will serve as an additional tool for understanding the IDP structure-function relationship on a more detailed level.

The early communication stages between serine proteases and enterovirus capsids in the race for viral disintegration

Serine proteases are important environmental contributors of enterovirus biocontrol. However, the structural features of molecular interaction accounting for the susceptibility of enteroviruses to proteases remains unexplained. Here, we describe the molecular mechanisms involved in the recruitment of serine proteases to viral capsids. Among the virus types used, coxsackievirus A9 (CVA9), but not CVB5 and echovirus 11 (E11), was inactivated by Subtilisin A in a host-independent manner, while Bovine Pancreatic Trypsin (BPT) only reduced CVA9 infectivity in a host-dependent manner. Predictive interaction models of each protease with capsid protomers indicate the main targets as internal disordered protein (IDP) segments exposed either on the 5-fold vertex (DE loop VP1) or at the 5/2-fold intersection (C-terminal end VP1) of viral capsids. We further show that a functional binding protease/capsid depends on both the strength and the evolution over time of protease-VP1 complexes, and lastly on the local adaptation of proteases on surrounding viral regions. Finally, we predicted three residues on CVA9 capsid that trigger cleavage by Subtilisin A, one of which may act as a sensor residue contributing to enzyme recognition on the DE loop. Overall, this study describes an important biological mechanism involved in enteroviruses biocontrol.

Molecular Insights into Aggrephagy: Their Cellular Functions in the Context of Neurodegenerative Diseases

Protein homeostasis or proteostasis is an equilibrium of biosynthetic production, folding and transport of proteins, and their timely and efficient degradation. Proteostasis is guaranteed by a network of protein quality control systems aimed at maintaining the proteome function and avoiding accumulation of potentially cytotoxic proteins. Terminal unfolded and dysfunctional proteins can be directly turned over by the ubiquitin-proteasome system (UPS) or first amassed into aggregates prior to degradation. Aggregates can also be disposed into lysosomes by a selective type of autophagy known as aggrephagy, which relies on a set of so-called selective autophagy receptors (SARs) and adaptor proteins. Failure in eliminating aggregates, also due to defects in aggrephagy, can have devastating effects as underscored by several neurodegenerative diseases or proteinopathies, which are characterized by the accumulation of aggregates mostly formed by a specific disease-associated, aggregate-prone protein depending on the clinical pathology. Despite its medical relevance, however, the process of aggrephagy is far from being understood. Here we review the findings that have helped in assigning a possible function to specific SARs and adaptor proteins in aggrephagy in the context of proteinopathies, and also highlight the interplay between aggrephagy and the pathogenesis of proteinopathies.

Navigating the complexity of p53-DNA binding: implications for cancer therapy

Abstract

The tumor suppressor protein p53, a transcription factor playing a key role in cancer prevention, interacts with DNA as its primary means of determining cell fate in the event of DNA damage. When it becomes mutated, it opens damaged cells to the possibility of reproducing unchecked, which can lead to formation of cancerous tumors. Despite its critical role, therapies at the molecular level to restore p53 native function remain elusive, due to its complex nature. Nevertheless, considerable information has been amassed, and new means of investigating the problem have become available.

Objectives

We consider structural, biophysical, and bioinformatic insights and their implications for the role of direct and indirect readout and how they contribute to binding site recognition, particularly those of low consensus. We then pivot to consider advances in computational approaches to drug discovery.

Materials and methods

We have conducted a review of recent literature pertinent to the p53 protein.

Results

Considerable literature corroborates the idea that p53 is a complex allosteric protein that discriminates its binding sites not only via consensus sequence through direct H-bond contacts, but also a complex combination of factors involving the flexibility of the binding site. New computational methods have emerged capable of capturing such information, which can then be utilized as input to machine learning algorithms towards the goal of more intelligent and efficient de novo allosteric drug design.

Conclusions

Recent improvements in machine learning coupled with graph theory and sector analysis hold promise for advances to more intelligently design allosteric effectors that may be able to restore native p53-DNA binding activity to mutant proteins.

Clinical relevance

The ideas brought to light by this review constitute a significant advance that can be applied to ongoing biophysical studies of drugs for p53, paving the way for the continued development of new methodologies for allosteric drugs. Our discoveries hold promise to provide molecular therapeutics which restore p53 native activity, thereby offering new insights for cancer therapies.

Graphical Abstract

Structural representation of the p53 DBD (PDBID 1TUP). DNA consensus sequence is shown in gray, and the protein is shown in blue. Red beads indicate hotspot residue mutations, green beads represent DNA interacting residues, and yellow beads represent both.

The non-catalytic domains of O-GlcNAc cycling enzymes present new opportunities for function-specific control

O-GlcNAcylation is an essential protein glycosylation governed by two O-GlcNAc cycling enzymes: O-GlcNAc transferase (OGT) installs a single sugar moiety N-acetylglucosamine (GlcNAc) on protein serine and threonine residues, and O-GlcNAcase (OGA) removes them. Aberrant O-GlcNAcylation has been implicated in various diseases. However, the large repertoire of more than 1000 O-GlcNAcylated proteins and the elusive mechanisms of OGT/OGA in substrate recognition present significant challenges in targeting the dysregulated O-GlcNAcylation for therapeutic development. Recently, emerging evidence suggested that the non-catalytic domains play critical roles in regulating the functional specificity of OGT/OGA via modulating their protein interactions and substrate recognition. Here, we discuss recent studies on the structures, mechanisms, and related tools of the OGT/OGA non-catalytic domains, highlighting new opportunities for function-specific control.

In Situ ATR-FTIR Studies on the β-Sheet Formation of Native and Regenerated Bombyx mori Silk Material in Solution and Its Potential for Drug Releasing Coatings

Dynamic attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy at both solutions and coatings of a semicrystalline silk material derived from Bombyx mori was applied to monitor the β-sheet conformation, which is known to correlate with silk protein crystallinity. The secondary structure-sensitive Amide I band was analyzed. Two silk protein samples were studied: native-based silk buffer fibroin (NSF) was extracted from silk glands and regenerated silk fibroin (RSF) was extracted from degummed cocoons. Solutions of both NSF and RSF at 2 mg/mL featured low initial β-sheet contents of 5-12%, which further increased to 47-53% after 24 h. RSF and NSF solutions at 23 mg/mL also featured low initial β-sheet contents of 9-10%, which yet only slightly increased to 16-17% after 24 h. Coatings deposited from RSF solutions showed high surface integrity (Q > 99%) after rinsing in mineralized water, enabling interfacial drug delivery applications. RSF coatings were post-treated with either formic acid (FA) or pure methanol (MeOH) vapor to showcase inducibility of crystalline domains in RSF coatings. Such coatings were loaded with the model antibiotic drugs tetracycline (TCL) and streptomycin (STRP), and the sustained release of TCL was followed in contact with (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) (HEPES) buffer. RSF/TCL coatings post-treated with formic acid (FA) vapor followed by methanol (MeOH) vapor showed a significantly lower (52%) initial burst of rather hydrophobic TCL compared to untreated RSF/TCL coatings (72%), while no such significant release difference was observed for hydrophilic STRP. This was rationalized by a specific interaction between nonpolar TCL and hydrophobic crystalline RSF domains.

SP1 undergoes phase separation and activates RGS20 expression through super-enhancers to promote lung adenocarcinoma progression

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide, but the underlying molecular mechanisms remain largely unclear. The transcription factor (TF) specificity protein 1 (SP1) plays a crucial role in the development of various cancers, including LUAD. Recent studies have indicated that master TFs may form phase-separated macromolecular condensates to promote super-enhancer (SE) assembly and oncogene expression. In this study, we demonstrated that SP1 undergoes phase separation and that its zinc finger 3 in the DNA-binding domain is essential for this process. Through Cleavage Under Targets & Release Using Nuclease (CUT&RUN) using antibodies against SP1 and H3K27ac, we found a significant correlation between SP1 enrichment and SE elements, identified the regulator of the G protein signaling 20 (RGS20) gene as the most likely target regulated by SP1 through SE mechanisms, and verified this finding using different approaches. The oncogenic activity of SP1 relies on its phase separation ability and RGS20 gene activation, which can be abolished by glycogen synthase kinase J4 (GSK-J4), a demethylase inhibitor. Together, our findings provide evidence that SP1 regulates its target oncogene expression through phase separation and SE mechanisms, thereby promoting LUAD cell progression. This study also revealed an innovative target for LUAD therapies through intervening in SP1-mediated SE formation.

Intrinsically Disordered Membrane Anchors of Rheb, RhoA, and DiRas3 Small GTPases: Molecular Dynamics, Membrane Organization, and Interactions

Protein structure has been well established to play a key role in determining function; however, intrinsically disordered proteins and regions (IDPs and IDRs) defy this paradigm. IDPs and IDRs exist as an ensemble of structures rather than a stable 3D structure yet play essential roles in many cell-signaling processes. Nearly all Ras superfamily GTPases are tethered to membranes by a lipid tail at the end of a flexible IDR. The sequence of the IDR is a key determinant of membrane localization, and interaction between the IDR and the membrane has been shown to affect signaling in RAS proteins through the modulation of dynamic membrane organization. Here, we utilized atomistic molecular dynamics simulations to study the membrane interaction, conformational dynamics, and lipid sorting of three IDRs from small GTPases Rheb, RhoA, and DiRas3 in model membranes representing their physiological target membranes. We found that complementarity between the lipidated IDR sequence and target membrane lipid composition is a determinant of conformational plasticity. We also show that electrostatic interactions between anionic lipids and basic residues on IDRs are correlated with sampling of semistable conformational substates, and lack of these interactions is associated with greater conformational diversity. Finally, we show that small GTPase IDRs with a polybasic domain alter local lipid composition by segregating anionic lipids and, in some cases, excluding other lipids from their immediate vicinity in favor of anionic lipids.

High-throughput structure determination of an intrinsically disordered protein using cell-free protein crystallization

Intrinsically disordered proteins (IDPs) play a crucial role in various biological phenomena, dynamically changing their conformations in response to external environmental cues. To gain a deeper understanding of these proteins, it is essential to identify the determinants that fix their structures at the atomic level. Here, we developed a pipeline for rapid crystal structure analysis of IDP using a cell-free protein crystallization (CFPC) method. Through this approach, we successfully demonstrated the determination of the structure of an IDP to uncover the key determinants that stabilize its conformation. Specifically, we focused on the 11-residue fragment of c-Myc, which forms an α-helix through dimerization with a binding partner protein. This fragment was strategically recombined with an in-cell crystallizing protein and was expressed in a cell-free system. The resulting crystal structures of the c-Myc fragment were successfully determined at a resolution of 1.92 Å and we confirmed that they are identical to the structures of the complex with the native binding partner protein. This indicates that the environment of the scaffold crystal can fix the structure of c-Myc. Significantly, these crystals were obtained directly from a small reaction mixture (30 µL) incubated for only 72 h. Analysis of eight crystal structures derived from 22 mutants revealed two hydrophobic residues as the key determinants responsible for stabilizing the α-helical structure. These findings underscore the power of our CFPC screening method as a valuable tool for determining the structures of challenging target proteins and elucidating the essential molecular interactions that govern their stability.

Intrinsic Disorder in the Host Proteins Entrapped in Rabies Virus Particles

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.

Biomolecular condensates of Chlorocatechol 1,2-Dioxygenase as prototypes of enzymatic microreactors for the degradation of polycyclic aromatic hydrocarbons

Polycyclic aromatic hydrocarbons (PAHs) are molecules with two or more fused aromatic rings that occur naturally in the environment due to incomplete combustion of organic substances. However, the increased demand for fossil fuels in recent years has increased anthropogenic activity, contributing to the environmental concentration of PAHs. The enzyme chlorocatechol 1,2-dioxygenase from Pseudomonas putida (Pp 1,2-CCD) is responsible for the breakdown of the aromatic ring of catechol, making it a potential player in bioremediation strategies. Pp 1,2-CCD can tolerate a broader range of substrates, including halogenated compounds, than other dioxygenases. Here, we report the construction of a chimera protein able to form biomolecular condensates with potential application in bioremediation. The chimera protein was built by conjugating Pp 1,2-CCD to low complex domains (LCDs) derived from the DEAD-box protein Dhh1. We showed that the chimera could undergo liquid-liquid phase separation (LLPS), forming a protein-rich liquid droplet under different conditions (variable protein and PEG8000 concentrations and pH values), in which the protein maintained its structure and main biophysical properties. The condensates were active against 4-chlorocatechol, showing that the chimera droplets preserved the enzymatic activity of the native protein. Therefore, it constitutes a prototype of a microreactor with potential use in bioremediation.

Maintenance of R-loop structures by phosphorylated hTERT preserves genome integrity

As aberrant accumulation of RNA-DNA hybrids (R-loops) causes DNA damage and genome instability, cells express regulators of R-loop structures. Here we report that RNA-dependent RNA polymerase (RdRP) activity of human telomerase reverse transcriptase (hTERT) regulates R-loop formation. We found that the phosphorylated form of hTERT (p-hTERT) exhibits RdRP activity in nuclear speckles both in telomerase-positive cells and telomerase-negative cells with alternative lengthening of telomeres (ALT) activity. The p-hTERT did not associate with telomerase RNA component in nuclear speckles but, instead, with TERRA RNAs to resolve R-loops. Targeting of the TERT gene in ALT cells ablated RdRP activity and impaired tumour growth. Using a genome-scale CRISPR loss-of-function screen, we identified Fanconi anaemia/BRCA genes as synthetic lethal partners of hTERT RdRP. Inactivation of RdRP and Fanconi anaemia/BRCA genes caused accumulation of R-loop structures and DNA damage. These findings indicate that RdRP activity of p-hTERT guards against genome instability by removing R-loop structures.

Formation of Amyloid-Like Conformational States of β-Structured Membrane Proteins on the Example of OMPF Porin from the Yersinia pseudotuberculosis Outer Membrane

The work presents results of the in vitro and in silico study of formation of amyloid-like structures under harsh denaturing conditions by non-specific OmpF porin of Yersinia pseudotuberculosis (YpOmpF), a membrane protein with β-barrel conformation. It has been shown that in order to obtain amyloid-like porin aggregates, preliminary destabilization of its structure in a buffer solution with acidic pH at elevated temperature followed by long-term incubation at room temperature is necessary. After heating at 95°C in a solution with pH 4.5, significant conformational rearrangements are observed in the porin molecule at the level of tertiary and secondary structure of the protein, which are accompanied by the increase in the content of total β-structure and sharp decrease in the value of characteristic viscosity of the protein solution. Subsequent long-term exposure of the resulting unstable intermediate YpOmpF at room temperature leads to formation of porin aggregates of various shapes and sizes that bind thioflavin T, a specific fluorescent dye for the detection of amyloid-like protein structures. Compared to the initial protein, early intermediates of the amyloidogenic porin pathway, oligomers, have been shown to have increased toxicity to the Neuro-2aCCL-131™ mouse neuroblastoma cells. The results of computer modeling and analysis of the changes in intrinsic fluorescence during protein aggregation suggest that during formation of amyloid-like aggregates, changes in the structure of YpOmpF affect not only the areas with an internally disordered structure corresponding to the external loops of the porin, but also main framework of the molecule, which has a rigid spatial structure inherent to β-barrel.

Deciphering the dual nature of nesfatin-1: a tale of zinc ion's Janus-faced influence

BACKGROUND

Nucleobindin-2 (Nucb2) and nesfatin-1 (N1) are widely distributed hormones that regulate numerous physiological processes, from energy homeostasis to carcinogenesis. However, the role of nesfatin-2 (N2), the second product of Nucb2 proteolytic processing, remains elusive. To elucidate the relationship between the structure and function of nesfatins, we investigated the properties of chicken and human homologs of N1, as well as a fragment of Nucb2 consisting of N1 and N2 conjoined in a head-to-tail manner (N1/2).

RESULTS

Our findings indicate that Zn(II) sensing, in the case of N1, is conserved between chicken and human species. However, the data presented here reveal significant differences in the molecular features of the analyzed peptides, particularly in the presence of Zn(II). We demonstrated that Zn(II) has a Janus effect on the M30 region (a crucial anorexigenic core) of N1 and N1/2. In N1 homologs, Zn(II) binding results in the concealment of the M30 region driven by a disorder-to-order transition and adoption of the amyloid fold. In contrast, in N1/2 molecules, Zn(II) binding causes the exposure of the M30 region and its destabilization, resulting in strong exposure of the region recognized by prohormone convertases within the N1/2 molecule.

CONCLUSIONS

In conclusion, we found that Zn(II) binding is conserved between chicken and human N1. However, despite the high homology of chicken and human N1, their interaction modes with Zn(II) appear to differ. Furthermore, Zn(II) binding might be essential for regulating the function of nesfatins by spatiotemporally hindering the N1 anorexigenic M30 core and concomitantly facilitating N1 release from Nucb2.

Genetically Fusing Order-Promoting and Thermoresponsive Building Blocks to Design Hybrid Biomaterials

The unique biophysical and biochemical properties of intrinsically disordered proteins (IDPs) and their recombinant derivatives, intrinsically disordered protein polymers (IDPPs) offer opportunities for producing multistimuli-responsive materials; their sequence-encoded disorder and tendency for phase separation facilitate the development of multifunctional materials. This review highlights the strategies for enhancing the structural diversity of elastin-like polypeptides (ELPs) and resilin-like polypeptides (RLPs), and their self-assembled structures via genetic fusion to ordered motifs such as helical or beta sheet domains. In particular, this review describes approaches that harness the synergistic interplay between order-promoting and thermoresponsive building blocks to design hybrid biomaterials, resulting in well-structured, stimuli-responsive supramolecular materials ordered on the nanoscale.

Linear and Nonlinear Dielectric Response of Intrinsically Disordered Proteins

Linear and nonlinear dielectric responses of solutions of intrinsically disordered proteins (IDPs) were analyzed by combining molecular dynamics simulations with formal theories. A large increment of the linear dielectric function over that of the solvent is found and related to large dipole moments of IDPs. The nonlinear dielectric effect (NDE) of the IDP far exceeds that of the bulk electrolyte, offering a route to interrogate protein conformational and rotational statistics and dynamics. Conformational flexibility of the IDP makes the dipole moment statistics consistent with the gamma/log-normal distributions and contributes to the NDE through the dipole moment's non-Gaussian parameter. The intrinsic non-Gaussian parameter of the dipole moment combines with the protein osmotic compressibility in the nonlinear dielectric susceptibility when dipolar correlations are screened by the electrolyte. The NDE is dominated by dipolar correlations when electrolyte screening is reduced.

Hydrodynamic Radii of Intrinsically Disordered Proteins: Fast Prediction by Minimum Dissipation Approximation and Experimental Validation

The diffusion coefficients of globular and fully unfolded proteins can be predicted with high accuracy solely from their mass or chain length. However, this approach fails for intrinsically disordered proteins (IDPs) containing structural domains. We propose a rapid predictive methodology for estimating the diffusion coefficients of IDPs. The methodology uses accelerated conformational sampling based on self-avoiding random walks and includes hydrodynamic interactions between coarse-grained protein subunits, modeled using the generalized Rotne-Prager-Yamakawa approximation. To estimate the hydrodynamic radius, we rely on the minimum dissipation approximation recently introduced by Cichocki et al. Using a large set of experimentally measured hydrodynamic radii of IDPs over a wide range of chain lengths and domain contributions, we demonstrate that our predictions are more accurate than the Kirkwood approximation and phenomenological approaches. Our technique may prove to be valuable in predicting the hydrodynamic properties of both fully unstructured and multidomain disordered proteins.

In Silico Analysis of Protein-Protein Interactions of Putative Endoplasmic Reticulum Metallopeptidase 1 in Schizosaccharomyces pombe

Ermp1 is a putative metalloprotease from Schizosaccharomyces pombe and a member of the Fxna peptidases. Although their function is unknown, orthologous proteins from rats and humans have been associated with the maturation of ovarian follicles and increased ER stress. This study focuses on proposing the first prediction of PPI by comparison of the interologues between humans and yeasts, as well as the molecular docking and dynamics of the M28 domain of Ermp1 with possible target proteins. As results, 45 proteins are proposed that could interact with the metalloprotease. Most of these proteins are related to the transport of Ca2+ and the metabolism of amino acids and proteins. Docking and molecular dynamics suggest that the M28 domain of Ermp1 could hydrolyze leucine and methionine residues of Amk2, Ypt5 and Pex12. These results could support future experimental investigations of other Fxna peptidases, such as human ERMP1.

COSA-1 mediated pro-crossover complex formation promotes meiotic crossing over in C. elegans

Accurate chromosome segregation during meiosis requires the establishment of at least one crossover (CO) between each pair of homologous chromosomes. CO formation depends on a group of conserved pro-CO proteins, which colocalize at CO-designated sites during late meiotic prophase I. However, it remains unclear whether these pro-CO proteins form a functional complex and how they promote meiotic CO formation in vivo. Here, we show that COSA-1, a key component required for CO formation, interacts with other pro-CO factors, MSH-5 and ZHP-3, via its N-terminal disordered region. Point mutations that impair these interactions do not affect CO designation, but they strongly hinder the accumulation of COSA-1 at CO-designated sites and result in defective CO formation. These defects can be partially bypassed by artificially tethering an interaction-compromised COSA-1 derivate to ZHP-3. Furthermore, we revealed that the accumulation of COSA-1 into distinct foci is required to assemble functional 'recombination nodules'. These prevent early CO-designated recombination intermediates from being dismantled by the RTEL-1 helicase and protect late recombination intermediates, such as Holliday junctions, until they are resolved by CO-specific resolvases. Altogether, our findings provide insight into COSA-1 mediated pro-CO complex assembly and its contribution to CO formation.

Towards the understanding of molecular motors and its relationship with local unfolding

Molecular motors are machines essential for life since they convert chemical energy into mechanical work. However, the precise mechanism by which nucleotide binding, catalysis, or release of products is coupled to the work performed by the molecular motor is still not entirely clear. This is due, in part, to a lack of understanding of the role of force in the mechanical-structural processes involved in enzyme catalysis. From a mechanical perspective, one promising hypothesis is the Haldane-Pauling hypothesis which considers the idea that part of the enzymatic catalysis is strain-induced. It suggests that enzymes cannot be efficient catalysts if they are fully complementary to the substrates. Instead, they must exert strain on the substrate upon binding, using enzyme-substrate energy interaction (binding energy) to accelerate the reaction rate. A novel idea suggests that during catalysis, significant strain energy is built up, which is then released by a local unfolding/refolding event known as 'cracking'. Recent evidence has also shown that in catalytic reactions involving conformational changes, part of the heat released results in a center-of-mass acceleration of the enzyme, raising the possibility that the heat released by the reaction itself could affect the enzyme's integrity. Thus, it has been suggested that this released heat could promote or be linked to the cracking seen in proteins such as adenylate kinase (AK). We propose that the energy released as a consequence of ligand binding/catalysis is associated with the local unfolding/refolding events (cracking), and that this energy is capable of driving the mechanical work.

Proteolytic stability and aggregation in a key metabolic enzyme of bacteria

Proteins that are kinetically stable are thought to be less prone to both aggregation and proteolysis. We demonstrate that the classical lac system of Escherichia coli can be leveraged as a model system to study this relation. β-galactosidase (LacZ) plays a critical role in lactose metabolism and is an extremely stable protein that can persist in growing cells for multiple generations after expression has stopped. By attaching degradation tags to the LacZ protein, we find that LacZ can be transiently degraded during lac operon expression but once expression has stopped functional LacZ is protected from degradation. We reversibly destabilize its tetrameric assembly using α-complementation, and show that unassembled LacZ monomers and dimers can either be degraded or lead to formation of aggregates within cells, while the tetrameric state protects against proteolysis and aggregation. We show that the presence of aggregates is associated with cell death, and that these proteotoxic stress phenotypes can be alleviated by attaching an ssrA tag to LacZ monomers which leads to their degradation. We unify our findings using a biophysical model that enables the interplay of protein assembly, degradation, and aggregation to be studied quantitatively in vivo. This work may yield approaches to reversing and preventing protein-misfolding disease states, while elucidating the functions of proteolytic stability in constant and fluctuating environments.

Transferable deep generative modeling of intrinsically disordered protein conformations

Intrinsically disordered proteins have dynamic structures through which they play key biological roles. The elucidation of their conformational ensembles is a challenging problem requiring an integrated use of computational and experimental methods. Molecular simulations are a valuable computational strategy for constructing structural ensembles of disordered proteins but are highly resource-intensive. Recently, machine learning approaches based on deep generative models that learn from simulation data have emerged as an efficient alternative for generating structural ensembles. However, such methods currently suffer from limited transferability when modeling sequences and conformations absent in the training data. Here, we develop a novel generative model that achieves high levels of transferability for intrinsically disordered protein ensembles. The approach, named idpSAM, is a latent diffusion model based on transformer neural networks. It combines an autoencoder to learn a representation of protein geometry and a diffusion model to sample novel conformations in the encoded space. IdpSAM was trained on a large dataset of simulations of disordered protein regions performed with the ABSINTH implicit solvent model. Thanks to the expressiveness of its neural networks and its training stability, idpSAM faithfully captures 3D structural ensembles of test sequences with no similarity in the training set. Our study also demonstrates the potential for generating full conformational ensembles from datasets with limited sampling and underscores the importance of training set size for generalization. We believe that idpSAM represents a significant progress in transferable protein ensemble modeling through machine learning.

Lipids and proteins: Insights into the dynamics of assembly, recognition, condensate formation. What is still missing?

Lipid membranes and proteins, which are part of us throughout our lives, have been studied for decades. However, every year, new discoveries show how little we know about them. In a reader-friendly manner for people not involved in the field, this paper tries to serve as a bridge between physicists and biologists and new young researchers diving into the field to show its relevance, pointing out just some of the plethora of lines of research yet to be unraveled. It illustrates how new ways, from experimental to theoretical approaches, are needed in order to understand the structures and interactions that take place in a single lipid, protein, or multicomponent system, as we are still only scratching the surface.

Amyloids, amorphous aggregates and assemblies of peptides - Assessing aggregation

Amyloid and amorphous aggregates represent the two major categories of aggregates associated with diseases, and although exhibiting distinct features, researchers often treat them as equivalent, which demonstrates the need for more thorough characterization. Here, we compare amyloid and amorphous aggregates based on their biochemical properties, kinetics, and morphological features. To further decipher this issue, we propose the use of peptide self-assemblies as minimalistic models for understanding the aggregation process. Peptide building blocks are significantly smaller than proteins that participate in aggregation, however, they make a plausible means to bridge the gap in discerning the aggregation process at the more complex, protein level. Additionally, we explore the potential use of peptide-inspired models to research the liquid-liquid phase separation as a feasible mechanism preceding amyloid formation. Connecting these concepts can help clarify our understanding of aggregation-related disorders and potentially provide novel drug targets to impede and reverse these serious illnesses.

Intrinsically disordered membrane anchors of Rheb, RhoA and DiRas3 small GTPases: Molecular dynamics, membrane organization, and interactions

Protein structure has been well established to play a key role in determining function; however, intrinsically disordered proteins and regions (IDPs and IDRs) defy this paradigm. IDPs and IDRs exist as an ensemble of structures rather than a stable 3D structure yet play essential roles in many cell signaling processes. Nearly all Ras Superfamily GTPases are tethered to membranes by a lipid tail at the end of a flexible IDR. The sequence of these IDRs are key determinants of membrane localization, and interactions between the IDR and the membrane have been shown to affect signaling in RAS proteins through modulation of dynamic membrane organization. Here we utilized atomistic molecular dynamics simulations to study the membrane interactions, conformational dynamics, and lipid sorting of three IDRs from small GTPases Rheb, RhoA and DiRas3 in model membranes representing their physiological target membranes. We found that complementarity between lipidated IDR sequence and target membrane lipid composition is a determinant of conformational plasticity. We also show that electrostatic interactions between anionic lipids and basic residues on IDRs generate semi-stable conformational sub-states, and a lack of these residues leads to greater conformational diversity. Finally, we show that small GTPase IDRs with a polybasic domain alter local lipid composition by segregating anionic membrane lipids, and, in some cases, excluding other lipids from their immediate proximity in favor of anionic lipids.

Viral Receptor-Binding Protein Evolves New Function through Mutations That Cause Trimer Instability and Functional Heterogeneity

When proteins evolve new activity, a concomitant decrease in stability is often observed because the mutations that confer new activity can destabilize the native fold. In the conventional model of protein evolution, reduced stability is considered a purely deleterious cost of molecular innovation because unstable proteins are prone to aggregation and are sensitive to environmental stressors. However, recent work has revealed that nonnative, often unstable protein conformations play an important role in mediating evolutionary transitions, raising the question of whether instability can itself potentiate the evolution of new activity. We explored this question in a bacteriophage receptor-binding protein during host-range evolution. We studied the properties of the receptor-binding protein of bacteriophage λ before and after host-range evolution and demonstrated that the evolved protein is relatively unstable and may exist in multiple conformations with unique receptor preferences. Through a combination of structural modeling and in vitro oligomeric state analysis, we found that the instability arises from mutations that interfere with trimer formation. This study raises the intriguing possibility that protein instability might play a previously unrecognized role in mediating host-range expansions in viruses.

Plant RNA-binding proteins: Phase separation dynamics and functional mechanisms underlying plant development and stress responses

RNA-binding proteins (RBPs) accompany RNA from synthesis to decay, mediating every aspect of RNA metabolism and impacting diverse cellular and developmental processes in eukaryotes. Many RBPs undergo phase separation along with their bound RNA to form and function in dynamic membraneless biomolecular condensates for spatiotemporal coordination or regulation of RNA metabolism. Increasing evidence suggests that phase-separating RBPs with RNA-binding domains and intrinsically disordered regions play important roles in plant development and stress adaptation. Here, we summarize the current knowledge about how dynamic partitioning of RBPs into condensates controls plant development and enables sensing of experimental changes to confer growth plasticity under stress conditions, with a focus on the dynamics and functional mechanisms of RBP-rich nuclear condensates and cytoplasmic granules in mediating RNA metabolism. We also discuss roles of multiple factors, such as environmental signals, protein modifications, and N6-methyladenosine RNA methylation, in modulating the phase separation behaviors of RBPs, and highlight the prospects and challenges for future research on phase-separating RBPs in crops.

Protein structure-function continuum model: Emerging nexuses between specificity, evolution, and structure

The rationale for replacing the old binary of structure-function with the trinity of structure, disorder, and function has gained considerable ground in recent years. A continuum model based on the expanded form of the existing paradigm can now subsume importance of both conformational flexibility and intrinsic disorder in protein function. The disorder is actually critical for understanding the protein-protein interactions in many regulatory processes, formation of membrane-less organelles, and our revised notions of specificity as amply illustrated by moonlighting proteins. While its importance in formation of amyloids and function of prions is often discussed, the roles of intrinsic disorder in infectious diseases and protein function under extreme conditions are also becoming clear. This review is an attempt to discuss how our current understanding of protein function, specificity, and evolution fit better with the continuum model. This integration of structure and disorder under a single model may bring greater clarity in our continuing quest for understanding proteins and molecular mechanisms of their functionality.

Impact of mutations on the stability of SARS-CoV-2 nucleocapsid protein structure

The nucleocapsid (N) protein of SARS-CoV-2 is known to participate in various host cellular processes, including interferon inhibition, RNA interference, apoptosis, and regulation of virus life cycles. Additionally, it has potential as a diagnostic antigen and/or immunogen. Our research focuses on examining structural changes caused by mutations in the N protein. We have modeled the complete tertiary structure of native and mutated forms of the N protein using Alphafold2. Notably, the N protein contains 3 disordered regions. The focus was on investigating the impact of mutations on the stability of the protein's dimeric structure based on binding free energy calculations (MM-PB/GB-SA) and RMSD fluctuations after MD simulations. The results demonstrated that 28 mutations out of 37 selected mutations analyzed, compared with wild-type N protein, resulted in a stable dimeric structure, while 9 mutations led to destabilization. Our results are important to understand the tertiary structure of the N protein dimer of SARS-CoV-2 and the effect of mutations on it, their behavior in the host cell, as well as for the research of other viruses belonging to the same genus additionally, to anticipate potential strategies for addressing this viral illness․.