A High-Throughput Screen for Transcription Activation Domains Reveals Their Sequence Features and Permits Prediction by Deep Learning.

Acidic transcription activation domains (ADs) are encoded by a wide range of seemingly unrelated amino acid sequences, making it difficult to recognize features that promote their dynamic behavior, "fuzzy" interactions, and target specificity. We screened a large set of random 30-mer peptides for AD function in yeast and trained a deep neural network (ADpred) on the AD-positive and -negative sequences. ADpred identifies known acidic ADs within transcription factors and accurately predicts the consequences of mutations. Our work reveals that strong acidic ADs contain multiple clusters of hydrophobic residues near acidic side chains, explaining why ADs often have a biased amino acid composition. ADs likely use a binding mechanism similar to avidity where a minimum number of weak dynamic interactions are required between activator and target to generate biologically relevant affinity and in vivo function. This mechanism explains the basis for fuzzy binding observed between acidic ADs and targets.

Lethal perturbation of an Escherichia coli regulatory network is triggered by a restriction-modification system's regulator and can be mitigated by excision of the cryptic prophage Rac.

Bacterial gene regulatory networks orchestrate responses to environmental challenges. Horizontal gene transfer can bring in genes with regulatory potential, such as new transcription factors (TFs), and this can disrupt existing networks. Serious regulatory perturbations may even result in cell death. Here, we show the impact on Escherichia coli of importing a promiscuous TF that has adventitious transcriptional effects within the cryptic Rac prophage. A cascade of regulatory network perturbations occurred on a global level. The TF, a C regulatory protein, normally controls a Type II restriction-modification system, but in E. coli K-12 interferes with expression of the RacR repressor gene, resulting in de-repression of the normally-silent Rac ydaT gene. YdaT is a prophage-encoded TF with pleiotropic effects on E. coli physiology. In turn, YdaT alters expression of a variety of bacterial regulons normally controlled by the RcsA TF, resulting in deficient lipopolysaccharide biosynthesis and cell division. At the same time, insufficient RacR repressor results in Rac DNA excision, halting Rac gene expression due to loss of the replication-defective Rac prophage. Overall, Rac induction appears to counteract the lethal toxicity of YdaT. We show here that E. coli rewires its regulatory network, so as to minimize the adverse regulatory effects of the imported C TF. This complex set of interactions may reflect the ability of bacteria to protect themselves by having robust mechanisms to maintain their regulatory networks, and/or suggest that regulatory C proteins from mobile operons are under selection to manipulate their host's regulatory networks for their own benefit.

Proteome-pI 2.0: proteome isoelectric point database update.

Proteome-pI 2.0 is an update of an online database containing predicted isoelectric points and pKa dissociation constants of proteins and peptides. The isoelectric point-the pH at which a particular molecule carries no net electrical charge-is an important parameter for many analytical biochemistry and proteomics techniques. Additionally, it can be obtained directly from the pKa values of individual charged residues of the protein. The Proteome-pI 2.0 database includes data for over 61 million protein sequences from 20 115 proteomes (three to four times more than the previous release). The isoelectric point for proteins is predicted by 21 methods, whereas pKa values are inferred by one method. To facilitate bottom-up proteomics analysis, individual proteomes were digested in silico with the five most commonly used proteases (trypsin, chymotrypsin, trypsin + LysC, LysN, ArgC), and the peptides' isoelectric point and molecular weights were calculated. The database enables the retrieval of virtual 2D-PAGE plots and customized fractions of a proteome based on the isoelectric point and molecular weight. In addition, isoelectric points for proteins in NCBI non-redundant (nr), UniProt, SwissProt, and Protein Data Bank are available in both CSV and FASTA formats. The database can be accessed at http://isoelectricpointdb2.org.

IPC 2.0: prediction of isoelectric point and pKa dissociation constants.

The isoelectric point is the pH at which a particular molecule is electrically neutral due to the equilibrium of positive and negative charges. In proteins and peptides, this depends on the dissociation constant (pKa) of charged groups of seven amino acids and NH+ and COO- groups at polypeptide termini. Information regarding isoelectric point and pKa is extensively used in two-dimensional gel electrophoresis (2D-PAGE), capillary isoelectric focusing (cIEF), crystallisation, and mass spectrometry. Therefore, there is a strong need for the in silico prediction of isoelectric point and pKa values. In this paper, I present Isoelectric Point Calculator 2.0 (IPC 2.0), a web server for the prediction of isoelectric points and pKa values using a mixture of deep learning and support vector regression models. The prediction accuracy (RMSD) of IPC 2.0 for proteins and peptides outperforms previous algorithms: 0.848 versus 0.868 and 0.222 versus 0.405, respectively. Moreover, the IPC 2.0 prediction of pKa using sequence information alone was better than the prediction from structure-based methods (0.576 versus 0.826) and a few folds faster. The IPC 2.0 webserver is freely available at www.ipc2-isoelectric-point.org.

Molecular Characterization of a DNA Polymerase from Thermus thermophilus MAT72 Phage vB_Tt72: A Novel Type-A Family Enzyme with Strong Proofreading Activity.

We present a structural and functional analysis of the DNA polymerase of thermophilic Thermus thermophilus MAT72 phage vB_Tt72. The enzyme shows low sequence identity (<30%) to the members of the type-A family of DNA polymerases, except for two yet uncharacterized DNA polymerases of T. thermophilus phages: φYS40 (91%) and φTMA (90%). The Tt72 polA gene does not complement the Escherichia colipolA− mutant in replicating polA-dependent plasmid replicons. It encodes a 703-aa protein with a predicted molecular weight of 80,490 and an isoelectric point of 5.49. The enzyme contains a nucleotidyltransferase domain and a 3'-5' exonuclease domain that is engaged in proofreading. Recombinant enzyme with His-tag at the N-terminus was overproduced in E. coli, subsequently purified by immobilized metal affinity chromatography, and biochemically characterized. The enzyme exists in solution in monomeric form and shows optimum activity at pH 8.5, 25 mM KCl, and 0.5 mM Mg2+. Site-directed analysis proved that highly-conserved residues D15, E17, D78, D180, and D184 in 3'-5' exonuclease and D384 and D615 in the nucleotidyltransferase domain are critical for the enzyme's activity. Despite the source of origin, the Tt72 DNA polymerase has not proven to be highly thermoresistant, with a temperature optimum at 55 °C. Above 60 °C, the rapid loss of function follows with no activity > 75 °C. However, during heat treatment (10 min at 75 °C), trehalose, trimethylamine N-oxide, and betaine protected the enzyme against thermal inactivation. A midpoint of thermal denaturation at Tm = 74.6 °C (ΔHcal = 2.05 × 104 cal mol−1) and circular dichroism spectra > 60 °C indicate the enzyme's moderate thermal stability.

Novel Lytic Enzyme of Prophage Origin from Clostridium botulinum E3 Strain Alaska E43 with Bactericidal Activity against Clostridial Cells.

Clostridium botulinum is a Gram-positive, anaerobic, spore-forming bacterium capable of producing botulinum toxin and responsible for botulism of humans and animals. Phage-encoded enzymes called endolysins, which can lyse bacteria when exposed externally, have potential as agents to combat bacteria of the genus Clostridium. Bioinformatics analysis revealed in the genomes of several Clostridium species genes encoding putative N-acetylmuramoyl-l-alanine amidases with anti-clostridial potential. One such enzyme, designated as LysB (224-aa), from the prophage of C. botulinum E3 strain Alaska E43 was chosen for further analysis. The recombinant 27,726 Da protein was expressed and purified from E. coli Tuner(DE3) with a yield of 37.5 mg per 1 L of cell culture. Size-exclusion chromatography and analytical ultracentrifugation experiments showed that the protein is dimeric in solution. Bioinformatics analysis and results of site-directed mutagenesis studies imply that five residues, namely H25, Y54, H126, S132, and C134, form the catalytic center of the enzyme. Twelve other residues, namely M13, H43, N47, G48, W49, A50, L73, A75, H76, Q78, N81, and Y182, were predicted to be involved in anchoring the protein to the lipoteichoic acid, a significant component of the Gram-positive bacterial cell wall. The LysB enzyme demonstrated lytic activity against bacteria belonging to the genera Clostridium, Bacillus, Staphylococcus, and Deinococcus, but did not lyse Gram-negative bacteria. Optimal lytic activity of LysB occurred between pH 4.0 and 7.5 in the absence of NaCl. This work presents the first characterization of an endolysin derived from a C. botulinum Group II prophage, which can potentially be used to control this important pathogen.

UV Sensor Based on Fiber Bragg Grating Covered with Graphene Oxide Embedded in Composite Materials.

Polymer-matrix composites degrade under the influence of UV radiation in the range of the 290-400 nm band. The degradation of polymer-matrix composites exposed to UV radiation is characterized by extensive aging of the epoxy matrix, resulting in deterioration of their mechanical properties. Glass fibers/epoxy resin composites were made by an out-of-autoclave method whereas a fiber optic sensor was placed between different layers of laminates. In our work, we used a fiber Bragg grating sensor covered with graphene oxide and embedded in a polymer matrix composite to monitor UV radiation intensity. Measurements of UV radiation may allow monitoring the aging process of individual components of the polymer composite. In order to estimate the number of microcracks of epoxy resin, microstructure observations were carried out using a scanning electron microscope.

Proteome-pI: proteome isoelectric point database.

Proteome-pI is an online database containing information about predicted isoelectric points for 5029 proteomes calculated using 18 methods. The isoelectric point, the pH at which a particular molecule carries no net electrical charge, is an important parameter for many analytical biochemistry and proteomics techniques, especially for 2D gel electrophoresis (2D-PAGE), capillary isoelectric focusing, liquid chromatography-mass spectrometry and X-ray protein crystallography. The database, available at http://isoelectricpointdb.org allows the retrieval of virtual 2D-PAGE plots and the development of customised fractions of proteome based on isoelectric point and molecular weight. Moreover, Proteome-pI facilitates statistical comparisons of the various prediction methods as well as biological investigation of protein isoelectric point space in all kingdoms of life. For instance, using Proteome-pI data, it is clear that Eukaryotes, which evolved tight control of homeostasis, encode proteins with pI values near the cell pH. In contrast, Archaea living frequently in extreme environments can possess proteins with a wide range of isoelectric points. The database includes various statistics and tools for interactive browsing, searching and sorting. Apart from data for individual proteomes, datasets corresponding to major protein databases such as UniProtKB/TrEMBL and the NCBI non-redundant (nr) database have also been precalculated and made available in CSV format.

Sequence-specific cleavage of dsRNA by Mini-III RNase.

Ribonucleases (RNases) play a critical role in RNA processing and degradation by hydrolyzing phosphodiester bonds (exo- or endonucleolytically). Many RNases that cut RNA internally exhibit substrate specificity, but their target sites are usually limited to one or a few specific nucleotides in single-stranded RNA and often in a context of a particular three-dimensional structure of the substrate. Thus far, no RNase counterparts of restriction enzymes have been identified which could cleave double-stranded RNA (dsRNA) in a sequence-specific manner. Here, we present evidence for a sequence-dependent cleavage of long dsRNA by RNase Mini-III from Bacillus subtilis (BsMiniIII). Analysis of the sites cleaved by this enzyme in limited digest of bacteriophage Φ6 dsRNA led to the identification of a consensus target sequence. We defined nucleotide residues within the preferred cleavage site that affected the efficiency of the cleavage and were essential for the discrimination of cleavable versus non-cleavable dsRNA sequences. We have also determined that the loop α5b-α6, a distinctive structural element in Mini-III RNases, is crucial for the specific cleavage, but not for dsRNA binding. Our results suggest that BsMiniIII may serve as a prototype of a sequence-specific dsRNase that could possibly be used for targeted cleavage of dsRNA.

MQAPsingle: A quasi single-model approach for estimation of the quality of individual protein structure models.

We present a Model Quality Assessment Program (MQAP), called MQAPsingle, for ranking and assessing the absolute global quality of single protein models. MQAPsingle is quasi single-model MQAP, a method that combines advantages of both "pure" single-model MQAPs and clustering MQAPs. This approach results in higher accuracy compared to the state-of-the-art single-model MQAPs. Notably, the prediction for a given model is the same regardless if this model is submitted to our server alone or together with other models. Proteins 2016; 84:1021-1028. © 2015 Wiley Periodicals, Inc.

GDFuzz3D: a method for protein 3D structure reconstruction from contact maps, based on a non-Euclidean distance function.

MOTIVATION: To date, only a few distinct successful approaches have been introduced to reconstruct a protein 3D structure from a map of contacts between its amino acid residues (a 2D contact map). Current algorithms can infer structures from information-rich contact maps that contain a limited fraction of erroneous predictions. However, it is difficult to reconstruct 3D structures from predicted contact maps that usually contain a high fraction of false contacts. RESULTS: We describe a new, multi-step protocol that predicts protein 3D structures from the predicted contact maps. The method is based on a novel distance function acting on a fuzzy residue proximity graph, which predicts a 2D distance map from a 2D predicted contact map. The application of a Multi-Dimensional Scaling algorithm transforms that predicted 2D distance map into a coarse 3D model, which is further refined by typical modeling programs into an all-atom representation. We tested our approach on contact maps predicted de novo by MULTICOM, the top contact map predictor according to CASP10. We show that our method outperforms FT-COMAR, the state-of-the-art method for 3D structure reconstruction from 2D maps. For all predicted 2D contact maps of relatively low sensitivity (60-84%), GDFuzz3D generates more accurate 3D models, with the average improvement of 4.87 Å in terms of RMSD. AVAILABILITY AND IMPLEMENTATION: GDFuzz3D server and standalone version are freely available at http://iimcb.genesilico.pl/gdserver/GDFuzz3D/. CONTACT: iamb@genesilico.pl SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Computational modeling of protein-RNA complex structures.

Protein-RNA interactions play fundamental roles in many biological processes, such as regulation of gene expression, RNA splicing, and protein synthesis. The understanding of these processes improves as new structures of protein-RNA complexes are solved and the molecular details of interactions analyzed. However, experimental determination of protein-RNA complex structures by high-resolution methods is tedious and difficult. Therefore, studies on protein-RNA recognition and complex formation present major technical challenges for macromolecular structural biology. Alternatively, protein-RNA interactions can be predicted by computational methods. Although less accurate than experimental measurements, theoretical models of macromolecular structures can be sufficiently accurate to prompt functional hypotheses and guide e.g. identification of important amino acid or nucleotide residues. In this article we present an overview of strategies and methods for computational modeling of protein-RNA complexes, including software developed in our laboratory, and illustrate it with practical examples of structural predictions.

CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction.

We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks.

Female-specific gene expression in dioecious liverwort Pellia endiviifolia is developmentally regulated and connected to archegonia production.

BACKGROUND: In flowering plants a number of genes have been identified which control the transition from a vegetative to generative phase of life cycle. In bryophytes representing basal lineage of land plants, there is little data regarding the mechanisms that control this transition. Two species from bryophytes - moss Physcomitrella patens and liverwort Marchantia polymorpha are under advanced molecular and genetic research. The goal of our study was to identify genes connected to female gametophyte development and archegonia production in the dioecious liverwort Pellia endiviifolia species B, which is representative of the most basal lineage of the simple thalloid liverworts. RESULTS: The utility of the RDA-cDNA technique allowed us to identify three genes specifically expressed in the female individuals of P.endiviifolia: PenB_CYSP coding for cysteine protease, PenB_MT2 and PenB_MT3 coding for Mysterious Transcripts1 and 2 containing ORFs of 143 and 177 amino acid residues in length, respectively. The exon-intron structure of all three genes has been characterized and pre-mRNA processing was investigated. Interestingly, five mRNA isoforms are produced from the PenB_MT2 gene, which result from alternative splicing within the second and third exon. All observed splicing events take place within the 5'UTR and do not interfere with the coding sequence. All three genes are exclusively expressed in the female individuals, regardless of whether they were cultured in vitro or were collected from a natural habitat. Moreover we observed ten-fold increased transcripts level for all three genes in the archegonial tissue in comparison to the vegetative parts of the same female thalli grown in natural habitat suggesting their connection to archegonia development. CONCLUSIONS: We have identified three genes which are specifically expressed in P.endiviifolia sp B female gametophytes. Moreover, their expression is connected to the female sex-organ differentiation and is developmentally regulated. The contribution of the identified genes may be crucial for successful liverwort sexual reproduction.

Novel highly thermostable endolysin from Thermus scotoductus MAT2119 bacteriophage Ph2119 with amino acid sequence similarity to eukaryotic peptidoglycan recognition proteins.

In this study, we present the discovery and characterization of a highly thermostable endolysin from bacteriophage Ph2119 infecting Thermus strain MAT2119 isolated from geothermal areas in Iceland. Nucleotide sequence analysis of the 16S rRNA gene affiliated the strain with the species Thermus scotoductus. Bioinformatics analysis has allowed identification in the genome of phage 2119 of an open reading frame (468 bp in length) coding for a 155-amino-acid basic protein with an Mr of 17,555. Ph2119 endolysin does not resemble any known thermophilic phage lytic enzymes. Instead, it has conserved amino acid residues (His(30), Tyr(58), His(132), and Cys(140)) that form a Zn(2+) binding site characteristic of T3 and T7 lysozymes, as well as eukaryotic peptidoglycan recognition proteins, which directly bind to, but also may destroy, bacterial peptidoglycan. The purified enzyme shows high lytic activity toward thermophiles, i.e., T. scotoductus (100%), Thermus thermophilus (100%), and Thermus flavus (99%), and also, to a lesser extent, toward mesophilic Gram-negative bacteria, i.e., Escherichia coli (34%), Serratia marcescens (28%), Pseudomonas fluorescens (13%), and Salmonella enterica serovar Panama (10%). The enzyme has shown no activity against a number of Gram-positive bacteria analyzed, with the exception of Deinococcus radiodurans (25%) and Bacillus cereus (15%). Ph2119 endolysin was found to be highly thermostable: it retains approximately 87% of its lytic activity after 6 h of incubation at 95°C. The optimum temperature range for the enzyme activity is 50°C to 78°C. The enzyme exhibits lytic activity in the pH range of 6 to 10 (maximum at pH 7.5 to 8.0) and is also active in the presence of up to 500 mM NaCl.

Crohn's disease risk alleles on the NOD2 locus have been maintained by natural selection on standing variation.

Risk alleles for complex diseases are widely spread throughout human populations. However, little is known about the geographic distribution and frequencies of risk alleles, which may contribute to differences in disease susceptibility and prevalence among populations. Here, we focus on Crohn's disease (CD) as a model for the evolutionary study of complex disease alleles. Recent genome-wide association studies and classical linkage analyses have identified more than 70 susceptible genomic regions for CD in Europeans, but only a few have been confirmed in non-European populations. Our analysis of eight European-specific susceptibility genes using HapMap data shows that at the NOD2 locus the CD-risk alleles are linked with a haplotype specific to CEU at a frequency that is significantly higher compared with the entire genome. We subsequently examined nine global populations and found that the CD-risk alleles spread through hitchhiking with a high-frequency haplotype (H1) exclusive to Europeans. To examine the neutrality of NOD2, we performed phylogenetic network analyses, coalescent simulation, protein structural prediction, characterization of mutation patterns, and estimations of population growth and time to most recent common ancestor (TMRCA). We found that while H1 was significantly prevalent in European populations, the H1 TMRCA predated human migration out of Africa. H1 is likely to have undergone negative selection because 1) the root of H1 genealogy is defined by a preexisting amino acid substitution that causes serious conformational changes to the NOD2 protein, 2) the haplotype has almost become extinct in Africa, and 3) the haplotype has not been affected by the recent European expansion reflected in the other haplotypes. Nevertheless, H1 has survived in European populations, suggesting that the haplotype is advantageous to this group. We propose that several CD-risk alleles, which destabilize and disrupt the NOD2 protein, have been maintained by natural selection on standing variation because the deleterious haplotype of NOD2 is advantageous in diploid individuals due to heterozygote advantage and/or intergenic interactions.

Plasma Treatment of PDMS for Microcontact Printing (µCP) of Lectins Decreases Silicone Transfer and Increases the Adhesion of Bladder Cancer Cells.

The present study investigates silicone transfer occurring during microcontact printing (µCP) of lectins with polydimethylsiloxane (PDMS) stamps and its impact on the adhesion of cells. Static adhesion assays and single-cell force spectroscopy (SCFS) are used to compare adhesion of nonmalignant (HCV29) and cancer (HT1376) bladder cells, respectively, to high-affinity lectin layers (PHA-L and WGA, respectively) prepared by physical adsorption and µCP. The chemical composition of the µCP lectin patterns was monitored by time-of-flight secondary ion mass spectrometry (ToF-SIMS). We show that the amount of transferred silicone in the µCP process depends on the preprocessing of the PDMS stamps. It is revealed that silicone contamination within the patterned lectin layers inhibits the adhesion of bladder cells, and the work of adhesion is lower for µCP lectins than for drop-cast lectins. The binding capacity of microcontact printed lectins was larger when the PDMS stamps were treated with UV ozone plasma as compared to sonication in ethanol and deionized water. ToF-SIMS data show that ozone-based treatment of PDMS stamps used for µCP of lectin reduces the silicone contamination in the imprinting protocol regardless of stamp geometry (flat vs microstructured). The role of other possible contributors, such as the lectin conformation and organization of lectin layers, is also discussed.

Molecular characterization of the PhiKo endolysin from Thermus thermophilus HB27 bacteriophage phiKo and its cryptic lytic peptide RAP-29.

Introduction: In the era of increasing bacterial resistance to antibiotics, new bactericidal substances are sought, and lysins derived from extremophilic organisms have the undoubted advantage of being stable under harsh environmental conditions. The PhiKo endolysin is derived from the phiKo bacteriophage infecting Gram-negative extremophilic bacterium Thermus thermophilus HB27. This enzyme shows similarity to two previously investigated thermostable type-2 amidases, the Ts2631 and Ph2119 from Thermus scotoductus bacteriophages, that revealed high lytic activity not only against thermophiles but also against Gram-negative mesophilic bacteria. Therefore, antibacterial potential of the PhiKo endolysin was investigated in the study presented here. Methods: Enzyme activity was assessed using turbidity reduction assays (TRAs) and antibacterial tests. Differential scanning calorimetry was applied to evaluate protein stability. The Collection of Anti-Microbial Peptides (CAMP) and Antimicrobial Peptide Calculator and Predictor (APD3) were used to predict regions with antimicrobial potential in the PhiKo primary sequence. The minimum inhibitory concentration (MIC) of the RAP-29 synthetic peptide was determined against Gram-positive and Gram-negative selected strains, and mechanism of action was investigated with use of membrane potential sensitive fluorescent dye 3,3'-Dipropylthiacarbocyanine iodide (DiSC3(5)). Results and discussion: The PhiKo endolysin is highly thermostable with melting temperature of 91.70°C. However, despite its lytic effect against such extremophiles as: T. thermophilus, Thermus flavus, Thermus parvatiensis, Thermus scotoductus, and Deinococcus radiodurans, PhiKo showed moderate antibacterial activity against mesophiles. Consequently, its protein sequence was searched for regions with potential antibacterial activity. A highly positively charged region was identified and synthetized (PhiKo105-133). The novel RAP-29 peptide lysed mesophilic strains of staphylococci and Gram-negative bacteria, reducing the number of cells by 3.7-7.1 log units and reaching the minimum inhibitory concentration values in the range of 2-31 µM. This peptide is unstructured in an aqueous solution but forms an α-helix in the presence of detergents. Moreover, it binds lipoteichoic acid and lipopolysaccharide, and causes depolarization of bacterial membranes. The RAP-29 peptide is a promising candidate for combating bacterial pathogens. The existence of this cryptic peptide testifies to a much wider panel of antimicrobial peptides than thought previously.

MetaDisorder: a meta-server for the prediction of intrinsic disorder in proteins.

BACKGROUND: Intrinsically unstructured proteins (IUPs) lack a well-defined three-dimensional structure. Some of them may assume a locally stable structure under specific conditions, e.g. upon interaction with another molecule, while others function in a permanently unstructured state. The discovery of IUPs challenged the traditional protein structure paradigm, which stated that a specific well-defined structure defines the function of the protein. As of December 2011, approximately 60 methods for computational prediction of protein disorder from sequence have been made publicly available. They are based on different approaches, such as utilizing evolutionary information, energy functions, and various statistical and machine learning methods. RESULTS: Given the diversity of existing intrinsic disorder prediction methods, we decided to test whether it is possible to combine them into a more accurate meta-prediction method. We developed a method based on arbitrarily chosen 13 disorder predictors, in which the final consensus was weighted by the accuracy of the methods. We have also developed a disorder predictor GSmetaDisorder3D that used no third-party disorder predictors, but alignments to known protein structures, reported by the protein fold-recognition methods, to infer the potentially structured and unstructured regions. Following the success of our disorder predictors in the CASP8 benchmark, we combined them into a meta-meta predictor called GSmetaDisorderMD, which was the top scoring method in the subsequent CASP9 benchmark. CONCLUSIONS: A series of disorder predictors described in this article is available as a MetaDisorder web server at http://iimcb.genesilico.pl/metadisorder/. Results are presented both in an easily interpretable, interactive mode and in a simple text format suitable for machine processing.