RBPmap: A Tool for Mapping and Predicting the Binding Sites of RNA-Binding Proteins Considering the Motif Environment.

RNA-binding proteins (RBPs) play a key role in post-transcriptional regulation via binding to coding and non-coding RNAs. Recent development in experimental technologies, aimed to identify the targets of RBPs, has significantly broadened our knowledge on protein-RNA interactions. However, for many RBPs in many organisms and cell types, experimental RNA-binding data is not available. In this chapter we describe a computational approach, named RBPmap, available as a web service via http://rbpmap.technion.ac.il/ and as a stand-alone version for download. RBPmap was designed for mapping and predicting the binding sites of any RBP within a nucleic acid sequence, given the availability of an experimentally defined binding motif of the RBP. The algorithm searches for a sub-sequence that significantly matches the RBP motif, considering the clustering propensity of other weak matches within the motif environment. Here, we present different applications of RBPmap for discovering the involvement of RBPs and their targets in a variety of cellular processes, in health and disease states. Finally, we demonstrate the performance of RBPmap in predicting the binding targets of RBPs in large-scale RNA-binding data, reinforcing the strength of the tool in distinguishing cognate binding sites from weak motifs.

SMARTIV: combined sequence and structure de-novo motif discovery for in-vivo RNA binding data.

Gene expression regulation is highly dependent on binding of RNA-binding proteins (RBPs) to their RNA targets. Growing evidence supports the notion that both RNA primary sequence and its local secondary structure play a role in specific Protein-RNA recognition and binding. Despite the great advance in high-throughput experimental methods for identifying sequence targets of RBPs, predicting the specific sequence and structure binding preferences of RBPs remains a major challenge. We present a novel webserver, SMARTIV, designed for discovering and visualizing combined RNA sequence and structure motifs from high-throughput RNA-binding data, generated from in-vivo experiments. The uniqueness of SMARTIV is that it predicts motifs from enriched k-mers that combine information from ranked RNA sequences and their predicted secondary structure, obtained using various folding methods. Consequently, SMARTIV generates Position Weight Matrices (PWMs) in a combined sequence and structure alphabet with assigned P-values. SMARTIV concisely represents the sequence and structure motif content as a single graphical logo, which is informative and easy for visual perception. SMARTIV was examined extensively on a variety of high-throughput binding experiments for RBPs from different families, generated from different technologies, showing consistent and accurate results. Finally, SMARTIV is a user-friendly webserver, highly efficient in run-time and freely accessible via http://smartiv.technion.ac.il/.

A combined sequence and structure based method for discovering enriched motifs in RNA from in vivo binding data.

RNA binding proteins (RBPs) play an important role in regulating many processes in the cell. RBPs often recognize their RNA targets in a specific manner. In addition to the RNA primary sequence, the structure of the RNA has been shown to play a central role in RNA recognition by RBPs. In recent years, many experimental approaches, both in vitro and in vivo, were developed and employed to identify and characterize RBP targets and extract their binding specificities. In vivo binding techniques, such as CrossLinking and ImmunoPrecipitation (CLIP)-based methods, enable the characterization of protein binding sites on RNA targets. However, these methods do not provide information regarding the structural preferences of the protein. While methods to obtain the structure of RNA are available, inferring both the sequence and the structure preferences of RBPs remains a challenge. Here we present SMARTIV, a novel computational tool for discovering combined sequence and structure binding motifs from in vivo RNA binding data relying on the sequences of the target sites, the ranking of their binding scores and their predicted secondary structure. The combined motifs are provided in a unified representation that is informative and easy for visual perception. We tested the method on CLIP-seq data from different platforms for a variety of RBPs. Overall, we show that our results are highly consistent with known binding motifs of RBPs, offering additional information on their structural preferences.

BindUP: a web server for non-homology-based prediction of DNA and RNA binding proteins.

Gene expression is a multi-step process involving many layers of regulation. The main regulators of the pathway are DNA and RNA binding proteins. While over the years, a large number of DNA and RNA binding proteins have been identified and extensively studied, it is still expected that many other proteins, some with yet another known function, are awaiting to be discovered. Here we present a new web server, BindUP, freely accessible through the website http://bindup.technion.ac.il/, for predicting DNA and RNA binding proteins using a non-homology-based approach. Our method is based on the electrostatic features of the protein surface and other general properties of the protein. BindUP predicts nucleic acid binding function given the proteins three-dimensional structure or a structural model. Additionally, BindUP provides information on the largest electrostatic surface patches, visualized on the server. The server was tested on several datasets of DNA and RNA binding proteins, including proteins which do not possess DNA or RNA binding domains and have no similarity to known nucleic acid binding proteins, achieving very high accuracy. BindUP is applicable in either single or batch modes and can be applied for testing hundreds of proteins simultaneously in a highly efficient manner.

RBPmap: a web server for mapping binding sites of RNA-binding proteins.

Regulation of gene expression is executed in many cases by RNA-binding proteins (RBPs) that bind to mRNAs as well as to non-coding RNAs. RBPs recognize their RNA target via specific binding sites on the RNA. Predicting the binding sites of RBPs is known to be a major challenge. We present a new webserver, RBPmap, freely accessible through the website http://rbpmap.technion.ac.il/ for accurate prediction and mapping of RBP binding sites. RBPmap has been developed specifically for mapping RBPs in human, mouse and Drosophila melanogaster genomes, though it supports other organisms too. RBPmap enables the users to select motifs from a large database of experimentally defined motifs. In addition, users can provide any motif of interest, given as either a consensus or a PSSM. The algorithm for mapping the motifs is based on a Weighted-Rank approach, which considers the clustering propensity of the binding sites and the overall tendency of regulatory regions to be conserved. In addition, RBPmap incorporates a position-specific background model, designed uniquely for different genomic regions, such as splice sites, 5' and 3' UTRs, non-coding RNA and intergenic regions. RBPmap was tested on high-throughput RNA-binding experiments and was proved to be highly accurate.

DRIMust: a web server for discovering rank imbalanced motifs using suffix trees.

Cellular regulation mechanisms that involve proteins and other active molecules interacting with specific targets often involve the recognition of sequence patterns. Short sequence elements on DNA, RNA and proteins play a central role in mediating such molecular recognition events. Studies that focus on measuring and investigating sequence-based recognition processes make use of statistical and computational tools that support the identification and understanding of sequence motifs. We present a new web application, named DRIMust, freely accessible through the website http://drimust.technion.ac.il for de novo motif discovery services. The DRIMust algorithm is based on the minimum hypergeometric statistical framework and uses suffix trees for an efficient enumeration of motif candidates. DRIMust takes as input ranked lists of sequences in FASTA format and returns motifs that are over-represented at the top of the list, where the determination of the threshold that defines top is data driven. The resulting motifs are presented individually with an accurate P-value indication and as a Position Specific Scoring Matrix. Comparing DRIMust with other state-of-the-art tools demonstrated significant advantage to DRIMust, both in result accuracy and in short running times. Overall, DRIMust is unique in combining efficient search on large ranked lists with rigorous P-value assessment for the detected motifs.

SFmap: a web server for motif analysis and prediction of splicing factor binding sites.

Alternative splicing (AS) is a post-transcriptional process considered to be responsible for the huge diversity of proteins in higher eukaryotes. AS events are regulated by different splicing factors (SFs) that bind to sequence elements on the RNA. SFmap is a web server for predicting putative SF binding sites in genomic data (http://sfmap.technion.ac.il). SFmap implements the COS(WR) algorithm, which computes similarity scores for a given regulatory motif based on information derived from its sequence environment and its evolutionary conservation. Input for SFmap is a human genomic sequence or a list of sequences in FASTA format that can either be uploaded from a file or pasted into a window. SFmap searches within a given sequence for significant hits of binding motifs that are either stored in our database or defined by the user. SFmap results are provided both as a text file and as a graphical web interface.

ConSeq: the identification of functionally and structurally important residues in protein sequences.

MOTIVATION: ConSeq is a web server for the identification of biologically important residues in protein sequences. Functionally important residues that take part, e.g. in ligand binding and protein-protein interactions, are often evolutionarily conserved and are most likely to be solvent-accessible, whereas conserved residues within the protein core most probably have an important structural role in maintaining the protein's fold. Thus, estimated evolutionary rates, as well as relative solvent accessibility predictions, are assigned to each amino acid in the sequence; both are subsequently used to indicate residues that have potential structural or functional importance. AVAILABILITY: The ConSeq web server is available at http://conseq.bioinfo.tau.ac.il/ SUPPLEMENTARY INFORMATION: The ConSeq methodology, a description of its performance in a set of five well-documented proteins, a comparison to other methods, and the outcome of its application to a set of 111 proteins of unknown function, are presented at http://conseq.bioinfo.tau.ac.il/ under 'OVERVIEW', 'VALIDATION', 'COMPARISON' and 'PREDICTIONS', respectively.

ConSurf: identification of functional regions in proteins by surface-mapping of phylogenetic information.

UNLABELLED: We recently developed algorithmic tools for the identification of functionally important regions in proteins of known three dimensional structure by estimating the degree of conservation of the amino-acid sites among their close sequence homologues. Projecting the conservation grades onto the molecular surface of these proteins reveals patches of highly conserved (or occasionally highly variable) residues that are often of important biological function. We present a new web server, ConSurf, which automates these algorithmic tools. ConSurf may be used for high-throughput characterization of functional regions in proteins. AVAILABILITY: The ConSurf web server is available at:http://consurf.tau.ac.il. SUPPLEMENTARY INFORMATION: A set of examples is available at http://consurf.tau.ac.il under 'GALLERY'.