Exploring Short Linear Motifs Using the ELM Database and Tools

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.

The HABD: Home of All Biological Databases Empowering Biological Research With Cutting-Edge Database Systems

The emergence of computer technologies and computing power has led to the development of several database systems that provide standardized access to vast quantities of data, making it possible to collect, search, index, evaluate, and extract useful knowledge across various fields. The Home of All Biological Databases (HABD) has been established as a continually expanding platform that aims to store, organize, and distribute biological data in a searchable manner, removing all dead and non-accessible data. The platform meticulously categorizes data into various categories, such as COVID-19 Pandemic Database (CO-19PDB), Database relevant to Human Research (DBHR), Cancer Research Database (CRDB), Latest Database of Protein Research (LDBPR), Fungi Databases Collection (FDBC), and many other databases that are categorized based on biological phenomena. It currently provides a total of 22 databases, including 6 published, 5 submitted, and the remaining in various stages of development. These databases encompass a range of areas, including phytochemical-specific and plastic biodegradation databases. HABD is equipped with search engine optimization (SEO) analyzer and Neil Patel tools, which ensure excellent SEO and high-speed value. With timely updates, HABD aims to facilitate the processing and visualization of data for scientists, providing a one-stop-shop for all biological databases. Computer platforms, such as PhP, html, CSS, Java script and Biopython, are used to build all the databases. © 2024 Wiley Periodicals LLC.

The next wave of interactomics: Mapping the SLiM-based interactions of the intrinsically disordered proteome

Short linear motifs (SLiMs) are a unique and ubiquitous class of protein interaction modules that perform key regulatory functions and drive dynamic complex formation. For decades, interactions mediated by SLiMs have accumulated through detailed low-throughput experiments. Recent methodological advances have opened this previously underexplored area of the human interactome to high-throughput protein-protein interaction discovery. In this article, we discuss that SLiM-based interactions represent a significant blind spot in the current interactomics data, introduce the key methods that are illuminating the elusive SLiM-mediated interactome of the human cell on a large scale, and discuss the implications for the field.

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.

Integrating protein copy numbers with interaction networks to quantify stoichiometry in clathrin-mediated endocytosis

Proteins that drive processes like clathrin-mediated endocytosis (CME) are expressed at copy numbers within a cell and across cell types varying from hundreds (e.g. auxilin) to millions (e.g. clathrin). These variations contain important information about function, but without integration with the interaction network, they cannot capture how supply and demand for each protein depends on binding to shared and distinct partners. Here we construct the interface-resolved network of 82 proteins involved in CME and establish a metric, a stoichiometric balance ratio (SBR), that quantifies whether each protein in the network has an abundance that is sub- or super-stoichiometric dependent on the global competition for binding. We find that highly abundant proteins (like clathrin) are super-stoichiometric, but that not all super-stoichiometric proteins are highly abundant, across three cell populations (HeLa, fibroblast, and neuronal synaptosomes). Most strikingly, within all cells there is significant competition to bind shared sites on clathrin and the central AP-2 adaptor by other adaptor proteins, resulting in most being in excess supply. Our network and systematic analysis, including response to perturbations of network components, show how competition for shared binding sites results in functionally similar proteins having widely varying stoichiometries, due to variations in both abundance and their unique network of binding partners.

Intrinsic disorder in proteins associated with oxidative stress-induced JNK signaling

The c-Jun N-terminal kinase (JNK) signaling cascade is a mitogen-activated protein kinase (MAPK) signaling pathway that can be activated in response to a wide range of environmental stimuli. Based on the type, degree, and duration of the stimulus, the JNK signaling cascade dictates the fate of the cell by influencing gene expression through its substrate transcription factors. Oxidative stress is a result of a disturbance in the pro-oxidant/antioxidant homeostasis of the cell and is associated with a large number of diseases, such as neurodegenerative disorders, cancer, diabetes, cardiovascular diseases, and disorders of the immune system, where it activates the JNK signaling pathway. Among different biological roles ascribed to the intrinsically disordered proteins (IDPs) and hybrid proteins containing ordered domains and intrinsically disordered protein regions (IDPRs) are signaling hub functions, as intrinsic disorder allows proteins to undertake multiple interactions, each with a different consequence. In order to ensure precise signaling, the cellular abundance of IDPs is highly regulated, and mutations or changes in abundance of IDPs/IDPRs are often associated with disease. In this study, we have used a combination of six disorder predictors to evaluate the presence of intrinsic disorder in proteins of the oxidative stress-induced JNK signaling cascade, and as per our findings, none of the 18 proteins involved in this pathway are ordered. The highest level of intrinsic disorder was observed in the scaffold proteins, JIP1, JIP2, JIP3; dual specificity phosphatases, MKP5, MKP7; 14-3-3ζ and transcription factor c-Jun. The MAP3Ks, MAP2Ks, MAPKs, TRAFs, and thioredoxin were the proteins that were predicted to be moderately disordered. Furthermore, to characterize the predicted IDPs/IDPRs in the proteins of the JNK signaling cascade, we identified the molecular recognition features (MoRFs), posttranslational modification (PTM) sites, and short linear motifs (SLiMs) associated with the disordered regions. These findings will serve as a foundation for experimental characterization of disordered regions in these proteins, which represents a crucial step for a better understanding of the roles of IDPRs in diseases associated with this important pathway.

DBHR: a collection of databases relevant to human research

BACKGROUND

The achievement of the human genome project provides a basis for the systematic study of the human genome from evolutionary history to disease-specific medicine. With the explosive growth of biological data, a growing number of biological databases are being established to support human-related research.

OBJECTIVE

The main objective of our study is to store, organize and share data in a structured and searchable manner. In short, we have planned the future development of new features in the database research area.

MATERIALS & METHODS

In total, we collected and integrated 680 human databases from scientific published work. Multiple options are presented for accessing the data, while original links and short descriptions are also presented for each database.

RESULTS & DISCUSSION

We have provided the latest collection of human research databases on a single platform with six categories: DNA database, RNA database, protein database, expression database, pathway database and disease database.

CONCLUSION

Taken together, our database will be useful for further human research study and will be modified over time. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://habdsk.org/database.php.

A functionally divergent intrinsically disordered region underlying the conservation of stochastic signaling

Stochastic signaling dynamics expand living cells' information processing capabilities. An increasing number of studies report that regulators encode information in their pulsatile dynamics. The evolutionary mechanisms that lead to complex signaling dynamics remain uncharacterized, perhaps because key interactions of signaling proteins are encoded in intrinsically disordered regions (IDRs), whose evolution is difficult to analyze. Here we focused on the IDR that controls the stochastic pulsing dynamics of Crz1, a transcription factor in fungi downstream of the widely conserved calcium signaling pathway. We find that Crz1 IDRs from anciently diverged fungi can all respond transiently to calcium stress; however, only Crz1 IDRs from the Saccharomyces clade support pulsatility, encode extra information, and rescue fitness in competition assays, while the Crz1 IDRs from distantly related fungi do none of the three. On the other hand, we find that Crz1 pulsing is conserved in the distantly related fungi, consistent with the evolutionary model of stabilizing selection on the signaling phenotype. Further, we show that a calcineurin docking site in a specific part of the IDRs appears to be sufficient for pulsing and show evidence for a beneficial increase in the relative calcineurin affinity of this docking site. We propose that evolutionary flexibility of functionally divergent IDRs underlies the conservation of stochastic signaling by stabilizing selection.

Short Linear Motifs Characterizing Snake Venom and Mammalian Phospholipases A2

Snake venom phospholipases A2 (PLA2s) have sequences and structures very similar to those of mammalian group I and II secretory PLA2s, but they possess many toxic properties, ranging from the inhibition of coagulation to the blockage of nerve transmission, and the induction of muscle necrosis. The biological properties of these proteins are not only due to their enzymatic activity, but also to protein–protein interactions which are still unidentified. Here, we compare sequence alignments of snake venom and mammalian PLA2s, grouped according to their structure and biological activity, looking for differences that can justify their different behavior. This bioinformatics analysis has evidenced three distinct regions, two central and one C-terminal, having amino acid compositions that distinguish the different categories of PLA2s. In these regions, we identified short linear motifs (SLiMs), peptide modules involved in protein–protein interactions, conserved in mammalian and not in snake venom PLA2s, or vice versa. The different content in the SLiMs of snake venom with respect to mammalian PLA2s may result in the formation of protein membrane complexes having a toxic activity, or in the formation of complexes whose activity cannot be blocked due to the lack of switches in the toxic PLA2s, as the motif recognized by the prolyl isomerase Pin1.

The dark side of Alzheimer's disease: unstructured biology of proteins from the amyloid cascade signaling pathway

Alzheimer's disease (AD) is a leading cause of age-related dementia worldwide. Despite more than a century of intensive research, we are not anywhere near the discovery of a cure for this disease or a way to prevent its progression. Among the various molecular mechanisms proposed for the description of the pathogenesis and progression of AD, the amyloid cascade hypothesis, according to which accumulation of a product of amyloid precursor protein (APP) cleavage, amyloid β (Aβ) peptide, induces pathological changes in the brain observed in AD, occupies a unique niche. Although multiple proteins have been implicated in this amyloid cascade signaling pathway, their structure-function relationships are mostly unexplored. However, it is known that two major proteins related to AD pathology, Aβ peptide, and microtubule-associated protein tau belong to the category of intrinsically disordered proteins (IDPs), which are the functionally important proteins characterized by a lack of fixed, ordered three-dimensional structure. IDPs and intrinsically disordered protein regions (IDPRs) play numerous vital roles in various cellular processes, such as signaling, cell cycle regulation, macromolecular recognition, and promiscuous binding. However, the deregulation and misfolding of IDPs may lead to disturbed signaling, interactions, and disease pathogenesis. Often, molecular recognition-related IDPs/IDPRs undergo disorder-to-order transition upon binding to their biological partners and contain specific disorder-based binding motifs, known as molecular recognition features (MoRFs). Knowing the intrinsic disorder status and disorder-based functionality of proteins associated with amyloid cascade signaling pathway may help to untangle the mechanisms of AD pathogenesis and help identify therapeutic targets. In this paper, we have used multiple computational tools to evaluate the presence of intrinsic disorder and MoRFs in 27 proteins potentially relevant to the amyloid cascade signaling pathway. Among these, BIN1, APP, APOE, PICALM, PSEN1 and CD33 were found to be highly disordered. Furthermore, their disorder-based binding regions and associated short linear motifs have also been identified. These findings represent important foundation for the future research, and experimental characterization of disordered regions in these proteins is required to better understand their roles in AD pathogenesis.

Unique and exclusive peptide signatures directly identify intrinsically disordered proteins from sequences without structural information

Intrinsically disordered proteins are now widely accepted to play crucial roles in biological functions. Identification of signatures of intrinsic disorder is one of the key steps towards building a proper repertoire for their occurrence in proteomes. In this work, systematic computational synthesis of a library of all possible (3368400) dipeptides, tripeptides, tetrapeptides and pentapeptides using the natural 20 amino acids allowed us to identify 36 unique tetrapeptides present exclusively in intrinsically disordered proteins and absent in the complete primary sequence space of naturally occurring structured proteins. Further, out of more than 530000 known naturally occurring primary sequences without any structural information, 1349 sequences contain the above identified unique signatures of intrinsic disorder. These sequences, having cellular functions varying from housekeeping to metabolic to transport, more than double the number of the currently known intrinsically disordered proteins. On similar lines, we report that 26577 pentapeptide signatures exclusive to intrinsically disordered proteins, and absent in naturally occurring structured proteins, identify ∼50% of more than half-a-million curated protein sequences without structural information to be intrinsically disordered. The results reported are a major leap forward in exploring functional manifestations of intrinsically disordered proteins.Communicated by Ramaswamy H. Sarma.

New technologies to analyse protein function: an intrinsic disorder perspective

Functions of intrinsically disordered proteins do not require structure. Such structure-independent functionality has melted away the classic rigid "lock and key" representation of structure-function relationships in proteins, opening a new page in protein science, where molten keys operate on melted locks and where conformational flexibility and intrinsic disorder, structural plasticity and extreme malleability, multifunctionality and binding promiscuity represent a new-fangled reality. Analysis and understanding of this new reality require novel tools, and some of the techniques elaborated for the examination of intrinsically disordered protein functions are outlined in this review.

How to Annotate and Submit a Short Linear Motif to the Eukaryotic Linear Motif Resource

Over the past few years, it has become apparent that approximately 35% of the human proteome consists of intrinsically disordered regions. Many of these disordered regions are rich in short linear motifs (SLiMs) which mediate protein-protein interactions. Although these motifs are short and often partially conserved, they are involved in many important aspects of protein function, including cleavage, targeting, degradation, docking, phosphorylation, and other posttranslational modifications. The Eukaryotic Linear Motif resource (ELM) was established over 15 years ago as a repository to store and catalogue the scientific discoveries of motifs. Each motif in the database is annotated and curated manually, based on the experimental evidence gathered from publications. The entries themselves are submitted to ELM by filling in two annotation templates designed for motif class and motif instance annotation. In this protocol, we describe the steps involved in annotating new motifs and how to submit them to ELM.

Resources to Discover and Use Short Linear Motifs in Viral Proteins

Viral proteins evade host immune function by molecular mimicry, often achieved by short linear motifs (SLiMs) of three to ten consecutive amino acids (AAs). Motif mimicry tolerates mutations, evolves quickly to modify interactions with the host, and enables modular interactions with protein complexes. Host cells cannot easily coordinate changes to conserved motif recognition and binding interfaces under selective pressure to maintain critical signaling pathways. SLiMs offer potential for use in synthetic biology, such as better immunogens and therapies, but may also present biosecurity challenges. We survey viral uses of SLiMs to mimic host proteins, and information resources available for motif discovery. As the number of examples continues to grow, knowledge management tools are essential to help organize and compare new findings.

SLiM-Enrich: computational assessment of protein-protein interaction data as a source of domain-motif interactions

Many important cellular processes involve protein–protein interactions (PPIs) mediated by a Short Linear Motif (SLiM) in one protein interacting with a globular domain in another. Despite their significance, these domain-motif interactions (DMIs) are typically low affinity, which makes them challenging to identify by classical experimental approaches, such as affinity pulldown mass spectrometry (AP-MS) and yeast two-hybrid (Y2H). DMIs are generally underrepresented in PPI networks as a result. A number of computational methods now exist to predict SLiMs and/or DMIs from experimental interaction data but it is yet to be established how effective different PPI detection methods are for capturing these low affinity SLiM-mediated interactions. Here, we introduce a new computational pipeline (SLiM-Enrich) to assess how well a given source of PPI data captures DMIs and thus, by inference, how useful that data should be for SLiM discovery. SLiM-Enrich interrogates a PPI network for pairs of interacting proteins in which the first protein is known or predicted to interact with the second protein via a DMI. Permutation tests compare the number of known/predicted DMIs to the expected distribution if the two sets of proteins are randomly associated. This provides an estimate of DMI enrichment within the data and the false positive rate for individual DMIs. As a case study, we detect significant DMI enrichment in a high-throughput Y2H human PPI study. SLiM-Enrich analysis supports Y2H data as a source of DMIs and highlights the high false positive rates associated with naïve DMI prediction. SLiM-Enrich is available as an R Shiny app. The code is open source and available via a GNU GPL v3 license at: https://github.com/slimsuite/SLiMEnrich. A web server is available at: http://shiny.slimsuite.unsw.edu.au/SLiMEnrich/.

The C-terminal coiled-coil domain of Corynebacterium diphtheriae DIP0733 is crucial for interaction with epithelial cells and pathogenicity in invertebrate animal model systems

Background

Corynebacterium diphtheriae is the etiologic agent of diphtheria and different systemic infections. The bacterium has been classically described as an extracellular pathogen. However, a number of studies revealed its ability to invade epithelial cells, indicating a more complex pathogen-host interaction. The molecular mechanisms controlling and facilitating internalization of C. diphtheriae still remains unclear. Recently, the DIP0733 transmembrane protein was found to play an important role in the interaction with matrix proteins and cell surfaces, nematode colonization, cellular internalization and induction of cell death.

Results

In this study, we identified a number of short linear motifs and structural elements of DIP0733 with putative importance in virulence, using bioinformatic approaches. A C-terminal coiled-coil region of the protein was considered particularly important, since it was found only in DIP0733 homologs in pathogenic Corynebacterium species but not in non-pathogenic corynebacteria. Infections of epithelial cells and transepithelial resistance assays revealed that bacteria expressing the truncated form of C. diphtheriae DIP0733 and C. glutamicum DIP0733 homolog are less virulent, while the fusion of the coiled-coil sequence to the DIP0733 homolog from C. glutamicum resulted in increased pathogenicity. These results were supported by nematode killing assays and experiments using wax moth larvae as invertebrate model systems.

Conclusions

Our data indicate that the coil-coiled domain of DIP0733 is crucial for interaction with epithelial cells and pathogenicity in invertebrate animal model systems.

Electronic supplementary material

The online version of this article (10.1186/s12866-018-1247-z) contains supplementary material, which is available to authorized users.

What We Learned From Big Data for Autophagy Research

Autophagy is the process by which cytoplasmic components are engulfed in double-membraned vesicles before being delivered to the lysosome to be degraded. Defective autophagy has been linked to a vast array of human pathologies. The molecular mechanism of the autophagic machinery is well-described and has been extensively investigated. However, understanding the global organization of the autophagy system and its integration with other cellular processes remains a challenge. To this end, various bioinformatics and network biology approaches have been developed by researchers in the last few years. Recently, large-scale multi-omics approaches (like genomics, transcriptomics, proteomics, lipidomics, and metabolomics) have been developed and carried out specifically focusing on autophagy, and generating multi-scale data on the related components. In this review, we outline recent applications of in silico investigations and big data analyses of the autophagy process in various biological systems.

PSSMSearch: a server for modeling, visualization, proteome-wide discovery and annotation of protein motif specificity determinants

There is a pressing need for in silico tools that can aid in the identification of the complete repertoire of protein binding (SLiMs, MoRFs, miniMotifs) and modification (moiety attachment/removal, isomerization, cleavage) motifs. We have created PSSMSearch, an interactive web-based tool for rapid statistical modeling, visualization, discovery and annotation of protein motif specificity determinants to discover novel motifs in a proteome-wide manner. PSSMSearch analyses proteomes for regions with significant similarity to a motif specificity determinant model built from a set of aligned motif-containing peptides. Multiple scoring methods are available to build a position-specific scoring matrix (PSSM) describing the motif specificity determinant model. This model can then be modified by a user to add prior knowledge of specificity determinants through an interactive PSSM heatmap. PSSMSearch includes a statistical framework to calculate the significance of specificity determinant model matches against a proteome of interest. PSSMSearch also includes the SLiMSearch framework's annotation, motif functional analysis and filtering tools to highlight relevant discriminatory information. Additional tools to annotate statistically significant shared keywords and GO terms, or experimental evidence of interaction with a motif-recognizing protein have been added. Finally, PSSM-based conservation metrics have been created for taxonomic range analyses. The PSSMSearch web server is available at http://slim.ucd.ie/pssmsearch/.

The present and the future of motif-mediated protein-protein interactions

Protein-protein interactions (PPIs) are essential to governing virtually all cellular processes. Of particular importance are the versatile motif-mediated interactions (MMIs), which are thus far underrepresented in available interaction data. This is largely due to technical difficulties inherent in the properties of MMIs, but due to the increasing recognition of the vital roles of MMIs in biology, several systematic approaches have recently been developed to detect novel MMIs. Consequently, rapidly growing numbers of motifs are being identified and pursued further for therapeutic applications. In this review, we discuss the current understanding on the diverse functions and disease-relevance of MMIs, the key methodologies for detection of MMIs, and the potential of MMIs for drug development.

The eukaryotic linear motif resource - 2018 update

Short linear motifs (SLiMs) are protein binding modules that play major roles in almost all cellular processes. SLiMs are short, often highly degenerate, difficult to characterize and hard to detect. The eukaryotic linear motif (ELM) resource (elm.eu.org) is dedicated to SLiMs, consisting of a manually curated database of over 275 motif classes and over 3000 motif instances, and a pipeline to discover candidate SLiMs in protein sequences. For 15 years, ELM has been one of the major resources for motif research. In this database update, we present the latest additions to the database including 32 new motif classes, and new features including Uniprot and Reactome integration. Finally, to help provide cellular context, we present some biological insights about SLiMs in the cell cycle, as targets for bacterial pathogenicity and their functionality in the human kinome.