Computational Identification of Post Translational Modification Regulated RNA Binding Protein Motifs

RNA and its associated RNA binding proteins (RBPs) mitigate a diverse array of cellular functions and phenotypes. The interactions between RNA and RBPs are implicated in many roles of biochemical processing by the cell such as localization, protein translation, and RNA stability. Recent discoveries of novel mechanisms that are of significant evolutionary advantage between RBPs and RNA include the interaction of the RBP with the 3’ and 5’ untranslated region (UTR) of target mRNA. These mechanisms are shown to function through interaction of a trans-factor (RBP) and a cis-regulatory element (3’ or 5’ UTR) by the binding of a RBP to a regulatory-consensus nucleic acid motif region that is conserved throughout evolution. Through signal transduction, regulatory RBPs are able to temporarily dissociate from their target sites on mRNAs and induce translation, typically through a post-translational modification (PTM). These small, regulatory motifs located in the UTR of mRNAs are subject to a loss-of-function due to single polymorphisms or other mutations that disrupt the motif and inhibit the ability to associate into the complex with RBPs. The identification of a consensus motif for a given RBP is difficult, time consuming, and requires a significant degree of experimentation to identify each motif-containing gene on a genomic scale. We have developed a computational algorithm to analyze high-throughput genomic arrays that contain differential binding induced by a PTM for a RBP of interest–RBP-PTM Target Scan (RPTS). We demonstrate the ability of this application to accurately predict a PTM-specific binding motif to an RBP that has no antibody capable of distinguishing the PTM of interest, negating the use of in-vitro exonuclease digestion techniques.     

New approaches to target RNA binding proteins

RNA binding proteins (RBPs) are a large and diverse class of proteins that regulate all aspects of RNA biology. As RBP dysregulation has been implicated in a number of human disorders, including cancers and neurodegenerative disease, small molecule chemical probes that target individual RBPs represent useful tools for deciphering RBP function and guiding the production of new therapeutics. While RBPs are often thought of as tough-to-drug, the discovery of a number of small molecules that target RBPs has spurred considerable recent interest in new strategies for RBP chemical probe discovery. Here we review current and emerging technologies for high throughput RBP-small molecule screening that we expect will help unlock the full therapeutic potential of this exciting protein class.     

Global signatures of protein binding on structured RNAs in Saccharomyces cerevisiae

Protein binding is essential to the transport,decay and regulation of almost all RNA molecules.However,the structural preference of protein binding on RNAs and their cellular functions and dynamics upon changing environmental conditions are poorly understood.Here,we integrated various high-throughput data and introduced a computational framework to describe the global interactions between RNA binding proteins(RBPs)and structured RNAs in yeast at single-nucleotide resolution.We found that on average,in terms of percent total lengths,~15%of mRNA untranslated regions(UTRs),~37%of canonical non-coding RNAs(ncRNAs)and~11%of long ncRNAs(lncRNAs)are bound by proteins.The RBP binding sites,in general,tend to occur at single-stranded loops,with evolutionarily conserved signatures,and often facilitate a specific RNA structure conformation in vivo.We found that four nucleotide modifications of tRNA are significantly associated with RBP binding.We also identified various structural motifs bound by RBPs in the UTRs of mRNAs,associated with localization,degradation and stress responses.Moreover,we identified>200 novel lncRNAs bound by RBPs,and about half of them contain conserved secondary structures.We present the first ensemble pattern of RBP binding sites in the structured non-coding regions of a eukaryotic genome,emphasizing their structural context and cellular functions.     

The Plant PTM Viewer,a central resource for exploring plant protein modifications

Post‐translational modifications (PTMs) of proteins are central in any kind of cellular signaling. Modern mass spectrometry technologies enable comprehensive identification and quantification of various PTMs. Given the increased numbers and types of mapped protein modifications, a database is necessary that simultaneously integrates and compares site‐specific information for different PTMs, especially in plants for which the available PTM data are poorly catalogued. Here, we present the Plant PTM Viewer (http://www.psb.ugent.be/PlantPTMViewer), an integrative PTM resource that comprises approximately 370 000 PTM sites for 19 types of protein modifications in plant proteins from five different species. The Plant PTM Viewer provides the user with a protein sequence overview in which the experimentally evidenced PTMs are highlighted together with an estimate of the confidence by which the modified peptides and, if possible, the actual modification sites were identified and with functional protein domains or active site residues. The PTM sequence search tool can query PTM combinations in specific protein sequences, whereas the PTM BLAST tool searches for modified protein sequences to detect conserved PTMs in homologous sequences. Taken together, these tools help to assume the role and potential interplay of PTMs in specific proteins or within a broader systems biology context. The Plant PTM Viewer is an open repository that allows the submission of mass spectrometry‐based PTM data to remain at pace with future PTM plant studies.     

High throughput platform to explore RNA–protein interactomes

RNA binding proteins (RBPs) and RNA interaction is an emerging topic in molecular biology. Many reports showed that such interactions contribute to many cellular processes as well as disease development. Several standard in vitro and in vivo methods were developed to fulfill the needs of this RBP–RNA interaction study to explore their biological functions. However, these methods have their limitations in terms of throughput. In this review, we emphasize two important high throughput methods to studying RBP–RNA interactions, affinity purification and protein microarray. These methods have recently become robust techniques regarding their efficiency in systematically analyzing RBP–RNA interactions. Here, we provide technique overviews, strategies and applications of these methods during biological research. Although these technologies are just beginning to be explored, they will be most important methods in this study.     

Directed evolution of orthogonal RNA–RBP pairs through library-vs-library in vitro selection

RNA-binding proteins (RBPs) and their RNA ligands play many critical roles in gene regulation and RNA processing in cells. They are also useful for various applications in cell biology and synthetic biology. However, re-engineering novel and orthogonal RNA–RBP pairs from natural components remains challenging while such synthetic RNA–RBP pairs could significantly expand the RNA–RBP toolbox for various applications. Here, we report a novel library-vs-library in vitro selection strategy based on Phage Display coupled with Systematic Evolution of Ligands by EXponential enrichment (PD-SELEX). Starting with pools of 1.1 × 10¹² unique RNA sequences and 4.0 × 10⁸ unique phage-displayed L7Ae-scaffold (LS) proteins, we selected RNA–RBP complexes through a two-step affinity purification process. After six rounds of library-vs-library selection, the selected RNAs and LS proteins were analyzed by next-generation sequencing (NGS). Further deconvolution of the enriched RNA and LS protein sequences revealed two synthetic and orthogonal RNA–RBP pairs that exhibit picomolar affinity and >4000-fold selectivity.     

Consequences of post-translational modifications on amyloid proteins as revealed by protein semisynthesis

Alterations to the global levels of certain types of post-translational modifications (PTMs) are commonly observed in neurodegenerative diseases. The net influence of these PTM changes to the progression of these diseases can be deduced from cellular and animal studies. However, at the molecular level, how one PTM influences a given protein is not uniform and cannot be easily generalized from systemic observations, thus requiring protein-specific interrogations. Given that protein aggregation is a shared pathological hallmark in neurodegeneration, it is important to understand how these PTMs affect the behavior of amyloid-forming proteins. For this purpose, protein semisynthesis techniques, largely via native chemical and expressed protein ligation, have been widely used. These approaches have thus far led to our increased understanding of the site-specific consequences of certain PTMs to amyloidogenic proteins’ endogenous function, their propensity for aggregation, and the structural variations these PTMs induce toward the aggregates formed.     

Phosphorylation regulates arginine-rich RNA-binding protein solubility and oligomerization

Posttranslational modifications (PTMs) such as phosphorylation of RNA-binding proteins (RBPs) regulate several critical steps in RNA metabolism, including spliceosome assembly, alternative splicing, and mRNA export. Notably, serine-/arginine- (SR)-rich RBPs are densely phosphorylated compared with the remainder of the proteome. Previously, we showed that dephosphorylation of the splicing factor SRSF2 regulated increased interactions with similar arginine-rich RBPs U1-70K and LUC7L3. However, the large-scale functional and structural impact of these modifications on RBPs remains unclear. In this work, we dephosphorylated nuclear extracts using phosphatase in vitro and analyzed equal amounts of detergent-soluble and -insoluble fractions by mass-spectrometry-based proteomics. Correlation network analysis resolved 27 distinct modules of differentially soluble nucleoplasm proteins. We found classes of arginine-rich RBPs that decrease in solubility following dephosphorylation and enrich the insoluble pelleted fraction, including the SR protein family and the SR-like LUC7L RBP family. Importantly, increased insolubility was not observed across broad classes of RBPs. We determined that phosphorylation regulated SRSF2 structure, as dephosphorylated SRSF2 formed high-molecular-weight oligomeric species in vitro. Reciprocally, phosphorylation of SRSF2 by serine/arginine protein kinase 2 (SRPK2) in vitro decreased high-molecular-weight SRSF2 species formation. Furthermore, upon pharmacological inhibition of SRPKs in mammalian cells, we observed SRSF2 cytoplasmic mislocalization and increased formation of cytoplasmic granules as well as cytoplasmic tubular structures that associated with microtubules by immunocytochemical staining. Collectively, these findings demonstrate that phosphorylation may be a critical modification that prevents arginine-rich RBP insolubility and oligomerization.     

Molecular dynamics shows complex interplay and long-range effects of post-translational modifications in yeast protein interactions

Post-translational modifications (PTMs) play a vital, yet often overlooked role in the living cells through modulation of protein properties, such as localization and affinity towards their interactors, thereby enabling quick adaptation to changing environmental conditions. We have previously benchmarked a computational framework for the prediction of PTMs’ effects on the stability of protein-protein interactions, which has molecular dynamics simulations followed by free energy calculations at its core. In the present work, we apply this framework to publicly available data on Saccharomyces cerevisiae protein structures and PTM sites, identified in both normal and stress conditions. We predict proteome-wide effects of acetylations and phosphorylations on protein-protein interactions and find that acetylations more frequently have locally stabilizing roles in protein interactions, while the opposite is true for phosphorylations. However, the overall impact of PTMs on protein-protein interactions is more complex than a simple sum of local changes caused by the introduction of PTMs and adds to our understanding of PTM cross-talk. We further use the obtained data to calculate the conformational changes brought about by PTMs. Finally, conservation of the analyzed PTM residues in orthologues shows that some predictions for yeast proteins will be mirrored to other organisms, including human. This work, therefore, contributes to our overall understanding of the modulation of the cellular protein interaction networks in yeast and beyond.     

Deciphering a global network of functionally associated post‐translational modifications

Various post‐translational modifications (PTMs) fine‐tune the functions of almost all eukaryotic proteins, and co‐regulation of different types of PTMs has been shown within and between a number of proteins. Aiming at a more global view of the interplay between PTM types, we collected modifications for 13 frequent PTM types in 8 eukaryotes, compared their speed of evolution and developed a method for measuring PTM co‐evolution within proteins based on the co‐occurrence of sites across eukaryotes. As many sites are still to be discovered, this is a considerable underestimate, yet, assuming that most co‐evolving PTMs are functionally associated, we found that PTM types are vastly interconnected, forming a global network that comprise in human alone >50 000 residues in about 6000 proteins. We predict substantial PTM type interplay in secreted and membrane‐associated proteins and in the context of particular protein domains and short‐linear motifs. The global network of co‐evolving PTM types implies a complex and intertwined post‐translational regulation landscape that is likely to regulate multiple functional states of many if not all eukaryotic proteins.     

Decoding the PTM-switchboard of Notch

The developmentally indispensable Notch pathway exhibits a high grade of pleiotropism in its biological output. Emerging evidence supports the notion of post-translational modifications (PTMs) as a modus operandi controlling dynamic fine-tuning of Notch activity. Although, the intricacy of Notch post-translational regulation, as well as how these modifications lead to multiples of divergent Notch phenotypes is still largely unknown, numerous studies show a correlation between the site of modification and the output. These include glycosylation of the extracellular domain of Notch modulating ligand binding, and phosphorylation of the PEST domain controlling half-life of the intracellular domain of Notch. Furthermore, several reports show that multiple PTMs can act in concert, or compete for the same sites to drive opposite outputs. However, further investigation of the complex PTM crosstalk is required for a complete understanding of the PTM-mediated Notch switchboard. In this review, we aim to provide a consistent and up-to-date summary of the currently known PTMs acting on the Notch signaling pathway, their functions in different contexts, as well as explore their implications in physiology and disease. Furthermore, we give an overview of the present state of PTM research methodology, and allude to a future with PTM-targeted Notch therapeutics.     

Uncovering post-translational modification-associated protein–protein interactions

In living systems, the chemical space and functional repertoire of proteins are dramatically expanded through the post-translational modification (PTM) of various amino acid residues. These modifications frequently trigger unique protein–protein interactions (PPIs) – for example with reader proteins that directly bind the modified amino acid residue – which leads to downstream functional outcomes. The modification of a protein can also perturb its PPI network indirectly, for example, through altering its conformation or subcellular localization. Uncovering the network of unique PTM-triggered PPIs is essential to fully understand the roles of an ever-expanding list of PTMs in our biology. In this review, we discuss established strategies and current challenges associated with this endeavor.     

Structural Analysis of PTM Hotspots (SAPH-ire) – A Quantitative Informatics Method Enabling the Discovery of Novel Regulatory Elements in Protein Families

Predicting the biological function potential of post-translational modifications (PTMs) is becoming increasingly important in light of the exponential increase in available PTM data from high-throughput proteomics. We developed structural analysis of PTM hotspots (SAPH-ire)—a quantitative PTM ranking method that integrates experimental PTM observations, sequence conservation, protein structure, and interaction data to allow rank order comparisons within or between protein families. Here, we applied SAPH-ire to the study of PTMs in diverse G protein families, a conserved and ubiquitous class of proteins essential for maintenance of intracellular structure (tubulins) and signal transduction (large and small Ras-like G proteins). A total of 1728 experimentally verified PTMs from eight unique G protein families were clustered into 451 unique hotspots, 51 of which have a known and cited biological function or response. Using customized software, the hotspots were analyzed in the context of 598 unique protein structures. By comparing distributions of hotspots with known versus unknown function, we show that SAPH-ire analysis is predictive for PTM biological function. Notably, SAPH-ire revealed high-ranking hotspots for which a functional impact has not yet been determined, including phosphorylation hotspots in the N-terminal tails of G protein gamma subunits—conserved protein structures never before reported as regulators of G protein coupled receptor signaling. To validate this prediction we used the yeast model system for G protein coupled receptor signaling, revealing that gamma subunit–N-terminal tail phosphorylation is activated in response to G protein coupled receptor stimulation and regulates protein stability in vivo. These results demonstrate the utility of integrating protein structural and sequence features into PTM prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data.Post-translational modifications (PTMs)¹ are a rapidly expanding and important class of protein feature that broaden the functional diversity of proteins in a proteome. By definition, PTMs change protein structure and therefore have the potential to affect protein function by altering protein interactions, protein stability or catalytic activity (1, 2). As they have been found to occur on nearly every protein in the eukaryotic proteome, PTMs broadly impact nearly all known cellular processes. Over 300 different types of PTM are known, ranging from single atom modifications (e.g. oxide) to small protein modifiers (e.g. ubiquitin), which can occur on all but five amino acid residues resulting from enzymatic or nonenzymatic processes (3). Over 220,000 distinct PTM sites have been experimentally identified across ∼77,000 different proteins to date (dbPTM; http://dbptm.mbc.nctu.edu.tw/statistics.php) – numbers that continue to grow exponentially because of improved methods for high throughput detection by mass spectrometry (MS). By virtue of how they are detected, most PTM data are sequence-linked and lack structural context.The function of most PTMs is unknown because the rate of PTM detection far surpasses the rate at which any one modification can be studied empirically. Moreover, the functional impact of every PTM is likely not equivalent (4). For example, computational analysis of phosphorylation sites in yeast and human proteomes indicate that well-conserved phosphosites are more likely to have a functional consequence compared with poorly conserved sites, yet only a fraction of phosphosites are well conserved (5, 6). Consequently, the development of tools that provide functional prioritization of PTMs could have a broad impact on our understanding of protein regulation, biological mechanism, and molecular evolution.The emerging need for methods that predict the functional impact of a PTM has not yet been met. Longstanding methods capitalize predominantly on the sequence context of PTMs and have been used to predict sites of modification (expasy.org/proteomics/post-translational_modification) and to compare enzyme/substrate interactions (7–9). More recently, studies aimed at expanding the parameters associated with functional PTMs have emerged. In these cases, a set of common features correlated with functional importance are derived from the analysis of PTMs within and between organisms including: number of PTM observations at a multiple sequence alignment position (i.e. hotspots), measures of co-occurrence between different PTMs (e.g. distance between phosphorylation and ubiquitination sites), biological dynamics (up or down-regulation), and protein–protein interaction influence (7, 10–12). Recent efforts to provide structural context by linking individual PTMs to three-dimensional structures in the protein data bank (PDB) have also been described (13, 14). However, these resources are extensions of existing PTM databases that allow visualization of single instances of modification onto individual proteins, but do not provide quantitative or analytical value.In principle, combining PTM hotspot and structural analysis would offer multiple advantages over any one approach used in isolation. Sequence homology provides protein family membership—thereby clustering PTMs into hotspots for groups of proteins to provide information about: (1) the evolutionary conservation and (2) observation frequencies of PTMs within the family. A primary consequence of their sequence homology is that members of a protein family will exhibit similar structures and protein interactions—features that dictate the function of protein systems. A secondary consequence is that PTM hotspots generated by alignment can be projected onto family-representative protein structures, which places each PTM hotspot into a three-dimensional context that can be visualized for each family. The structural context enabled by this projection can also provide spatial information about the PTM site that can supplement the sequence characteristics of the hotspot, namely: (3) solvent accessibility, which provides an estimate of whether a modification could occur on the folded protein; and (4) protein interface residence, which indicates the potential of the PTM to disrupt protein–protein interactions. Despite the theoretical advantages, no single tool has been developed that exploits the quantitative output from both sequence and structural data to evaluate the function potential of PTMs.Here we describe a new analytical method – Structural Analysis of PTM Hotspots (SAPH-ire), which ranks PTM hotspots by their potential to impact biological function for distinct protein families (Fig. 1). We demonstrate the application of SAPH-ire to the complete set of PTMs for eight distinct protein families including large heterotrimeric G proteins—revealing high-ranking hotspots for which a biological function has not yet been determined. In particular, SAPH-ire revealed the N-terminal tail (Nt) of G protein gamma (Gγ) subunits as one of the highest ranking PTM hotspots for heterotrimeric G proteins (Gα, Gβ, and Gγ). We tested this prediction by monitoring the phosphorylation state and mutation effects of phosphorylation sites in the N terminus of the yeast Gγ subunit (Ste18). Consistent with SAPH-ire predictions, we found that phosphorylation of Ste18-Nt is biologically responsive to a GPCR stimulus and that phospho-null or phospho-mimic mutation of these sites controls protein abundance in an opposite manner in vivo. Thus, SAPH-ire is a powerful new method for predicting the function potential of PTM hotspots, which can guide empirical research toward the discovery of new protein regulatory elements based on high-throughput proteomics.Open in a separate windowFig. 1.Schematic diagram of the SAPH-ire method. A, SAPH-ire integrates InterPro, the Protein Data bank (PDB) and a customized database of experimentally validated PTMs. Uniprot entries with PTMs that belong to specific InterPro-classified protein families undergo multiple-sequence alignment (MSA) and PTM hotspot analysis (HSA), which layers all PTMs for a given alignment position in the MSA. The total PTMs observed in each hotspot and the conservation of a modifiable residue (e.g. conservation lysine at a ubiquitination hotspot) at the hotspot are quantified. B, PTM hotspots within the protein family are then projected onto all known crystal structures for the family using the Structural Projection of PTMs (SPoP) tool. From the structural topology of PTM hotspots generated by SPoP, the solvent accessible surface area (SASA) and protein interface residence is quantified for each hotspot. C, PTM Function Potential Calculator (FPC) integrates the output from HSA and SPoP, resulting in PTM function potential scores for each hotspot. The function potential score can be used to rank PTM hotspots within or between protein families – prioritizing hotspots with the greatest potential to be biologically regulated and/or effect a biological function for the protein family of interest.