Specific Targeting of Plant and Apicomplexa Parasite Tubulin through Differential Screening Using In Silico and Assay-Based Approaches.

Dinitroanilines are chemical compounds with high selectivity for plant cell α-tubulin in which they promote microtubule depolymerization. They target α-tubulin regions that have diverged over evolution and show no effect on non-photosynthetic eukaryotes. Hence, they have been used as herbicides over decades. Interestingly, dinitroanilines proved active on microtubules of eukaryotes deriving from photosynthetic ancestors such as Toxoplasma gondii and Plasmodium falciparum, which are responsible for toxoplasmosis and malaria, respectively. By combining differential in silico screening of virtual chemical libraries on Arabidopsis thaliana and mammal tubulin structural models together with cell-based screening of chemical libraries, we have identified dinitroaniline related and non-related compounds. They inhibit plant, but not mammalian tubulin assembly in vitro, and accordingly arrest A. thaliana development. In addition, these compounds exhibit a moderate cytotoxic activity towards T. gondii and P. falciparum. These results highlight the potential of novel herbicidal scaffolds in the design of urgently needed anti-parasitic drugs.

Glycerolipids in photosynthesis: composition, synthesis and trafficking.

Glycerolipids constituting the matrix of photosynthetic membranes, from cyanobacteria to chloroplasts of eukaryotic cells, comprise monogalactosyldiacylglycerol, digalactosyldiacylglycerol, sulfoquinovosyldiacylglycerol and phosphatidylglycerol. This review covers our current knowledge on the structural and functional features of these lipids in various cellular models, from prokaryotes to eukaryotes. Their relative proportions in thylakoid membranes result from highly regulated and compartmentalized metabolic pathways, with a cooperation, in the case of eukaryotes, of non-plastidic compartments. This review also focuses on the role of each of these thylakoid glycerolipids in stabilizing protein complexes of the photosynthetic machinery, which might be one of the reasons for their fascinating conservation in the course of evolution. This article is part of a Special Issue entitled: Dynamic and ultrastructure of bioenergetic membranes and their components.

Correction: LC-MS/MS versus TLC plus GC methods: Consistency of glycerolipid and fatty acid profiles in microalgae and higher plant cells and effect of a nitrogen starvation.

[This corrects the article DOI: 10.1371/journal.pone.0182423.].

LC-MS/MS versus TLC plus GC methods: Consistency of glycerolipid and fatty acid profiles in microalgae and higher plant cells and effect of a nitrogen starvation.

Methods to analyze lipidomes have considerably evolved, more and more based on mass spectrometry technics (LC-MS/MS). However, accurate quantifications using these methods require 13C-labeled standards for each lipid, which is not feasible because of the very large number of molecules. Thus, quantifications rely on standard molecules representative of a whole class of lipids, which might lead to false estimations of some molecular species. Here, we determined and compared glycerolipid distributions from three different types of cells, two microalgae (Phaeodactylum tricornutum, Nannochloropsis gaditana) and one higher plant (Arabidopsis thaliana), using either LC-MS/MS or Thin Layer Chromatography coupled with Gas Chromatography (TLC-GC), this last approach relying on the precise quantification of the fatty acids present in each glycerolipid class. Our results showed that the glycerolipid distribution was significantly different depending on the method used. How can one reconcile these two analytical methods? Here we propose that the possible bias with MS data can be circumvented by systematically running in tandem with the sample to be analyzed a lipid extract from a qualified control (QC) of each type of cells, previously analyzed by TLC-GC, and used as an external standard to quantify the MS results. As a case study, we applied this method to compare the impact of a nitrogen deficiency on the three types of cells.

Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?

The organization and mining of malaria genomic and post-genomic data is important to significantly increase the knowledge of the biology of its causative agents, and is motivated, on a longer term, by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum, but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should, therefore, be as reliable and versatile as possible. In this context, five aspects of the organization and mining of malaria genomic and post-genomic data were examined: 1) the comparison of protein sequences including compositionally atypical malaria sequences, 2) the high throughput reconstruction of molecular phylogenies, 3) the representation of biological processes, particularly metabolic pathways, 4) the versatile methods to integrate genomic data, biological representations and functional profiling obtained from X-omic experiments after drug treatments and 5) the determination and prediction of protein structures and their molecular docking with drug candidate structures. Recent progress towards a grid-enabled chemogenomic knowledge space is discussed.

A configuration space of homologous proteins conserving mutual information and allowing a phylogeny inference based on pair-wise Z-score probabilities.

BACKGROUND: Popular methods to reconstruct molecular phylogenies are based on multiple sequence alignments, in which addition or removal of data may change the resulting tree topology. We have sought a representation of homologous proteins that would conserve the information of pair-wise sequence alignments, respect probabilistic properties of Z-scores (Monte Carlo methods applied to pair-wise comparisons) and be the basis for a novel method of consistent and stable phylogenetic reconstruction. RESULTS: We have built up a spatial representation of protein sequences using concepts from particle physics (configuration space) and respecting a frame of constraints deduced from pair-wise alignment score properties in information theory. The obtained configuration space of homologous proteins (CSHP) allows the representation of real and shuffled sequences, and thereupon an expression of the TULIP theorem for Z-score probabilities. Based on the CSHP, we propose a phylogeny reconstruction using Z-scores. Deduced trees, called TULIP trees, are consistent with multiple-alignment based trees. Furthermore, the TULIP tree reconstruction method provides a solution for some previously reported incongruent results, such as the apicomplexan enolase phylogeny. CONCLUSION: The CSHP is a unified model that conserves mutual information between proteins in the way physical models conserve energy. Applications include the reconstruction of evolutionary consistent and robust trees, the topology of which is based on a spatial representation that is not reordered after addition or removal of sequences. The CSHP and its assigned phylogenetic topology, provide a powerful and easily updated representation for massive pair-wise genome comparisons based on Z-score computations.

Construction of non-symmetric substitution matrices derived from proteomes with biased amino acid distributions.

Automatic comparison of compositionally biased genomes, such as that of the malarial causative agent Plasmodium falciparum (82% adenosine + thymidine), with genomes of average composition, is currently limited. Indeed, popular tools such as BLAST require that amino acid distributions be similar in aligned sequences. However, the P. falciparum genome is so biased that six amino acids account for more than 50% of the protein composition. One reason for the comparison methods failure lies in the compositional difference between the query and the subject proteomes, which is not taken into account in the amino acid substitution matrices. This paper introduces a method to derive substitution matrices, in particular BLOSUM 62, in the frame of the information theory. It allows the construction of non-symmetrical matrices, taking into account the non-symmetric amino acid distributions. The dirAtPf family of matrices allowing the comparison of P. falciparum and A. thaliana is given as an example. This paper further provides an analysis of the obtained matrices in the frame of the information theory, supporting the discrimination advantage they bring.

Analysis of the compositional biases in Plasmodium falciparum genome and proteome using Arabidopsis thaliana as a reference.

Comparative genomic analysis of the malaria causative agent, Plasmodium falciparum, with other eukaryotes for which the complete genome is available, revealed that the genome from P. falciparum was more similar to the genome of a plant, Arabidopsis thaliana, than to other non-apicomplexan taxa. Plant-like sequences are thought to result from horizontal gene transfers after a secondary endosymbiosis involving an algal ancestor. The use of the A. thaliana genome and proteome as a reference gives an opportunity to refine our understanding of the extreme compositional bias in the P. falciparum genome that leads to a proteome-wide amino acid bias. A set of pairs of non-redundant protein homologues was selected owing to rigorous genome-wide sequence comparison methods. The introduction of A. thaliana as a reference was a mean to weight the magnitude of the protein evolutionary divergence in P. falciparum. The correlation of the amino acid proportions with evolutionary time supports the hypothesis that amino acids encoded by GC-rich codons are directionally substituted into amino acids encoded by AT-rich codons in the P. falciparum proteome. The long-term deviation of codons in malarial sequences appears as a possible consequence of a genome-wide tri-nucleotidic signature imprinting. Additionally, this study suggests possible working guidelines to improve the accuracy of P. falciparum sequence comparisons, for homology searches and phylogenetic studies.

Expanding the chemical diversity of CK2 inhibitors.

None of the already described CK2 inhibitors did fulfill the requirements for successful clinical settings. In order to find innovative CK2 inhibitors based on new scaffolds, we have performed a high-throughput screening of diverse chemical libraries. We report here the identification and characterization of several classes of new inhibitors. Whereas some share characteristics of previously known CK2 inhibitors, others are chemically unrelated and may represent new opportunities for the development of better CK2 inhibitors. By combining structure-activity relationships with a docking procedure, we were able to determine the binding mode of these inhibitors. Interestingly, beside the identification of several nanomolar ATP-competitive inhibitors, one class of chemical inhibitors displays a non-ATP competitive mode of inhibition, a feature that suggests that CK2 possess distinct druggable binding sites. For the most promising inhibitors, selectivity profiling was performed. We also provide evidence that some chemical compounds are inhibiting CK2 in living cells. Finally, the collected data allowed us to draw the rules about the chemical requirements for CK2 inhibition both in vitro and in a cellular context.

Fundamentals of massive automatic pairwise alignments of protein sequences: theoretical significance of Z-value statistics.

MOTIVATION: Different automatic methods of sequence alignments are routinely used as a starting point for homology searches and function inference. Confidence in an alignment probability is one of the major fundamentals of massive automatic genome-scale pairwise comparisons, for clustering of putative orthologs and paralogs, sequenced genome annotation or multiple-genomic tree constructions. Extreme value distribution based on the Karlin-Altschul model, usually advised for large-scale comparisons are not always valid, particularly in the case of comparisons of non-biased with nucleotide-biased genomes (such that of Plasmodium falciparum). Z-values estimates based on Monte Carlo technics, can be calculated experimentally for any alignment output, whatever the method used. Empirically, a Z-value higher than approximately 8 is supposed reasonable to assess that an alignment score is significant, but this arbitrary figure was never theoretically justified. RESULTS: In this paper, we used the Bienaymé-Chebyshev inequality to demonstrate a theorem of the upper limit of an alignment score probability (or P-value). This theorem implies that a computed Z-value is a statistical test, a single-linkage clustering criterion and that 1/Z-value(2) is an upper limit to the probability of an alignment score whatever the actual probability law is. Therefore, this study provides the missing theoretical link between a Z-value cut-off used for an automatic clustering of putative orthologs and/or paralogs, and the corresponding statistical risk in such genome-scale comparisons (using non-biased or biased genomes).