Combination of scoring schemes for protein docking

<p>Abstract</p> <p>Background</p> <p>Docking algorithms are developed to predict in which orientation two proteins are likely to bind under natural conditions. The currently used methods usually consist of a sampling step followed by a scoring step. We developed a weighted geometric correlation based on optimised atom specific weighting factors and combined them with our previously published amino acid specific scoring and with a comprehensive SVM-based scoring function.</p> <p>Results</p> <p>The scoring with the atom specific weighting factors yields better results than the amino acid specific scoring. In combination with SVM-based scoring functions the percentage of complexes for which a near native structure can be predicted within the top 100 ranks increased from 14% with the geometric scoring to 54% with the combination of all scoring functions. Especially for the enzyme-inhibitor complexes the results of the ranking are excellent. For half of these complexes a near-native structure can be predicted within the first 10 proposed structures and for more than 86% of all enzyme-inhibitor complexes within the first 50 predicted structures.</p> <p>Conclusion</p> <p>We were able to develop a combination of different scoring schemes which considers a series of previously described and some new scoring criteria yielding a remarkable improvement of prediction quality.</p

A Comparative Chemogenomics Strategy to Predict Potential Drug Targets in the Metazoan Pathogen, Schistosoma mansoni

Schistosomiasis is a prevalent and chronic helmintic disease in tropical regions. Treatment and control relies on chemotherapy with just one drug, praziquantel and this reliance is of concern should clinically relevant drug resistance emerge and spread. Therefore, to identify potential target proteins for new avenues of drug discovery we have taken a comparative chemogenomics approach utilizing the putative proteome of Schistosoma mansoni compared to the proteomes of two model organisms, the nematode, Caenorhabditis elegans and the fruitfly, Drosophila melanogaster. Using the genome comparison software Genlight, two separate in silico workflows were implemented to derive a set of parasite proteins for which gene disruption of the orthologs in both the model organisms yielded deleterious phenotypes (e.g., lethal, impairment of motility), i.e., are essential genes/proteins. Of the 67 and 68 sequences generated for each workflow, 63 were identical in both sets, leading to a final set of 72 parasite proteins. All but one of these were expressed in the relevant developmental stages of the parasite infecting humans. Subsequent in depth manual curation of the combined workflow output revealed 57 candidate proteins. Scrutiny of these for 'druggable' protein homologs in the literature identified 35 S. mansoni sequences, 18 of which were homologous to proteins with 3D structures including co-crystallized ligands that will allow further structure-based drug design studies. The comparative chemogenomics strategy presented generates a tractable set of S. mansoni proteins for experimental validation as drug targets against this insidious human pathogen

L1pred: A Sequence-Based Prediction Tool for Catalytic Residues in Enzymes with the L1-logreg Classifier

To understand enzyme functions, identifying the catalytic residues is a usual first step. Moreover, knowledge about catalytic residues is also useful for protein engineering and drug-design. However, to experimentally identify catalytic residues remains challenging for reasons of time and cost. Therefore, computational methods have been explored to predict catalytic residues. Here, we developed a new algorithm, L1pred, for catalytic residue prediction, by using the L1-logreg classifier to integrate eight sequence-based scoring functions. We tested L1pred and compared it against several existing sequence-based methods on carefully designed datasets Data604 and Data63. With ten-fold cross-validation, L1pred showed the area under precision-recall curve (AUPR) and the area under ROC curve (AUC) of 0.2198 and 0.9494 on the training dataset, Data604, respectively. In addition, on the independent test dataset, Data63, it showed the AUPR and AUC values of 0.2636 and 0.9375, respectively. Compared with other sequence-based methods, L1pred showed the best performance on both datasets. We also analyzed the importance of each attribute in the algorithm, and found that all the scores contributed more or less equally to the L1pred performance

Tuning Curvature and Stability of Monoolein Bilayers by Designer Lipid-Like Peptide Surfactants

This study reports the effect of loading four different charged designer lipid-like short anionic and cationic peptide surfactants on the fully hydrated monoolein (MO)-based Pn3m phase (Q224). The studied peptide surfactants comprise seven amino acid residues, namely A6D, DA6, A6K, and KA6. D (aspartic acid) bears two negative charges, K (lysine) bears one positive charge, and A (alanine) constitutes the hydrophobic tail. To elucidate the impact of these peptide surfactants, the ternary MO/peptide/water system has been investigated using small-angle X-ray scattering (SAXS), within a certain range of peptide concentrations (R≤0.2) and temperatures (25 to 70°C). We demonstrate that the bilayer curvature and the stability are modulated by: i) the peptide/lipid molar ratio, ii) the peptide molecular structure (the degree of hydrophobicity, the type of the hydrophilic amino acid, and the headgroup location), and iii) the temperature. The anionic peptide surfactants, A6D and DA6, exhibit the strongest surface activity. At low peptide concentrations (R = 0.01), the Pn3m structure is still preserved, but its lattice increases due to the strong electrostatic repulsion between the negatively charged peptide molecules, which are incorporated into the interface. This means that the anionic peptides have the effect of enlarging the water channels and thus they serve to enhance the accommodation of positively charged water-soluble active molecules in the Pn3m phase. At higher peptide concentration (R = 0.10), the lipid bilayers are destabilized and the structural transition from the Pn3m to the inverted hexagonal phase (H2) is induced. For the cationic peptides, our study illustrates how even minor modifications, such as changing the location of the headgroup (A6K vs. KA6), affects significantly the peptide's effectiveness. Only KA6 displays a propensity to promote the formation of H2, which suggests that KA6 molecules have a higher degree of incorporation in the interface than those of A6K

Cryoelectron Tomography of HIV-1 Envelope Spikes: Further Evidence for Tripod-Like Legs

A detailed understanding of the morphology of the HIV-1 envelope (Env) spike is key to understanding viral pathogenesis and for informed vaccine design. We have previously presented a cryoelectron microscopic tomogram (cryoET) of the Env spikes on SIV virions. Several structural features were noted in the gp120 head and gp41 stalk regions. Perhaps most notable was the presence of three splayed legs projecting obliquely from the base of the spike head toward the viral membrane. Subsequently, a second 3D image of SIV spikes, also obtained by cryoET, was published by another group which featured a compact vertical stalk. We now report the cryoET analysis of HIV-1 virion-associated Env spikes using enhanced analytical cryoET procedures. More than 2,000 Env spike volumes were initially selected, aligned, and sorted into structural classes using algorithms that compensate for the “missing wedge” and do not impose any symmetry. The results show varying morphologies between structural classes: some classes showed trimers in the head domains; nearly all showed two or three legs, though unambiguous three-fold symmetry was not observed either in the heads or the legs. Subsequently, clearer evidence of trimeric head domains and three splayed legs emerged when head and leg volumes were independently aligned and classified. These data show that HIV-1, like SIV, also displays the tripod-like leg configuration, and, unexpectedly, shows considerable gp41 leg flexibility/heteromorphology. The tripod-like model for gp41 is consistent with, and helps explain, many of the unique biophysical and immunological features of this region

Thermotropic phase behavior and headgroup interactions of the nonbilayer lipids phosphatidylethanolamine and monogalactosyldiacylglycerol in the dry state

<p>Abstract</p> <p>Background</p> <p>Although biological membranes are organized as lipid bilayers, they contain a substantial fraction of lipids that have a strong tendency to adopt a nonlamellar, most often inverted hexagonal (H_II) phase. The polymorphic phase behavior of such nonbilayer lipids has been studied previously with a variety of methods in the fully hydrated state or at different degrees of dehydration. Here, we present a study of the thermotropic phase behavior of the nonbilayer lipids egg phosphatidylethanolamine (EPE) and monogalactosyldiacylglycerol (MGDG) with a focus on interactions between the lipid molecules in the interfacial and headgroup regions.</p> <p>Results</p> <p>Liposomes were investigated in the dry state by Fourier-transform Infrared (FTIR) spectroscopy and Differential Scanning Calorimetry (DSC). Dry EPE showed a gel to liquid-crystalline phase transition below 0°C and a liquid-crystalline to H_IItransition at 100°C. MGDG, on the other hand, was in the liquid-crystalline phase down to -30°C and showed a nonbilayer transition at about 85°C. Mixtures (1:1 by mass) with two different phosphatidylcholines (PC) formed bilayers with no evidence for nonbilayer transitions up to 120°C. FTIR spectroscopy revealed complex interactions between the nonbilayer lipids and PC. Strong H-bonding interactions occurred between the sugar headgroup of MGDG and the phosphate, carbonyl and choline groups of PC. Similarly, the ethanolamine moiety of EPE was H-bonded to the carbonyl and choline groups of PC and probably interacted through charge pairing with the phosphate group.</p> <p>Conclusions</p> <p>This study provides a comprehensive characterization of dry membranes containing the two most important nonbilayer lipids (PE and MGDG) in living cells. These data will be of particular relevance for the analysis of interactions between membranes and low molecular weight solutes or soluble proteins that are presumably involved in cellular protection during anhydrobiosis.</p

Mining a Cathepsin Inhibitor Library for New Antiparasitic Drug Leads

The targeting of parasite cysteine proteases with small molecules is emerging as a possible approach to treat tropical parasitic diseases such as sleeping sickness, Chagas' disease, and malaria. The homology of parasite cysteine proteases to the human cathepsins suggests that inhibitors originally developed for the latter may be a source of promising lead compounds for the former. We describe here the screening of a unique ∼2,100-member cathepsin inhibitor library against five parasite cysteine proteases thought to be relevant in tropical parasitic diseases. Compounds active against parasite enzymes were subsequently screened against cultured Plasmodium falciparum, Trypanosoma brucei brucei and/or Trypanosoma cruzi parasites and evaluated for cytotoxicity to mammalian cells. The end products of this effort include the identification of sub-micromolar cell-active leads as well as the elucidation of structure-activity trends that can guide further optimization efforts

Discovering Sequence Motifs with Arbitrary Insertions and Deletions

Biology is encoded in molecular sequences: deciphering this encoding remains a grand scientific challenge. Functional regions of DNA, RNA, and protein sequences often exhibit characteristic but subtle motifs; thus, computational discovery of motifs in sequences is a fundamental and much-studied problem. However, most current algorithms do not allow for insertions or deletions (indels) within motifs, and the few that do have other limitations. We present a method, GLAM2 (Gapped Local Alignment of Motifs), for discovering motifs allowing indels in a fully general manner, and a companion method GLAM2SCAN for searching sequence databases using such motifs. glam2 is a generalization of the gapless Gibbs sampling algorithm. It re-discovers variable-width protein motifs from the PROSITE database significantly more accurately than the alternative methods PRATT and SAM-T2K. Furthermore, it usefully refines protein motifs from the ELM database: in some cases, the refined motifs make orders of magnitude fewer overpredictions than the original ELM regular expressions. GLAM2 performs respectably on the BAliBASE multiple alignment benchmark, and may be superior to leading multiple alignment methods for “motif-like” alignments with N- and C-terminal extensions. Finally, we demonstrate the use of GLAM2 to discover protein kinase substrate motifs and a gapped DNA motif for the LIM-only transcriptional regulatory complex: using GLAM2SCAN, we identify promising targets for the latter. GLAM2 is especially promising for short protein motifs, and it should improve our ability to identify the protein cleavage sites, interaction sites, post-translational modification attachment sites, etc., that underlie much of biology. It may be equally useful for arbitrarily gapped motifs in DNA and RNA, although fewer examples of such motifs are known at present. GLAM2 is public domain software, available for download at http://bioinformatics.org.au/glam2