Mining alpha-helix-forming molecular recognition features with cross species sequence alignments

On the Roles of Protein Intrinsic Disorder in the Origin of Life and Evolution

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.

Advanced computational approaches to understand protein aggregation

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

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.

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

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

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

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

Design of stable circular permutants of the GroEL chaperone apical domain

Enhancing protein stability holds paramount significance in biotechnology, therapeutics, and the food industry. Circular permutations offer a distinctive avenue for manipulating protein stability while keeping intra-protein interactions intact. Amidst the creation of circular permutants, determining the optimal placement of the new N- and C-termini stands as a pivotal, albeit largely unexplored, endeavor. In this study, we employed PONDR-FIT's predictions of disorder propensity to guide the design of circular permutants for the GroEL apical domain (residues 191-345). Our underlying hypothesis posited that a higher predicted disorder value would correspond to reduced stability in the circular permutants, owing to the increased likelihood of fluctuations in the novel N- and C-termini. To substantiate this hypothesis, we engineered six circular permutants, positioning glycines within the loops as locations for the new N- and C-termini. We demonstrated the validity of our hypothesis along the set of the designed circular permutants, as supported by measurements of melting temperatures by circular dichroism and differential scanning microcalorimetry. Consequently, we propose a novel computational methodology that rationalizes the design of circular permutants with projected stability. Video Abstract.

Functional unfoldomics: Roles of intrinsic disorder in protein (multi)functionality

Intrinsically disordered proteins (IDPs), which are functional proteins without stable tertiary structure, and hybrid proteins containing ordered domains and intrinsically disordered regions (IDRs) constitute prominent parts of all proteomes collectively known as unfoldomes. IDPs/IDRs exist as highly dynamic structural ensembles of rapidly interconverting conformations and are characterized by the exceptional structural heterogeneity, where their different parts are (dis)ordered to different degree, and their overall structure represents a complex mosaic of foldons, inducible foldons, inducible morphing foldons, non-foldons, semifoldons, and even unfoldons. Despite their lack of unique 3D structures, IDPs/IDRs play crucial roles in the control of various biological processes and the regulation of different cellular pathways and are commonly involved in recognition and signaling, indicating that the disorder-based functional repertoire is complementary to the functions of ordered proteins. Furthermore, IDPs/IDRs are frequently multifunctional, and this multifunctionality is defined by their structural flexibility and heterogeneity. Intrinsic disorder phenomenon is at the roots of the structure-function continuum model, where the structure continuum is defined by the presence of differently (dis)ordered regions, and the function continuum arises from the ability of all these differently (dis)ordered parts to have different functions. In their everyday life, IDPs/IDRs utilize a broad spectrum of interaction mechanisms thereby acting as interaction specialists. They are crucial for the biogenesis of numerous proteinaceous membrane-less organelles driven by the liquid-liquid phase separation. This review introduces functional unfoldomics by representing some aspects of the intrinsic disorder-based functionality.

Structure-Function Characterisation of Eop1 Effectors from the Erwinia-Pantoea Clade Reveals They May Acetylate Their Defence Target through a Catalytic Dyad

The YopJ group of acetylating effectors from phytopathogens of the genera Pseudomonas and Ralstonia have been widely studied to understand how they modify and suppress their host defence targets. In contrast, studies on a related group of effectors, the Eop1 group, lag far behind. Members of the Eop1 group are widely present in the Erwinia-Pantoea clade of Gram-negative bacteria, which contains phytopathogens, non-pathogens and potential biocontrol agents, implying that they may play an important role in agroecological or pathological adaptations. The lack of research in this group of YopJ effectors has left a significant knowledge gap in their functioning and role. For the first time, we perform a comparative analysis combining AlphaFold modelling, in planta transient expressions and targeted mutational analyses of the Eop1 group effectors from the Erwinia-Pantoea clade, to help elucidate their likely activity and mechanism(s). This integrated study revealed several new findings, including putative binding sites for inositol hexakisphosphate and acetyl coenzyme A and newly postulated target-binding domains, and raises questions about whether these effectors function through a catalytic triad mechanism. The results imply that some Eop1s may use a catalytic dyad acetylation mechanism that we found could be promoted by the electronegative environment around the active site.

The PALB2 DNA-binding domain is an intrinsically disordered recombinase

The Partner and Localizer of BRCA2 (PALB2) tumor suppressor is a scaffold protein that links BRCA1 with BRCA2 to initiate homologous recombination (HR). PALB2 interaction with DNA strongly enhances HR efficiency. The PALB2 DNA-binding domain (PALB2-DBD) supports DNA strand exchange, a complex multistep reaction supported by only a few protein families such as RecA-like recombinases or Rad52. The mechanisms of PALB2 DNA binding and strand exchange are unknown. We performed circular dichroism, electron paramagnetic spectroscopy, and small-angle X-ray scattering analyses and determined that PALB2-DBD is intrinsically disordered, even when bound to DNA. The intrinsically disordered nature of this domain was further supported by bioinformatics analysis. Intrinsically disordered proteins (IDPs) are prevalent in the human proteome and have many important biological functions. The complexity of the strand exchange reaction significantly expands the functional repertoire of IDPs. The results of confocal single-molecule FRET indicated that PALB2-DBD binding leads to oligomerization-dependent DNA compaction. We hypothesize that PALB2-DBD uses a chaperone-like mechanism to aid formation and resolution of complex DNA and RNA multichain intermediates during DNA replication and repair. Since PALB2-DBD alone or within the full-length PALB2 is predicted to have strong liquid-liquid phase separation (LLPS) potential, protein-nucleic acids condensates are likely to play a role in complex functionality of PALB2-DBD. Similar DNA-binding intrinsically disordered regions may represent a novel class of functional domains that evolved to function in eukaryotic nucleic acid metabolism complexes.

Chaotic aging: intrinsically disordered proteins in aging-related processes

The development of aging is associated with the disruption of key cellular processes manifested as well-established hallmarks of aging. Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) have no stable tertiary structure that provide them a power to be configurable hubs in signaling cascades and regulate many processes, potentially including those related to aging. There is a need to clarify the roles of IDPs/IDRs in aging. The dataset of 1702 aging-related proteins was collected from established aging databases and experimental studies. There is a noticeable presence of IDPs/IDRs, accounting for about 36% of the aging-related dataset, which is however less than the disorder content of the whole human proteome (about 40%). A Gene Ontology analysis of the used here aging proteome reveals an abundance of IDPs/IDRs in one-third of aging-associated processes, especially in genome regulation. Signaling pathways associated with aging also contain IDPs/IDRs on different hierarchical levels, revealing the importance of "structure-function continuum" in aging. Protein-protein interaction network analysis showed that IDPs present in different clusters associated with different aging hallmarks. Protein cluster with IDPs enrichment has simultaneously high liquid-liquid phase separation (LLPS) probability, "nuclear" localization and DNA-associated functions, related to aging hallmarks: genomic instability, telomere attrition, epigenetic alterations, and stem cells exhaustion. Intrinsic disorder, LLPS, and aggregation propensity should be considered as features that could be markers of pathogenic proteins. Overall, our analyses indicate that IDPs/IDRs play significant roles in aging-associated processes, particularly in the regulation of DNA functioning. IDP aggregation, which can lead to loss of function and toxicity, could be critically harmful to the cell. A structure-based analysis of aging and the identification of proteins that are particularly susceptible to disturbances can enhance our understanding of the molecular mechanisms of aging and open up new avenues for slowing it down.

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

A central challenge in the study of intrinsically disordered proteins is the characterization of the mechanisms by which they bind their physiological interaction partners. Here, we utilize a deep learning based Markov state modeling approach to characterize the folding-upon-binding pathways observed in a long-time scale 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 do not, however, find evidence for the existence of canonical conformational selection or induced fit binding pathways. We observe four kinetically separated native-like bound states that interconvert on time scales 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.

I-Shaped Dimers of a Plant Chloroplast FOF1-ATP Synthase in Response to Changes in Ionic Strength

F-type ATP synthases play a key role in oxidative and photophosphorylation processes generating adenosine triphosphate (ATP) for most biochemical reactions in living organisms. In contrast to the mitochondrial F_OF₁-ATP synthases, those of chloroplasts are known to be mostly monomers with approx. 15% fraction of oligomers interacting presumably non-specifically in a thylakoid membrane. To shed light on the nature of this difference we studied interactions of the chloroplast ATP synthases using small-angle X-ray scattering (SAXS) method. Here, we report evidence of I-shaped dimerization of solubilized F_OF₁-ATP synthases from spinach chloroplasts at different ionic strengths. The structural data were obtained by SAXS and demonstrated dimerization in response to ionic strength. The best model describing SAXS data was two ATP-synthases connected through F₁/F₁' parts, presumably via their δ-subunits, forming "I" shape dimers. Such I-shaped dimers might possibly connect the neighboring lamellae in thylakoid stacks assuming that the F_OF₁ monomers comprising such dimers are embedded in parallel opposing stacked thylakoid membrane areas. If this type of dimerization exists in nature, it might be one of the pathways of inhibition of chloroplast F_OF₁-ATP synthase for preventing ATP hydrolysis in the dark, when ionic strength in plant chloroplasts is rising. Together with a redox switch inserted into a γ-subunit of chloroplast F_OF₁ and lateral oligomerization, an I-shaped dimerization might comprise a subtle regulatory process of ATP synthesis and stabilize the structure of thylakoid stacks in chloroplasts.

Moonlighting enzymes: when cellular context defines specificity

It is not often realized that the absolute protein specificity is an exception rather than a rule. Two major kinds of protein multi-specificities are promiscuity and moonlighting. This review discusses the idea of enzyme specificity and then focusses on moonlighting. Some important examples of protein moonlighting, such as crystallins, ceruloplasmin, metallothioniens, macrophage migration inhibitory factor, and enzymes of carbohydrate metabolism are discussed. How protein plasticity and intrinsic disorder enable the removing the distinction between enzymes and other biologically active proteins are outlined. Finally, information on important roles of moonlighting in human diseases is updated.

Intrinsic disorder in the open reading frame 2 of hepatitis E virus: a protein with multiple functions beyond viral capsid

BACKGROUND

Hepatitis E virus (HEV) is the cause of a liver disease hepatitis E. The translation product of HEV ORF2 has recently been demonstrated as a protein involved in multiple functions besides performing its major role of a viral capsid. As intrinsically disordered regions (IDRs) are linked to various essential roles in the virus's life cycle, we analyzed the disorder pattern distribution of the retrieved ORF2 protein sequences by employing different online predictors. Our findings might provide some clues on the disorder-based functions of ORF2 protein that possibly help us in understanding its behavior other than as a HEV capsid protein.

RESULTS

The modeled three dimensional (3D) structures of ORF2 showed the predominance of random coils or unstructured regions in addition to major secondary structure components (alpha helix and beta strand). After initial scrutinization, the predictors VLXT and VSL2 predicted ORF2 as a highly disordered protein while the predictors VL3 and DISOPRED3 predicted ORF2 as a moderately disordered protein, thus categorizing HEV-ORF2 into IDP (intrinsically disordered protein) or IDPR (intrinsically disordered protein region) respectively. Thus, our initial predicted disorderness in ORF2 protein 3D structures was in excellent agreement with their predicted disorder distribution patterns (evaluated through different predictors). The abundance of MoRFs (disorder-based protein binding sites) in ORF2 was observed that signified their interaction with binding partners which might further assist in viral infection. As IDPs/IDPRs are targets of regulation, we carried out the phosphorylation analysis to reveal the presence of post-translationally modified sites. Prevalence of several disordered-based phosphorylation sites further signified the involvement of ORF2 in diverse and significant biological processes. Furthermore, ORF2 structure-associated functions revealed its involvement in several crucial functions and biological processes like binding and catalytic activities.

CONCLUSIONS

The results predicted ORF2 as a protein with multiple functions besides its role as a capsid protein. Moreover, the occurrence of IDPR/IDP in ORF2 protein suggests that its disordered region might serve as novel drug targets via functioning as potential interacting domains. Our data collectively might provide significant implication in HEV vaccine search as disorderness in viral proteins is related to mechanisms involved in immune evasion.

Computational prediction of disordered binding regions

One of the key features of intrinsically disordered regions (IDRs) is their ability to interact with a broad range of partner molecules. Multiple types of interacting IDRs were identified including molecular recognition fragments (MoRFs), short linear sequence motifs (SLiMs), and protein-, nucleic acids- and lipid-binding regions. Prediction of binding IDRs in protein sequences is gaining momentum in recent years. We survey 38 predictors of binding IDRs that target interactions with a diverse set of partners, such as peptides, proteins, RNA, DNA and lipids. We offer a historical perspective and highlight key events that fueled efforts to develop these methods. These tools rely on a diverse range of predictive architectures that include scoring functions, regular expressions, traditional and deep machine learning and meta-models. Recent efforts focus on the development of deep neural network-based architectures and extending coverage to RNA, DNA and lipid-binding IDRs. We analyze availability of these methods and show that providing implementations and webservers results in much higher rates of citations/use. We also make several recommendations to take advantage of modern deep network architectures, develop tools that bundle predictions of multiple and different types of binding IDRs, and work on algorithms that model structures of the resulting complexes.

Computational Prediction of Protein Intrinsically Disordered Region Related Interactions and Functions

Intrinsically Disordered Proteins (IDPs) and Regions (IDRs) exist widely. Although without well-defined structures, they participate in many important biological processes. In addition, they are also widely related to human diseases and have become potential targets in drug discovery. However, there is a big gap between the experimental annotations related to IDPs/IDRs and their actual number. In recent decades, the computational methods related to IDPs/IDRs have been developed vigorously, including predicting IDPs/IDRs, the binding modes of IDPs/IDRs, the binding sites of IDPs/IDRs, and the molecular functions of IDPs/IDRs according to different tasks. In view of the correlation between these predictors, we have reviewed these prediction methods uniformly for the first time, summarized their computational methods and predictive performance, and discussed some problems and perspectives.

Liaisons dangereuses: Intrinsic Disorder in Cellular Proteins Recruited to Viral Infection-Related Biocondensates

Liquid-liquid phase separation (LLPS) is responsible for the formation of so-called membrane-less organelles (MLOs) that are essential for the spatio-temporal organization of the cell. Intrinsically disordered proteins (IDPs) or regions (IDRs), either alone or in conjunction with nucleic acids, are involved in the formation of these intracellular condensates. Notably, viruses exploit LLPS at their own benefit to form viral replication compartments. Beyond giving rise to biomolecular condensates, viral proteins are also known to partition into cellular MLOs, thus raising the question as to whether these cellular phase-separating proteins are drivers of LLPS or behave as clients/regulators. Here, we focus on a set of eukaryotic proteins that are either sequestered in viral factories or colocalize with viral proteins within cellular MLOs, with the primary goal of gathering organized, predicted, and experimental information on these proteins, which constitute promising targets for innovative antiviral strategies. Using various computational approaches, we thoroughly investigated their disorder content and inherent propensity to undergo LLPS, along with their biological functions and interactivity networks. Results show that these proteins are on average, though to varying degrees, enriched in disorder, with their propensity for phase separation being correlated, as expected, with their disorder content. A trend, which awaits further validation, tends to emerge whereby the most disordered proteins serve as drivers, while more ordered cellular proteins tend instead to be clients of viral factories. In light of their high disorder content and their annotated LLPS behavior, most proteins in our data set are drivers or co-drivers of molecular condensation, foreshadowing a key role of these cellular proteins in the scaffolding of viral infection-related MLOs.

Biological soft matter: intrinsically disordered proteins in liquid-liquid phase separation and biomolecular condensates

The facts that many proteins with crucial biological functions do not have unique structures and that many biological processes are compartmentalized into the liquid-like biomolecular condensates, which are formed via liquid-liquid phase separation (LLPS) and are not surrounded by the membrane, are revolutionizing the modern biology. These phenomena are interlinked, as the presence of intrinsic disorder represents an important requirement for a protein to undergo LLPS that drives biogenesis of numerous membrane-less organelles (MLOs). Therefore, one can consider these phenomena as crucial constituents of a new IDP-LLPS-MLO field. Furthermore, intrinsically disordered proteins (IDPs), LLPS, and MLOs represent a clear link between molecular and cellular biology and soft matter and condensed soft matter physics. Both IDP and LLPS/MLO fields are undergoing explosive development and generate the ever-increasing mountain of crucial data. These new data provide answers to so many long-standing questions that it is difficult to imagine that in the very recent past, protein scientists and cellular biologists operated without taking these revolutionary concepts into account. The goal of this essay is not to deliver a comprehensive review of the IDP-LLPS-MLO field but to provide a brief and rather subjective outline of some of the recent developments in these exciting fields.

The unstructured linker of Mlh1 contains a motif required for endonuclease function which is mutated in cancers

DNA mismatch repair (MMR) prevents mutations caused by DNA-replication errors and suppresses multiple types of cancers. During MMR, the Mlh1-Pms1 complex is recruited to mispair-containing DNA and nicks the newly replicated DNA strand, targeting it for degradation and resynthesis. Here, we identified an amino acid sequence within the unstructured linker of Mlh1 required for endonuclease activity. This sequence functioned when moved within the Mlh1 linker or when moved to the Pms1 linker. These results reveal a functional role for the intrinsically disordered region, which is conserved from yeast to humans and is mutated in cancer, suggesting that it organizes the catalytically active complex even though the required sequence can be distant from the active site.

Eukaryotic DNA mismatch repair (MMR) depends on recruitment of the Mlh1-Pms1 endonuclease (human MLH1-PMS2) to mispaired DNA. Both Mlh1 and Pms1 contain a long unstructured linker that connects the N- and carboxyl-terminal domains. Here, we demonstrated the Mlh1 linker contains a conserved motif (Saccharomyces cerevisiae residues 391–415) required for MMR. The Mlh1-R401A,D403A-Pms1 linker motif mutant protein was defective for MMR and endonuclease activity in vitro, even though the conserved motif could be >750 Å from the carboxyl-terminal endonuclease active site or the N-terminal adenosine triphosphate (ATP)-binding site. Peptides encoding this motif inhibited wild-type Mlh1-Pms1 endonuclease activity. The motif functioned in vivo at different sites within the Mlh1 linker and within the Pms1 linker. Motif mutations in human cancers caused a loss-of-function phenotype when modeled in S. cerevisiae. These results suggest that the Mlh1 motif promotes the PCNA-activated endonuclease activity of Mlh1-Pms1 via interactions with DNA, PCNA, RFC, or other domains of the Mlh1-Pms1 complex.

Connecting sequence features within the disordered C-terminal linker of Bacillus subtilis FtsZ to functions and bacterial cell division

Intrinsically disordered regions (IDRs) can function as autoregulators of folded enzymes to which they are tethered. One example is the bacterial cell division protein FtsZ. This includes a folded core and a C-terminal tail (CTT) that encompasses a poorly conserved, disordered C-terminal linker (CTL) and a well-conserved 17-residue C-terminal peptide (CT17). Sites for GTPase activity of FtsZs are formed at the interface between GTP binding sites and T7 loops on cores of adjacent subunits within dimers. Here, we explore the basis of autoregulatory functions of the CTT in Bacillus subtilis FtsZ (Bs-FtsZ). Molecular simulations show that the CT17 of Bs-FtsZ makes statistically significant CTL-mediated contacts with the T7 loop. Statistical coupling analysis of more than 1,000 sequences from FtsZ orthologs reveals clear covariation of the T7 loop and the CT17 with most of the core domain, whereas the CTL is under independent selection. Despite this, we discover the conservation of nonrandom sequence patterns within CTLs across orthologs. To test how the nonrandom patterns of CTLs mediate CTT-core interactions and modulate FtsZ functionalities, we designed Bs-FtsZ variants by altering the patterning of oppositely charged residues within the CTL. Such alterations disrupt the core-CTT interactions, lead to anomalous assembly and inefficient GTP hydrolysis in vitro and protein degradation, aberrant assembly, and disruption of cell division in vivo. Our findings suggest that viable CTLs in FtsZs are likely to be IDRs that encompass nonrandom, functionally relevant sequence patterns that also preserve three-way covariation of the CT17, the T7 loop, and core domain.

Prediction of protein-protein interaction sites in intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) participate in many biological processes by interacting with other proteins, including the regulation of transcription, translation, and the cell cycle. With the increasing amount of disorder sequence data available, it is thus crucial to identify the IDP binding sites for functional annotation of these proteins. Over the decades, many computational approaches have been developed to predict protein-protein binding sites of IDP (IDP-PPIS) based on protein sequence information. Moreover, there are new IDP-PPIS predictors developed every year with the rapid development of artificial intelligence. It is thus necessary to provide an up-to-date overview of these methods in this field. In this paper, we collected 30 representative predictors published recently and summarized the databases, features and algorithms. We described the procedure how the features were generated based on public data and used for the prediction of IDP-PPIS, along with the methods to generate the feature representations. All the predictors were divided into three categories: scoring functions, machine learning-based prediction, and consensus approaches. For each category, we described the details of algorithms and their performances. Hopefully, our manuscript will not only provide a full picture of the status quo of IDP binding prediction, but also a guide for selecting different methods. More importantly, it will shed light on the inspirations for future development trends and principles.

A Study on the Nature of SARS-CoV-2 Using the Shell Disorder Models: Reproducibility, Evolution, Spread, and Attenuation

The basic tenets of the shell disorder model (SDM) as applied to COVID-19 are that the harder outer shell of the virus shell (lower PID—percentage of intrinsic disorder—of the membrane protein M, PID_M) and higher flexibility of the inner shell (higher PID of the nucleocapsid protein N, PID_N) are correlated with the contagiousness and virulence, respectively. M protects the virion from the anti-microbial enzymes in the saliva and mucus. N disorder is associated with the rapid replication of the virus. SDM predictions are supported by two experimental observations. The first observation demonstrated lesser and greater presence of the Omicron particles in the lungs and bronchial tissues, respectively, as there is a greater level of mucus in the bronchi. The other observation revealed that there are lower viral loads in 2017-pangolin-CoV, which is predicted to have similarly low PID_N as Omicron. The abnormally hard M, which is very rarely seen in coronaviruses, arose from the fecal–oral behaviors of pangolins via exposure to buried feces. Pangolins provide an environment for coronavirus (CoV) attenuation, which is seen in Omicron. Phylogenetic study using M shows that COVID-19-related bat-CoVs from Laos and Omicron are clustered in close proximity to pangolin-CoVs, which suggests the recurrence of interspecies transmissions. Hard M may have implications for long COVID-19, with immune systems having difficulty degrading viral proteins/particles.

Challenges in describing the conformation and dynamics of proteins with ambiguous behavior

Traditionally, our understanding of how proteins operate and how evolution shapes them is based on two main data sources: the overall protein fold and the protein amino acid sequence. However, a significant part of the proteome shows highly dynamic and/or structurally ambiguous behavior, which cannot be correctly represented by the traditional fixed set of static coordinates. Representing such protein behaviors remains challenging and necessarily involves a complex interpretation of conformational states, including probabilistic descriptions. Relating protein dynamics and multiple conformations to their function as well as their physiological context (e.g., post-translational modifications and subcellular localization), therefore, remains elusive for much of the proteome, with studies to investigate the effect of protein dynamics relying heavily on computational models. We here investigate the possibility of delineating three classes of protein conformational behavior: order, disorder, and ambiguity. These definitions are explored based on three different datasets, using interpretable machine learning from a set of features, from AlphaFold2 to sequence-based predictions, to understand the overlap and differences between these datasets. This forms the basis for a discussion on the current limitations in describing the behavior of dynamic and ambiguous proteins.

Comparative study of structures and functional motifs in lectins from the commercially important photosynthetic microorganisms

Photosynthetic microorganisms, specifically cyanobacteria and microalgae, can synthesize a vast array of biologically active molecules, such as lectins, that have great potential for various biotechnological and biomedical applications. However, since the structures of these proteins are not well established, likely due to the presence of intrinsically disordered regions, our ability to better understand their functionality is hampered. We embarked on a study of the carbohydrate recognition domain (CRD), intrinsically disordered regions (IDRs), amino acidic composition, as well as and functional motifs in lectins from cyanobacteria of the genus Arthrospira and microalgae Chlorella and Dunaliella genus using a combination of bioinformatics techniques. This search revealed the presence of five distinctive CRD types differently distributed between the genera. Most CRDs displayed a group-specific distribution, except to C. sorokiniana possessing distinctive CRD probably due to its specific lifestyle. We also found that all CRDs contain short IDRs. Bacterial lectin of Arthrospira prokarionte showed lower intrinsic disorder and proline content when compared to the lectins from the eukaryotic microalgae (Chlorella and Dunaliella). Among the important functions predicted in all lectins were several specific motifs, which directly interacts with proteins involved in the cell-cycle control and which may be used for pharmaceutical purposes. Since the aforementioned properties of each type of lectin were investigated in silico, they need experimental confirmation. The results of our study provide an overview of the distribution of CRD, IDRs, and functional motifs within lectin from the commercially important microalgae.

Electronic Polarization at the Interface between the p53 Transactivation Domain and Two Binding Partners

Intrinsically disordered proteins (IDPs) are an abundant class of highly charged proteins that participate in numerous crucial biological processes, often in regulatory roles. IDPs do not have one major free energy minimum with a dominant structure, instead existing as conformational ensembles of multiple semistable conformations. p53 is a prototypical protein with disordered regions and binds to many structurally diverse partners, making it a useful model for exploring the role of electrostatic interactions at IDP binding interfaces. In this study, we used the Drude-2019 force field to simulate the p53 transactivation domain with two protein partners to probe the role of electrostatic interactions in IDP protein-protein interactions. We found that the Drude-2019 polarizable force field reasonably reproduced experimental chemical shifts of the p53 transactivation domain (TAD) in one complex for which these data are available. We also found that the proteins in these complexes displayed dipole response at specific residues of each protein and that residues primarily involved in binding showed a large percent change in dipole moment between the unbound and complexed states. Probing the role of electrostatic interactions in IDP binding can allow us greater fundamental understanding of these interactions and may help with targeting p53 or its partners for drug design.

Shell Disorder Models Detect That Omicron Has Harder Shells with Attenuation but Is Not a Descendant of the Wuhan-Hu-1 SARS-CoV-2

Before the SARS-CoV-2 Omicron variant emergence, shell disorder models (SDM) suggested that an attenuated precursor from pangolins may have entered humans in 2017 or earlier. This was based on a shell disorder analysis of SARS-CoV-1/2 and pangolin-Cov-2017. The SDM suggests that Omicron is attenuated with almost identical N (inner shell) disorder as pangolin-CoV-2017 (N-PID (percentage of intrinsic disorder): 44.8% vs. 44.9%-lower than other variants). The outer shell disorder (M-PID) of Omicron is lower than that of other variants and pangolin-CoV-2017 (5.4% vs. 5.9%). COVID-19-related CoVs have the lowest M-PIDs (hardest outer shell) among all CoVs. This is likely to be responsible for the higher contagiousness of SARS-CoV-2 and Omicron, since hard outer shell protects the virion from salivary/mucosal antimicrobial enzymes. Phylogenetic study using M reveals that Omicron branched off from an ancestor of the Wuhan-Hu-1 strain closely related to pangolin-CoVs. M, being evolutionarily conserved in COVID-19, is most ideal for COVID-19 phylogenetic study. Omicron may have been hiding among burrowing animals (e.g., pangolins) that provide optimal evolutionary environments for attenuation and increase shell hardness, which is essential for fecal-oral-respiratory transmission via buried feces. Incoming data support SDM e.g., the presence of fewer infectious particles in the lungs than in the bronchi upon infection.

Liquid-liquid phase separation as an organizing principle of intracellular space: overview of the evolution of the cell compartmentalization concept

At the turn of the twenty-first century, fundamental changes took place in the understanding of the structure and function of proteins and then in the appreciation of the intracellular space organization. A rather mechanistic model of the organization of living matter, where the function of proteins is determined by their rigid globular structure, and the intracellular processes occur in rigidly determined compartments, was replaced by an idea that highly dynamic and multifunctional "soft matter" lies at the heart of all living things. According this "new view", the most important role in the spatio-temporal organization of the intracellular space is played by liquid-liquid phase transitions of biopolymers. These self-organizing cellular compartments are open dynamic systems existing at the edge of chaos. They are characterized by the exceptional structural and compositional dynamics, and their multicomponent nature and polyfunctionality provide means for the finely tuned regulation of various intracellular processes. Changes in the external conditions can cause a disruption of the biogenesis of these cellular bodies leading to the irreversible aggregation of their constituent proteins, followed by the transition to a gel-like state and the emergence of amyloid fibrils. This work represents a historical overview of changes in our understanding of the intracellular space compartmentalization. It also reflects methodological breakthroughs that led to a change in paradigms in this area of science and discusses modern ideas about the organization of the intracellular space. It is emphasized here that the membrane-less organelles have to combine a certain resistance to the changes in their environment and, at the same time, show high sensitivity to the external signals, which ensures the normal functioning of the cell.

Computational, Experimental, and Clinical Evidence of a Specific but Peculiar Evolutionary Nature of (COVID-19) SARS-CoV-2

The shell disorder models have predicted that SARS-CoV-2 is of a specific but peculiar evolutionary nature. All coronaviruses (CoVs) closely related to SARS-CoV-2 have been found to have the hardest outer shells (M protein) among CoVs. This hard shell (low M percentage of intrinsic disorder (PID)) is associated with burrowing animals, for example, pangolins, and is believed to be responsible for the high contagiousness of SARS-CoV-2 because it will be more resistant to antimicrobial enzymes found in saliva/mucus. Incoming clinical and experimental data do support this along with a prediction based on another aspect of the shell (N, inner shell) disorder models that SARS-CoV-1 is more virulent than SARS-CoV-2 because SARS-CoV-2 produces fewer virus copies in vital organs even if large amounts of infections particles are shed orally and nasally. A phylogenetic study using M reveals a closer relationship of SARS-CoV to pangolin-CoVs than the bat-RaTG13 found in Yunnan, China. Previous studies may have been confused by recombinations that were poorly handled. The shell disorder models suggest that a pangolin-CoV strain may have entered the human population in 2017 or before as an attenuated virus, which could explain why SARS-CoV is found to be highly adapted to humans.

MoRF-FUNCpred: Molecular Recognition Feature Function Prediction Based on Multi-Label Learning and Ensemble Learning

Intrinsically disordered regions (IDRs) without stable structure are important for protein structures and functions. Some IDRs can be combined with molecular fragments to make itself completed the transition from disordered to ordered, which are called molecular recognition features (MoRFs). There are five main functions of MoRFs: molecular recognition assembler (MoR_assembler), molecular recognition chaperone (MoR_chaperone), molecular recognition display sites (MoR_display_sites), molecular recognition effector (MoR_effector), and molecular recognition scavenger (MoR_scavenger). Researches on functions of molecular recognition features are important for pharmaceutical and disease pathogenesis. However, the existing computational methods can only predict the MoRFs in proteins, failing to distinguish their different functions. In this paper, we treat MoRF function prediction as a multi-label learning task and solve it with the Binary Relevance (BR) strategy. Finally, we use Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), and Random Forest (RF) as basic models to construct MoRF-FUNCpred through ensemble learning. Experimental results show that MoRF-FUNCpred performs well for MoRF function prediction. To the best knowledge of ours, MoRF-FUNCpred is the first predictor for predicting the functions of MoRFs. Availability and Implementation: The stand alone package of MoRF-FUNCpred can be accessed from https://github.com/LiangYu-Xidian/MoRF-FUNCpred.

Dilute phase oligomerization can oppose phase separation and modulate material properties of a ribonucleoprotein condensate

SignificanceA large subclass of biomolecular condensates are linked to RNA regulation and are known as ribonucleoprotein (RNP) bodies. While extensive work has identified driving forces for biomolecular condensate formation, relatively little is known about forces that oppose assembly. Here, using a fungal RNP protein, Whi3, we show that a portion of its intrinsically disordered, glutamine-rich region modulates phase separation by forming transient alpha helical structures that promote the assembly of dilute phase oligomers. These oligomers detour Whi3 proteins from condensates, thereby impacting the driving forces for phase separation, the protein-to-RNA ratio in condensates, and the material properties of condensates. Our findings show how nanoscale conformational and oligomerization equilibria can influence mesoscale phase equilibria.

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

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

Intrinsically disordered proteins play diverse roles in cell signaling

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

The protein disorder cycle

This mini-review represents a brief, disorder-centric consideration of the interplay between order and disorder in proteins. The goal here is to show that inside the cell, folding, non-folding, and misfolding of proteins are interlinked on multiple levels. This is evidenced by the highly heterogeneous spatio-temporal structural organization of a protein molecule, where one can find differently (dis)ordered components that can undergo local or global order-to-disorder and disorder-to-order transitions needed for functionality. This is further illustrated by the fact that at particular moments of their life, most notably during their synthesis and degradation, all proteins are at least partially disordered. In addition to these intrinsic forms of disorder, proteins are constantly facing extrinsic disorder, which is intrinsic disorder in their functional partners. All this comprises the multileveled protein disorder cycle.

Co-opting disorder into order: Intrinsically disordered proteins and the early evolution of complex multicellularity

Intrinsically disordered proteins (IDPs) are proteins that lack rigid structures yet play important roles in myriad biological phenomena. A distinguishing feature of IDPs is that they often mediate specific biological outcomes via multivalent weak cooperative interactions with multiple partners. Here, we show that several proteins specifically associated with processes that were key in the evolution of complex multicellularity in the lineage leading to the multicellular green alga Volvox carteri are IDPs. We suggest that, by rewiring cellular protein interaction networks, IDPs facilitated the co-option of ancestral pathways for specialized multicellular functions, underscoring the importance of IDPs in the early evolution of complex multicellularity.

Predicting Protein Conformational Disorder and Disordered Binding Sites

In the last two decades it has become increasingly evident that a large number of proteins adopt either a fully or a partially disordered conformation. Intrinsically disordered proteins are ubiquitous proteins that fulfill essential biological functions while lacking a stable 3D structure. Their conformational heterogeneity is encoded by the amino acid sequence, thereby allowing intrinsically disordered proteins or regions to be recognized based on their sequence properties. The identification of disordered regions facilitates the functional annotation of proteins and is instrumental for delineating boundaries of protein domains amenable to crystallization. This chapter focuses on the methods currently employed for predicting protein disorder and identifying intrinsically disordered binding sites.

Computational prediction and validation of specific EmbR binding site on PknH

Tuberculosis drug resistance continues to threaten global health but the underline molecular mechanisms are not clear. Ethambutol (EMB), one of the well-known first - line drugs in tuberculosis treatment is, unfortunately, not free from drug resistance problems. Genomic studies have shown that some genetic mutations in Mycobacterium tuberculosis (Mtb) EmbR, and EmbC/A/B genes cause EMB resistance. EmbR-PknH pair controls embC/A/B operon, which encodes EmbC/A/B genes, and EMB interacts with EmbA/B proteins. However, the EmbR binding site on PknH was unknown. We conducted molecular simulation on the EmbR– peptides binding structures and discovered phosphorylated PknH 273–280 (N′-HEALS^PDPD-C′) makes β strand with the EmbR FHA domain, as β-MoRF (MoRF; molecular recognition feature) does at its binding site. Hydrogen bond number analysis also supported the peptides' β-MoRF forming activity at the EmbR FHA domain. Also, we discovered that previously known phosphorylation residues might have their chronological order according to the phosphorylation status. The discovery validated that Mtb PknH 273–280 (N′-HEALSDPD-C′) has reliable EmbR binding affinity. This approach is revolutionary in the computer-aided drug discovery field, because it is the first trial to discover the protein-protein interaction site, and find binding partner in nature from this site.

Prediction of MoRFs based on sequence properties and convolutional neural networks

Background

Intrinsically disordered proteins possess flexible 3-D structures, which makes them play an important role in a variety of biological functions. Molecular recognition features (MoRFs) act as an important type of functional regions, which are located within longer intrinsically disordered regions and undergo disorder-to-order transitions upon binding their interaction partners.

Results

We develop a method, MoRF_CNN, to predict MoRFs based on sequence properties and convolutional neural networks (CNNs). The sequence properties contain structural and physicochemical properties which are used to describe the differences between MoRFs and non-MoRFs. Especially, to highlight the correlation between the target residue and adjacent residues, three windows are selected to preprocess the selected properties. After that, these calculated properties are combined into the feature matrix to predict MoRFs through the constructed CNN. Comparing with other existing methods, MoRF_CNN obtains better performance.

Conclusions

MoRF_CNN is a new individual MoRFs prediction method which just uses protein sequence properties without evolutionary information. The simulation results show that MoRF_CNN is effective and competitive.

What's in the BAGs? Intrinsic disorder angle of the multifunctionality of the members of a family of chaperone regulators

In humans, the family of Bcl-2 associated athanogene (BAG) proteins includes six members characterized by exceptional multifunctionality and engagement in the pathogenesis of various diseases. All of them are capable of interacting with a multitude of often unrelated binding partners. Such binding promiscuity and related functional and pathological multifacetedness cannot be explained or understood within the frames of the classical "one protein-one structure-one function" model, which also fails to explain the presence of multiple isoforms generated for BAG proteins by alternative splicing or alternative translation initiation and their extensive posttranslational modifications. However, all these mysteries can be solved by taking into account the intrinsic disorder phenomenon. In fact, high binding promiscuity and potential to participate in a broad spectrum of interactions with multiple binding partners, as well as a capability to be multifunctional and multipathogenic, are some of the characteristic features of intrinsically disordered proteins and intrinsically disordered protein regions. Such functional proteins or protein regions lacking unique tertiary structures constitute a cornerstone of the protein structure-function continuum concept. The aim of this paper is to provide an overview of the functional roles of human BAG proteins from the perspective of protein intrinsic disorder which will provide a means for understanding their binding promiscuity, multifunctionality, and relation to the pathogenesis of various diseases.

The Participation of the Intrinsically Disordered Regions of the bHLH-PAS Transcription Factors in Disease Development

The basic helix–loop–helix/Per-ARNT-SIM (bHLH-PAS) proteins are a family of transcription factors regulating expression of a wide range of genes involved in different functions, ranging from differentiation and development control by oxygen and toxins sensing to circadian clock setting. In addition to the well-preserved DNA-binding bHLH and PAS domains, bHLH-PAS proteins contain long intrinsically disordered C-terminal regions, responsible for regulation of their activity. Our aim was to analyze the potential connection between disordered regions of the bHLH-PAS transcription factors, post-transcriptional modifications and liquid-liquid phase separation, in the context of disease-associated missense mutations. Highly flexible disordered regions, enriched in short motives which are more ordered, are responsible for a wide spectrum of interactions with transcriptional co-regulators. Based on our in silico analysis and taking into account the fact that the functions of transcription factors can be modulated by posttranslational modifications and spontaneous phase separation, we assume that the locations of missense mutations inducing disease states are clearly related to sequences directly undergoing these processes or to sequences responsible for their regulation.

Prediction of protein-binding residues: dichotomy of sequence-based methods developed using structured complexes versus disordered proteins

MOTIVATION

There are over 30 sequence-based predictors of the protein-binding residues (PBRs). They use either structure-annotated or disorder-annotated training datasets, potentially creating a dichotomy where the structure-/disorder-specific models may not be able to cross-over to accurately predict the other type. Moreover, the structure-trained predictors were shown to substantially cross-predict PBRs among residues that interact with non-protein partners (nucleic acids and small ligands). We address these issues by performing first-of-its-kind comparative study of a representative collection of disorder- and structure-trained predictors using a comprehensive benchmark set with the structure- and disorder-derived annotations of PBRs (to analyze the cross-over) and the protein-, nucleic acid- and small ligand-binding proteins (to study the cross-predictions).

RESULTS

Three predictors provide accurate results: SCRIBER, ANCHOR and disoRDPbind. Some of the structure-trained methods make accurate predictions on the structure-annotated proteins. Similarly, the disorder-trained predictors predict well on the disorder-annotated proteins. However, the considered predictors generally fail to cross-over, with the exception of SCRIBER. Our study also reveals that virtually all methods substantially cross-predict PBRs, except for SCRIBER for the structure-annotated proteins and disoRDPbind for the disorder-annotated proteins. We formulate a novel hybrid predictor, hybridPBRpred, that combines results produced by disoRDPbind and SCRIBER to accurately predict disorder- and structure-annotated PBRs. HybridPBRpred generates accurate results that cross-over structure- and disorder-annotated proteins and produces relatively low amount of cross-predictions, offering an accurate alternative to predict PBRs.

AVAILABILITY AND IMPLEMENTATION

HybridPBRpred webserver, benchmark dataset and supplementary information are available at http://biomine.cs.vcu.edu/servers/hybridPBRpred/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Multifunctionality and intrinsic disorder of royal jelly proteome

Royal Jelly (RJ) is a gelatinous white-yellowish fluid, possessing a sour taste and a slight phenolic smell that is secreted by the hypopharyngeal and mandibular salivary glands of the nurse honeybees, and is used in nutrition of larvae and adult queens. Similar to other substances associated with the activities of honeybees, RJ not only contains nutritive components, such as carbohydrates, proteins, peptides, lipids, vitamins, and mineral salts, but also represents a natural ingredient with cosmetic and health-promoting properties. RJ is characterized by remarkable multifunctionality, possessing numerous biological activities. Although this multifunctionality of RJ can be considered as a consequence of its complex nature, many proteins and peptides in RJ are polyfunctional entities themselves. In this article, we show that RJ proteins contain different levels of intrinsic disorder, have sites of post-translational modifications, can be found in multiple isoforms, and many of them possess disorder-based binding sites, suggesting that the conformational ensembles of the RJ proteins might undergo change as a result of their interaction with specific binding partners. All these observations suggest that the multifunctionality of proteins and peptides from RJ is determined by their structural heterogeneity and polymorphism, and serve as an illustration of the protein structure-function continuum concept.

Mutations in membrane-fusion subunit of spike glycoprotein play crucial role in the recent outbreak of COVID-19

Coronavirus disease‐2019 (COVID‐19), the ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is a major threat to the entire human race. It is reported that SARS‐CoV‐2 seems to have relatively low pathogenicity and higher transmissibility than previously outbroke SARS‐CoV. To explore the reason of the increased transmissibility of SARS‐CoV‐2 compared with SARS‐CoV, we have performed a comparative analysis on the structural proteins (spike, envelope, membrane, and nucleoprotein) of two viruses. Our analysis revealed that extensive substitutions of hydrophobic to polar and charged amino acids in spike glycoproteins of SARS‐CoV2 creates an intrinsically disordered region (IDR) at the beginning of membrane‐fusion subunit and intrinsically disordered residues in fusion peptide. IDR provides a potential site for proteolysis by furin and enriched disordered residues facilitate prompt fusion of the SARS‐CoV2 with host membrane by recruiting molecular recognition features. Here, we have hypothesized that mutation‐driven accumulation of intrinsically disordered residues in spike glycoproteins play dual role in enhancing viral transmissibility than previous SARS‐coronavirus. These analyses may help in epidemic surveillance and preventive measures against COVID‐19.

Spike glycoprotein of SARS‐CoV2 experiences higher synonymous and non‐synonymous substitution rates than other three structural (E, M, N) proteins.

Extensive hydrophobic to polar and charged amino acid substitutions in S proteins during evolution from SARS‐CoV generate intrinsically disordered residues in the membrane fusion subunit (S2) of S protein.

Intrinsically disordered region at the beginning of S2 offers cleavage site of furin protease and by virtue of their flexible nature, they provide sensitive site for efficient proteolysis to activate the fusion peptide.

Enrichment of intrinsically disordered residues in fusion peptide prompts rapid fusion of viral envelop with host membrane by recruiting several MoRFs.

Intrinsic disorderness in spike glycoproteins in SARS‐CoV2 play dual role in enhancing their transmissibility than previous SARS‐corona virus.

Decoding Protein-protein Interactions: An Overview

Drug discovery has focused on the paradigm "one drug, one target" for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.

Shell disorder and the HIV vaccine mystery: lessons from the legendary Oswald Avery

The search for a human immunodeficiency virus (HIV) vaccine has spanned nearly four decades without much success. A much needed paradigm shift can be found in the abnormally high levels of intrinsic disorder in the outer shells of HIVs, the hepatitis C virus (HCV), and herpes simplex viruses (HSVs), for which successful vaccines have not been established. On the other hand, this feature (high levels of intrinsic disorder in the outer shells) is completely absent in classic viruses for which effective vaccines are found, such as the rabies virus. The motions arising from the disordered outer shell result in the inability of antibodies to bind tightly to the polysaccharides on the viral surface proteins, and, therefore, induce inadequate immune response. Experiments conducted by the legendary Avery Oswald in the 1920s form the theoretical underpinning of this new model. Failures of the vaccines based on the HIV glycoprotein Gp120 and other vaccines can be traced back to the lack of understanding of the important roles of shell disorder in a "Trojan-horse" immune evasion mechanism utilized by the virus.Communicated by Ramaswamy H. Sarma.

Functional characterization of an unknown soybean intrinsically disordered protein in vitro and in Escherichia coli

Intrinsically disordered proteins (IDPs) possess a wide range of biological function in all organisms, however the specific functions of most IDPs are still unknown. Soybean LOC protein, LOC for short, is a heat-stable protein, which is more abundant in the stress-resistant radicles. Sequence alignment and phylogenetic analysis showed that LOC is a functionally unknown protein and conserved in Fabaceae. LOC, being enriched in most disorder-promoting residues and depleted in most order-promoting residues, was predicted to contain high levels of intrinsic disorder by several commonly used computational tools. However, it was also predicted to contain two disorder-based protein-protein binding sites and two short α-helical segments. The circular dichroism spectroscopic analysis showed that this protein is mostly disordered in water, but can form more α-helical structure in the presence of SDS and TFE. Functional in vitro studies showed that the LOC protein is able to prevent lactate dehydrogenase inactivation by freeze-thaw at a molar ratio of 10:1. Furthermore, in vivo analyses revealed the survival rate of Escherichia coli over-expressing LOC protein under the conditions of osmotic stress was noticeably increased in comparison with the control. These observations suggest that the intrinsically disordered protein LOC might serve as a chaperone and/or cell protector.

Molecular simulations of IDPs: From ensemble generation to IDP interactions leading to disorder-to-order transitions

Intrinsically disordered proteins (IDPs) lack a well-defined three-dimensional structure but do exhibit some dynamical and structural ordering. The structural plasticity of IDPs indicates that entropy-driven motions are crucial for their function. Many IDPs undergo function-related disorder-to-order transitions upon by their interaction with specific binding partners. Approaches that are based on both experimental and theoretical tools enable the biophysical characterization of IDPs. Molecular simulations provide insights into IDP structural ensembles and disorder-to-order transition mechanisms. However, such studies depend strongly on the chosen force field parameters and simulation techniques. In this chapter, we provide an overview of IDP characteristics, review all-atom force fields recently developed for IDPs, and present molecular dynamics-based simulation methods that allow IDP ensemble generation as well as the characterization of disorder-to-order transitions. In particular, we introduce metadynamics, replica exchange molecular dynamics simulations, and also kinetic models resulting from Markov State modeling, and provide various examples for the successful application of these simulation methods to IDPs.

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.