Assessment of the Activity of Nitroisoxazole Derivatives against Trypanosoma cruzi.

The development of new compounds to treat Chagas disease is imperative due to the adverse effects of current drugs and their low efficacy in the chronic phase. This study aims to investigate nitroisoxazole derivatives that produce oxidative stress while modifying the compounds' lipophilicity, affecting their ability to fight trypanosomes. The results indicate that these compounds are more effective against the epimastigote form of T. cruzi, with a 52 ± 4% trypanocidal effect for compound 9. However, they are less effective against the trypomastigote form, with a 15 ± 3% trypanocidal effect. Additionally, compound 11 interacts with a higher number of amino acid residues within the active site of the enzyme cruzipain. Furthermore, it was also found that the presence of a nitro group allows for the generation of free radicals; likewise, the large size of the compound enables increased interaction with aminoacidic residues in the active site of cruzipain, contributing to trypanocidal activity. This activity depends on the size and lipophilicity of the compounds. The study recommends exploring new compounds based on the nitroisoxazole skeleton, with larger substituents and lipophilicity to enhance their trypanocidal activity.

Py-CoMFA, docking, and molecular dynamics simulations of Leishmania (L.) amazonensis arginase inhibitors.

Leishmaniasis is a disease caused by a protozoan of the genus Leishmania, affecting millions of people, mainly in tropical countries, due to poor social conditions and low economic development. First-line chemotherapeutic agents involve highly toxic pentavalent antimonials, while treatment failure is mainly due to the emergence of drug-resistant strains. Leishmania arginase (ARG) enzyme is vital in pathogenicity and contributes to a higher infection rate, thus representing a potential drug target. This study helps in designing ARG inhibitors for the treatment of leishmaniasis. Py-CoMFA (3D-QSAR) models were constructed using 34 inhibitors from different chemical classes against ARG from L. (L.) amazonensis (LaARG). The 3D-QSAR predictions showed an excellent correlation between experimental and calculated pIC50 values. The molecular docking study identified the favorable hydrophobicity contribution of phenyl and cyclohexyl groups as substituents in the enzyme allosteric site. Molecular dynamics simulations of selected protein-ligand complexes were conducted to understand derivatives' interaction modes and affinity in both active and allosteric sites. Two cinnamide compounds, 7g and 7k, were identified, with similar structures to the reference 4h allosteric site inhibitor. These compounds can guide the development of more effective arginase inhibitors as potential antileishmanial drugs.

IFPTML Mapping of Drug Graphs with Protein and Chromosome Structural Networks vs. Pre-Clinical Assay Information for Discovery of Antimalarial Compounds.

The parasite species of genus Plasmodium causes Malaria, which remains a major global health problem due to parasite resistance to available Antimalarial drugs and increasing treatment costs. Consequently, computational prediction of new Antimalarial compounds with novel targets in the proteome of Plasmodium sp. is a very important goal for the pharmaceutical industry. We can expect that the success of the pre-clinical assay depends on the conditions of assay per se, the chemical structure of the drug, the structure of the target protein to be targeted, as well as on factors governing the expression of this protein in the proteome such as genes (Deoxyribonucleic acid, DNA) sequence and/or chromosomes structure. However, there are no reports of computational models that consider all these factors simultaneously. Some of the difficulties for this kind of analysis are the dispersion of data in different datasets, the high heterogeneity of data, etc. In this work, we analyzed three databases ChEMBL (Chemical database of the European Molecular Biology Laboratory), UniProt (Universal Protein Resource), and NCBI-GDV (National Center for Biotechnology Information-Genome Data Viewer) to achieve this goal. The ChEMBL dataset contains outcomes for 17,758 unique assays of potential Antimalarial compounds including numeric descriptors (variables) for the structure of compounds as well as a huge amount of information about the conditions of assays. The NCBI-GDV and UniProt datasets include the sequence of genes, proteins, and their functions. In addition, we also created two partitions (cassayj = caj and cdataj = cdj) of categorical variables from theChEMBL dataset. These partitions contain variables that encode information about experimental conditions of preclinical assays (caj) or about the nature and quality of data (cdj). These categorical variables include information about 22 parameters of biological activity (ca0), 28 target proteins (ca1), and 9 organisms of assay (ca2), etc. We also created another partition of (cprotj = cpj) including categorical variables with biological information about the target proteins, genes, and chromosomes. These variables cover32 genes (cp0), 10 chromosomes (cp1), gene orientation (cp2), and 31 protein functions (cp3). We used a Perturbation-Theory Machine Learning Information Fusion (IFPTML) algorithm to map all this information (from three databases) into and train a predictive model. Shannon's entropy measure Shk (numerical variables) was used to quantify the information about the structure of drugs, protein sequences, gene sequences, and chromosomes in the same information scale. Perturbation Theory Operators (PTOs) with the form of Moving Average (MA) operators have been used to quantify perturbations (deviations) in the structural variables with respect to their expected values for different subsets (partitions) of categorical variables. We obtained three IFPTML models using General Discriminant Analysis (GDA), Classification Tree with Univariate Splits (CTUS), and Classification Tree with Linear Combinations (CTLC). The IFPTML-CTLC presented the better performance with Sensitivity Sn(%) = 83.6/85.1, and Specificity Sp(%) = 89.8/89.7 for training/validation sets, respectively. This model could become a useful tool for the optimization of preclinical assays of new Antimalarial compounds vs. different proteins in the proteome of Plasmodium.

Identification of druggable small molecule antagonists of the Plasmodium falciparum hexose transporter PfHT and assessment of ligand access to the glucose permeation pathway via FLAG-mediated protein engineering.

Although the Plasmodium falciparum hexose transporter PfHT has emerged as a promising target for anti-malarial therapy, previously identified small-molecule inhibitors have lacked promising drug-like structural features necessary for development as clinical therapeutics. Taking advantage of emerging insight into structure/function relationships in homologous facilitative hexose transporters and our novel high throughput screening platform, we investigated the ability of compounds satisfying Lipinksi rules for drug likeness to directly interact and inhibit PfHT. The Maybridge HitFinder chemical library was interrogated by searching for compounds that reduce intracellular glucose by >40% at 10 µM. Testing of initial hits via measurement of 2-deoxyglucose (2-DG) uptake in PfHT over-expressing cell lines identified 6 structurally unique glucose transport inhibitors. WU-1 (3-(2,6-dichlorophenyl)-5-methyl-N-[2-(4-methylbenzenesulfonyl)ethyl]-1,2-oxazole-4-carboxamide) blocked 2-DG uptake (IC50 = 5.8 ± 0.6 µM) with minimal effect on the human orthologue class I (GLUTs 1-4), class II (GLUT8) and class III (GLUT5) facilitative glucose transporters. WU-1 showed comparable potency in blocking 2-DG uptake in freed parasites and inhibiting parasite growth, with an IC50 of 6.1 ± 0.8 µM and EC50 of 5.5 ± 0.6 µM, respectively. WU-1 also directly competed for N-[2-[2-[2-[(N-biotinylcaproylamino)ethoxy)ethoxyl]-4-[2-(trifluoromethyl)-3H-diazirin-3-yl]benzoyl]-1,3-bis(mannopyranosyl-4-yloxy)-2-propylamine (ATB-BMPA) binding and inhibited the transport of D-glucose with an IC50 of 5.9 ± 0.8 µM in liposomes containing purified PfHT. Kinetic analysis revealed that WU-1 acts as a non-competitive inhibitor of zero-trans D-fructose uptake. Decreased potency for WU-1 and the known endofacial ligand cytochalasin B was observed when PfHT was engineered to contain an N-terminal FLAG tag. This modification resulted in a concomitant increase in affinity for 4,6-O-ethylidene-α-D-glucose, an exofacially directed transport antagonist, but did not alter the Km for 2-DG. Taken together, these data are consistent with a model in which WU-1 binds preferentially to the transporter in an inward open conformation and support the feasibility of developing potent and selective PfHT antagonists as a novel class of anti-malarial drugs.

Purification of Glycosylphosphatidylinositol-Anchored Mucins from Trypanosoma cruzi Trypomastigotes and Synthesis of α-Gal-Containing Neoglycoproteins: Application as Biomarkers for Reliable Diagnosis and Early Assessment of Chemotherapeutic Outcomes of Chagas Disease.

Chagas disease (ChD), caused by the protozoan parasite Trypanosoma cruzi, affects millions of people worldwide. Chemotherapy is restricted to two drugs, which are partially effective and may cause severe side effects, leading to cessation of treatment in a significant number of patients. Currently, there are no biomarkers to assess therapeutic efficacy of these drugs in the chronic stage. Moreover, no preventive or therapeutic vaccines are available. In this chapter, we describe the purification of Trypanosoma cruzi trypomastigote-derived glycosylphosphatidylinositol (GPI)-anchored mucins (tGPI-mucins) for their use as antigens for the reliable primary or confirmatory diagnosis and as prognostic biomarkers for early assessment of cure following ChD chemotherapy. We also describe, as an example, the synthesis of a potential tGPI-mucin-derived α-Gal-terminating glycan and its coupling to a carrier protein for use as diagnostic and prognostic biomarker in ChD.

Prediction of Signal Peptides in Proteins from Malaria Parasites.

Signal peptides are N-terminal presequences responsible for targeting proteins to the endomembrane system, and subsequent subcellular or extracellular compartments, and consequently condition their proper function. The significance of signal peptides stimulates development of new computational methods for their detection. These methods employ learning systems trained on datasets comprising signal peptides from different types of proteins and taxonomic groups. As a result, the accuracy of predictions are high in the case of signal peptides that are well-represented in databases, but might be low in other, atypical cases. Such atypical signal peptides are present in proteins found in apicomplexan parasites, causative agents of malaria and toxoplasmosis. Apicomplexan proteins have a unique amino acid composition due to their AT-biased genomes. Therefore, we designed a new, more flexible and universal probabilistic model for recognition of atypical eukaryotic signal peptides. Our approach called signalHsmm includes knowledge about the structure of signal peptides and physicochemical properties of amino acids. It is able to recognize signal peptides from the malaria parasites and related species more accurately than popular programs. Moreover, it is still universal enough to provide prediction of other signal peptides on par with the best preforming predictors.

Antimalarial proteasome inhibitor reveals collateral sensitivity from intersubunit interactions and fitness cost of resistance.

We describe noncovalent, reversible asparagine ethylenediamine (AsnEDA) inhibitors of the Plasmodium falciparum proteasome (Pf20S) ß5 subunit that spare all active subunits of human constitutive and immuno-proteasomes. The compounds are active against erythrocytic, sexual, and liver-stage parasites, against parasites resistant to current antimalarials, and against P. falciparum strains from patients in Africa. The ß5 inhibitors synergize with a ß2 inhibitor in vitro and in mice and with artemisinin. P. falciparum selected for resistance to an AsnEDA ß5 inhibitor surprisingly harbored a point mutation in the noncatalytic ß6 subunit. The ß6 mutant was resistant to the species-selective Pf20S ß5 inhibitor but remained sensitive to the species-nonselective ß5 inhibitors bortezomib and carfilzomib. Moreover, resistance to the Pf20S ß5 inhibitor was accompanied by increased sensitivity to a Pf20S ß2 inhibitor. Finally, the ß5 inhibitor-resistant mutant had a fitness cost that was exacerbated by irradiation. Thus, used in combination, multistage-active inhibitors of the Pf20S ß5 and ß2 subunits afford synergistic antimalarial activity with a potential to delay the emergence of resistance to artemisinins and each other.

Identification of internalin-A-like virulent proteins in Leishmania donovani.

BACKGROUND: An active immune surveillance and a range of barriers to infection allow the host to effectively eliminate microbial pathogens. However, pathogens may use diverse strategies to subdue such host defences. For instance, one such mechanism is the use of leucine-rich repeat (LRR) proteins by pathogens (microbial) to cause infection. In this study, we aimed at identifying novel virulence factor(s) in Leishmania donovani, based on the possibility of lateral gene transfers of bacterial virulence factor(s) to L. donovani. METHODS: Rigorous homology searching protocols including Hidden Markov Model (HMM) and BLASTp based searches were employed to detect remote but significant similarities between L. donovani proteins and bacterial virulence factors. RESULTS: We found that some L. donovani proteins are similar to internalin-A (Inl-A) protein of Listeria monocytogenes, a surface LRR protein that helps mediate host cell invasion by interacting with E-cadherin on the cell membrane. However, to date, no such invasion mechanism has been reported in Leishmania donovani, the causative agent of visceral leishmaniasis. Moreover, a comparative LRR motif analysis of L. donovani Inl-A-like proteins against the Inl-A protein of L. monocytogenes revealed existence of characteristic consensus LRR regions, suggesting a reliable evolutionary relationship between them. Further, through rigorous three dimensional (3D) modeling of L. donovani Inl-A-like proteins and subsequent molecular docking studies we suggest the probability of human E-cadherin binding with the L. donovani Inl-A-like proteins. CONCLUSIONS: We have identified three potential candidates (UniProt ID: E9B7L9, E9BMT7 and E9BUL5) of Inl-A-like LRR containing proteins in L. donovani with the help of systematic whole genome sequence analysis. Thus, herein we propose the existence of a novel class of Inl-A-like virulence factor proteins in L. donovani and other Leishmania species based on sequence similarity, phylogenetic analysis and molecular modelling studies in L. donovani.

Homology Modeling Procedures for Cytoskeletal Proteins of Tetrahymena and Other Ciliated Protists.

In recent years there has been an explosive increase in the number of annotated protein sequences available through genome sequencing, as well as an accumulation of published protein structural data based on crystallographic and NMR methods. When taken together with the development of computational methods for the prediction of protein structural and functional properties through homology modeling, an opportunity exists for prediction of properties of cytoskeletal proteins in a suitable model organism, such as Tetrahymena thermophila and its ciliated protist relatives. In particular, the recently sequenced genome of T. thermophila, long a model for cytoskeletal studies, provides a good starting point for undertaking such homology modeling studies. Homology modeling can produce functional predictions, for example regarding potential molecular interactions, that are of great interest to the drug industry and Tetrahymena is an attractive model system in which to follow up computational predictions with experimental analyses. We provide here procedures that can be followed to gain entry into this promising avenue of analysis.

Three-dimensional structure model and predicted ATP interaction rewiring of a deviant RNA ligase 2.

BACKGROUND: RNA ligases 2 are scarce and scattered across the tree of life. Two members of this family are well studied: the mitochondrial RNA editing ligase from the parasitic trypanosomes (Kinetoplastea), a promising drug target, and bacteriophage T4 RNA ligase 2, a workhorse in molecular biology. Here we report the identification of a divergent RNA ligase 2 (DpRNL) from Diplonema papillatum (Diplonemea), a member of the kinetoplastids' sister group. METHODS: We identified DpRNL with methods based on sensitive hidden Markov Model. Then, using homology modeling and molecular dynamics simulations, we established a three dimensional structure model of DpRNL complexed with ATP and Mg2+. RESULTS: The 3D model of Diplonema was compared with available crystal structures from Trypanosoma brucei, bacteriophage T4, and two archaeans. Interaction of DpRNL with ATP is predicted to involve double π-stacking, which has not been reported before in RNA ligases. This particular contact would shift the orientation of ATP and have considerable consequences on the interaction network of amino acids in the catalytic pocket. We postulate that certain canonical amino acids assume different functional roles in DpRNL compared to structurally homologous residues in other RNA ligases 2, a reassignment indicative of constructive neutral evolution. Finally, both structure comparison and phylogenetic analysis show that DpRNL is not specifically related to RNA ligases from trypanosomes, suggesting a unique adaptation of the latter for RNA editing, after the split of diplonemids and kinetoplastids. CONCLUSION: Homology modeling and molecular dynamics simulations strongly suggest that DpRNL is an RNA ligase 2. The predicted innovative reshaping of DpRNL's catalytic pocket is worthwhile to be tested experimentally.

Energy cost for the proper ionization of active site residues in 6-phosphogluconate dehydrogenase from T. brucei.

The catalytic mechanism of 6-phosphogluconate dehydrogenase requires the inversion of a Lys/Glu couple from its natural ionization state. The pKa of these residues in free and substrate bound enzymes has been determined measuring by ITC the proton release/uptake induced by substrate binding at different pH values. Wt 6-phosphogluconate dehydrogenase from Trypanosoma brucei and two active site enzyme mutants, K185H and E192Q were investigated. Substrate binding was accompanied by proton release and was dependent on the ionization of a group with pKa 7.07 which was absent in the E192Q mutant. Kinetic data highlighted two pKa, 7.17 and 9.64, in the enzyme-substrate complex, the latter being absent in the E192Q mutant, suggesting that the substrate binding shifts Glu192 pKa from 7.07 to 9.64. A comparison of wt and E192Q mutant appears to show that the substrate binding shifts Lys185 pKa from 9.9 to 7.17. By comparing differences in proton release and the binding enthalpy of wt and mutant enzymes, the enthalpic cost of the change in the protonation state of Lys185 and Glu192 was estimated at ≈6.1kcal/mol. The change in protonation state of Lys185 and Glu192 has little effect on Gibbs free energy, 240-325cal/mol. However proton balance evidences the dissociation of other group(s) that can be collectively described by a single pKa shift from 9.1 to 7.54. This further change in ionization state of the enzyme causes an increase of free energy with a total cost of 1.2-2.3kcal/mol to set the enzyme into a catalytically competent form.

A new computational approach redefines the subtelomeric vir superfamily of Plasmodium vivax.

BACKGROUND: Subtelomeric multigene families of malaria parasites encode virulent determinants. The published genome sequence of Plasmodium vivax revealed the largest subtelomeric multigene family of human malaria parasites, the vir super-family, presently composed of 346 vir genes subdivided into 12 different subfamilies based on sequence homologies detected by BLAST. RESULTS: A novel computational approach was used to redefine vir genes. First, a protein-weighted graph was built based on BLAST alignments. This graph was processed to ensure that edge weights are not exclusively based on the BLAST score between the two corresponding proteins, but strongly dependant on their graph neighbours and their associations. Then the Markov Clustering Algorithm was applied to the protein graph. Next, the Homology Block concept was used to further validate this clustering approach. Finally, proteome-wide analysis was carried out to predict new VIR members. Results showed that (i) three previous subfamilies cannot longer be classified as vir genes; (ii) most previously unclustered vir genes were clustered into vir subfamilies; (iii) 39 hypothetical proteins were predicted as VIR proteins; (iv) many of these findings are supported by a number of structural and functional evidences, sub-cellular localization studies, gene expression analysis and chromosome localization (v) this approach can be used to study other multigene families in malaria. CONCLUSIONS: This methodology, resource and new classification of vir genes will contribute to a new structural framing of this multigene family and other multigene families of malaria parasites, facilitating the design of experiments to understand their role in pathology, which in turn may help furthering vaccine development.

Predicting secretory proteins of malaria parasite by incorporating sequence evolution information into pseudo amino acid composition via grey system model.

The malaria disease has become a cause of poverty and a major hindrance to economic development. The culprit of the disease is the parasite, which secretes an array of proteins within the host erythrocyte to facilitate its own survival. Accordingly, the secretory proteins of malaria parasite have become a logical target for drug design against malaria. Unfortunately, with the increasing resistance to the drugs thus developed, the situation has become more complicated. To cope with the drug resistance problem, one strategy is to timely identify the secreted proteins by malaria parasite, which can serve as potential drug targets. However, it is both expensive and time-consuming to identify the secretory proteins of malaria parasite by experiments alone. To expedite the process for developing effective drugs against malaria, a computational predictor called "iSMP-Grey" was developed that can be used to identify the secretory proteins of malaria parasite based on the protein sequence information alone. During the prediction process a protein sample was formulated with a 60D (dimensional) feature vector formed by incorporating the sequence evolution information into the general form of PseAAC (pseudo amino acid composition) via a grey system model, which is particularly useful for solving complicated problems that are lack of sufficient information or need to process uncertain information. It was observed by the jackknife test that iSMP-Grey achieved an overall success rate of 94.8%, remarkably higher than those by the existing predictors in this area. As a user-friendly web-server, iSMP-Grey is freely accessible to the public at http://www.jci-bioinfo.cn/iSMP-Grey. Moreover, for the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated mathematical equations involved in this paper.

The crystal structure of Leishmania major N(5),N(10)-methylenetetrahydrofolate dehydrogenase/cyclohydrolase and assessment of a potential drug target.

Three enzyme activities in the protozoan Leishmania major, namely N(5),N(10)-methylenetetrahydrofolate dehydrogenase/N(5),N(10)-methenyltetrahydrofolate cyclohydrolase (DHCH) and N(10)-formyltetrahydrofolate ligase (FTL) produce the essential intermediate N(10)-formyltetrahydrofolate. Although trypanosomatids possess at least one functional DHCH, the same is not true for FTL, which is absent in Trypanosoma brucei. Here, we present the 2.7 Å resolution crystal structure of the bifunctional apo-DHCH from L. major, which is a potential drug target. Sequence alignments show that the cytosolic enzymes found in trypanosomatids share a high level of identity of approximately 60%. Additionally, residues that interact and participate in catalysis in the human homologue are conserved amongst trypanosomatid sequences and this may complicate attempts to derive potent, parasite specific DHCH inhibitors.

Target highlights in CASP9: Experimental target structures for the critical assessment of techniques for protein structure prediction.

One goal of the CASP community wide experiment on the critical assessment of techniques for protein structure prediction is to identify the current state of the art in protein structure prediction and modeling. A fundamental principle of CASP is blind prediction on a set of relevant protein targets, that is, the participating computational methods are tested on a common set of experimental target proteins, for which the experimental structures are not known at the time of modeling. Therefore, the CASP experiment would not have been possible without broad support of the experimental protein structural biology community. In this article, several experimental groups discuss the structures of the proteins which they provided as prediction targets for CASP9, highlighting structural and functional peculiarities of these structures: the long tail fiber protein gp37 from bacteriophage T4, the cyclic GMP-dependent protein kinase Iß dimerization/docking domain, the ectodomain of the JTB (jumping translocation breakpoint) transmembrane receptor, Autotaxin in complex with an inhibitor, the DNA-binding J-binding protein 1 domain essential for biosynthesis and maintenance of DNA base-J (ß-D-glucosyl-hydroxymethyluracil) in Trypanosoma and Leishmania, an so far uncharacterized 73 residue domain from Ruminococcus gnavus with a fold typical for PDZ-like domains, a domain from the phycobilisome core-membrane linker phycobiliprotein ApcE from Synechocystis, the heat shock protein 90 activators PFC0360w and PFC0270w from Plasmodium falciparum, and 2-oxo-3-deoxygalactonate kinase from Klebsiella pneumoniae.

Identification of Plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models.

BACKGROUND: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. RESULTS: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. CONCLUSIONS: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria.

Overexpression, purification and assessment of cyclosporin binding of a family of cyclophilins and cyclophilin-like proteins of the human malarial parasite Plasmodium falciparum.

Malaria represents a global health, economic and social burden of enormous magnitude. Chemotherapy is at the moment a largely effective weapon against the disease, but the appearance of drug-resistant parasites is reducing the effectiveness of most drugs. Finding new drug-target candidates is one approach to the development of new drugs. The family of cyclophilins may represent a group of potential targets. They are involved in protein folding and regulation due to their peptidyl-prolyl cis-trans isomerase and/or chaperone activities. They also mediate the action of the immunosuppressive drug cyclosporin A, which additionally has strong antimalarial activity. In the genome database of the most lethal human malarial parasite Plasmodium falciparum, 11 genes apparently encoding cyclophilin or cyclophilin-like proteins were found, but most of these have not yet been characterized. Previously a pET vector conferring a C-terminal His6 tag was used for recombinant expression and purification of one member of the P. falciparum cyclophilin family in Escherichia coli. The approach here was to use an identical method to produce all of the other members of this family and thereby allow the most consistent functional comparisons. We were successful in generating all but three of the family, plus a single amino-acid mutant, in the same recombinant form as either full-length proteins or isolated cyclophilin-like domains. The recombinant proteins were assessed by thermal melt assay for correct folding and cyclosporin A binding.

Plasmodium falciparum erythrocyte membrane protein 1 diversity in seven genomes--divide and conquer.

The var gene encoded hyper-variable Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) family mediates cytoadhesion of infected erythrocytes to human endothelium. Antibodies blocking cytoadhesion are important mediators of malaria immunity acquired by endemic populations. The development of a PfEMP1 based vaccine mimicking natural acquired immunity depends on a thorough understanding of the evolved PfEMP1 diversity, balancing antigenic variation against conserved receptor binding affinities. This study redefines and reclassifies the domains of PfEMP1 from seven genomes. Analysis of domains in 399 different PfEMP1 sequences allowed identification of several novel domain classes, and a high degree of PfEMP1 domain compositional order, including conserved domain cassettes not always associated with the established group A-E division of PfEMP1. A novel iterative homology block (HB) detection method was applied, allowing identification of 628 conserved minimal PfEMP1 building blocks, describing on average 83% of a PfEMP1 sequence. Using the HBs, similarities between domain classes were determined, and Duffy binding-like (DBL) domain subclasses were found in many cases to be hybrids of major domain classes. Related to this, a recombination hotspot was uncovered between DBL subdomains S2 and S3. The VarDom server is introduced, from which information on domain classes and homology blocks can be retrieved, and new sequences can be classified. Several conserved sequence elements were found, including: (1) residues conserved in all DBL domains predicted to interact and hold together the three DBL subdomains, (2) potential integrin binding sites in DBLα domains, (3) an acylation motif conserved in group A var genes suggesting N-terminal N-myristoylation, (4) PfEMP1 inter-domain regions proposed to be elastic disordered structures, and (5) several conserved predicted phosphorylation sites. Ideally, this comprehensive categorization of PfEMP1 will provide a platform for future studies on var/PfEMP1 expression and function.

New assembly, reannotation and analysis of the Entamoeba histolytica genome reveal new genomic features and protein content information.

BACKGROUND: In order to maintain genome information accurately and relevantly, original genome annotations need to be updated and evaluated regularly. Manual reannotation of genomes is important as it can significantly reduce the propagation of errors and consequently diminishes the time spent on mistaken research. For this reason, after five years from the initial submission of the Entamoeba histolytica draft genome publication, we have re-examined the original 23 Mb assembly and the annotation of the predicted genes. PRINCIPAL FINDINGS: The evaluation of the genomic sequence led to the identification of more than one hundred artifactual tandem duplications that were eliminated by re-assembling the genome. The reannotation was done using a combination of manual and automated genome analysis. The new 20 Mb assembly contains 1,496 scaffolds and 8,201 predicted genes, of which 60% are identical to the initial annotation and the remaining 40% underwent structural changes. Functional classification of 60% of the genes was modified based on recent sequence comparisons and new experimental data. We have assigned putative function to 3,788 proteins (46% of the predicted proteome) based on the annotation of predicted gene families, and have identified 58 protein families of five or more members that share no homology with known proteins and thus could be entamoeba specific. Genome analysis also revealed new features such as the presence of segmental duplications of up to 16 kb flanked by inverted repeats, and the tight association of some gene families with transposable elements. SIGNIFICANCE: This new genome annotation and analysis represents a more refined and accurate blueprint of the pathogen genome, and provides an upgraded tool as reference for the study of many important aspects of E. histolytica biology, such as genome evolution and pathogenesis.

Using hidden markov models to discover new protein transport machines.

Protein import and export pathways are driven by protein translocases, often comprised of multiple subunits, and usually conserved across a range of organisms. Protein import into mitochondria is fundamental to eukaryotic organisms and is initiated when substrate proteins are translocated across the mitochondrial outer membrane by the TOM complex. The essential subunit of this complex is a protein called Tom40, which is probably a beta-barrel in structure and serves as the translocation pore. We describe a hidden Markov model search designed to find the Tom40 sequence in the amoeba Entamoeba histolytica. This organism has a highly reduced "mitosome", an organelle whose relationship to mitochondria has been the subject of controversy. The Tom40 sequence could not be found with BLAST-based searches, but a hidden Markov model search identified a likely candidate to form the protein import pore in the outer mitosomal membrane in E. histolytica.