quantitative structure activity relationship

Summary

Summary: A quantitative prediction of the biological, ecotoxicological or pharmaceutical activity of a molecule. It is based upon structure and activity information gathered from a series of similar compounds.

Top Publications

  1. ncbi Quantitative structure activity relationship studies on the flavonoid mediated inhibition of multidrug resistance proteins 1 and 2
    Jelmer J van Zanden
    Division of Toxicology, Wageningen University, P O Box 8000, 6700 EA Wageningen, The Netherlands
    Biochem Pharmacol 69:699-708. 2005
  2. pmc Computer-aided drug discovery and development (CADDD): in silico-chemico-biological approach
    I M Kapetanovic
    Chemopreventive Agent Development Research Group, Division of Cancer Prevention, National Cancer Institute, 6130 Executive Building, Suite 2117, MSC 7322, Bethesda, MD 20892 7322, United States
    Chem Biol Interact 171:165-76. 2008
  3. ncbi Similarity-based virtual screening using 2D fingerprints
    Peter Willett
    Krebs Institute for Biomolecular Research and Department of Information Studies, University of Sheffield, 211 Portobello, Sheffield S1 4DP, UK
    Drug Discov Today 11:1046-53. 2006
  4. ncbi Quantitative structure activity relationship (QSAR) of piperine analogs for bacterial NorA efflux pump inhibitors
    Amit Nargotra
    Indian Institute of Integrative Medicine, Jammu 180001, J and K, India
    Eur J Med Chem 44:4128-35. 2009
  5. ncbi A support vector machines approach for virtual screening of active compounds of single and multiple mechanisms from large libraries at an improved hit-rate and enrichment factor
    L Y Han
    Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543, Singapore
    J Mol Graph Model 26:1276-86. 2008
  6. ncbi A combined approach to drug metabolism and toxicity assessment
    Sean Ekins
    Computational Biology, GeneGo, Inc, 500 Renaissance Drive, Suite 106, St Joseph, MI 49085, USA
    Drug Metab Dispos 34:495-503. 2006
  7. ncbi Predictive QSAR modeling workflow, model applicability domains, and virtual screening
    Alexander Tropsha
    Laboratory for Molecular Modeling and, Carolina Center for Exploratory Cheminformatics Research, CB 7360 School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
    Curr Pharm Des 13:3494-504. 2007
  8. ncbi A shape-based 3-D scaffold hopping method and its application to a bacterial protein-protein interaction
    Thomas S Rush
    Department of Chemical and Screening Sciences, Wyeth Research, 87 Cambridge Park Drive, Cambridge, MA 02140, USA
    J Med Chem 48:1489-95. 2005
  9. ncbi Molecular similarity: a key technique in molecular informatics
    Andreas Bender
    Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK
    Org Biomol Chem 2:3204-18. 2004
  10. ncbi Global Bayesian models for the prioritization of antitubercular agents
    Philip Prathipati
    Novartis Institute for Tropical Diseases, 10 Biopolis Road, 05 01 Chromos 138670, Singapore
    J Chem Inf Model 48:2362-70. 2008

Detail Information

Publications311 found, 100 shown here

  1. ncbi Quantitative structure activity relationship studies on the flavonoid mediated inhibition of multidrug resistance proteins 1 and 2
    Jelmer J van Zanden
    Division of Toxicology, Wageningen University, P O Box 8000, 6700 EA Wageningen, The Netherlands
    Biochem Pharmacol 69:699-708. 2005
    ..0 microM for MRP1 and 8.5 microM for MRP2. For inhibition of MRP1, a quantitative structure activity relationship (QSAR) was obtained that indicates three structural characteristics to be of major importance ..
  2. pmc Computer-aided drug discovery and development (CADDD): in silico-chemico-biological approach
    I M Kapetanovic
    Chemopreventive Agent Development Research Group, Division of Cancer Prevention, National Cancer Institute, 6130 Executive Building, Suite 2117, MSC 7322, Bethesda, MD 20892 7322, United States
    Chem Biol Interact 171:165-76. 2008
    ..It is expected that the power of CADDD will grow as the technology continues to evolve...
  3. ncbi Similarity-based virtual screening using 2D fingerprints
    Peter Willett
    Krebs Institute for Biomolecular Research and Department of Information Studies, University of Sheffield, 211 Portobello, Sheffield S1 4DP, UK
    Drug Discov Today 11:1046-53. 2006
    ..We demonstrate the effectiveness of this approach to screening, and also describe an approximate form of group fusion, turbo similarity searching, that can be used when just a single reference structure is available...
  4. ncbi Quantitative structure activity relationship (QSAR) of piperine analogs for bacterial NorA efflux pump inhibitors
    Amit Nargotra
    Indian Institute of Integrative Medicine, Jammu 180001, J and K, India
    Eur J Med Chem 44:4128-35. 2009
    b>Quantitative structure activity relationship (QSAR) analysis of piperine analogs as inhibitors of efflux pump NorA from Staphylococcus aureus has been performed in order to obtain a highly accurate model enabling prediction of inhibition ..
  5. ncbi A support vector machines approach for virtual screening of active compounds of single and multiple mechanisms from large libraries at an improved hit-rate and enrichment factor
    L Y Han
    Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543, Singapore
    J Mol Graph Model 26:1276-86. 2008
    ..24.3-87.6% of the predicted hits are outside the known hit families. SVM appears to be potentially useful for facilitating lead discovery in VS of large compound libraries...
  6. ncbi A combined approach to drug metabolism and toxicity assessment
    Sean Ekins
    Computational Biology, GeneGo, Inc, 500 Renaissance Drive, Suite 106, St Joseph, MI 49085, USA
    Drug Metab Dispos 34:495-503. 2006
    ..These case studies demonstrate the combination of QSARs and systems biology methods...
  7. ncbi Predictive QSAR modeling workflow, model applicability domains, and virtual screening
    Alexander Tropsha
    Laboratory for Molecular Modeling and, Carolina Center for Exploratory Cheminformatics Research, CB 7360 School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
    Curr Pharm Des 13:3494-504. 2007
    b>Quantitative Structure Activity Relationship (QSAR) modeling has been traditionally applied as an evaluative approach, i.e., with the focus on developing retrospective and explanatory models of existing data...
  8. ncbi A shape-based 3-D scaffold hopping method and its application to a bacterial protein-protein interaction
    Thomas S Rush
    Department of Chemical and Screening Sciences, Wyeth Research, 87 Cambridge Park Drive, Cambridge, MA 02140, USA
    J Med Chem 48:1489-95. 2005
    ..These experimental results validate this use of ROCS for chemotype switching or "lead hopping" and suggest that it is of general interest for lead identification in drug discovery endeavors...
  9. ncbi Molecular similarity: a key technique in molecular informatics
    Andreas Bender
    Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK
    Org Biomol Chem 2:3204-18. 2004
    ..The key issues of solvation effects, heterogeneity of binding sites and the fundamental problem of the form of similarity measure to use are addressed...
  10. ncbi Global Bayesian models for the prioritization of antitubercular agents
    Philip Prathipati
    Novartis Institute for Tropical Diseases, 10 Biopolis Road, 05 01 Chromos 138670, Singapore
    J Chem Inf Model 48:2362-70. 2008
    ..Strategies for enhancing the repertoire of antiTB compounds with the model, including virtual screening of large databases and combinatorial library design, are proposed...
  11. ncbi Do structurally similar molecules have similar biological activity?
    Yvonne C Martin
    Global Pharmaceutical Research and Development, Abbott Laboratories, Abbott Park, IL 60064 6100, USA
    J Med Chem 45:4350-8. 2002
    ..The current study emphasizes the statistical or probabilistic nature of library design and that perfect results cannot be expected...
  12. ncbi Comparative evaluation of high-performance liquid chromatography stationary phases used for the separation of peptides in terms of quantitative structure-retention relationships
    Monika Michel
    Department of Environmental Chemistry and Bioanalytics, Nicolaus Copernicus University, Gagarin St 7, 87 100 Torun, Poland
    J Chromatogr A 1175:49-54. 2007
    ..On the other hand, the combination of QSRR and principal component analysis (PCA) can be considered as the efficient tool allowing column classification and searching for orthogonal HPLC conditions required to separate peptides...
  13. ncbi Pharmacophore discovery--lessons learned
    John H Van Drie
    Vertex Pharmaceuticals, 130 Waverly St, Cambridge, MA 02139, USA
    Curr Pharm Des 9:1649-64. 2003
    ..Also, practical tips are described for using the author's methodology for pharmacophore discovery, DANTE...
  14. ncbi Comparative binding energy (COMBINE) analysis of OppA-peptide complexes to relate structure to binding thermodynamics
    Ting Wang
    European Media Laboratory, Schloss Wolfsbrunnenweg 33, 69118 Heidelberg, Germany
    J Med Chem 45:4828-37. 2002
    ..This study also points to the general applicability of COMBINE analysis to estimating thermodynamic parameters for protein-peptide complexes...
  15. ncbi Quantitative structure-activity relationship of various endogenous estrogen metabolites for human estrogen receptor alpha and beta subtypes: Insights into the structural determinants favoring a differential subtype binding
    Bao Ting Zhu
    Department of Basic Pharmaceutical Sciences, College of Pharmacy, University of South Carolina, Basic Pharmaceutical Sciences, College of Pharmacy, 700 Sumter Street, Columbia, South Carolina 29209, USA
    Endocrinology 147:4132-50. 2006
    ....
  16. ncbi Rational selection of training and test sets for the development of validated QSAR models
    Alexander Golbraikh
    Division of Medicinal Chemistry and Natural Products, School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 7360, USA
    J Comput Aided Mol Des 17:241-53. 2003
    ..We formulate a set of general criteria for the evaluation of predictive power of QSAR models...
  17. ncbi Comparison of shape-matching and docking as virtual screening tools
    Paul C D Hawkins
    OpenEye Scientific Software, Santa Fe, New Mexico 87507, USA
    J Med Chem 50:74-82. 2007
    ..The results show that a shape-based, ligand-centric approach is more consistent than, and often superior to, the protein-centric approach taken by docking...
  18. ncbi Quantitative structure activity relationship and risk analysis of some heavy metal residues in the milk of cattle and goat
    F Muhammad
    Department of Physiology and Pharmacology, University of Agriculture, Faisalabad, Pakistan
    Toxicol Ind Health 25:177-81. 2009
    ..Lead concentration in the milk of goat was significantly higher as compared to cattle milk. Quantitative structure activity relationship (QSAR) models were suggested to predict the residues of unknown heavy metals in the milk of ..
  19. ncbi Quantitative structure activity relationship (QSAR) analysis of substituted 4-oxothiazolidines and 5-arylidines as lipoxygenase inhibitors
    A N Choudhary
    Department of Pharmaceutical Sciences, Bhimtal Campus, Bhimtal, Kumaun University, Nainital, India
    Mini Rev Med Chem 10:705-14. 2010
    ..The positive contribution of topological parameters (BI, MTI, CC and TVC) illustrates that increase in branching and presence of heteroatom is favorable for lipoxygenase inhibitory activity...
  20. ncbi A 3D QSAR pharmacophore model and quantum chemical structure--activity analysis of chloroquine(CQ)-resistance reversal
    Apurba K Bhattacharjee
    Division of Experimental Therapeutics, Walter Reed Army Institute of Research, Silver Spring, Maryland 20910 7500, USA
    J Chem Inf Comput Sci 42:1212-20. 2002
    ..Significantly, nine out of 11 of a group of structurally diverse CQ-resistance reversal agents mapped very well on the 3D QSAR pharmacophore model...
  21. ncbi Quantitative structure activity relationship of IA3-like peptides as aspartic proteinase inhibitors
    Juan Alexander Padrón-García
    Laboratory of Theoretical and Computational Chemistry, Chemistry Faculty, Havana University, 10400, Havana, Cuba
    Proteins 75:859-69. 2009
    ..The models described represent valuable tools for the future design of novel inhibitor variants active against ScPr and other aspartic proteinases...
  22. ncbi Optimizing fragment and scaffold docking by use of molecular interaction fingerprints
    Gilles Marcou
    Bioinformatics of the Drug, UMR 7175 CNRS ULP, Université Louis Pasteur Strasbourg I, 74 route du Rhin, B P 24, F 67400 Illkirch, France
    J Chem Inf Model 47:195-207. 2007
    ....
  23. ncbi Diverse, high-quality test set for the validation of protein-ligand docking performance
    Michael J Hartshorn
    Astex Therapeutics, Ltd, 436 Cambridge Science Park, Milton Road, Cambridge CB4 0QA, United Kingdom
    J Med Chem 50:726-41. 2007
    ..Relatively unbiased protocols give success rates of approximately 80% for redocking into native structures, but it is possible to get success rates of over 90% with some protocols...
  24. ncbi QSRR: quantitative structure-(chromatographic) retention relationships
    Roman Kaliszan
    Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdansk, Gen J Hallera 107, 80416 Gdańsk, Poland
    Chem Rev 107:3212-46. 2007
  25. ncbi Quantitative structure-activity relationship analysis of functionalized amino acid anticonvulsant agents using k nearest neighbor and simulated annealing PLS methods
    Min Shen
    Division of Medicinal Chemistry and Natural Products, School of Pharmacy, CB 7360, University of North Carolina, Chapel Hill, NC 27599 7360, USA
    J Med Chem 45:2811-23. 2002
    ..The successful development of highly predictive QSAR models affords further design and discovery of novel anticonvulsant agents...
  26. ncbi Screening of 397 chemicals and development of a quantitative structure--activity relationship model for androgen receptor antagonism
    Anne Marie Vinggaard
    National Food Institute, Department of Toxicology and Risk Assessment, Technical University of Denmark, Mørkhøj Bygade 19, DK 2860 Søborg, Denmark
    Chem Res Toxicol 21:813-23. 2008
    ..We conclude that the predictability of the global QSAR model for this end point is good. This most comprehensive QSAR model may become a valuable tool for screening large numbers of chemicals for AR antagonism...
  27. ncbi Recent developments of the chemistry development kit (CDK) - an open-source java library for chemo- and bioinformatics
    Christoph Steinbeck
    Cologne University Bioinformatics Center CUBIC, Germany
    Curr Pharm Des 12:2111-20. 2006
    ..This article introduces the CDK's new QSAR capabilities and the recently introduced interface to statistical software...
  28. ncbi Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection
    Alexander Golbraikh
    The Laboratory for Molecular Modeling, School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 7360, USA
    J Comput Aided Mol Des 16:357-69. 2002
    ..We suggest that rational approaches to the selection of training and test sets based on diversity principles should be used routinely in all QSAR modeling research...
  29. pmc Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs
    Lennart Eriksson
    Umetrics, Umea, Sweden
    Environ Health Perspect 111:1361-75. 2003
    ..Finally, we emphasize that rigorous and independent validation of QSARs is an essential step toward their regulatory acceptance and implementation...
  30. pmc The importance of discerning shape in molecular pharmacology
    Sandhya Kortagere
    Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA 19129, USA
    Trends Pharmacol Sci 30:138-47. 2009
    ..The results from recently published studies show that shape and shape-based descriptors are at least as useful as other traditional molecular descriptors...
  31. ncbi A framework for using structural, reactivity, metabolic and physicochemical similarity to evaluate the suitability of analogs for SAR-based toxicological assessments
    Shengde Wu
    Central Product Safety Department, The Procter and Gamble Company, Miami Valley Innovation Center, 11810 E Miami River Road, Cincinnati, OH 45040, USA
    Regul Toxicol Pharmacol 56:67-81. 2010
    ....
  32. ncbi Data analysis of high-throughput screening results: application of multidomain clustering to the NCI anti-HIV data set
    Susan Y Tamura
    Bioreason, Inc, 150 Washington Avenue, Suite 220, Santa Fe, NM 87501, USA
    J Med Chem 45:3082-93. 2002
    ..The detection of structure-activity relationships (SAR), aided by the unique classification method, is described in this article...
  33. ncbi Comparison of knowledge-based and distance geometry approaches for generation of molecular conformations
    B P Feuston
    Molecular Systems Department, Merck Research Laboratories, P O Box 4, West Point, Pennsylvania 19486, USA
    J Chem Inf Comput Sci 41:754-63. 2001
    ..The present knowledge-based approach (i) generates conformations closer to the experimentally determined conformation, (ii) generates them sooner, and (iii) is significantly faster than the DG method...
  34. ncbi A new method for estimating the importance of hydrophobic groups in the binding site of a protein
    Matthew D Kelly
    Department of Pharmacology, University of Cambridge, UK
    J Med Chem 48:1069-78. 2005
    ..The method is also able to rationalize differences in binding affinity for ligand-protein complexes with largely hydrophobic binding sites...
  35. ncbi Searching for an enhanced predictive tool for mutagenicity
    G Klopman
    Department of Chemistry, Case Western Reserve University, Euclid Avenue, Cleveland, OH 44106, USA
    SAR QSAR Environ Res 15:251-63. 2004
    ..It was shown that the multiple-database mutagenicity model showed a clear advantage over normally used single-database models. The expertise produced by this analysis can be used to predict the mutagenic potential of new compounds...
  36. ncbi Evaluation and comparison of 3D-QSAR CoMSIA models for CDK1, CDK5, and GSK-3 inhibition by paullones
    Conrad Kunick
    Institut fur Pharmazie, Abteilung für Pharmazeutische Chemie, Universitat Hamburg, Bundesstrasse 45, D 20146 Hamburg, Germany
    J Med Chem 47:22-36. 2004
    ..929 and q(2)() = 0.699), which were clearly superior to the models for CDK5 (r(2)() = 0.874 and q(2)() = 0.652) and GSK-3 (r(2)() = 0.871 and q(2)() = 0.554)...
  37. ncbi Quantitative structure-activity relationship analysis of pyridinone HIV-1 reverse transcriptase inhibitors using the k nearest neighbor method and QSAR-based database mining
    Jose Luis Medina-Franco
    Departamento de Farmacia, Facultad de Quimica, Universidad Nacional Autonoma de Mexico, 04510, Mexico City, Mexico
    J Comput Aided Mol Des 19:229-42. 2005
    ..0) software. Docking results suggested that these types of compounds could be binding in the NNRTI binding site in a similar mode to a known non-nucleoside inhibitor nevirapine...
  38. pmc A novel automated lazy learning QSAR (ALL-QSAR) approach: method development, applications, and virtual screening of chemical databases using validated ALL-QSAR models
    Shuxing Zhang
    Division of Medicinal Chemistry and Natural Products, School of Pharmacy, CB 7360 Beard Hall, University of North Carolina, Chapel Hill, North Carolina 27599, USA
    J Chem Inf Model 46:1984-95. 2006
    ..Because of its local nature, the ALL-QSAR approach appears to be especially well-suited for the development of highly predictive models for the sparse or unevenly distributed data sets...
  39. ncbi Combining 4D pharmacophore generation and multidimensional QSAR: modeling ligand binding to the bradykinin B2 receptor
    Markus A Lill
    Biographics Laboratory 3R, Friedensgasse 35, 4056 Basel, Switzerland
    J Chem Inf Model 46:2135-45. 2006
    ..These converged at a cross-validated r2 of 0.752 and 0.815 and yielded a predictive r2 of 0.784 and 0.853 for a test set (for Quasar and Raptor, respectively)...
  40. ncbi Using ensembles to classify compounds for drug discovery
    J Kevin Lanctot
    Deltagen Research Laboratories, Inc, 740 Bay Road, Redwood City, California 94063, USA
    J Chem Inf Comput Sci 43:2163-9. 2003
    ..Of the four possible pairings, the combination of chi-square and high ranking set cover performed the best on a Thrombin data set...
  41. ncbi (Q)SARs: gatekeepers against risk on chemicals?
    E M Hulzebos
    National Institute of Public Health and Environment, RIVM, Anthonie van Leeuwenhoeklaan 9, P O Box 1, 3720 BA Bilthoven, The Netherlands
    SAR QSAR Environ Res 14:285-316. 2003
    ..Therefore, if the regulatory trend is that (Q)SARs have to be applied more and more systematically in the risk assessment process, their validity and the available tools have to be explored further...
  42. ncbi Coupling in silico and in vitro analysis of peptide-MHC binding: a bioinformatic approach enabling prediction of superbinding peptides and anchorless epitopes
    Irini A Doytchinova
    Edward Jenner Institute for Vaccine Research Compton, High Street, Berkshire, Compton RG20 7NN, United Kingdom
    J Immunol 172:7495-502. 2004
    ....
  43. ncbi QSAR studies of paeonol analogues for inhibition of platelet aggregation
    Mukesh Doble
    Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600036, India
    Bioorg Med Chem 13:5996-6001. 2005
    ..89 and q(pre)2 = 0.66. The correlation coefficient between antiplatelet inhibition activity with an interaction energy between the paeonol compounds with COX-1 enzyme is only 0.39...
  44. ncbi Fragment-based drug design: how big is too big?
    Philip J Hajduk
    Pharmaceutical Discovery Division, Abbott Laboratories, R46Y, AP 10, 100 Abbott Park Road, Abbott Park, Illinois 60064, USA
    J Med Chem 49:6972-6. 2006
    ..These data place well-defined limits on the ideal size and potency of fragment leads that are being considered for use in fragment-based drug design...
  45. ncbi An automated PLS search for biologically relevant QSAR descriptors
    Marius Olah
    Division of Biocomputing, University of New Mexico School of Medicine, I University of New Mexico, MSC08 4560, Albuquerque, NM 87131, USA
    J Comput Aided Mol Des 18:437-49. 2004
    ..At the individual level, size-related descriptors and topological indices (in the 2D property space), and branched SMARTS, aromatic and ring atom types and halogens are found to be most relevant according to the VIP criterion...
  46. ncbi Quantitative structure-activity relationship and quantitative structure-pharmacokinetics relationship of 1,4-dihydropyridines and pyridines as multidrug resistance modulators
    Xiao Fei Zhou
    Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, 517 Hochstetter Hall, Amherst, New York 14260 1200, USA
    Pharm Res 22:1989-96. 2005
    ..The aim of this study was to develop quantitative structure-activity/pharmacokinetic relationships (QSAR/QSPKR) for a series of synthesized 1,4-dihydropyridines (DHPs) and pyridines as P-glycoprotein (P-gp) inhibitors...
  47. ncbi First QSAR report on FSH receptor antagonistic activity: quantitative investigations on physico-chemical and structural features among 6-amino-4-phenyltetrahydroquinoline derivatives
    E Manivannan
    School of Pharmacy, Devi Ahilya Vishwavidyalaya, Ring Road, Indore 452017, India
    Bioorg Med Chem Lett 15:4496-501. 2005
    ....
  48. ncbi Ligand-based structural hypotheses for virtual screening
    Ajay N Jain
    UCSF Cancer Research Institute and Comprehensive Cancer Center, University of California, San Francisco, California 94143 0128, USA
    J Med Chem 47:947-61. 2004
    ..The methods are practically applicable for rational design of ligands and for high-throughput virtual screening and offer competitive performance to many structure-based docking algorithms...
  49. ncbi Quantitative structure-activity relationship based quantification of the impacts of enzyme-substrate binding on rates of peroxidase-mediated reactions of estrogenic phenolic chemicals
    Lisa M Colosi
    Environmental and Water Resources Engineering Program and Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109 2099, USA
    J Am Chem Soc 128:4041-7. 2006
    ....
  50. ncbi A systematic approach to simulating metabolism in computational toxicology. I. The TIMES heuristic modelling framework
    Ovanes G Mekenyan
    Laboratory of Mathematical Chemistry, Bourgas As Zlatarov University, 8010 Bourgas, Bulgaria
    Curr Pharm Des 10:1273-93. 2004
    ..The conceptual approach for metabolic simulation will be presented along with practical uses in forecasting plausible activated metabolites...
  51. ncbi Structure-toxicity relationships of nitroaromatic compounds
    Olexandr Isayev
    Computational Center for Molecular Structure and Interactions, Jackson State University, Jackson, Mississippi, USA
    Mol Divers 10:233-45. 2006
    ..The toxicity LD50 parameter for rats has been utilized for the first time for QSAR analysis of nitrobenzenes. The predictive ability of the models is determined by a cross-validation "leave-one-out" method...
  52. ncbi New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity
    Channa K Hattotuwagama
    Edward Jenner Institute for Vaccine Research, Compton, Berkshire RG20 7NN, UK
    Org Biomol Chem 2:3274-83. 2004
    ..They can be used for the accurate prediction of T-cell epitopes and are freely available online ( http://www.jenner.ac.uk/MHCPred)...
  53. ncbi A combined approach of docking and 3D QSAR study of beta-ketoacyl-acyl carrier protein synthase III (FabH) inhibitors
    Ali Ashek
    Biochemicals Research Center, Korea Institute of Science and Technology, Cheongryang, Seoul, Republic of Korea
    Bioorg Med Chem 14:1474-82. 2006
    ..These results should be applicable to the prediction of the activities of new FabH inhibitors, as well as providing structural understanding...
  54. ncbi Transporter associated with antigen processing preselection of peptides binding to the MHC: a bioinformatic evaluation
    Irini Doytchinova
    Edward Jenner Institute for Vaccine Research, Compton, Berkshire, United Kingdom
    J Immunol 173:6813-9. 2004
    ..The reduction in the number of nonbinders varied from 10% (TAP-independent) to 33% (TAP-dependent), suggesting that TAP preselection is an important component in the successful in silico prediction of T cell epitopes...
  55. ncbi Megavariate analysis of environmental QSAR data. Part I--a basic framework founded on principal component analysis (PCA), partial least squares (PLS), and statistical molecular design (SMD)
    Lennart Eriksson
    Umetrics AB, POB 7960, S 907 19, Umea, Sweden
    Mol Divers 10:169-86. 2006
    ..PLS is the regression extension of PCA and is used for establishing QSARs. SMD is essential for selecting informative training and test sets of compounds for QSAR calibration and validation...
  56. ncbi BRUTUS: optimization of a grid-based similarity function for rigid-body molecular superposition. 1. Alignment and virtual screening applications
    Anu J Tervo
    Department of Pharmaceutical Chemistry, University of Kuopio, Finland
    J Med Chem 48:4076-86. 2005
    ..This fast and efficient molecular-field-based algorithm is applicable for virtual screening of structurally diverse, active molecules...
  57. ncbi New predictors for several ADME/Tox properties: aqueous solubility, human oral absorption, and Ames genotoxicity using topological descriptors
    Joseph R Votano
    ChemSilico LLC, Tewksbury, MA, USA
    Mol Divers 8:379-91. 2004
    ..With new drugs a concordance of 92% was reached, which increased to 97% when the reliably indicator was invoked...
  58. ncbi Bioavailability prediction based on molecular structure for a diverse series of drugs
    Joseph V Turner
    Faculty of Pharmacy, The University of Sydney, Sydney NSW 2006 Australia
    Pharm Res 21:68-82. 2004
    ..Radial basis function artificial neural networks and theoretical descriptors were used to develop a quantitative structure-pharmacokinetic relationship for structurally diverse drug compounds...
  59. ncbi Prediction of high-performance liquid chromatography retention of peptides with the use of quantitative structure-retention relationships
    Roman Kaliszan
    Medical University of Gdanńsk, Department of Biopharmaceutics and Pharmacodynamics, Gdanńsk, Poland
    Proteomics 5:409-15. 2005
    ..The QSRR equation obtained predicts in a convenient and reliable manner the retention times for any peptide in a once characterized HPLC system...
  60. ncbi General linearized biexponential model for QSAR data showing bilinear-type distribution
    Peter Buchwald
    IVAX Research, Inc, 4400 Biscayne Blvd, Miami, Florida 33137, USA
    J Pharm Sci 94:2355-79. 2005
    ....
  61. ncbi Virtual screening of DNA minor groove binders
    David A Evans
    Cancer Research UK Biomolecular Structure Group, The School of Pharmacy, University of London, 29 39 Brunswick Square, London WC1N 1AX, UK
    J Med Chem 49:4232-8. 2006
    ....
  62. ncbi Comparison of MLR, PLS and GA-MLR in QSAR analysis
    A K Saxena
    Medicinal Chemistry Division, Central Drug Research Institute, Chattan Manzil, P O Box 173, Lucknow 226001, India
    SAR QSAR Environ Res 14:433-45. 2003
    ....
  63. ncbi Development and validation of k-nearest-neighbor QSPR models of metabolic stability of drug candidates
    Min Shen
    Division of Medicinal Chemistry and Natural Products, School of Pharmacy, CB 7360, University of North Carolina, Chapel Hill, North Carolina 27599 7360, USA
    J Med Chem 46:3013-20. 2003
    ..This success (83% concordance) in correctly picking chemicals that are metabolically stable in the human S9 homogenate spells a rapid, computational screen for generating components of the ADME profile in a drug discovery process...
  64. ncbi Pharmacophore and three-dimensional quantitative structure activity relationship methods for modeling cytochrome p450 active sites
    S Ekins
    Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana 46285, USA
    Drug Metab Dispos 29:936-44. 2001
    ....
  65. ncbi QSAR with few compounds and many features
    D M Hawkins
    School of Statistics, 313 Ford Hall, 224 Church Street S E, University of Minnesota, Minneapolis, Minnesota 55455, USA
    J Chem Inf Comput Sci 41:663-70. 2001
    ..Conventional regression diagnostics can be used in followup to identify nonlinearities and other departures from model. We illustrate the approach with QSAR models of four data sets using calculated molecular descriptors...
  66. ncbi QSAR study of antioxidant activity of wine polyphenols
    Vesna Rastija
    Faculty of Agriculture, Josip Juraj Strossmayer University of Osijek, Trg Sv Trojstva 3, Osijek 31000, Croatia
    Eur J Med Chem 44:400-8. 2009
    ..We demonstrated that a size and shape of molecules, as well as steric properties, play an important role in the antioxidant activity of polyphenols...
  67. ncbi Quantitative structure activity relationship model for predicting the depletion percentage of skin allergic chemical substances of glutathione
    Hongzong Si
    Institute for Computational Science and Engineering, Qingdao University, Qingdao 266071, China
    Anal Chim Acta 591:255-64. 2007
    ..52 and 0.94 for the training set, 22.80 and 0.85 for the test set, respectively. It is shown that the GEP predicted results are in good agreement with experimental ones, better than those of the heuristic method...
  68. ncbi The molecular descriptor logSumAA and its alternatives in QSRR models to predict the retention of peptides
    K Bodzioch
    Department of Analytical Chemistry and Pharmaceutical Technology, Vrije Universiteit Brussel VUB, Laarbeeklaan 103, 1090 Brussels, Belgium
    J Pharm Biomed Anal 50:563-9. 2009
    ..It resulted in QSRR models with similar predictive properties as those with logSum(AA), but with a reduced workload...
  69. ncbi Rate-limited steps of human oral absorption and QSAR studies
    Yuan H Zhao
    Department of Chemistry, University College London, United Kingdom
    Pharm Res 19:1446-57. 2002
    ..To classify the dissolution and diffusion rate-limited drugs and establish quantitative relationships between absorption and molecular descriptors...
  70. ncbi Toward the quantitative prediction of T-cell epitopes: coMFA and coMSIA studies of peptides with affinity for the class I MHC molecule HLA-A*0201
    I A Doytchinova
    Edward Jenner Institute for Vaccine Research, Compton, Berkshire, RG20 7NN, UK
    J Med Chem 44:3572-81. 2001
    ....
  71. ncbi QSAR and k-nearest neighbor classification analysis of selective cyclooxygenase-2 inhibitors using topologically-based numerical descriptors
    G W Kauffman
    Department of Chemistry, The Pennsylvania State University, 152 Davey Laboratory, University Park, PA 16802, USA
    J Chem Inf Comput Sci 41:1553-60. 2001
    ..A k-nearest neighbor classification study of the data set discriminating between active and inactive members produced a nine-descriptor model able to accurately classify 83.3% of the prediction set compounds correctly...
  72. ncbi Performance of Kier-Hall E-state descriptors in quantitative structure activity relationship (QSAR) studies of multifunctional molecules
    Darko Butina
    ChemoMine Consultancy, 201 Icknield Way, Letchworth Garden City, Herts SG6 4TT, UK
    Molecules 9:1004-9. 2004
    ....
  73. ncbi Beware of q2!
    Alexander Golbraikh
    Laboratory for Molecular Modeling, Division of Medicinal Chemistry and Natural Products, School of Pharmacy, University of North Carolina at Chapel Hill, 27599, USA
    J Mol Graph Model 20:269-76. 2002
    ..We emphasize that the external validation is the only way to establish a reliable QSAR model. We formulate a set of criteria for evaluation of predictive ability of QSAR models...
  74. ncbi QSAR models using a large diverse set of estrogens
    L M Shi
    ROW Sciences Inc, Jefferson, Arkansas 72079, USA
    J Chem Inf Comput Sci 41:186-95. 2001
    ....
  75. ncbi The expanding role of predictive toxicology: an update on the (Q)SAR models for mutagens and carcinogens
    Romualdo Benigni
    Istituto Superiore di Sanita, Environment and Health Department, Rome, Italy
    J Environ Sci Health C Environ Carcinog Ecotoxicol Rev 25:53-97. 2007
    ....
  76. ncbi Development of quantitative structure-activity relationship and classification models for a set of carbonic anhydrase inhibitors
    Brian E Mattioni
    Department of Chemistry, The Pennsylvania State University, 152 Davey Laboratory, University Park, Pennsylvania 16802, USA
    J Chem Inf Comput Sci 42:94-102. 2002
    ..1%, respectively, were obtained. For the three-class (active/moderate/inactive) problem, a five-descriptor model was deemed optimal producing a training set percent classification rate of 98.8% and prediction set rate of 79.0%...
  77. ncbi Atomic property fields: generalized 3D pharmacophoric potential for automated ligand superposition, pharmacophore elucidation and 3D QSAR
    Maxim Totrov
    Molsoft LLC, 3366 N Torrey Pines Ct, Ste 300, La Jolla CA 92037, USA
    Chem Biol Drug Des 71:15-27. 2008
    ..The new methods are shown to perform competitively in comparison to current state-of-the-art methods...
  78. ncbi Computational toxicology: an overview of the sources of data and of modelling methods
    Florian Nigsch
    Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK
    Expert Opin Drug Metab Toxicol 5:1-14. 2009
    ..Computational toxicology is an area of active development and great potential. There are tangible reasons for the emerging interest in this discipline from academia, industry, regulatory bodies and governments...
  79. ncbi Surface descriptors for protein-ligand affinity prediction
    Ismael Zamora
    DMPK and Bioanalytical Chemistry, AstraZeneca R and D Molndal, S 431 83 Molndal, Sweden
    J Med Chem 46:25-33. 2003
    ..Using the VolSurf computational framework, both ligand-receptor binding and the ligand's pharmacokinetic behavior can be modeled simultaneously during the preclinical aspects of drug discovery...
  80. ncbi Predictions of peptides' retention times in reversed-phase liquid chromatography as a new supportive tool to improve protein identification in proteomics
    Tomasz Baczek
    Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdansk, Gdansk, Poland
    Proteomics 9:835-47. 2009
    ..It is concluded that proper processing of chromatographic data by statistical learning techniques can result in information of direct use for proteomics, which is otherwise wasted...
  81. ncbi Quantitative structure activity relationship and pharmacophore studies of adenosine receptor A2B inhibitors
    Tej Bhalla Joseph
    Biocampus, GVKBIO sciences, S 1, Phase 1, TIE, Balanagar, Hyderabad 500036, India
    Chem Biol Drug Des 72:395-408. 2008
    ..These observations provide important insights to the rationale development of novel and potent compounds against ADoR A2B...
  82. ncbi Receptor flexibility in de novo ligand design and docking
    Ian L Alberts
    De Novo Pharmaceuticals, Compass House, Vision Park, Histon, Cambridge CB4 9ZR, U K
    J Med Chem 48:6585-96. 2005
    ..The results of corresponding simulations for both rigid and flexible binding sites are compared in order to gauge the influence of receptor flexibility in drug discovery protocols...
  83. ncbi Optimization of a pharmacophore model for 5-HT4 agonists using CoMFA and receptor based alignment
    Magdy N Iskander
    The Department of Medicinal Chemistry, Victorian College of Pharmacy, Monash University, 381 Royal Parade, Parkville, VIC 3052, Australia
    Eur J Med Chem 41:16-26. 2006
    ..664 up from 0.477 in model A. The contributions from the LogP factor were minimal, 0.085 in both models. The synthesized compounds showed agonist activity at mumol level...
  84. ncbi Development and validation of AMANDA, a new algorithm for selecting highly relevant regions in Molecular Interaction Fields
    Angel Duran
    Research Unit on Biomedical Informatics GRIB, IMIM Universitat Pompeu Fabra, Avinguda Dr Aiguader 88, E 08003 Barcelona, Spain
    J Chem Inf Model 48:1813-23. 2008
    ..In both cases the results show that the novel method is highly suitable for describing ligand-receptor interactions and compares favorably with other state-of-the-art methods...
  85. ncbi Molecule kernels: a descriptor- and alignment-free quantitative structure-activity relationship approach
    Johannes A Mohr
    School for Electrical Engineering and Computer Science, Berlin Institute of Technology, Berlin, Germany
    J Chem Inf Model 48:1868-81. 2008
    b>Quantitative structure activity relationship (QSAR) analysis is traditionally based on extracting a set of molecular descriptors and using them to build a predictive model...
  86. ncbi Is it possible to increase hit rates in structure-based virtual screening by pharmacophore filtering? An investigation of the advantages and pitfalls of post-filtering
    Daniel Muthas
    Department of Medicinal Chemistry, Division of Organic Pharmaceutical Chemistry, BMC, Uppsala University, P O Box 574, SE 751 23 Uppsala, Sweden
    J Mol Graph Model 26:1237-51. 2008
    ..This indicates that this is a general method, which works for diverse targets and different docking softwares...
  87. ncbi Identification of novel extracellular signal-regulated kinase docking domain inhibitors
    Chad N Hancock
    Department of Pharmaceutical Sciences, School of Pharmacy, and Molecular and Cell Biology Program, University of Maryland, Baltimore, 21201, USA
    J Med Chem 48:4586-95. 2005
    ..These active compounds may serve as lead candidates for development of novel specific inhibitors of ERK-substrate interactions involved in cell proliferation...
  88. ncbi Molecular modeling of two CYP2C19 SNPs and its implications for personalized drug design
    Jing Fang Wang
    Bioinformatic Center, Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Graduate School of the Chinese Academy of Sciences, Shanghai 200031, China
    Protein Pept Lett 15:27-32. 2008
    ....
  89. pmc Receptor guided 3D-QSAR: a useful approach for designing of IGF-1R inhibitors
    M Muddassar
    Future Fusion Technology Division, Computational Science Center, Korea Institute of Science and Technology, P O BOX 131, Cheongryang, Seoul 130 650, South Korea
    J Biomed Biotechnol 2008:837653. 2008
    ..In this paper, we report on our three-dimensional quantitative structure activity relationship (3D-QSAR) studies for this series of compounds...
  90. ncbi Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening
    Jui Hua Hsieh
    Laboratory for Molecular Modeling, Division of Medicinal Chemistry and Natural Products, University of North Carolina at Chapel Hill, CB 7360, Beard Hall, Chapel Hill, NC, 27599 7360, USA
    J Comput Aided Mol Des 22:593-609. 2008
    ..Our studies suggest that validated QSAR models could complement structure based docking and scoring approaches in identifying promising hits by virtual screening of molecular libraries...
  91. ncbi Improving binding mode predictions by docking into protein-specifically adapted potential fields
    Sebastian Radestock
    Department of Biology and Computer Science, J W Goethe University, Frankfurt, Germany
    J Med Chem 48:5466-79. 2005
    ..Implications of our findings for binding affinity predictions and its usage in virtual screening are further discussed...
  92. ncbi Structure-based virtual screening for low molecular weight chemical starting points for dipeptidyl peptidase IV inhibitors
    Richard A Ward
    Cancer Discovery, AstraZeneca, Alderley Park, Macclesfield, Cheshire, SK10 4TG, UK
    J Med Chem 48:6991-6. 2005
    ..These had activities ranging from 30% to 82% when tested at a concentration of 30 microM in an enzyme inhibition assay...
  93. ncbi Three-dimensional models of non-steroidal ligands: a comparative molecular field analysis
    Irwin R A Menezes
    Núcleo de Estudos em Química Medicinal NEQUIM, Departamento de Quimica, Universidade Federal de Minas Gerais, Av Pres Antônio Carlos 6627, 31270 901 Belo Horizonte MG, Brazil
    Steroids 71:417-28. 2006
    ..Since the structure of estrogen receptor is solved, the results of the present 3D QSAR models, given by the PLS maps based on molecular interaction fields (MIF) were compared to ligand-binding ER domains and showed good agreement...
  94. ncbi Molecular docking studies on 4-thiazolidinones as HIV-1 RT inhibitors
    Ravindra K Rawal
    Medicinal and Process Chemistry Division, Central Drug Research Institute, Lucknow, 226001, India
    J Mol Model 13:155-61. 2007
    ..The results of docking studies provide an insight into the pharmacophoric structural requirements for the HIV-1 RT inhibitory activity of this class of molecules...
  95. ncbi A critical assessment of docking programs and scoring functions
    Gregory L Warren
    GlaxoSmithKline Pharmaceuticals, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, USA
    J Med Chem 49:5912-31. 2006
    ..For prediction of compound affinity, none of the docking programs or scoring functions made a useful prediction of ligand binding affinity...
  96. ncbi Structural and chemical basis for enhanced affinity and potency for a large series of estrogen receptor ligands: 2D and 3D QSAR studies
    Livia de B Salum
    Laboratorio de Quimica Medicinal e Computacional, Centro de Biotecnologia Molecular Estrutural, Instituto de Fisica de Sao Carlos, Universidade de Sao Paulo, Av Trabalhador Sao Carlense 400, 13560 970 Sao Carlos, SP, Brazil
    J Mol Graph Model 26:434-42. 2007
    ..The final QSAR models as well as the information gathered from 3D contour maps should be useful for the design of novel ERalpha modulators having improved affinity and potency...
  97. ncbi Molecular complexity analysis of de novo designed ligands
    Krisztina Boda
    ICAMS, School of Chemistry, University of Leeds, LS2 9JT, UK
    J Med Chem 49:5869-79. 2006
    ....
  98. ncbi A method for induced-fit docking, scoring, and ranking of flexible ligands. Application to peptidic and pseudopeptidic beta-secretase (BACE 1) inhibitors
    Nicolas Moitessier
    Department of Chemistry, McGill University, 801 Sherbrooke Street W, Montreal, Quebec H3A 2K6, Canada
    J Med Chem 49:5885-94. 2006
    ..The significant enrichment at the top of the ranking list in active compounds demonstrated the ability of the docking and scoring protocol to rank the compounds relative to their activities...
  99. ncbi Pharmacophore modeling and in silico screening for new KDR kinase inhibitors
    Hui Yu
    Central Experimental Laboratory, the First People s Hospital, Shanghai Jiaotong University, Shanghai 200080, China
    Bioorg Med Chem Lett 17:2126-33. 2007
    ..One hit illustrated high binding affinity with KDR kinase measured by the surface plasmon resonance biosensor. Docking studies may help elucidate the mechanisms of KDR kinase receptor-ligand interactions...
  100. pmc CoMSIA and docking study of rhenium based estrogen receptor ligand analogs
    Peter Wolohan
    Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, Campus Box 8225, St Louis, MO 63110, USA
    Steroids 72:247-60. 2007
    ....
  101. ncbi An integrated in silico analysis of drug-binding to human serum albumin
    Ernesto Estrada
    Complex Systems Research Group, X rays Unit, Edificio CACTUS, Santiago de Compostela 15982, Spain
    J Chem Inf Model 46:2709-24. 2006
    ..A small number of fragments appear very frequently in most drugs. These molecular "empathic" fragments are good candidates for guiding future drug discovery research...

Research Grants17

  1. Inhibitors of the ENT4 Adenosine Transporter for Cardioprotection
    John K Buolamwini; Fiscal Year: 2010
    ..We will investigate structure-activity relationships (SARs) and test the cardioprotective properties of the compounds in an isolated rat heart ischemia model. ..
  2. Development of Therapeutic Inhibitors to Anthrax Toxins
    JOHNNY PETERSON; Fiscal Year: 2006
    ..inhibitors that block the Zn++-metalloprotease activity of LF, and we will use these data in 3D-Quantitative structure activity relationship (QSAR) computations to optimize the enzyme inhibitors...
  3. Discovery of Selective MT1 Melatonin Receptor Ligands for Sleep Disorders
    Margarita L Dubocovich; Fiscal Year: 2010
    ..a combination of in silico ligand-based discovery using phamacophores, virtual screening, and quantitative structure activity relationship and comparative molecular field analysis;2) Determine ligand affinity, agonist potency, and ..
  4. Novel Antirivals for Hantavirus Pulmonary Syndrome
    JEFFREY ARTERBURN; Fiscal Year: 2003
    ..and in vitro evaluation of resulting change in antiviral activity profile to develop a quantitative structure activity relationship model (QSAR), that will lead to the development of highly active analogs for therapy...
  5. DEVELOPMENT OF VESICULAR ACETYLCHOLINE TRANSPORTER IMAGING AGENTS FOR PET
    Zhude Tu; Fiscal Year: 2010
    ....
  6. Predictive QSAR Modeling of HIV-1 Integrase Inhibitors
    Rajni Garg; Fiscal Year: 2009
    ..The goal of this project is to understand the interactions between the HIV-1 integrase enzyme and its inhibitors that will help in the design of new drugs active against drug-resistant HIV-1. ..
  7. Anti-Cancer Drug Design Targeting Human Topoisomerase I
    Lance Stewart; Fiscal Year: 2002
    ..The most promising compounds will be examined for their efficacy in stopping human tumor growth in the mouse xenotransplant model. PROPOSED COMMERCIAL APPLICATION: Not available ..
  8. Structural Studies of AIDS-Responsive Drugs
    Vivian Cody; Fiscal Year: 2010
    ..These results will help guide the design of species selective inhibitors. Mutagenesis studies will be carried out to test these possibilitiesin the structure-based correlations to help design novel pjDHFRinhibitors. ..
  9. A Molecular Basis for Phytoestrogen Chemoprevention
    Andrew Mesecar; Fiscal Year: 2002
    ..aid in the design of new compounds that can serve as selective estrogen modulators (SERMs). ..
  10. QSAR STUDIES BY LIPOSOME ELECTROKINETIC CHROMATOGRAPHY
    Morteza Khaledi; Fiscal Year: 2003
    ..We will investigate the usefulness of computer assisted modeling and, simulation in developing rapid and effective methods for optimization of MECC and MLC separations. ..
  11. Discovery and Optimization of Novel Integrase Inhibitors as Anti-HIV Agents
    John K Buolamwini; Fiscal Year: 2010
    ..The PI has discovered potent integrase inhibitors. The objectives of the grant proposal are to optimize activity and test toxicity. ..
  12. Canthinones as Human Isozyme Selective PDE4 Inhibitors
    KEVIN CZERWINSKI; Fiscal Year: 2002
    ..necessary for optimum inhibitory activity against human isoforms and the development of a quantitative structure activity relationship to guide the development of new molecular targets has not been explored...
  13. Search for the Molecular Targets of Phenols
    CYNTHIA SELASSIE; Fiscal Year: 2006
    ..It is envisioned that the combined experimental-computational approach to phenol toxicity will provide guidance for the inclusion or exclusion of the OH group from new drug entities. [unreadable] [unreadable]..
  14. In Vitro Gene Expression Model Predicting Drug Induced Liver Disease
    Bruce E Seligmann; Fiscal Year: 2010
    ..In Phase II we will improve the model and extend it to other liver diseases, to a rat primary hepatocyte system, and to an in vivo biomarker system using circulating blood cells. ..
  15. FOCUSED PARALLEL SYNTHESIS OF DICATION ANTIFUNGAL AGENTS
    Richard Tidwell; Fiscal Year: 2003
    ..abstract_text> ..
  16. STRUCTURE SELECTIVITY RELATIONSHIPS OF ANTIBACTERIAL AGE
    CYNTHIA SELASSIE; Fiscal Year: 1992
    ..These enzyme inhibitors will also be evaluated in cellular systems (E. coli cultures sensitive and resistant to methotrexate)...
  17. AGMATINASE INHIBITORS FOR HYPOXIC-ISCHEMIC NEW BORN BRAIN DAMAGE
    John Piletz; Fiscal Year: 2007
    ..The overall goal of these studies is to develop a treatment for perinatal brain damage in human infants. [unreadable] [unreadable] [unreadable]..