Genome-wide survey of putative RNA-binding proteins encoded in the human proteome

Novel biomolecules in targeted cancer therapy: a new approach towards precision medicine

Cancer is a major threat to human life around the globe, and the discovery of novel biomolecules continue to be an urgent therapeutic need that is still unmet. Precision medicine relies on targeted therapeutic strategies. Researchers are better equipped to develop therapies that target proteins as they understand more about the genetic alterations and molecules that cause progression of cancer. There has been a recent diversification of the sorts of targets exploited in treatment. Therapeutic antibody and biotechnology advancements enabled curative treatments to reach previously inaccessible sites. New treatment strategies have been initiated for several undruggable targets. The application of tailored therapy has been proven to have efficient results in controlling cancer progression. Novel biomolecules like SMDCs, ADCs, mABs, and PROTACS has gained vast attention in the recent years. Several studies have shown that using these novel technology helps in reducing the drug dosage as well as to overcome drug resistance in different cancer types. Therefore, it is crucial to fully untangle the mechanism and collect evidence to understand the significance of these novel drug targets and strategies. This review article will be discussing the importance and role of these novel biomolecules in targeted cancer therapies.

Aptamer-Based Targeted Protein Degradation

The selective removal of misfolded, aggregated, or aberrantly overexpressed protein plays an essential role in maintaining protein-dominated biological processes. In parallel, the precise knockout of abnormal proteins is inseparable from the accurate identification of proteins within complex environments. Guided by these precepts, small molecules, or antibodies, are commonly used as protein recognition tools for developing targeted protein degradation (TPD) technology. Indeed, TPD has shown tremendous prospects in chronic diseases, rare diseases, cancer research, and other fields. Meanwhile, aptamers are short RNA or DNA oligonucleotides that can bind to target proteins with high specificity and strong affinity. Accordingly, aptamers are actively used in designing and constructing TPD technology. In this perspective, we provide a brief introduction to TPD technology in its current progress, and we summarize its application challenges. Recent advances in aptamer-based TPD technology are reviewed, together with corresponding challenges and outlooks.

Computational tools to study RNA-protein complexes

RNA is the key player in many cellular processes such as signal transduction, replication, transport, cell division, transcription, and translation. These diverse functions are accomplished through interactions of RNA with proteins. However, protein–RNA interactions are still poorly derstood in contrast to protein–protein and protein–DNA interactions. This knowledge gap can be attributed to the limited availability of protein-RNA structures along with the experimental difficulties in studying these complexes. Recent progress in computational resources has expanded the number of tools available for studying protein-RNA interactions at various molecular levels. These include tools for predicting interacting residues from primary sequences, modelling of protein-RNA complexes, predicting hotspots in these complexes and insights into derstanding in the dynamics of their interactions. Each of these tools has its strengths and limitations, which makes it significant to select an optimal approach for the question of interest. Here we present a mini review of computational tools to study different aspects of protein-RNA interactions, with focus on overall application, development of the field and the future perspectives.

Landscape of functional interactions of human processive ribonucleases revealed by high-throughput siRNA screenings

Processive exoribonucleases are executors of RNA decay. In humans, their physical but not functional interactions were thoughtfully investigated. Here we have screened cells deficient in DIS3, XRN2, EXOSC10, DIS3L, and DIS3L2 with a custom siRNA library and determined their genetic interactions (GIs) with diverse pathways of RNA metabolism. We uncovered a complex network of positive interactions that buffer alterations in RNA degradation and reveal reciprocal cooperation with genes involved in transcription, RNA export, and splicing. Further, we evaluated the functional distinctness of nuclear DIS3 and cytoplasmic DIS3L using a library of all known genes associated with RNA metabolism. Our analysis revealed that DIS3 mutation suppresses RNA splicing deficiency, while DIS3L GIs disclose the interplay of cytoplasmic RNA degradation with nuclear RNA processing. Finally, genome-wide DIS3 GI map uncovered relations with genes not directly involved in RNA metabolism, like microtubule organization or regulation of telomerase activity.

RNA-PROTACs: Degraders of RNA-Binding Proteins

Defects in the functions of RNA binding proteins (RBPs) are at the origin of many diseases; however, targeting RBPs with conventional drugs has proven difficult. PROTACs are a new class of drugs that mediate selective degradation of a target protein through a cell's ubiquitination machinery. PROTACs comprise a moiety that binds the selected protein, conjugated to a ligand of an E3 ligase. Herein, we introduce RNA-PROTACs as a new concept in the targeting of RBPs. These chimeric structures employ small RNA mimics as targeting groups that dock the RNA-binding site of the RBP, whereupon a conjugated E3-recruiting peptide derived from the HIF-1α protein directs the RBP for proteasomal degradation. We performed a proof-of-concept demonstration with the degradation of two RBPs-a stem cell factor LIN28 and a splicing factor RBFOX1-and showed their use in cancer cell lines. The RNA-PROTAC approach opens the way to rapid, selective targeting of RBPs in a rational and general fashion.

Genetic information from discordant sibling pairs points to ESRP2 as a candidate trans-acting regulator of the CF modifier gene SCNN1B

SCNN1B encodes the beta subunit of the epithelial sodium channel ENaC. Previously, we reported an association between SNP markers of SCNN1B gene and disease severity in cystic fibrosis-affected sibling pairs. We hypothesized that factors interacting with the SCNN1B genomic sequence are responsible for intrapair discordance. Concordant and discordant pairs differed at six SCNN1B markers (Praw = 0.0075, Pcorr = 0.0397 corrected for multiple testing). To identify the factors binding to these six SCNN1B SNPs, we performed an electrophoretic mobility shift assay and captured the DNA-protein complexes. Based on protein mass spectrometry data, the epithelial splicing regulatory protein ESRP2 was identified when using SCNN1B-derived probes and the ESRP2-SCNN1B interaction was independently confirmed by coimmunoprecipitation assays. We observed an alternative SCNN1B transcript and demonstrated in 16HBE14o- cells that levels of this transcript are decreased upon ESRP2 silencing by siRNA. Furthermore, we confirmed that mildly and severely affected siblings have different ESPR2 genetic backgrounds and that ESRP2 markers are linked to the response of CF patients' nasal epithelium to amiloride, indicating ENaC involvement (Pbest = 0.0131, Pcorr = 0.068 for multiple testing). Our findings demonstrate that sibling pairs clinically discordant for CF can be used to identify meaningful DNA regulatory elements and interacting factors.

EcRBPome: a comprehensive database of all known E. coli RNA-binding proteins

The repertoire of RNA-binding proteins (RBPs) in bacteria play a crucial role in their survival, and interactions with the host machinery, but there is little information, record or characterisation in bacterial genomes. As a first step towards this, we have chosen the bacterial model system Escherichia coli, and organised all RBPs in this organism into a comprehensive database named EcRBPome. It contains RBPs recorded from 614 complete E. coli proteomes available in the RefSeq database (as of October 2018). The database provides various features related to the E. coli RBPs, like their domain architectures, PDB structures, GO and EC annotations etc. It provides the assembly, bioproject and biosample details of each strain, as well as cross-strain comparison of occurrences of various RNA-binding domains (RBDs). The percentage of RBPs, the abundance of the various RBDs harboured by each strain have been graphically represented in this database and available alongside other files for user download. To the best of our knowledge, this is the first database of its kind and we hope that it will be of great use to the biological community.

Bioinformatics Tools and Benchmarks for Computational Docking and 3D Structure Prediction of RNA-Protein Complexes

RNA-protein (RNP) interactions play essential roles in many biological processes, such as regulation of co-transcriptional and post-transcriptional gene expression, RNA splicing, transport, storage and stabilization, as well as protein synthesis. An increasing number of RNP structures would aid in a better understanding of these processes. However, due to the technical difficulties associated with experimental determination of macromolecular structures by high-resolution methods, studies on RNP recognition and complex formation present significant challenges. As an alternative, computational prediction of RNP interactions can be carried out. Structural models obtained by theoretical predictive methods are, in general, less reliable compared to models based on experimental measurements but they can be sufficiently accurate to be used as a basis for to formulating functional hypotheses. In this article, we present an overview of computational methods for 3D structure prediction of RNP complexes. We discuss currently available methods for macromolecular docking and for scoring 3D structural models of RNP complexes in particular. Additionally, we also review benchmarks that have been developed to assess the accuracy of these methods.

In Silico Prediction and Validation of Novel RNA Binding Proteins and Residues in the Human Proteome

Deciphering a complete landscape of protein-RNA interactions in the human proteome remains an elusive challenge. We computationally elucidate RNA binding proteins (RBPs) using an approach that complements previous efforts. We employ two modern complementary sequence-based methods that provide accurate predictions from the structured and the intrinsically disordered sequences, even in the absence of sequence similarity to the known RBPs. We generate and analyze putative RNA binding residues on the whole proteome scale. Using a conservative setting that ensures low, 5% false positive rate, we identify 1511 putative RBPs that include 281 known RBPs and 166 RBPs that were previously predicted. We empirically demonstrate that these overlaps are statistically significant. We also validate the putative RBPs based on two major hallmarks of their RNA binding residues: high levels of evolutionary conservation and enrichment in charged amino acids. Moreover, we show that the novel RBPs are significantly under-annotated functionally which coincides with the fact that they were not yet found to interact with RNAs. We provide two examples of our novel putative RBPs for which there is recent evidence of their interactions with RNAs. The dataset of novel putative RBPs and RNA binding residues for the future hypothesis generation is provided in the Supporting Information.

Evolutionary plasticity of the NHL domain underlies distinct solutions to RNA recognition

RNA-binding proteins regulate all aspects of RNA metabolism. Their association with RNA is mediated by RNA-binding domains, of which many remain uncharacterized. A recently reported example is the NHL domain, found in prominent regulators of cellular plasticity like the C. elegans LIN-41. Here we employ an integrative approach to dissect the RNA specificity of LIN-41. Using computational analysis, structural biology, and in vivo studies in worms and human cells, we find that a positively charged pocket, specific to the NHL domain of LIN-41 and its homologs (collectively LIN41), recognizes a stem-loop RNA element, whose shape determines the binding specificity. Surprisingly, the mechanism of RNA recognition by LIN41 is drastically different from that of its more distant relative, the fly Brat. Our phylogenetic analysis suggests that this reflects a rapid evolution of the domain, presenting an interesting example of a conserved protein fold that acquired completely different solutions to RNA recognition.

The C. elegans LIN-41 and its homologs, including human TRIM71/LIN41, contain the RNA binding NHL domain. Here the authors combine computational analysis, structural biology and in vivo studies, to explain how these proteins bind RNA and how rapid evolution of NHL domains resulted in different solutions to RNA recognition.

RNA-binding activity of TRIM25 is mediated by its PRY/SPRY domain and is required for ubiquitination

BACKGROUND

TRIM25 is a novel RNA-binding protein and a member of the Tripartite Motif (TRIM) family of E3 ubiquitin ligases, which plays a pivotal role in the innate immune response. However, there is scarce knowledge about its RNA-related roles in cell biology. Furthermore, its RNA-binding domain has not been characterized.

RESULTS

Here, we reveal that the RNA-binding activity of TRIM25 is mediated by its PRY/SPRY domain, which we postulate to be a novel RNA-binding domain. Using CLIP-seq and SILAC-based co-immunoprecipitation assays, we uncover TRIM25's endogenous RNA targets and protein binding partners. We demonstrate that TRIM25 controls the levels of Zinc Finger Antiviral Protein (ZAP). Finally, we show that the RNA-binding activity of TRIM25 is important for its ubiquitin ligase activity towards itself (autoubiquitination) and its physiologically relevant target ZAP.

CONCLUSIONS

Our results suggest that many other proteins with the PRY/SPRY domain could have yet uncharacterized RNA-binding potential. Together, our data reveal new insights into the molecular roles and characteristics of RNA-binding E3 ubiquitin ligases and demonstrate that RNA could be an essential factor in their enzymatic activity.

Bioinformatics comparisons of RNA-binding proteins of pathogenic and non-pathogenic Escherichia coli strains reveal novel virulence factors

Background

Pathogenic bacteria have evolved various strategies to counteract host defences. They are also exposed to environments that are undergoing constant changes. Hence, in order to survive, bacteria must adapt themselves to the changing environmental conditions by performing regulations at the transcriptional and/or post-transcriptional levels. Roles of RNA-binding proteins (RBPs) as virulence factors have been very well studied. Here, we have used a sequence search-based method to compare and contrast the proteomes of 16 pathogenic and three non-pathogenic E. coli strains as well as to obtain a global picture of the RBP landscape (RBPome) in E. coli.

Results

Our results show that there are no significant differences in the percentage of RBPs encoded by the pathogenic and the non-pathogenic E. coli strains. The differences in the types of Pfam domains as well as Pfam RNA-binding domains, encoded by these two classes of E. coli strains, are also insignificant. The complete and distinct RBPome of E. coli has been established by studying all known E. coli strains till date. We have also identified RBPs that are exclusive to pathogenic strains, and most of them can be exploited as drug targets since they appear to be non-homologous to their human host proteins. Many of these pathogen-specific proteins were uncharacterised and their identities could be resolved on the basis of sequence homology searches with known proteins. Detailed structural modelling, molecular dynamics simulations and sequence comparisons have been pursued for selected examples to understand differences in stability and RNA-binding.

Conclusions

The approach used in this paper to cross-compare proteomes of pathogenic and non-pathogenic strains may also be extended to other bacterial or even eukaryotic proteomes to understand interesting differences in their RBPomes. The pathogen-specific RBPs reported in this study, may also be taken up further for clinical trials and/or experimental validations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4045-3) contains supplementary material, which is available to authorized users.

The role of Trim25 in development, disease and RNA metabolism

Trim25 is a member of the tripartite motif family of E3 ubiquitin ligases. It plays major roles in innate immunity and defence against viral infection, control of cell proliferation and migration of cancer cells. Recent work identified Trim25 as being able to bind to RNA and to regulate Lin28a-mediated uridylation of pre-let-7. Here we review the current knowledge of the role of Trim25 in development, disease and RNA metabolism.

Surface charge tuneable fluorescent protein-based logic gates for smart delivery of nucleic acids

A versatile bio-logic system based on H₃₉GFP is operated in living cells with transfection of functional nucleic acids as the readout.

RStrucFam: a web server to associate structure and cognate RNA for RNA-binding proteins from sequence information

Background

RNA-binding proteins (RBPs) interact with their cognate RNA(s) to form large biomolecular assemblies. They are versatile in their functionality and are involved in a myriad of processes inside the cell. RBPs with similar structural features and common biological functions are grouped together into families and superfamilies. It will be useful to obtain an early understanding and association of RNA-binding property of sequences of gene products. Here, we report a web server, RStrucFam, to predict the structure, type of cognate RNA(s) and function(s) of proteins, where possible, from mere sequence information.

Results

The web server employs Hidden Markov Model scan (hmmscan) to enable association to a back-end database of structural and sequence families. The database (HMMRBP) comprises of 437 HMMs of RBP families of known structure that have been generated using structure-based sequence alignments and 746 sequence-centric RBP family HMMs. The input protein sequence is associated with structural or sequence domain families, if structure or sequence signatures exist. In case of association of the protein with a family of known structures, output features like, multiple structure-based sequence alignment (MSSA) of the query with all others members of that family is provided. Further, cognate RNA partner(s) for that protein, Gene Ontology (GO) annotations, if any and a homology model of the protein can be obtained. The users can also browse through the database for details pertaining to each family, protein or RNA and their related information based on keyword search or RNA motif search.

Conclusions

RStrucFam is a web server that exploits structurally conserved features of RBPs, derived from known family members and imprinted in mathematical profiles, to predict putative RBPs from sequence information. Proteins that fail to associate with such structure-centric families are further queried against the sequence-centric RBP family HMMs in the HMMRBP database. Further, all other essential information pertaining to an RBP, like overall function annotations, are provided. The web server can be accessed at the following link: http://caps.ncbs.res.in/rstrucfam.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1289-x) contains supplementary material, which is available to authorized users.