MODOMICS: a database of RNA modification pathways

MODOMICS is the first comprehensive database resource for systems biology of RNA modification. It integrates information about the chemical structure of modified nucleosides, their localization in RNA sequences, pathways of their biosynthesis and enzymes that carry out the respective reactions. MODOMICS also provides literature information, and links to other databases, including the available protein sequence and structure data. The current list of modifications and pathways is comprehensive, while the dataset of enzymes is limited to Escherichia coli and Saccharomyces cerevisiae and sequence alignments are presented only for tRNAs from these organisms. RNAs and enzymes from other organisms will be included in the near future. MODOMICS can be queried by the type of nucleoside (e.g. A, G, C, U, I, m(1)A, nm(5)s(2)U, etc.), type of RNA, position of a particular nucleoside, type of reaction (e.g. methylation, thiolation, deamination, etc.) and name or sequence of an enzyme of interest. Options for data presentation include graphs of pathways involving the query nucleoside, multiple sequence alignments of RNA sequences and tabular forms with enzyme and literature data. The contents of MODOMICS can be accessed through the World Wide Web at

Dimeric peroxiredoxins are druggable targets in human Burkitt lymphoma

Burkitt lymphoma is a fast-growing tumor derived from germinal center B cells. It is mainly treated with aggressive chemotherapy, therefore novel therapeutic approaches are needed due to treatment toxicity and developing resistance. Disturbance of red-ox homeostasis has recently emerged as an efficient antitumor strategy. Peroxiredoxins (PRDXs) are thioredoxin-family antioxidant enzymes that scavenge cellular peroxides and contribute to red-ox homeostasis. PRDXs are robustly expressed in various malignancies and critically involved in cell proliferation, differentiation and apoptosis. To elucidate potential role of PRDXs in lymphoma, we studied their expression level in B cell-derived primary lymphoma cells as well as in cell lines. We found that PRDX1 and PRDX2 are upregulated in tumor B cells as compared with normal counterparts. Concomitant knockdown of PRDX1 and PRDX2 significantly attenuated the growth rate of lymphoma cells. Furthermore, in human Burkitt lymphoma cell lines, we isolated dimeric 2-cysteine peroxiredoxins as targets for SK053, a novel thiol-specific small-molecule peptidomimetic with antitumor activity. We observed that treatment of lymphoma cells with SK053 triggers formation of covalent PRDX dimers, accumulation of intracellular reactive oxygen species, phosphorylation of ERK1/2 and AKT and leads to cell cycle arrest and apoptosis. Based on site-directed mutagenesis and modeling studies, we propose a mechanism of SK053-mediated PRDX crosslinking, involving double thioalkylation of active site cysteine residues. Altogether, our results suggest that peroxiredoxins are novel therapeutic targets in Burkitt lymphoma and provide the basis for new approaches to the treatment of this disease

Tridimensional model structure and patterns of molecular evolution of Pepino mosaic virus TGBp3 protein

<p>Abstract</p> <p>Background</p> <p><it>Pepino mosaic virus </it>(PepMV) is considered one of the most dangerous pathogens infecting tomatoes worldwide. The virus is highly diverse and four distinct genotypes, as well as inter-strain recombinants, have already been described. The isolates display a wide range on symptoms on infected plant species, ranging from mild mosaic to severe necrosis. However, little is known about the mechanisms and pattern of PepMV molecular evolution and about the role of individual proteins in host-pathogen interactions.</p> <p>Methods</p> <p>The nucleotide sequences of the triple gene block 3 (TGB3) from PepMV isolates varying in symptomatology and geographic origin have been analyzed. The modes and patterns of molecular evolution of the TGBp3 protein were investigated by evaluating the selective constraints to which particular amino acid residues have been subjected during the course of diversification. The tridimensional structure of TGBp3 protein has been modeled <it>de novo </it>using the Rosetta algorithm. The correlation between symptoms development and location of specific amino acids residues was analyzed.</p> <p>Results</p> <p>The results have shown that TGBp3 has been evolving mainly under the action of purifying selection operating on several amino acid sites, thus highlighting its functional role during PepMV infection. Interestingly, amino acid 67, which has been previously shown to be a necrosis determinant, was found to be under positive selection.</p> <p>Conclusions</p> <p>Identification of diverse selection events in TGB3p3 will help unraveling its biological functions and is essential to an understanding of the evolutionary constraints exerted on the <it>Potexvirus </it>genome. The estimated tridimensional structure of TGBp3 will serve as a platform for further sequence, structural and function analysis and will stimulate new experimental advances.</p

Molecular evolution of dihydrouridine synthases

Abstract Background Dihydrouridine (D) is a modified base found in conserved positions in the D-loop of tRNA in Bacteria, Eukaryota, and some Archaea. Despite the abundant occurrence of D, little is known about its biochemical roles in mediating tRNA function. It is assumed that D may destabilize the structure of tRNA and thus enhance its conformational flexibility. D is generated post-transcriptionally by the reduction of the 5,6-double bond of a uridine residue in RNA transcripts. The reaction is carried out by dihydrouridine synthases (DUS). DUS constitute a conserved family of enzymes encoded by the orthologous gene family COG0042. In protein sequence databases, members of COG0042 are typically annotated as “predicted TIM-barrel enzymes, possibly dehydrogenases, nifR3 family”. Results To elucidate sequence-structure-function relationships in the DUS family, a comprehensive bioinformatic analysis was carried out. We performed extensive database searches to identify all members of the currently known DUS family, followed by clustering analysis to subdivide it into subfamilies of closely related sequences. We analyzed phylogenetic distributions of all members of the DUS family and inferred the evolutionary tree, which suggested a scenario for the evolutionary origin of dihydrouridine-forming enzymes. For a human representative of the DUS family, the hDus2 protein suggested as a potential drug target in cancer, we generated a homology model. While this article was under review, a crystal structure of a DUS representative has been published, giving us an opportunity to validate the model. Conclusions We compared sequences and phylogenetic distributions of all members of the DUS family and inferred the phylogenetic tree, which provides a framework to study the functional differences among these proteins and suggests a scenario for the evolutionary origin of dihydrouridine formation. Our evolutionary and structural classification of the DUS family provides a background to study functional differences among these proteins that will guide experimental analyses.</p

Identification of STAT1 and STAT3 specific inhibitors using comparative virtual screening and docking validation.

Signal transducers and activators of transcription (STATs) facilitate action of cytokines, growth factors and pathogens. STAT activation is mediated by a highly conserved SH2 domain, which interacts with phosphotyrosine motifs for specific STAT-receptor contacts and STAT dimerization. The active dimers induce gene transcription in the nucleus by binding to a specific DNA-response element in the promoter of target genes. Abnormal activation of STAT signaling pathways is implicated in many human diseases, like cancer, inflammation and auto-immunity. Searches for STAT-targeting compounds, exploring the phosphotyrosine (pTyr)-SH2 interaction site, yielded many small molecules for STAT3 but sparsely for other STATs. However, many of these inhibitors seem not STAT3-specific, thereby questioning the present modeling and selection strategies of SH2 domain-based STAT inhibitors. We generated new 3D structure models for all human (h)STATs and developed a comparative in silico docking strategy to obtain further insight into STAT-SH2 cross-binding specificity of a selection of previously identified STAT3 inhibitors. Indeed, by primarily targeting the highly conserved pTyr-SH2 binding pocket the majority of these compounds exhibited similar binding affinity and tendency scores for all STATs. By comparative screening of a natural product library we provided initial proof for the possibility to identify STAT1 as well as STAT3-specific inhibitors, introducing the 'STAT-comparative binding affinity value' and 'ligand binding pose variation' as selection criteria. In silico screening of a multi-million clean leads (CL) compound library for binding of all STATs, likewise identified potential specific inhibitors for STAT1 and STAT3 after docking validation. Based on comparative virtual screening and docking validation, we developed a novel STAT inhibitor screening tool that allows identification of specific STAT1 and STAT3 inhibitory compounds. This could increase our understanding of the functional role of these STATs in different diseases and benefit the clinical need for more drugable STAT inhibitors with high specificity, potency and excellent bioavailability

Binding conformations of top-scored compounds from natural products library in the SH2 domain of hSTAT1 and hSTAT3.

<p><b>(A)</b> Binding pose variation of the top-scored hSTAT1-specific inhibitor in SH2 domain of hSTAT1 and hSTAT3. <b>(B)</b> Binding pose variation of the top-scored hSTAT3-specific inhibitor in SH2 domain of hSTAT1 and hSTAT3. The binding pose variations are shown in line representation, colored in blue and violet. Results were obtained using Surflex-Dock 2.6 program.</p

STAT3-CBAVs of STAT3-specific inhibitors.

<p>Graph presents comparative binding affinity values of a selection of STAT3-specific inhibitors docked to models of all hSTAT monomers.</p

Structural models and phylogenetic comparison of hSTAT monomers (1, 2, 3, 4, 5A, 5B and 6) with their specific pTyr-linkers.

<p><b>(A)</b> Phylogenetic distribution of hSTATs in form of a simplified phylogenetic tree. <b>(B)</b> Models of the monomers are shown in the cartoon representation with pTyr-peptides in the stick representation. Specific domains are positioned as follows: N-domain on the top-left, coiled-coiled domain on the bottom-center, C-domain on the top-right and SH2 domain on the top-center, to facilitate visual analysis of phosphotyrosine (pTyr)-linker and the SH2 interactions. Monomers are colored according to the predicted local deviation from the real structure (the predicted error of the model), as calculated by MetaMQAP. Blue indicates low predicted deviation of Cα atoms down to 0Å, red indicates unreliable regions with deviation > 5Å, green to orange indicate intermediate values. pTyr-peptides are colored in violet, while pTyr residue is colored in pink. <b>(C)</b> Models of hSTAT dimers with the linker of monomer I in the SH2 domain of monomer II. pTyr-peptides are presented in stick representation, pY+0—pTyr binding pocket, pY-X—hydrophobic side-pocket. SH2 domains are in the surface representation, colored according to the distribution of the electrostatic surface potential, calculated with APBS. Blue indicates positively charged regions, red indicates negatively charged regions.</p