Mechanism of action of cyclic antimicrobial peptides

This PhD thesis is the result of the combination of experimental and computational techniques with the aim of understanding the mechanism of action of de novo cyclic decapeptides with high antimicrobial activity. By experimental techniques the influence of the replacement of the phenylalanine for tryptophan residue in their antimicrobial activity was tested and the stability in human serum was also analyzed, in order to evaluate their potential therapeutic application as antitumor agents. On the other hand, the interaction amongst the peptide BPC194 c(KKLKKFKKLQ), the best candidate from the whole library of cyclic peptides, and a model anionic membrane was simulated. The results showed a structure-function relationship derived from the stable conformation of the peptides involved in the membrane permeabilization. As a result, a rational design was performed being BPC490 the peptide with best antimicrobial activity compared with the best active peptide from the original library.

Synteza, badania strukturalne i spektroskopowe oraz aktywność przeciwnowotworowa i przeciwdrobnoustrojowa nowych pochodnych salinomycyny

Wydział Chemii: Pracownia Chemii Bioorganicznej

The extrapolation problem and how population modeling can help

We argue that population modeling can add value to ecological risk assessment by reducing uncertainty when extrapolating from ecotoxicological observations to relevant ecological effects. We review other methods of extrapolation, ranging from application factors to species sensitivity distributions to suborganismal (biomarker and "-omics'') responses to quantitative structure activity relationships and model ecosystems, drawing attention to the limitations of each. We suggest a simple classification of population models and critically examine each model in an extrapolation context. We conclude that population models have the potential for adding value to ecological risk assessment by incorporating better understanding of the links between individual responses and population size and structure and by incorporating greater levels of ecological complexity. A number of issues, however, need to be addressed before such models are likely to become more widely used. In a science context, these involve challenges in parameterization, questions about appropriate levels of complexity, issues concerning how specific or general the models need to be, and the extent to which interactions through competition and trophic relationships can be easily incorporated.

QSAR studies of multidentate nitrogen ligands used in lanthanide and actinide extraction processes

Quantitative structure activity relationships (QSARs) have been developed to optimise the choice of nitrogen heterocyclic molecules that can be used to separate the minor actinides such as americium(III) from europium(III) in the aqueous PUREX raffinate of nuclear waste. Experimental data on distribution coefficients and separation factors (SFs) for 47 such ligands have been obtained and show SF values ranging from 0.61 to 100. The ligands were divided into a training set of 36 molecules to develop the QSAR and a test set of 11 molecules to validate the QSAR. Over 1500 molecular descriptors were calculated for each heterocycle and the Genetic Algorithm was used to select the most appropriate for use in multiple regression equations. Equations were developed fitting the separation factors to 6-8 molecular descriptors which gave r(2) values of >0.8 for the training set and values of >0.7 for the test set, thus showing good predictive quality. The descriptors used in the equations were primarily electronic and steric. These equations can be used to predict the separation factors of nitrogen heterocycles not yet synthesised and/or tested and hence obtain the most efficient ligands for lanthanide and actinide separation. (C) 2003 Elsevier B.V. All rights reserved.

Joint multiple dictionary learning for tensor sparse coding

Traditional dictionary learning algorithms are used for finding a sparse representation on high dimensional data by transforming samples into a one-dimensional (1D) vector. This 1D model loses the inherent spatial structure property of data. An alternative solution is to employ Tensor Decomposition for dictionary learning on their original structural form —a tensor— by learning multiple dictionaries along each mode and the corresponding sparse representation in respect to the Kronecker product of these dictionaries. To learn tensor dictionaries along each mode, all the existing methods update each dictionary iteratively in an alternating manner. Because atoms from each mode dictionary jointly make contributions to the sparsity of tensor, existing works ignore atoms correlations between different mode dictionaries by treating each mode dictionary independently. In this paper, we propose a joint multiple dictionary learning method for tensor sparse coding, which explores atom correlations for sparse representation and updates multiple atoms from each mode dictionary simultaneously. In this algorithm, the Frequent-Pattern Tree (FP-tree) mining algorithm is employed to exploit frequent atom patterns in the sparse representation. Inspired by the idea of K-SVD, we develop a new dictionary update method that jointly updates elements in each pattern. Experimental results demonstrate our method outperforms other tensor based dictionary learning algorithms.

Novel synthesised flavone derivatives provide significant insight into the structural features required for enhanced anti-proliferative activity

With many cancers showing resistance to current chemotherapies, the search for novel anti-cancer agents is attracting considerable attention. Natural flavonoids have been identified as useful leads in such programmes. However, since an in-depth understanding of the structural requirements for optimum activity is generally lacking, further research is required before the full potential of flavonoids as anti-proliferative agents can be realised. Herein a broad library of 76 methoxy and hydroxy flavones, and their 4-thio analogues, was constructed and their structure-activity relationships for anti-proliferative activity against the breast cancer cell lines MCF-7 (ER+ve), MCF-7/DX (ER+ve, anthracycline resistant) and MDA-MB-231 (ER-ve) were probed. Within this library, 42 compounds were novel, and all compounds were afforded in good yields and > 95% purity. The most promising lead compounds, specifically the novel hydroxy 4-thioflavones 15f and 16f, were further evaluated for their anti-proliferative activities against a broader range of cancer cell lines by the National Cancer Institute (NCI), USA and displayed significant growth inhibition profiles (e.g Compound-15f: MCF-7 (GI50 = 0.18 μM), T-47D (GI50 = 0.03 μM) and MDA-MB-468 (GI50 = 0.47 μM) and compound-16f: MCF-7 (GI50 = 1.46 μM), T-47D (GI50 = 1.27 μM) and MDA-MB-231 (GI50 = 1.81 μM). Overall, 15f and 16f exhibited 7-46 fold greater anti-proliferative potency than the natural flavone chrysin (2d). A systematic structure-activity relationship study against the breast cancer cell lines highlighted that free hydroxyl groups and the B-ring phenyl groups were essential for enhanced anti-proliferative activities. Substitution of the 4-C=O functionality with a 4-C=S functionality, and incorporation of electron withdrawing groups at C4’ of the B-ring phenyl, also enhanced activity. Molecular docking and mechanistic studies suggest that the anti-proliferative effects of flavones 15f and 16f are mediated via ER-independent cleavage of PARP and downregulation of GSK-3β for MCF-7 and MCF-7/DX cell lines. For the MDA-MB-231 cell line, restoration of the wild-type p53 DNA binding activity of mutant p53 tumour suppressor gene was indicated.

Atrophy and Neuron Loss: Effects of a Protein-Deficient Diet on Sympathetic Neurons

Protein deficiency is one of the biggest public health problems in the world, accounting for about 30-40% of hospital admissions in developing countries. Nutritional deficiencies lead to alterations in the peripheral nervous system and in the digestive system. Most studies have focused on the effects of protein-deficient diets on the enteric neurons, but not on sympathetic ganglia, which supply extrinsic sympathetic input to the digestive system. Hence, in this study, we investigated whether a protein-restricted diet would affect the quantitative structure of rat coeliac ganglion neurons. Five male Wistar rats (undernourished group) were given a pre- and postnatal hypoproteinic diet receiving 5% casein, whereas the nourished group (n = 5) was fed with 20% casein (normoproteinic diet). Blood tests were carried out on the animals, e.g., glucose, leptin, and triglyceride plasma concentrations. The main structural findings in this study were that a protein-deficient diet (5% casein) caused coeliac ganglion (78%) and coeliac ganglion neurons (24%) to atrophy and led to neuron loss (63%). Therefore, the fall in the total number of coeliac ganglion neurons in protein-restricted rats contrasts strongly with no neuron losses previously described for the enteric neurons of animals subjected to similar protein-restriction diets. Discrepancies between our figures and the data for enteric neurons (using very similar protein-restriction protocols) may be attributable to the counting method used. In light of this, further systematic investigations comparing 2-D and 3-D quantitative methods are warranted to provide even more advanced data on the effects that a protein-deficient diet may exert on sympathetic neurons. (C) 2009 Wiley-Liss, Inc.

CoMFA and CoMSIA 3D QSAR Models for a Series of Cyclic Imides with Analgesic Activity

Three-dimensional quantitative structure-activity relationships (3D-QSAR) were performed for a series of analgesic cyclic imides using the CoMFA and CoMSIA methods. Significant correlation coefficients ( CoMFA, r(2) = 0.95 and q(2) = 0.72; CoMSIA, r(2) = 0.96 and q(2) = 0.76) were obtained, and the generated models were externally validated using test sets. The final QSAR models as well as the information gathered from 3D contour maps should be useful for the design of novel cyclic imides having improved analgesic activity.

Classical and hologram QSAR studies on a series of inhibitors of trypanosomatid Glyceraldehyde-3-Phosphate Dehydrogenase

Leishmaniasis and trypanosomiasis are major causes of morbidity and mortality in both tropical and subtropical regions of the world. The current available drugs are limited, ineffective, and require long treatment regimens. Due to the high dependence of trypanosomatids on glycolysis as a source of energy, some glycolytic enzymes have been identified as attractive targets for drug design. In the present work, classical Two-Dimensional Quantitative Structure -Activity Relationships (2D QSAR) and Hologram QSAR (HQSAR) studies were performed on a series of adenosine derivatives as inhibitors of Leishmania mexicana Glyceraldehyde-3-Phosphate Dehydrogenase (LmGAPDH). Significant correlation coefficients (classical QSAR, r(2)=0.83 and q(2) =0.81; HQSAR, r(2)=0.91 and q(2) =0.86) were obtained for the 56 training set compounds, indicating the potential of the models for untested compounds. The models were then externally validated using a test set of 14 structurally related compounds and the predicted values were in good agreement with the experimental results (classical QSAR, r(pred)(2) = 0.94; HQSAR, r(pred)(2) = 0.92).

Discovery of New Inhibitors of Schistosoma mansoni PNP by Pharmacophore-Based Virtual Screening

Schistosomiasis is considered the second most important tropical parasitic disease, with severe socioeconomic consequences for millions of people worldwide. Schistosoma monsoni, one of the causative agents of human schistosomiasis, is unable to synthesize purine nucleotides de novo, which makes the enzymes of the purine salvage pathway important targets for antischistosomal drug development. In the present work, we describe the development of a pharmacophore model for ligands of S. mansoni purine nucleoside phosphorylase (SmPNP) as well as a pharmacophore-based virtual screening approach, which resulted in the identification of three thioxothiazolidinones (1-3) with substantial in vitro inhibitory activity against SmPNP. Synthesis, biochemical evaluation, and structure activity relationship investigations led to the successful development of a small set of thioxothiazolidinone derivatives harboring a novel chemical scaffold as new competitive inhibitors of SmPNP at the low-micromolar range. Seven compounds were identified with IC(50) values below 100 mu M. The most potent inhibitors 7, 10, and 17 with 1050 of 2, 18, and 38 mu M, respectively, could represent new potential lead compounds for further development of the therapy of schistosomiasis.

Cys mutants in functional regions of Sticholysin I clarify the participation of these residues in pore formation

Experimental evidence shows that the mechanism of pore formation by actinoporins is a multistep process, involving binding of the water-soluble monomer to the membrane and subsequent oligomerization on the membrane surface, leading to the formation of a functional pore. However, as for other eukaryotic pore-forming toxins, the molecular details of the mechanism of membrane insertion and oligomerization are not clear. In order to obtain further insight with regard to the structure-function relationship in sticholysins, we designed and produced three cysteine mutants of recombinant sticholysin I (rStI) in relevant functional regions for membrane interaction: StI E2C and StI F15C (in the N-terminal region) and StI R52C (in the membrane binding site). The conformational characterization derived from fluorescence and CD spectroscopic studies of StI E2C, StI F15C and StI R52C suggests that replacement of these residues by Cys in rStI did not noticeably change the conformation of the protein. The substitution by Cys of Arg(52) in the phosphocholine-binding site, provoked noticeable changes in rStI permeabilizing activity; however, the substitutions in the N-terminal region (Glu(2), Phe(15)) did not modify the toxin`s permeabilizing ability. The presence of a dimerized population stabilized by a disulfide bond in the StI E2C mutant showed higher pore-forming activity than when the protein is in the monomeric state, suggesting that sticholysins pre-ensembled at the N-terminal region could facilitate pore formation. (C) 2011 Elsevier Ltd. All rights reserved.

Conformational Properties of Angiotensin II and Its Active and Inactive TOAC-Labeled Analogs in the Presence of Micelles. Electron Paramagnetic Resonance, Fluorescence, and Circular Dichroism Studies

The interaction between angiotensin II (AII, DRVYIHPF) and its analogs carrying 2,2,6,6-tetramethylpiperidine-1-oxyl-4-amino-4-carboxylic acid (TOAC) and detergents-negatively charged sodium dodecyl sulfate (SDS) and zwitterionic N-hexadecyl-N,N-dimethyl-3-ammonio-1-propanesulfonate (HPS)-was examined by means of EPR, CD, and fluorescence. EPR spectra of partially active TOAC(1)-AII and inactive TOAC(3)-AII in aqueous solution indicated fast tumbling, the freedom of motion being greater at the N-terminus. Line broadening occurred upon interaction with micelles. Below SDS critical micelle concentration, broader lines indicated complex formation with tighter molecular packing than in micelles. Small changes in hyperfine splittings evinced TOAC location at the micelle-water interface. The interaction with anionic micelles was more effective than with zwitterionic micelles. Peptide-micelle interaction caused fluorescence increase. The TOAC-promoted intramolecular fluorescence quenching was more, pronounced for TOAC(3)-AII because of the proximity between the nitroxide and Tyr(4). CD spectra showed that although both AII and TOAC(1)-AII presented flexible conformations in water, TOAC(3)-AII displayed conformational restriction because of the TOAC-imposed bend (Schreier et al., Biopolymers 2004, 74, 389). In HPS, conformational changes were observed for the labeled peptides at neutral and basic pH. In SDS, all peptides underwent pH-dependent conformational changes. Although the spectra suggested similar folds for All and TOAC(1)-AII, different conformations were acquired by TOAC(3)-AII. The membrane environment has been hypothesized to shift conformational equilibria so as to stabilize the receptor-bound conformation of ligands. The fact that TOAC(3)-AII is unable to acquire conformations similar to those of native AII and partially active TOAC(1)-AII is probably the explanation for its lack of biological activity. (C) 2009 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 92: 525-537, 2009.

Designing Novel Antitrypanosomal Agents from a Mixed Graph-Theoretical Substructural Approach

Chagas disease is nowadays the most serious parasitic health problem. This disease is caused by Trypanosoma cruzi. The great number of deaths and the insufficient effectiveness of drugs against this parasite have alarmed the scientific community worldwide. In an attempt to overcome this problem, a model for the design and prediction of new antitrypanosomal agents was obtained. This used a mixed approach, containing simple descriptors based on fragments and topological substructural molecular design descriptors. A data set was made up of 188 compounds, 99 of them characterized an antitrypanosomal activity and 88 compounds that belong to other pharmaceutical categories. The model showed sensitivity, specificity and accuracy values above 85%. Quantitative fragmental contributions were also calculated. Then, and to confirm the quality of the model, 15 structures of molecules tested as antitrypanosomal compounds (that we did not include in this study) were predicted, taking into account the information on the abovementioned calculated fragmental contributions. The model showed an accuracy of 100% which means that the ""in silico"" methodology developed by our team is promising for the rational design of new antitrypanosomal drugs. (C) 2009 Wiley Periodicals, Inc. J Comput Chem 31: 882-894. 2010

Design of novel antituberculosis compounds using graph-theoretical and substructural approaches

The increasing resistance of Mycobacterium tuberculosis to the existing drugs has alarmed the worldwide scientific community. In an attempt to overcome this problem, two models for the design and prediction of new antituberculosis agents were obtained. The first used a mixed approach, containing descriptors based on fragments and the topological substructural molecular design approach (TOPS-MODE) descriptors. The other model used a combination of two-dimensional (2D) and three-dimensional (3D) descriptors. A data set of 167 compounds with great structural variability, 72 of them antituberculosis agents and 95 compounds belonging to other pharmaceutical categories, was analyzed. The first model showed sensitivity, specificity, and accuracy values above 80% and the second one showed values higher than 75% for these statistical indices. Subsequently, 12 structures of imidazoles not included in this study were designed, taking into account the two models. In both cases accuracy was 100%, showing that the methodology in silico developed by us is promising for the rational design of antituberculosis drugs.

Use of self-organizing maps and molecular descriptors to predict the cytotoxic activity of sesquiterpene lactones

Some sesquiterpene lactones (SLs) are the active compounds of a great number of traditionally medicinal plants from the Asteraceae family and possess considerable cytotoxic activity. Several studies in vitro have shown the inhibitory activity against cells derived from human carcinoma of the nasopharynx (KB). Chemical studies showed that the cytotoxic activity is due to the reaction of alpha,beta-unsaturated carbonyl structures of the SLs with thiols, such as cysteine. These studies support the view that SLs inhibit tumour growth by selective alkylation of growth-regulatory biological macromolecules, such as key enzymes, which control cell division, thereby inhibiting a variety of cellular functions, which directs the cells into apoptosis. In this study we investigated a set of 55 different sesquiterpene lactones, represented by 5 skeletons (22 germacranolides, 6 elemanolides, 2 eudesmanolides, 16 guaianolides and nor-derivatives and 9 pseudoguaianolides), in respect to their cytotoxic properties. The experimental results and 3D molecular descriptors were submitted to Kohonen self-organizing map (SOM) to classify (training set) and predict (test set) the cytotoxic activity. From the obtained results, it was concluded that only the geometrical descriptors showed satisfactory values. The Kohonen map obtained after training set using 25 geometrical descriptors shows a very significant match, mainly among the inactive compounds (similar to 84%). Analyzing both groups, the percentage seen is high (83%). The test set shows the highest match, where 89% of the substances had their cytotoxic activity correctly predicted. From these results, important properties for the inhibition potency are discussed for the whole dataset and for subsets of the different structural skeletons. (C) 2008 Elsevier Masson SAS. All rights reserved.