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Structural Classes (structural + class)
Kinds of Structural Classes Selected AbstractsPrediction of protein structural class by amino acid and polypeptide compositionFEBS JOURNAL, Issue 17 2002Rui-yan Luo A new approach of predicting structural classes of protein domain sequences is presented in this paper. Besides the amino acid composition, the composition of several dipeptides, tripeptides, tetrapeptides, pentapeptides and hexapeptides are taken into account based on the stepwise discriminant analysis. The result of jackknife test shows that this new approach can lead to higher predictive sensitivity and specificity for reduced sequence similarity datasets. Considering the dataset PDB40-B constructed by Brenner and colleagues, 75.2% protein domain sequences are correctly assigned in the jackknife test for the four structural classes: all-,, all-,, ,/, and , + ,, which is improved by 19.4% in jackknife test and 25.5% in resubstitution test, in contrast with the component-coupled algorithm using amino acid composition alone (AAC approach) for the same dataset. In the cross-validation test with dataset PDB40-J constructed by Park and colleagues, more than 80% predictive accuracy is obtained. Furthermore, for the dataset constructed by Chou and Maggiona, the accuracy of 100% and 99.7% can be easily achieved, respectively, in the resubstitution test and in the jackknife test merely taking the composition of dipeptides into account. Therefore, this new method provides an effective tool to extract valuable information from protein sequences, which can be used for the systematic analysis of small or medium size protein sequences. The computer programs used in this paper are available on request. [source] Chiral Amine Synthesis , Recent Developments and Trends for Enamide Reduction, Reductive Amination, and Imine ReductionADVANCED SYNTHESIS & CATALYSIS (PREVIOUSLY: JOURNAL FUER PRAKTISCHE CHEMIE), Issue 5 2010Thomas Abstract The review examines the chiral amine literature from 2000,2009 (May) concerning enantioselective and diastereoselective methods for N -acylenamide and enamine reduction, reductive amination, and imine reduction. The reaction steps for each strategy, from ketone to primary chiral amine, are clearly defined, with best methods and yields for starting material preparation and final deprotection noted. Categories of chiral amines have been defined in Section 1 to allow the reader to quickly understand whether their specific target amine falls within a difficult to synthesize, or not, structural class. Amino acids are not considered in this work. [source] Using grey dynamic modeling and pseudo amino acid composition to predict protein structural classesJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 12 2008Xuan Xiao Abstract Using the pseudo amino acid (PseAA) composition to represent the sample of a protein can incorporate a considerable amount of sequence pattern information so as to improve the prediction quality for its structural or functional classification. However, how to optimally formulate the PseAA composition is an important problem yet to be solved. In this article the grey modeling approach is introduced that is particularly efficient in coping with complicated systems such as the one consisting of many proteins with different sequence orders and lengths. On the basis of the grey model, four coefficients derived from each of the protein sequences concerned are adopted for its PseAA components. The PseAA composition thus formulated is called the "grey-PseAA" composition that can catch the essence of a protein sequence and better reflect its overall pattern. In our study we have demonstrated that introduction of the grey-PseAA composition can remarkably enhance the success rates in predicting the protein structural class. It is anticipated that the concept of grey-PseAA composition can be also used to predict many other protein attributes, such as subcellular localization, membrane protein type, enzyme functional class, GPCR type, protease type, among many others. © 2008 Wiley Periodicals, Inc. J Comput Chem 2008. [source] Analysis and prediction of protein folding rates using quadratic response surface modelsJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 10 2008Liang-Tsung Huang Abstract Understanding the relationship between amino acid sequences and folding rates of proteins is an important task in computational and molecular biology. In this work, we have systematically analyzed the composition of amino acid residues for proteins with different ranges of folding rates. We observed that the polar residues, Asn, Gln, Ser, and Lys, are dominant in fast folding proteins whereas the hydrophobic residues, Ala, Cys, Gly, and Leu, prefer to be in slow folding proteins. Further, we have developed a method based on quadratic response surface models for predicting the folding rates of 77 two- and three-state proteins. Our method showed a correlation of 0.90 between experimental and predicted protein folding rates using leave-one-out cross-validation method. The classification of proteins based on structural class improved the correlation to 0.98 and it is 0.99, 0.98, and 0.96, respectively, for all-,, all-,, and mixed class proteins. In addition, we have utilized Baysean classification theory for discriminating two- and three-state proteins, which showed an accuracy of 90%. We have developed a web server for predicting protein folding rates and it is available at http://bioinformatics.myweb.hinet.net/foldrate.htm. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2008 [source] Using pseudo amino acid composition to predict protein structural class: Approached by incorporating 400 dipeptide componentsJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 9 2007Hao Lin Abstract The proteins structure can be mainly classified into four classes: all-,, all - ,, ,/,, and , + , protein according to their chain fold topologies. For the purpose of predicting the protein structural class, a new predicting algorithm, in which the increment of diversity combines with Quadratic Discriminant analysis, is presented to study and predict protein structural class. On the basis of the concept of the pseudo amino acid composition (Chou, Proteins: Struct Funct Genet 2001, 43, 246; Erratum: Proteins Struct Funct Genet 2001, 44, 60), 400 dipeptide components and 20 amino acid composition are, respectively, selected as parameters of diversity source. Total of 204 nonhomologous proteins constructed by Chou (Chou, Biochem Biophys Res Commun 1999, 264, 216) are used for training and testing the predictive model. The predicted results by using the pseudo amino acids approach as proposed in this paper can remarkably improve the success rates, and hence the current method may play a complementary role to other existing methods for predicting protein structural classification. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007 [source] 2D representation of protein secondary structure sequences and its applicationsJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 11 2006Liwei Liu Abstract In terms of the classification of the protein secondary structures, we propose a 2D representation of protein secondary structure sequences. The representation are used to display, analyze, and compare the secondary structure sequences. Based on this representation, we assign the structural class to the protein, and verify the advantage or disadvantage of the methods of predicted protein second structure. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 1119,1124, 2006 [source] Cyclin-dependent kinase inhibitors for treating cancerMEDICINAL RESEARCH REVIEWS, Issue 6 2001Peter L. Toogood Abstract Cyclin dependent kinases (Cdks) are essential enzymes for the control of cell cycle progression. Inhibitors of cyclin-dependent kinases are anticipated to possess therapeutic utility against a wide variety of proliferative diseases, especially cancer. The field of published small molecule Cdk inhibitors is briefly reviewed here as background to a summary of work on a class of pyrido[2,3- d]pyrimidine Cdk inhibitors. Compounds from this class are described that display potency against cyclin D/Cdk4 up to IC50,=,0.004 ,M. Good to moderate selectivity for cyclin D/Cdk4 is also reported for compounds in this structural class. Structure-activity relationship data are presented for substitution at the C2 and N8 positions and these data are interpreted in the context of a binding model that is based on the Cdk2 crystal structure. A representative cyclin D/Cdk4 inhibitor (compound 56) is demonstrated to selectively inhibit the proliferation of an Rb+ cell line vs. a matched Rb, cell line and to produce a distinct G1 block consistent with cyclin D/Cdk4 inhibition in cells. © 2001 John Wiley & Sons, Inc. Med Res Rev, 21, No. 6, 487,498, 2001 [source] Training ACD/LogP with Experimental DataMOLECULAR INFORMATICS, Issue 7 2004Matthew Abstract The commercial physical property calculation software, ACD/Labs Physico-Chemical Laboratory, has the capability to accept experimental data for logP and pKa values which it can use to "train" its model to better predict un-represented structural classes. An attempt was made to produce a training set, called a "user database" by the software, based on Merck in-house data, which could be used to train the ACD/LogP model in order to achieve better predictivity on molecules of interest to Merck researchers. A user database consisting of a randomly selected 10% subset of the available Shake-Flask measured logP data was constructed and used to predict itself as well as the remaining 90% data set. The training produced a modest increase in accuracy of the model, with the R2 value of the prediction improving in the test set from 0.316 to 0.527. Narrowing the selection to a project-based, targeted subset of the in-house data in hopes of decreasing the diversity of the set, enhanced the coverage of the model but only produced an improvement in the R2 value from 0.350 to 0.537. Finally, training on a single, small representative of a structural class produced a sizable reduction in the bias of the prediction in a congeneric series of compounds, essentially confirming the original claim of the software developers. These improvements came with an increase in time and machine load to perform the calculation relative to the size of the training set. [source] High-performance liquid chromatographic separation of natural and synthetic desulphoglucosinolates and their chemical validation by UV, NMR and chemical ionisation-MS methodsPHYTOCHEMICAL ANALYSIS, Issue 4 2001Guy Kiddle Abstract Methods are described for the optimised extraction, desulphation and HPLC separation of desulphoglucosinolates. These methods provide rapid separation, identification and quantitative measurements of glucosinolates extracted from Brassica napus L and related crops, of unusual glucosinolates found in crucifer weed species, and also of synthetic alkylglucosinolates. The desulphoglucosinolates used in these studies were either chemically synthesised (at least one example from each major structural class), or purified from various plant sources. Validation of the identities of the desulphoglucosinolates was by comparison of retention times with standards, and by UV, 1H- and 13C-NMR and chemical ionisation MS analysis. A list of useful species, and the specific tissues, from which high concentrations of standards can be extracted is included. Copyright © 2001 John Wiley & Sons, Ltd. [source] Detection of orientation-specific anti-gp120 antibodies by a new N-glycanase protection assayAPMIS, Issue 2 2002G. J. Gram Several functions have been assigned to the extensive glycosylation of HIV-1 envelope glycoprotein gp120, especially immune escape mechanisms, but the intramolecular interactions between gp120 and its carbohydrate complement are not well understood. To analyse this phenomenon we established a new microwell deglycosylation assay for determining N-linked glycan accessibility after binding of gp120-specific agents. Orientation-specific exposition of gp120 in ELISA microplates was achieved by catching with either anti-C5 antibody D7324 or anti-V3 antibody NEA-9205. We found that soluble CD4 inhibited the deglycosylation of gp120 only when gp120 was caught by D7324 and not by NEA9205. In contrast, antibodies from HIV-infected individuals inhibited the deglycosylation best when gp120 was caught by NEA9205. These results demonstrated that both the CD4-binding site and the epitopes recognised by antibodies from HIV-infected individuals have N-glycans in the close vicinity. However, the difference in gp120 orientation indicates that antibodies in HIV-infected individuals, at least partly, bind to epitopes different from the CD4-binding site. Finally, we determined the structural class of the glycan of one V1 glycosylation site of prototype HIV-1 LAI gp120, which remained unsolved from previous studies, and found that it belonged to the complex type of glycans. [source] Toward a greater appreciation of noncovalent chemical/DNA interactions: Application of biological and computational approaches,ENVIRONMENTAL AND MOLECULAR MUTAGENESIS, Issue 2-3 2005Ronald D. Snyder Abstract Noncovalent DNA interactions, e.g., DNA intercalation and DNA groove-binding, have not been well studied relative to covalent interactions largely due to the inability of predicting and detecting such events in intact cells. We have adapted an in vitro bleomycin amplification method for DNA intercalation for use in cultured V79 Chinese hamster cells and have validated this approach through the use of a three-dimensional DNA computational docking model that quantifies potential strength of DNA intercalative binding based on electrostatics and hydrogen bonding. For many structural classes of molecules, DNA intercalation is necessary but not sufficient for genotoxicity. The present article reviews our progress to date in predicting and confirming noncovalent binding of drugs and other chemicals and in understanding the mechanistic relationship between intercalation and genotoxicity. Environ. Mol. Mutagen., 2005. © 2005 Wiley-Liss, Inc. [source] Prediction of protein structural class by amino acid and polypeptide compositionFEBS JOURNAL, Issue 17 2002Rui-yan Luo A new approach of predicting structural classes of protein domain sequences is presented in this paper. Besides the amino acid composition, the composition of several dipeptides, tripeptides, tetrapeptides, pentapeptides and hexapeptides are taken into account based on the stepwise discriminant analysis. The result of jackknife test shows that this new approach can lead to higher predictive sensitivity and specificity for reduced sequence similarity datasets. Considering the dataset PDB40-B constructed by Brenner and colleagues, 75.2% protein domain sequences are correctly assigned in the jackknife test for the four structural classes: all-,, all-,, ,/, and , + ,, which is improved by 19.4% in jackknife test and 25.5% in resubstitution test, in contrast with the component-coupled algorithm using amino acid composition alone (AAC approach) for the same dataset. In the cross-validation test with dataset PDB40-J constructed by Park and colleagues, more than 80% predictive accuracy is obtained. Furthermore, for the dataset constructed by Chou and Maggiona, the accuracy of 100% and 99.7% can be easily achieved, respectively, in the resubstitution test and in the jackknife test merely taking the composition of dipeptides into account. Therefore, this new method provides an effective tool to extract valuable information from protein sequences, which can be used for the systematic analysis of small or medium size protein sequences. The computer programs used in this paper are available on request. [source] The use of structural species size classes in the description of the woody vegetation of a nature reserveAFRICAN JOURNAL OF ECOLOGY, Issue 4 2004L. R. Brown Abstract The need for a scientifically based wildlife management plan and more knowledge on the vegetation ecology of the Borakalalo Nature Reserve prompted an ecological investigation of the Reserve. One of the aims was to develop a structural classification of the woody component using species size (SPIZE) classes. A further aim was to compare the various structural classes identified with the recognized floristically derived plant communities of the Reserve. The frequency, density, percentage crown cover and importance value for each woody species were calculated. A classification of the woody component was done using a TWINSPAN classification algorithm on this structural density data. Fifteen structural SPIZE classes were identified, described and compared with the described plant communities. The results of this study indicate that structural SPIZE classes could also be used to explain the spatial distribution of woody species within and between various plant communities. Résumé Le besoin de concevoir un plan d'aménagement scientifique, et un désir d'en savoir plus sur l'écologie de la végétation dans la Réserve Naturelle de Borakalalo, ont menéà une étude de cette Réserve. Un des buts principaux était d'établir une classification structurale de la partie boisée en fonction des catégories de taille des espèces (des catégories dites ,SPIZE', ou ,species size classes'). L'étude avait aussi comme but de comparer les diverse catégories structurelles identifiées avec les communautés végétales reconnues de la Réserve de dérivation floristique. La fréquence, la densité, le pourcentage de couverture de la cime et l'importance de chaque espèce boisée ont été calculés. Une classification de la partie boisée a été réalisée en se servant d'un algorithme dit ,TWINSPAN' pour évaluer les données sur la densité structurale. Quinze catégories SPIZE ont été identifiées, décrites et comparées avec les communautés végétales décrites. Les résultats de cette étude indiquent que les catégories SPIZE structurelles pourraient être utilisées davantage pour expliquer la distribution spatiale des espèces boisées entre et parmi les diverses communautés végétales. [source] Multiple classifier integration for the prediction of protein structural classesJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 14 2009Lei Chen Abstract Supervised classifiers, such as artificial neural network, partition trees, and support vector machines, are often used for the prediction and analysis of biological data. However, choosing an appropriate classifier is not straightforward because each classifier has its own strengths and weaknesses, and each biological dataset has its own characteristics. By integrating many classifiers together, people can avoid the dilemma of choosing an individual classifier out of many to achieve an optimized classification results (Rahman et al., Multiple Classifier Combination for Character Recognition: Revisiting the Majority Voting System and Its Variation, Springer, Berlin, 2002, 167,178). The classification algorithms come from Weka (Witten and Frank, Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann, San Francisco, 2005) (a collection of software tools for machine learning algorithms). By integrating many predictors (classifiers) together through simple voting, the correct prediction (classification) rates are 65.21% and 65.63% for a basic training dataset and an independent test set, respectively. These results are better than any single machine learning algorithm collected in Weka when exactly the same data are used. Furthermore, we introduce an integration strategy which takes care of both classifier weightings and classifier redundancy. A feature selection strategy, called minimum redundancy maximum relevance (mRMR), is transferred into algorithm selection to deal with classifier redundancy in this research, and the weightings are based on the performance of each classifier. The best classification results are obtained when 11 algorithms are selected by mRMR method, and integrated together through majority votes with weightings. As a result, the prediction correct rates are 68.56% and 69.29% for the basic training dataset and the independent test dataset, respectively. The web-server is available at http://chemdata.shu.edu.cn/protein_st/. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009 [source] Using support vector machines for prediction of protein structural classes based on discrete wavelet transformJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 8 2009Jian-Ding Qiu Abstract The prediction of secondary structure is a fundamental and important component in the analytical study of protein structure and functions. How to improve the predictive accuracy of protein structural classification by effectively incorporating the sequence-order effects is an important and challenging problem. In this study, a new method, in which the support vector machine combines with discrete wavelet transform, is developed to predict the protein structural classes. Its performance is assessed by cross-validation tests. The predicted results show that the proposed approach can remarkably improve the success rates, and might become a useful tool for predicting the other attributes of proteins as well. © 2008 Wiley Periodicals, Inc. J Comput Chem 2009 [source] Using grey dynamic modeling and pseudo amino acid composition to predict protein structural classesJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 12 2008Xuan Xiao Abstract Using the pseudo amino acid (PseAA) composition to represent the sample of a protein can incorporate a considerable amount of sequence pattern information so as to improve the prediction quality for its structural or functional classification. However, how to optimally formulate the PseAA composition is an important problem yet to be solved. In this article the grey modeling approach is introduced that is particularly efficient in coping with complicated systems such as the one consisting of many proteins with different sequence orders and lengths. On the basis of the grey model, four coefficients derived from each of the protein sequences concerned are adopted for its PseAA components. The PseAA composition thus formulated is called the "grey-PseAA" composition that can catch the essence of a protein sequence and better reflect its overall pattern. In our study we have demonstrated that introduction of the grey-PseAA composition can remarkably enhance the success rates in predicting the protein structural class. It is anticipated that the concept of grey-PseAA composition can be also used to predict many other protein attributes, such as subcellular localization, membrane protein type, enzyme functional class, GPCR type, protease type, among many others. © 2008 Wiley Periodicals, Inc. J Comput Chem 2008. [source] Using pseudo amino acid composition to predict protein structural classes: Approached with complexity measure factorJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 4 2006Xuan Xiao Abstract The structural class is an important feature widely used to characterize the overall folding type of a protein. How to improve the prediction quality for protein structural classification by effectively incorporating the sequence-order effects is an important and challenging problem. Based on the concept of the pseudo amino acid composition [Chou, K. C. Proteins Struct Funct Genet 2001, 43, 246; Erratum: Proteins Struct Funct Genet 2001, 44, 60], a novel approach for measuring the complexity of a protein sequence was introduced. The advantage by incorporating the complexity measure factor into the pseudo amino acid composition as one of its components is that it can catch the essence of the overall sequence pattern of a protein and hence more effectively reflect its sequence-order effects. It was demonstrated thru the jackknife crossvalidation test that the overall success rate by the new approach was significantly higher than those by the others. It has not escaped our notice that the introduction of the complexity measure factor can also be used to improve the prediction quality for, among many other protein attributes, subcellular localization, enzyme family class, membrane protein type, and G-protein couple receptor type. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 478,482, 2006 [source] Towards a rational development of anti-endotoxin agents: novel approaches to sequestration of bacterial endotoxins with small moleculesJOURNAL OF MOLECULAR RECOGNITION, Issue 6 2001Sunil A. David Abstract Endotoxins, or lipopolysaccharides (LPS), present on the surface of Gram-negative bacteria, play a key role in the pathogenesis of septic shock, a common clinical problem and a leading cause of mortality in critically ill patients, for which no specific therapeutic modalities are available at the present time. The toxic moiety of LPS is a glycolipid called ,lipid A', which is composed of a bisphosphorylated diglucosamine backbone bearing up to seven acyl chains in ester and amide linkages. Lipid A is structurally highly conserved in Gram-negative bacteria, and is therefore an attractive target for developing anti-endotoxin molecules designed to sequester, and thereby neutralize, the deleterious effects of endotoxins. The anionic and amphipathic nature of lipid A enables the interaction of a wide variety of cationic amphiphiles with the toxin. This review describes the systematic evaluation of several structural classes of cationic amphiphiles, both peptides and non-peptidic small molecules, in the broader context of recent efforts aimed at developing novel anti-endotoxin strategies. The derivation of a pharmacophore for LPS recognition has led to the identification of novel, nontoxic, structurally simple small molecules, the lipopolyamines. The lipopolyamines bind and neutralize LPS in in vitro experiments as well as in animal models of endotoxicity, and thus present novel and exciting leads for rational, structure-based development of LPS-sequestering agents of potential clinical value. Copyright © 2001 John Wiley & Sons, Ltd. [source] Bivalent phenethylamines as novel dopamine transporter inhibitors: evidence for multiple substrate-binding sites in a single transporterJOURNAL OF NEUROCHEMISTRY, Issue 6 2010Kyle C. Schmitt J. Neurochem. (2010) 112, 1605,1618. Abstract Bivalent ligands , compounds incorporating two receptor-interacting moieties linked by a flexible chain , often exhibit profoundly enhanced binding affinity compared with their monovalent components, implying concurrent binding to multiple sites on the target protein. It is generally assumed that neurotransmitter sodium symporter (NSS) proteins, such as the dopamine transporter (DAT), contain a single domain responsible for recognition of substrate molecules. In this report, we show that molecules possessing two substrate-like phenylalkylamine moieties linked by a progressively longer aliphatic spacer act as progressively more potent DAT inhibitors (rather than substrates). One compound bearing two dopamine (DA)-like pharmacophoric ,heads' separated by an 8-carbon linker achieved an 82-fold gain in inhibition of [3H] 2,-carbomethoxy-3,-(4-fluorophenyl)-tropane (CFT) binding compared with DA itself; bivalent compounds with a 6-carbon linker and heterologous combinations of DA-, amphetamine- and ,-phenethylamine-like heads all resulted in considerable and comparable gains in DAT affinity. A series of short-chain bivalent-like compounds with a single N -linkage was also identified, the most potent of which displayed a 74-fold gain in binding affinity. Computational modelling of the DAT protein and docking of the two most potent bivalent (-like) ligands suggested simultaneous occupancy of two discrete substrate-binding domains. Assays with the DAT mutants W84L and D313N , previously employed by our laboratory to probe conformation-specific binding of different structural classes of DAT inhibitors , indicated a bias of the bivalent ligands for inward-facing transporters. Our results strongly indicate the existence of multiple DAT substrate-interaction sites, implying that it is possible to design novel types of DAT inhibitors based upon the ,multivalent ligand' strategy. [source] Pharmaceutical antibiotic compounds in soils , a reviewJOURNAL OF PLANT NUTRITION AND SOIL SCIENCE, Issue 2 2003Sören Thiele-Bruhn Antibiotics are highly effective, bioactive substances. As a result of their consumption, excretion, and persistence, they are disseminated mostly via excrements and enter the soils and other environmental compartments. Resulting residual concentrations in soils range from a few ,g upto g kg,1 and correspond to those found for pesticides. Numerous antibiotic molecules comprise of a non-polar core combined with polar functional moieties. Many antibiotics are amphiphilic or amphoteric and ionize. However, physicochemical properties vary widely among compounds from the various structural classes. Existing analytical methods for environmental samples often combine an extraction with acidic buffered solvents and the use of LC-MS for determination. In soils, adsorption of antibiotics to the organic and mineral exchange sites is mostly due to charge transfer and ion interactions and not to hydrophobic partitioning. Sorption is strongly influenced by the pH of the medium and governs the mobility and transport of the antibiotics. In particular for the strongly adsorbed antibiotics, fast leaching through soils by macropore or preferential transport facilitated by dissolved soil colloids seems to be the major transport process. Antibiotics of numerous classes are photodegraded. However, on soil surfaces this process if of minor influence. Compared to this, biotransformation yields a more effective degradation and inactivation of antibiotics. However, some metabolites still comprise of an antibiotic potency. Degradation of antibiotics is hampered by fixation to the soil matrix; persisting antibiotics were already determined in soils. Effects on soil organisms are very diverse, although all antibiotics are highly bioactive. The absence of effects might in parts be due to a lack of suitable test methods. However, dose and persistence time related effects especially on soil microorganisms are often observed that might cause shifts of the microbial community. Significant effects on soil fauna were only determined for anthelmintics. Due to the antibiotic effect, resistance in soil microorganisms can be provoked by antibiotics. Additionally, the administration of antibiotics mostly causes the formation of resistant microorganisms within the treated body. Hence, resistant microorganisms reach directly the soils with contaminated excrements. When pathogens are resistant or acquire resistance from commensal microorganisms via gene transfer, humans and animals are endangered to suffer from infections that cannot be treated with pharmacotherapy. The uptake into plants even of mobile antibiotics is small. However, effects on plant growth were determined for some species and antibiotics. Pharmazeutische Antibiotika in Böden , ein Überblick Antibiotika sind hochgradig wirksame, bioaktive Substanzen. Infolge ihrer Anwendung, Ausscheidung und Persistenz werden sie meist über die Exkremente in Böden und andere Umweltkompartimente eingetragen. Die resultierenden Rückstandskonzentrationen in Böden im Bereich von wenigen ,g bis zu g kg,1 entsprechen in etwa denen von Pflanzenschutzmitteln. Die Molekülstruktur von Antibiotika besteht häufig aus einem unpolaren Kern und polaren Randgruppen. Viele Antibiotika sind amphiphil oder amphoter und bilden Ionen, jedoch weisen die zahlreichen Antibiotika unterschiedlicher Strukturklassen stark divergierende physikochemische Eigenschaften auf. In den vorliegenden Nachweis"methoden für Umweltproben werden häufig sauer gepufferte Lösungsmittel zur Extraktion und eine Bestimmung mittels LC-MS kombiniert. Die Adsorption der Antibiotika an den organischen als auch an den mineralischen Bodenaustauschern erfolgt zumeist durch Ladungs- und Ionenwechselwirkungen und weniger durch hydrophobe Bindungen. Das Verteilungsverhalten hängt dabei entscheidend vom pH-Wert des Mediums ab und beeinflusst die Mobilität und Verlagerung der Antibiotika. Bei vielen, insbesondere stark adsorbierten Antibiotika sind v.,a. schnelle Fließvorgänge wie durch präferenziellen und Makroporenfluss sowie der Cotransport mit gelösten Bodenkolloiden von besonderer Bedeutung. Antibiotika vieler Strukturklassen können durch Licht abgebaut werden. Dieser Abbaupfad spielt auf Bodenoberflächen jedoch nur eine untergeordnete Rolle. Hingegen kommt es insbesondere durch biologische Transformationsprozesse zu einer intensiven Degradation und Inaktivierung der Antibiotika. Verschiedene Metaboliten weisen jedoch ebenfalls ein antibiotisches Potential auf. Der Abbau der Antibiotika wird durch die Festlegung in Böden gehemmt; dementsprechend wurde eine Persistenz verschiedener Antibiotika nachgewiesen. Trotz der starken bioaktiven Wirkung aller Antibiotika sind die festgestellten Effekte auf Bodenorganismen sehr unterschiedlich. Dies liegt nicht zuletzt an einem Mangel an geeigneten Testmethoden. In der Regel sind jedoch von Dosis und Wirkungsdauer abhängige Effekte insbesondere auf Mikroorganismen festzustellen, die zu Veränderungen der Mikroorganismenpopulation führen können. Lediglich durch Anthelmintika wurden deutliche Wirkungen auf Vertreter der Bodenfauna hervorgerufen. Infolge der antibiotischen Wirkung der Pharmazeutika kann eine Resistenzbildung bei Bodenorganismen ausgelöst werden. Zudem hat die Medikation von Antibiotika die Bildung resistenter Mikroorganismen bereits im behandelten Organismus zur Folge. Durch deren anschließende Ausscheidung gelangen resistente Keime auch direkt in die Böden. Handelt es sich um resistente Pathogene oder kommt es zur Übertragung der Resistenzgene zwischen kommensalen und pathogenen Mikroorganismen, so besteht das erhebliche Risiko einer nicht therapierbaren Infektion von Mensch und Tier. Die Aufnahme selbst mobiler Antibiotika in die Pflanzen ist sehr gering. Dennoch wurden bei einigen Pflanzenarten Wirkungen von Antibiotika auf das Wachstum nachgewiesen. [source] Cyclic nucleotide phosphodiesterases and their role in immunomodulatory responses: Advances in the development of specific phosphodiesterase inhibitorsMEDICINAL RESEARCH REVIEWS, Issue 2 2005Ana Castro Abstract The activity of phosphodiesterases (PDEs) is associated with a wide variety of diseases and an intense effort toward the development of specific PDEs inhibitors has been generated for the last years. They are the enzymes responsible for the hydrolysis of intracellular cyclic adenosine and guanosine monophosphate, and their complexity, as well as their different functional role, makes these enzymes a very attractive therapeutic target. This review is focused on the role of PDEs played on immunomodulatory processes and the advance on the development of specific inhibitors, covering PDEs mainly related to the regulation of autoimmune processes, PDE4 and PDE7. The review also highlights the novel structural classes of PDE4 and PDE7 inhibitors, and the therapeutic potential that combined PDE4/PDE7 inhibitors offer as immunomodulatory agents. © 2004 Wiley Periodicals, Inc. Med Res Rev [source] Training ACD/LogP with Experimental DataMOLECULAR INFORMATICS, Issue 7 2004Matthew Abstract The commercial physical property calculation software, ACD/Labs Physico-Chemical Laboratory, has the capability to accept experimental data for logP and pKa values which it can use to "train" its model to better predict un-represented structural classes. An attempt was made to produce a training set, called a "user database" by the software, based on Merck in-house data, which could be used to train the ACD/LogP model in order to achieve better predictivity on molecules of interest to Merck researchers. A user database consisting of a randomly selected 10% subset of the available Shake-Flask measured logP data was constructed and used to predict itself as well as the remaining 90% data set. The training produced a modest increase in accuracy of the model, with the R2 value of the prediction improving in the test set from 0.316 to 0.527. Narrowing the selection to a project-based, targeted subset of the in-house data in hopes of decreasing the diversity of the set, enhanced the coverage of the model but only produced an improvement in the R2 value from 0.350 to 0.537. Finally, training on a single, small representative of a structural class produced a sizable reduction in the bias of the prediction in a congeneric series of compounds, essentially confirming the original claim of the software developers. These improvements came with an increase in time and machine load to perform the calculation relative to the size of the training set. [source] Regulation of Salmonella typhimurium virulence gene expression by cationic antimicrobial peptidesMOLECULAR MICROBIOLOGY, Issue 1 2003Martin W. Bader Summary Cationic antimicrobial peptides (CAMP) represent a conserved and highly effective component of innate immunity. During infection, the Gram-negative pathogen Salmonella typhimurium induces different mechanisms of CAMP resistance that promote pathogenesis in animals. This study shows that exposure of S. typhimurium to sublethal concentrations of CAMP activates the PhoP/PhoQ and RpoS virulence regulons, while repressing the transcription of genes required for flagella synthesis and the invasion-associated type III secretion system. We further demonstrate that growth of S. typhimurium in low doses of the ,-helical peptide C18G induces resistance to CAMP of different structural classes. Inducible resistance depends on the presence of PhoP, indicating that the PhoP/PhoQ system can sense sublethal concentrations of cationic antimicrobial peptides. Growth of S. typhimurium in the presence of CAMP also leads to RpoS-dependent protection against hydrogen peroxide. Because bacterial resistance to oxidative stress and CAMP are induced during infection of animals, CAMP may be an important signal recognized by bacteria on colonization of animal tissues. [source] Mosquito repellents: a review of chemical structure diversity and olfactionPEST MANAGEMENT SCIENCE (FORMERLY: PESTICIDE SCIENCE), Issue 9 2010Gretchen Paluch Abstract Research on mosquito chemical repellents continues to advance, along with knowledge of mosquito olfaction and behavior, mosquito,host interactions and chemical structure. New tools and technologies have revealed information about insect olfactory mechanisms and processing, providing a more complex approach for the interpretation of how chemical repellents influence host-seeking and feeding behavior. Even with these advances, there is still a large amount of information contained in the early works on insect repellents. Many of the standard test methods and chemicals that are still used for evaluating active repellents were developed in the 1940s. These studies contain valuable references to the activity of different structural classes of chemicals, and serve as a guide to optimization of select compounds for insect repellency effects. Copyright © 2010 Society of Chemical Industry [source] Functional site profiling and electrostatic analysis of cysteines modifiable to cysteine sulfenic acidPROTEIN SCIENCE, Issue 2 2008Freddie R. Salsbury Jr Abstract Cysteine sulfenic acid (Cys-SOH), a reversible modification, is a catalytic intermediate at enzyme active sites, a sensor for oxidative stress, a regulator of some transcription factors, and a redox-signaling intermediate. This post-translational modification is not random: specific features near the cysteine control its reactivity. To identify features responsible for the propensity of cysteines to be modified to sulfenic acid, a list of 47 proteins (containing 49 known Cys-SOH sites) was compiled. Modifiable cysteines are found in proteins from most structural classes and many functional classes, but have no propensity for any one type of protein secondary structure. To identify features affecting cysteine reactivity, these sites were analyzed using both functional site profiling and electrostatic analysis. Overall, the solvent exposure of modifiable cysteines is not different from the average cysteine. The combined sequence, structure, and electrostatic approaches reveal mechanistic determinants not obvious from overall sequence comparison, including: (1) pKas of some modifiable cysteines are affected by backbone features only; (2) charged residues are underrepresented in the structure near modifiable sites; (3) threonine and other polar residues can exert a large influence on the cysteine pKa; and (4) hydrogen bonding patterns are suggested to be important. This compilation of Cys-SOH modification sites and their features provides a quantitative assessment of previous observations and a basis for further analysis and prediction of these sites. Agreement with known experimental data indicates the utility of this combined approach for identifying mechanistic determinants at protein functional sites. [source] Crystal structure of E. coli ,,carbonic anhydrase, an enzyme with an unusual pH,dependent activityPROTEIN SCIENCE, Issue 5 2001Jeff D. Cronk CA, carbonic anhydrase; ECCA, Escherichia coli ,-carbonic anhydrase; PPCA, Porphyridium purpureum ,-carbonic anhydrase; PSCA, Pisum sativum ,-carbonic anhydrase; EXAFS, extended X-ray absorption fine structure spectroscopy; MAD, multiwavelength anomalous dispersion Abstract Carbonic anhydrases fall into three distinct evolutionary and structural classes: ,, ,, and ,. The ,-class carbonic anhydrases (,-CAs) are widely distributed among higher plants, simple eukaryotes, eubacteria, and archaea. We have determined the crystal structure of ECCA, a ,-CA from Escherichia coli, to a resolution of 2.0 Å. In agreement with the structure of the ,-CA from the chloroplast of the red alga Porphyridium purpureum, the active-site zinc in ECCA is tetrahedrally coordinated by the side chains of four conserved residues. These results confirm the observation of a unique pattern of zinc ligation in at least some ,-CAs. The absence of a water molecule in the inner coordination sphere is inconsistent with known mechanisms of CA activity. ECCA activity is highly pH-dependent in the physiological range, and its expression in yeast complements an oxygen-sensitive phenotype displayed by a ,-CA-deletion strain. The structural and biochemical characterizations of ECCA presented here and the comparisons with other ,-CA structures suggest that ECCA can adopt two distinct conformations displaying widely divergent catalytic rates. [source] Homology modeling and molecular dynamics simulations of lymphotactinPROTEIN SCIENCE, Issue 11 2000Buyong Ma Abstract We have modeled the structure of human lymphotactin (hLpnt), by homology modeling and molecular dynamics simulations. This chemokine is unique in having a single disulfide bond and a long C-terminal tail. Because other structural classes of chemokines have two pairs of Cys residues, compared to one in Lpnt, and because it has been shown that both disulfide bonds are required for stability and function, the question arises how the Lpnt maintains its structural integrity. The initial structure of hLpnt was constructed by homology modeling. The first 63 residues in the monomer of hLpnt were modeled using the structure of the human CC chemokine, RANTES, whose sequence appeared most similar. The structure of the long C-terminal tail, missing in RANTES, was taken from the human muscle fatty-acid binding protein. In a Protein Data Bank search, this protein was found to contain a sequence that was most homologous to the long tail. Consequently, the modeled hLpnt C-terminal tail consisted of both ,-helical and ,-motifs. The complete model of the hLpnt monomer consisted of two ,-helices located above the five-stranded ,-sheet. Molecular dynamics simulations of the solvated initial model have indicated that the stability of the predicted fold is related to the geometry of Pro78. The five-stranded ,-sheet appeared to be preserved only when Pro78 was modeled in the cis conformation. Simulations were also performed both for the C-terminal truncated forms of the hLpnt that contained one or two (CC chemokine-like) disulfide bonds, and for the chicken Lpnt (cLpnt). Our MD simulations indicated that the turn region (T30-G34) in hLpnt is important for the interactions with the receptor, and that the long C-terminal region stabilizes both the turn (T30-G34) and the five-stranded ,-sheet. The major conclusion from our theoretical studies is that the lack of one disulfide bond and the extension of the C-terminus in hLptn are mutually complementary. It is very likely that removal of two Cys residues sufficiently destabilizes the structure of a chemokine molecule, particularly the core ,-sheet, to abolish its biological function. However, this situation is rectified by the long C-terminal segment. The role of this long region is most likely to stabilize the first ,-turn region and ,-helix H1, explaining how this chemokine can function with a single disulfide bond. [source] Application of statistical potentials to protein structure refinement from low resolution ab initio modelsBIOPOLYMERS, Issue 4 2003Hui Lu Abstract Recently ab initio protein structure prediction methods have advanced sufficiently so that they often assemble the correct low resolution structure of the protein. To enhance the speed of conformational search, many ab initio prediction programs adopt a reduced protein representation. However, for drug design purposes, better quality structures are probably needed. To achieve this refinement, it is natural to use a more detailed heavy atom representation. Here, as opposed to costly implicit or explicit solvent molecular dynamics simulations, knowledge-based heavy atom pair potentials were employed. By way of illustration, we tried to improve the quality of the predicted structures obtained from the ab initio prediction program TOUCHSTONE by three methods: local constraint refinement, reduced predicted tertiary contact refinement, and statistical pair potential guided molecular dynamics. Sixty-seven predicted structures from 30 small proteins (less than 150 residues in length) representing different structural classes (,, ,, ,,/,) were examined. In 33 cases, the root mean square deviation (RMSD) from native structures improved by more than 0.3 Å; in 19 cases, the improvement was more than 0.5 Å, and sometimes as large as 1 Å. In only seven (four) cases did the refinement procedure increase the RMSD by more than 0.3 (0.5) Å. For the remaining structures, the refinement procedures changed the structures by less than 0.3 Å. While modest, the performance of the current refinement methods is better than the published refinement results obtained using standard molecular dynamics. © 2003 Wiley Periodicals, Inc. Biopolymers 70: 575,584, 2003 [source] | ||||||||||||||||