Lukasz Kozlowski

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

BackgroundIntrinsically 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.ResultsGiven 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.ConclusionsA 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.

Computational methods for prediction of protein–RNA interactions

Understanding the molecular mechanism of protein-RNA recognition and complex formation is a major challenge in structural biology. Unfortunately, the experimental determination of protein-RNA complexes by X-ray crystallography and nuclear magnetic resonance spectroscopy (NMR) is tedious and difficult. Alternatively, protein-RNA interactions can be predicted by computational methods. Although less accurate than experimental observations, computational predictions can be sufficiently accurate to prompt functional hypotheses and guide experiments, e.g. to identify individual amino acid or nucleotide residues. In this article we review 10 methods for predicting protein-RNA interactions, seven of which predict RNA-binding sites from protein sequences and three from structures. We also developed a meta-predictor that uses the output of top three sequence-based primary predictors to calculate a consensus prediction, which outperforms all the primary predictors. In order to fully cover the software for predicting protein-RNA interactions, we also describe five methods for protein-RNA docking. The article highlights the strengths and shortcomings of existing methods for the prediction of protein-RNA interactions and provides suggestions for their further development.

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.

A novel homozygous p.Arg527Leu LMNA mutation in two unrelated Egyptian families causes overlapping mandibuloacral dysplasia and progeria syndrome.

Mandibuloacral dysplasia (MAD) is a rare disease resulting from a mutation of LMNA gene encoding lamins A and C. The most common mutation associated with this disease is a homozygous arginine 527 replacement by histidine. Three female patients originating from two unrelated families from Northeast Egypt were examined. Their growth was retarded; they had microcephaly, widened cranial sutures, prominent eyes and cheeks, micrognathia, dental crowding, hypoplastic mandible, acro-osteolysis of distal phalanges, and joint contractures. In addition, they presented some progeroid features, such as pinched nose, premature loss of teeth, loss of hair, scleroderma-like skin atrophy, spine rigidity, and waddling gait. The clinical presentation of the disease varied between the patient originating from Family 1 and patients from Family 2, suggesting that unknown, possibly epigenetic factors, modify the course of the disease. The first symptoms of the disease appeared at the age of 2.5 (a girl from Family 1), 5, and 3 years (girls from Family 2). All patients had the same, novel homozygous c.1580G>T LMNA mutation, resulting in the replacement of arginine 527 by leucine. Computational predictions of such substitution effects suggested that it might alter protein stability and increase the tendency for protein aggregation, and as a result, might influence its interaction with other proteins. In addition, restriction fragment-length polymorphism analysis performed in 178 unrelated individuals showed that up to 1.12% of inhabitants of Northeast Egypt might be heterozygous carriers of this mutation, suggesting the presence of a founder effect in this area.

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.

Proteome-pI: proteome isoelectric point database

Abstract 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.

Novel Highly Thermostable Endolysin from Thermus scotoductus MAT2119 Bacteriophage Ph2119 with Amino Acid Sequence Similarity to Eukaryotic Peptidoglycan Recognition Proteins

ABSTRACT 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 M r of 17,555. Ph2119 endolysin does not resemble any known thermophilic phage lytic enzymes. Instead, it has conserved amino acid residues (His30, Tyr58, His132, and Cys140) that form a Zn2+ 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 Crohns 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.

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.

Biochemical Characterization and Validation of a Catalytic Site of a Highly Thermostable Ts2631 Endolysin from the Thermus scotoductus Phage vB_Tsc2631.

Phage vB_Tsc2631 infects the extremophilic bacterium Thermus scotoductus MAT2631 and uses the Ts2631 endolysin for the release of its progeny. The Ts2631 endolysin is the first endolysin from thermophilic bacteriophage with an experimentally validated catalytic site. In silico analysis and computational modelling of the Ts2631 endolysin structure revealed a conserved Zn2+ binding site (His30, Tyr58, His131 and Cys139) similar to Zn2+ binding site of eukaryotic peptidoglycan recognition proteins (PGRPs). We have shown that the Ts2631 endolysin lytic activity is dependent on divalent metal ions (Zn2+ and Ca2+). The Ts2631 endolysin substitution variants H30N, Y58F, H131N and C139S dramatically lost their antimicrobial activity, providing evidence for the role of the aforementioned residues in the lytic activity of the enzyme. The enzyme has proven to be not only thermoresistant, retaining 64.8% of its initial activity after 2 h at 95°C, but also highly thermodynamically stable (Tm = 99.82°C, ΔHcal = 4.58 × 104 cal mol-1). Substitutions of histidine residues (H30N and H131N) and a cysteine residue (C139S) resulted in variants aggregating at temperatures ≥75°C, indicating a significant role of these residues in enzyme thermostability. The substrate spectrum of the Ts2631 endolysin included extremophiles of the genus Thermus but also Gram-negative mesophiles, such as Escherichia coli, Salmonella panama, Pseudomonas fluorescens and Serratia marcescens. The broad substrate spectrum and high thermostability of this endolysin makes it a good candidate for use as an antimicrobial agent to combat Gram-negative pathogens.