Fernanda L. Sirota

Towards complete sets of farnesylated and geranylgeranylated proteins

Three different prenyltransferases attach isoprenyl anchors to C-terminal motifs in substrate proteins. These lipid anchors serve for membrane attachment or protein–protein interactions in many pathways. Although well-tolerated selective prenyltransferase inhibitors are clinically available, their mode of action remains unclear since the known substrate sets of the various prenyltransferases are incomplete. The Prenylation Prediction Suite (PrePS) has been applied for large-scale predictions of prenylated proteins. To prioritize targets for experimental verification, we rank the predictions by their functional importance estimated by evolutionary conservation of the prenylation motifs within protein families. The ranked lists of predictions are accessible as PRENbase (http://mendel.imp.univie.ac.at/sat/PrePS/PRENbase) and can be queried for verification status, type of modifying enzymes (anchor type), and taxonomic distribution. Our results highlight a large group of plant metal-binding chaperones as well as several newly predicted proteins involved in ubiquitin-mediated protein degradation, enriching the known functional repertoire of prenylated proteins. Furthermore, we identify two possibly prenylated proteins in Mimivirus. The section HumanPRENbase provides complete lists of predicted prenylated human proteins—for example, the list of farnesyltransferase targets that cannot become substrates of geranylgeranyltransferase 1 and, therefore, are especially affected by farnesyltransferase inhibitors (FTIs) used in cancer and anti-parasite therapy. We report direct experimental evidence verifying the prediction of the human proteins Prickle1, Prickle2, the BRO1 domain–containing FLJ32421 (termed BROFTI), and Rab28 (short isoform) as exclusive farnesyltransferase targets. We introduce PRENbase, a database of large-scale predictions of protein prenylation substrates ranked by evolutionary conservation of the motif. Experimental evidence is presented for the selective farnesylation of targets with an evolutionary conserved modification site.

ANNIE: integrated de novo protein sequence annotation

Function prediction of proteins with computational sequence analysis requires the use of dozens of prediction tools with a bewildering range of input and output formats. Each of these tools focuses on a narrow aspect and researchers are having difficulty obtaining an integrated picture. ANNIE is the result of years of close interaction between computational biologists and computer scientists and automates an essential part of this sequence analytic process. It brings together over 20 function prediction algorithms that have proven sufficiently reliable and indispensable in daily sequence analytic work and are meant to give scientists a quick overview of possible functional assignments of sequence segments in the query proteins. The results are displayed in an integrated manner using an innovative AJAX-based sequence viewer. ANNIE is available online at: http://annie.bii.a-star.edu.sg. This website is free and open to all users and there is no login requirement.

Parameterization of disorder predictors for large-scale applications requiring high specificity by using an extended benchmark dataset

BackgroundAlgorithms designed to predict protein disorder play an important role in structural and functional genomics, as disordered regions have been reported to participate in important cellular processes. Consequently, several methods with different underlying principles for disorder prediction have been independently developed by various groups. For assessing their usability in automated workflows, we are interested in identifying parameter settings and threshold selections, under which the performance of these predictors becomes directly comparable.ResultsFirst, we derived a new benchmark set that accounts for different flavours of disorder complemented with a similar amount of order annotation derived for the same protein set. We show that, using the recommended default parameters, the programs tested are producing a wide range of predictions at different levels of specificity and sensitivity. We identify settings, in which the different predictors have the same false positive rate. We assess conditions when sets of predictors can be run together to derive consensus or complementary predictions. This is useful in the framework of proteome-wide applications where high specificity is required such as in our in-house sequence analysis pipeline and the ANNIE webserver.ConclusionsThis work identifies parameter settings and thresholds for a selection of disorder predictors to produce comparable results at a desired level of specificity over a newly derived benchmark dataset that accounts equally for ordered and disordered regions of different lengths.

Tachyon search speeds up retrieval of similar sequences by several orders of magnitude

Summary: The usage of current sequence search tools becomes increasingly slower as databases of protein sequences continue to grow exponentially. Tachyon, a new algorithm that identifies closely related protein sequences ~200 times faster than standard BLAST, circumvents this limitation with a reduced database and oligopeptide matching heuristic. Availability and implementation: The tool is publicly accessible as a webserver at http://tachyon.bii.a-star.edu.sg and can also be accessed programmatically through SOAP. Contact: sebastianms@bii.a-star.edu.sg Supplementary information: Supplementary data are available at the Bioinformatics online.

Integrated Tools for Biomolecular Sequence-Based Function Prediction as Exemplified by the ANNOTATOR Software Environment

Given the amount of sequence data available today, in silico function prediction, which often includes detecting distant evolutionary relationships, requires sophisticated bioinformatic workflows. The algorithms behind these workflows exhibit complex data structures; they need the ability to spawn subtasks and tend to demand large amounts of resources. Performing sequence analytic tasks by manually invoking individual function prediction algorithms having to transform between differing input and output formats has become increasingly obsolete. After a period of linking individual predictors using ad hoc scripts, a number of integrated platforms are finally emerging. We present the ANNOTATOR software environment as an advanced example of such a platform.

Single-residue posttranslational modification sites at the N-terminus, C-terminus or in-between: To be or not to be exposed for enzyme access.

Many protein posttranslational modifications (PTMs) are the result of an enzymatic reaction. The modifying enzyme has to recognize the substrate proteins sequence motif containing the residue(s) to be modified; thus, the enzymes catalytic cleft engulfs these residue(s) and the respective sequence environment. This residue accessibility condition principally limits the range where enzymatic PTMs can occur in the protein sequence. Non‐globular, flexible, intrinsically disordered segments or large loops/accessible long side chains should be preferred whereas residues buried in the core of structures should be void of what we call canonical, enzyme‐generated PTMs. We investigate whether PTM sites annotated in UniProtKB (with MOD_RES/LIPID keys) are situated within sequence ranges that can be mapped to known 3D structures. We find that N‐ or C‐termini harbor essentially exclusively canonical PTMs. We also find that the overwhelming majority of all other PTMs are also canonical though, later in the proteins life cycle, the PTM sites can become buried due to complex formation. Among the remaining cases, some can be explained (i) with autocatalysis, (ii) with modification before folding or after temporary unfolding, or (iii) as products of interaction with small, diffusible reactants. Others require further research how these PTMs are mechanistically generated in vivo.

The Recipe for Protein Sequence-Based Function Prediction and Its Implementation in the ANNOTATOR Software Environment.

As biomolecular sequencing is becoming the main technique in life sciences, functional interpretation of sequences in terms of biomolecular mechanisms with in silico approaches is getting increasingly significant. Function prediction tools are most powerful for protein-coding sequences; yet, the concepts and technologies used for this purpose are not well reflected in bioinformatics textbooks. Notably, protein sequences typically consist of globular domains and non-globular segments. The two types of regions require cardinally different approaches for function prediction. Whereas the former are classic targets for homology-inspired function transfer based on remnant, yet statistically significant sequence similarity to other, characterized sequences, the latter type of regions are characterized by compositional bias or simple, repetitive patterns and require lexical analysis and/or empirical sequence pattern-function correlations. The recipe for function prediction recommends first to find all types of non-globular segments and, then, to subject the remaining query sequence to sequence similarity searches. We provide an updated description of the ANNOTATOR software environment as an advanced example of a software platform that facilitates protein sequence-based function prediction.

Conservation of the Extended Substrate Specificity Profiles Among Homologous Granzymes Across Species

Granzymes are structurally related serine proteases involved in cell death and immunity. To date four out of five human granzymes have assigned orthologs in mice; however for granzyme H, no murine ortholog has been suggested and its role in cytotoxicity remains controversial. Here, we demonstrate that, as is the case for granzyme C, human granzyme H is an inefficient cytotoxin that together with their similar pattern of GrB divergence and functional similarity strongly hint to their orthologous relationship. Besides analyzing the substrate specificity profile of granzyme H by substrate phage display, substrate cleavage susceptibility of human granzyme H and mouse granzyme C was assessed on a proteome-wide level. The extended specificity profiles of granzymes C and H (i.e. beyond cleavage positions P4-P4′) match those previously observed for granzyme B. We demonstrate conservation of these extended specificity profiles among various granzymes as granzyme B cleavage susceptibility of an otherwise granzyme H/C specific cleavage site can simply be conferred by altering the P1-residue to aspartate, the preferred P1-residue of granzyme B. Our results thus indicate a conserved, but hitherto underappreciated specificity-determining role of extended protease-substrate contacts in steering cleavage susceptibility.

Protein Sequence–Structure–Function–Network Links Discovered with the ANNOTATOR Software Suite: Application to ELYS/Mel-28

While very little genomic sequence is interpretable in terms of biological mechanism directly, the chances are much better for protein-coding genes that can be translated into protein sequences. This review considers the different concepts applicable to sequence analysis and function prediction of globular and non-globular protein segments. The publicly accessible ANNOTATOR software environment integrates most of the reliable protein sequence-based function prediction methods, protein domain databases and pathway, and protein–protein interaction collections developed in academia. As application example, the structural and functional domains of mel-28/ELYS, an important nuclear protein, are delineated and are proposed for experimental follow-up in structural biology and functional studies.