Molecular Evolution and Diversification of Proteins Involved in miRNA Maturation Pathway.

Small RNAs (smRNA, 19-25 nucleotides long), which are transcribed by RNA polymerase II, regulate the expression of genes involved in a multitude of processes in eukaryotes. miRNA biogenesis and the proteins involved in the biogenesis pathway differ across plant and animal lineages. The major proteins constituting the biogenesis pathway, namely, the Dicers (DCL/DCR) and Argonautes (AGOs), have been extensively studied. However, the accessory proteins (DAWDLE (DDL), SERRATE (SE), and TOUGH (TGH)) of the pathway that differs across the two lineages remain largely uncharacterized. We present the first detailed report on the molecular evolution and divergence of these proteins across eukaryotes. Although DDL is present in eukaryotes and prokaryotes, SE and TGH appear to be specific to eukaryotes. The addition/deletion of specific domains and/or domain-specific sequence divergence in the three proteins points to the observed functional divergence of these proteins across the two lineages, which correlates with the differences in miRNA length across the two lineages. Our data enhance the current understanding of the structure-function relationship of these proteins and reveals previous unexplored crucial residues in the three proteins that can be used as a basis for further functional characterization. The data presented here on the number of miRNAs in crown eukaryotic lineages are consistent with the notion of the expansion of the number of miRNA-coding genes in animal and plant lineages correlating with organismal complexity. Whether this difference in functionally correlates with the diversification (or presence/absence) of the three proteins studied here or the miRNA signaling in the plant and animal lineages is unclear. Based on our results of the three proteins studied here and previously available data concerning the evolution of miRNA genes in the plant and animal lineages, we believe that miRNAs probably evolved once in the ancestor to crown eukaryotes and have diversified independently in the eukaryotes.

The bio.tools registry of software tools and data resources for the life sciences.

Bioinformaticians and biologists rely increasingly upon workflows for the flexible utilization of the many life science tools that are needed to optimally convert data into knowledge. We outline a pan-European enterprise to provide a catalogue ( https://bio.tools ) of tools and databases that can be used in these workflows. bio.tools not only lists where to find resources, but also provides a wide variety of practical information.

SugarSketcher: Quick and Intuitive Online Glycan Drawing.

SugarSketcher is an intuitive and fast JavaScript interface module for online drawing of glycan structures in the popular Symbol Nomenclature for Glycans (SNFG) notation and exporting them to various commonly used formats encoding carbohydrate sequences (e.g., GlycoCT) or quality images (e.g., svg). It does not require a backend server or any specific browser plugins and can be integrated in any web glycoinformatics project. SugarSketcher allows drawing glycans both for glycobiologists and non-expert users. The "quick mode" allows a newcomer to build up a glycan structure having only a limited knowledge in carbohydrate chemistry. The "normal mode" integrates advanced options which enable glycobiologists to tailor complex carbohydrate structures. The source code is freely available on GitHub and glycoinformaticians are encouraged to participate in the development process while users are invited to test a prototype available on the ExPASY web-site and send feedback.

Molecular evolution and diversification of the SMXL gene family.

Strigolactones (SLs) are a relatively recent addition to the list of plant hormones that control different aspects of plant development. SL signalling is perceived by an α/ß hydrolase, DWARF 14 (D14). A close homolog of D14, KARRIKIN INSENSTIVE2 (KAI2), is involved in perception of an uncharacterized molecule called karrikin (KAR). Recent studies in Arabidopsis identified the SUPPRESSOR OF MAX2 1 (SMAX1) and SMAX1-LIKE 7 (SMXL7) to be potential SCF-MAX2 complex-mediated proteasome targets of KAI2 and D14, respectively. Genetic studies on SMXL7 and SMAX1 demonstrated distinct developmental roles for each, but very little is known about these repressors in terms of their sequence features. In this study, we performed an extensive comparative analysis of SMXLs and determined their phylogenetic and evolutionary history in the plant lineage. Our results show that SMXL family members can be sub-divided into four distinct phylogenetic clades/classes, with an ancient SMAX1. Further, we identified the clade-specific motifs that have evolved and that might act as determinants of SL-KAR signalling specificity. These specificities resulted from functional diversities among the clades. Our results suggest that a gradual co-evolution of SMXL members with their upstream receptors D14/KAI2 provided an increased specificity to both the SL perception and response in land plants.

PDBsum: Structural summaries of PDB entries.

PDBsum is a web server providing structural information on the entries in the Protein Data Bank (PDB). The analyses are primarily image-based and include protein secondary structure, protein-ligand and protein-DNA interactions, PROCHECK analyses of structural quality, and many others. The 3D structures can be viewed interactively in RasMol, PyMOL, and a JavaScript viewer called 3Dmol.js. Users can upload their own PDB files and obtain a set of password-protected PDBsum analyses for each. The server is freely accessible to all at: http://www.ebi.ac.uk/pdbsum.

MotiveValidator: interactive web-based validation of ligand and residue structure in biomolecular complexes.

Structure validation has become a major issue in the structural biology community, and an essential step is checking the ligand structure. This paper introduces MotiveValidator, a web-based application for the validation of ligands and residues in PDB or PDBx/mmCIF format files provided by the user. Specifically, MotiveValidator is able to evaluate in a straightforward manner whether the ligand or residue being studied has a correct annotation (3-letter code), i.e. if it has the same topology and stereochemistry as the model ligand or residue with this annotation. If not, MotiveValidator explicitly describes the differences. MotiveValidator offers a user-friendly, interactive and platform-independent environment for validating structures obtained by any type of experiment. The results of the validation are presented in both tabular and graphical form, facilitating their interpretation. MotiveValidator can process thousands of ligands or residues in a single validation run that takes no more than a few minutes. MotiveValidator can be used for testing single structures, or the analysis of large sets of ligands or fragments prepared for binding site analysis, docking or virtual screening. MotiveValidator is freely available via the Internet at http://ncbr.muni.cz/MotiveValidator.

Predicting p Ka values from EEM atomic charges.

: The acid dissociation constant p Ka is a very important molecular property, and there is a strong interest in the development of reliable and fast methods for p Ka prediction. We have evaluated the p Ka prediction capabilities of QSPR models based on empirical atomic charges calculated by the Electronegativity Equalization Method (EEM). Specifically, we collected 18 EEM parameter sets created for 8 different quantum mechanical (QM) charge calculation schemes. Afterwards, we prepared a training set of 74 substituted phenols. Additionally, for each molecule we generated its dissociated form by removing the phenolic hydrogen. For all the molecules in the training set, we then calculated EEM charges using the 18 parameter sets, and the QM charges using the 8 above mentioned charge calculation schemes. For each type of QM and EEM charges, we created one QSPR model employing charges from the non-dissociated molecules (three descriptor QSPR models), and one QSPR model based on charges from both dissociated and non-dissociated molecules (QSPR models with five descriptors). Afterwards, we calculated the quality criteria and evaluated all the QSPR models obtained. We found that QSPR models employing the EEM charges proved as a good approach for the prediction of p Ka (63% of these models had R2 > 0.9, while the best had R2 = 0.924). As expected, QM QSPR models provided more accurate p Ka predictions than the EEM QSPR models but the differences were not significant. Furthermore, a big advantage of the EEM QSPR models is that their descriptors (i.e., EEM atomic charges) can be calculated markedly faster than the QM charge descriptors. Moreover, we found that the EEM QSPR models are not so strongly influenced by the selection of the charge calculation approach as the QM QSPR models. The robustness of the EEM QSPR models was subsequently confirmed by cross-validation. The applicability of EEM QSPR models for other chemical classes was illustrated by a case study focused on carboxylic acids. In summary, EEM QSPR models constitute a fast and accurate p Ka prediction approach that can be used in virtual screening.

SiteBinder: an improved approach for comparing multiple protein structural motifs.

There is a paramount need to develop new techniques and tools that will extract as much information as possible from the ever growing repository of protein 3D structures. We report here on the development of a software tool for the multiple superimposition of large sets of protein structural motifs. Our superimposition methodology performs a systematic search for the atom pairing that provides the best fit. During this search, the RMSD values for all chemically relevant pairings are calculated by quaternion algebra. The number of evaluated pairings is markedly decreased by using PDB annotations for atoms. This approach guarantees that the best fit will be found and can be applied even when sequence similarity is low or does not exist at all. We have implemented this methodology in the Web application SiteBinder, which is able to process up to thousands of protein structural motifs in a very short time, and which provides an intuitive and user-friendly interface. Our benchmarking analysis has shown the robustness, efficiency, and versatility of our methodology and its implementation by the successful superimposition of 1000 experimentally determined structures for each of 32 eukaryotic linear motifs. We also demonstrate the applicability of SiteBinder using three case studies. We first compared the structures of 61 PA-IIL sugar binding sites containing nine different sugars, and we found that the sugar binding sites of PA-IIL and its mutants have a conserved structure despite their binding different sugars. We then superimposed over 300 zinc finger central motifs and revealed that the molecular structure in the vicinity of the Zn atom is highly conserved. Finally, we superimposed 12 BH3 domains from pro-apoptotic proteins. Our findings come to support the hypothesis that there is a structural basis for the functional segregation of BH3-only proteins into activators and enablers.

Electronegativity equalization method: parameterization and validation for organic molecules using the Merz-Kollman-Singh charge distribution scheme.

The electronegativity equalization method (EEM) was developed by Mortier et al. as a semiempirical method based on the density-functional theory. After parameterization, in which EEM parameters A(i), B(i), and adjusting factor kappa are obtained, this approach can be used for calculation of average electronegativity and charge distribution in a molecule. The aim of this work is to perform the EEM parameterization using the Merz-Kollman-Singh (MK) charge distribution scheme obtained from B3LYP/6-31G* and HF/6-31G* calculations. To achieve this goal, we selected a set of 380 organic molecules from the Cambridge Structural Database (CSD) and used the methodology, which was recently successfully applied to EEM parameterization to calculate the HF/STO-3G Mulliken charges on large sets of molecules. In the case of B3LYP/6-31G* MK charges, we have improved the EEM parameters for already parameterized elements, specifically C, H, N, O, and F. Moreover, EEM parameters for S, Br, Cl, and Zn, which have not as yet been parameterized for this level of theory and basis set, we also developed. In the case of HF/6-31G* MK charges, we have developed the EEM parameters for C, H, N, O, S, Br, Cl, F, and Zn that have not been parameterized for this level of theory and basis set so far. The obtained EEM parameters were verified by a previously developed validation procedure and used for the charge calculation on a different set of 116 organic molecules from the CSD. The calculated EEM charges are in a very good agreement with the quantum mechanically obtained ab initio charges.

Web server to identify similarity of amino acid motifs to compounds (SAAMCO).

Protein-protein interactions are fundamental in mediating biological processes including metabolism, cell growth, and signaling. To be able to selectively inhibit or induce protein activity or complex formation is a key feature in controlling disease. For those situations in which protein-protein interactions derive substantial affinity from short linear peptide sequences, or motifs, we can develop search algorithms for peptidomimetic compounds that resemble the short peptide's structure but are not compromised by poor pharmacological properties. SAAMCO is a Web service ( http://bioware.ucd.ie/ approximately saamco) that facilitates the screening of motifs with known structures against bioactive compound databases. It is built on an algorithm that defines compound similarity based on the presence of appropriate amino acid side chain fragments and a favorable Root Mean Squared Deviation (RMSD) between compound and motif structure. The methodology is efficient as the available compound databases are preprocessed and fast regular expression searches filter potential matches before time-intensive 3D superposition is performed. The required input information is minimal, and the compound databases have been selected to maximize the availability of information on biological activity. "Hits" are accompanied with a visualization window and links to source database entries. Motif matching can be defined on partial or full similarity which will increase or reduce respectively the number of potential mimetic compounds. The Web server provides the functionality for rapid screening of known or putative interaction motifs against prepared compound libraries using a novel search algorithm. The tabulated results can be analyzed by linking to appropriate databases and by visualization.

www.rnaworkbench.com: A new program for analyzing RNA interference.

RNA interference (RNAi) has become an important tool to study and utilize gene silencing by introducing short interfering RNA (siRNA). In order to predict the most efficient siRNAs, a new software tool, RNA Workbench (RNAWB), has been designed and is freely available (after registration) on http://www.rnaworkbench.com. In addition to the standard selection rules, RNAWB includes the possibility of statistical analyses of the applied selection rules (criteria). The role of RNA secondary structures in the RNA interference process as well as the application of sequence rules are discussed to show the applicability of the software.

Identification of potential small molecule peptidomimetics similar to motifs in proteins.

Protein-protein interactions are central to most biological processes and represent a large and important class of targets for human therapeutics. Small molecules containing peptide substituents may mimic regions of interacting proteins and inhibit their interactions. We set out to develop efficient methods to screen for similarities between known peptide structures within proteins and small molecules. We developed a method to rank peptide-compound similarities, that is restricted to small linear motifs in proteins, and to compounds containing amino acid substituents. Application to a search of the PubChem database (5.4 million compounds) using all short motifs on accessible surface areas in a nonredundant set of 11 488 peptides from the protein structure database PDB demonstrated the feasibility of the method for high throughput comparisons and the availability of compounds with comparable substituents: over 6 million compound-peptide pairs shared at least three amino acid substituents, approximately 100 000 of which had an rmsd score of less than 1 A. A Z-score function was developed that compares matches of a compound to different instances of the peptide motif in PDB, providing an appropriate scoring function for comparison among peptide-compound similarities involving different numbers of atoms (while simultaneously enriching for similarities that are likely to be more specific for the protein of interest). We applied the method to searches of known short protein motifs against the National Cancer Institute Developmental Therapeutic Program compound database, identifying a known true positive.