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Shape Analysis in Bioinformatics

By Emma Marie Petty


In this thesis we explore two main themes, both of which involve proteins. The first area of research focuses on the analyses of proteins displayed as spots on 2-dimensional\ud planes. The second area of research focuses on a specific protein and how interactions with this protein can naturally prevent or, in the presence of a pesticide, cause toxicity.\ud \ud The first area of research builds on previously developed EM methodology to infer the matching and transformation necessary to superimpose two partially labelled point configurations, focusing on the application to 2D protein images. We modify the methodology to account for the possibility of missing and misallocated markers, where\ud markers make up the labelled proteins manually located across images. We provide a way to account for the likelihood of an increased edge variance within protein images. We find that slight marker misallocations do not greatly influence the final output superimposition\ud when considering data simulated to mimic the given dataset. The methodology is also successfully used to automatically locate and remove a grossly misallocated marker within the given dataset before further analyses is carried out.\ud \ud We develop a method to create a union of replicate images, which can then be used alone in further analyses to reduce computational expense. We describe how the data can be modelled to enable the inference on the quality of a dataset, a property often overlooked in protein image analysis. To complete this line of research we provide a\ud method to rank points that are likely to be present in one group of images but absent in a second group. The produced score is used to highlight the proteins that are not present\ud in both image sets representing control or diseased tissue, therefore providing biological indicators which are vitally important to improve the accuracy of diagnosis.\ud \ud In the second area of research, we test the hypothesis that pesticide toxicity is related to the shape similarity between the pesticide molecule itself and the natural ligand of the protein to which a pesticide will bind (and ultimately cause toxicity). A ligand of aprotein is simply a small molecule that will bind to that protein. It seems intuitive that the similarities between a naturally formed ligand and a synthetically developed ligand (the pesticide) may be an indicator of how well a pesticide and the protein bind, as well as provide an indicator of pesticide toxicity. A graphical matching algorithm is used to infer the atomic matches across ligands, with Procrustes methodology providing the final superimposition before a measure of shape similarity is defined considering the\ud aligned molecules. We find evidence that the measure of shape similarity does provide a significant indicator of the associated pesticide toxicity, as well as providing a more significant indicator than previously found biological indicators.\ud \ud Previous research has found that the properties of a molecule in its bioactive form are more suitable indicators of an associated activity. Here, these findings dictate that\ud the docked conformation of a pesticide within the protein will provide more accurate indicators of the associated toxicity. So next we use a docking program to predict the\ud docked conformation of a pesticide. We provide a technique to calculate the similarity between the docks of both the pesticide and the natural ligand. A similar technique is\ud used to provide a measure for the closeness of fit between a pesticide and the protein. Both measures are then considered as independent variables for the prediction of toxicity. In this case the results show potential for the calculated variables to be useful toxicity predictors, though further analysis is necessary to properly explore their significance

Publisher: Statistics (Leeds)
Year: 2009
OAI identifier:

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  1. (1987). [Prediction of LD50 values by cell culture],
  2. (2004). 3D-Quantitative Structure-Activity Relationship study of organophosphate compounds, doi
  3. (1997). A comparitive QSAR analysis of acetylcholinesterase inhibitors currently studied for the treatment of Alzheimer´ s disease, doi
  4. (1992). A method for registration of 3-D shapes, doi
  5. (2003). A new point matching algorithm for non-rigid registration, doi
  6. (2003). A novel approach to spot detection for two-dimensionalgel electrophoresisimagesusing pixel value collection, doi
  7. (2000). A novel method of aligning molecules by local surface shape similarity,
  8. (1998). A review of image warping methods, doi
  9. (2007). A semiempirical free energy force field with charge-based desolvation, doi
  10. (2003). A.and Fujiyama, Point matching under nonuniform distortions, doi
  11. (2006). Adaptive contrast enhancement of two-dimensional electrophoretic protein gel images facilitates visualization, orientation and alignment, doi
  12. (1973). Algorithm457: Findingall cliques of an undirected graph, doi
  13. (2004). Alignment of three-dimensional molecules using an image recognition algorithm, doi
  14. (2003). Analysing twodimensional gel images. technical report,
  15. (2005). and description, doi
  16. (1958). Application of a theory of enzyme specificity to protein synthesis, doi
  17. (2001). Auomatic registration for images of two-dimensional protein gels, doi
  18. (1998). Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function, doi
  19. (2003). Automatic construction of statistical shape models for protein spot analysis in electrophoresis gels, doi
  20. (2006). Bayesian alignment using hierarchical models, with applications in protein bioinformatics, doi
  21. (2007). Bayesian analysis of human movement curves, doi
  22. (2003). Brooks III, Comparative study of several algorithms for flexible ligand docking, doi
  23. (1996). Comparing two-dimensional electrophoretic gel images across the internet, From genome to proteome: 2nd Sienna 2D electrophoresis meeting, doi
  24. (2003). Computational approaches to similarity searching in a functional site database for protein function prediction,
  25. (2002). Concepts in biochemistry,
  26. (2004). Current two-dimensional electrophoresis technology for proteomics, doi
  27. (2004). Development and testing of a general AMBER force field, doi
  28. (1997). DIfference Gel Electrophoresis: A single gel method for detecting changes in protein extracts, doi
  29. (2004). Efficient method for high-throughput virtual screening based on flexible docking: Discovery of novel acetylcholinesterase inhibitors, doi
  30. Einfluss der configuration auf die wirkung der enzyme, doi
  31. (2004). Elasticregistrationofelectrophoresisimagesusing intensity information and point landmarks, doi
  32. (1998). Explicit calculation of 3D molecular similarity, doi
  33. (1999). Exploratory data analysis groupware for qualitative and quantitative electrophoretic gel analysis over the internet-Webgel, doi
  34. (2007). FROG: a FRee Online druG 3D conformation generator, doi
  35. (1981). GELLAB: a computer system for 2D gel electrophoresis analysis. doi
  36. (1981). GELLAB: a computer system for 2D gel electrophoresis analysis. I. Segmentation of spots and system preliminaries, doi
  37. (1981). GELLAB: a computer system for 2D gel electrophoresis analysis. III. Multiple two-dimensional gel analysis, doi
  38. (1988). GESA - a two-dimensional processing system using knowledge base techniques, doi
  39. (1998). Graph matching with a dual-step EM algorithm, doi
  40. (2002). H.Wolfson,andR.Nussinov,Principlesofdocking: Anoverview of search algorithms and a guide to scoring functions, doi
  41. (1986). HERMeS: A second generation approach to the automatic analysis of two-dimensional electrophoresis gels. Part I: Data acquisition, doi
  42. (1986). HERMeS: A second generation approach to the automatic analysis of two-dimensional electrophoresis gels. Part II: Spot detection and integration, doi
  43. (1987). HERMeS: A second generation approach to the automatic analysis of two-dimensional electrophoresis gels. Part V: Data analysis, doi
  44. (1987). HERMeS:A secondgenerationapproachto theautomatic analysis of two-dimensional electrophoresis gels. Part III: Spot list matching, doi
  45. (1987). HERMeS:A secondgenerationapproachto theautomatic analysis of two-dimensional electrophoresis gels. Part IV: Data base organization and management, doi
  46. (1999). Highly resistance regression and object matching, doi
  47. (1993). Inhibition of hen brain acetylcholinesterase and neurotoxic esterase by chlorpyrifos in vivo and kinetics of inhibition of chlorpyrifos oxon in vitro: Application to assessment of neuropathic risk, doi
  48. (2008). Interface to lp solve v. 5.5 to solve linear/integer programs,
  49. (2001). Mass spectrometric imaging of immobilized pH gradient gels and creation of ‘virtual’ two-dimensional gels, doi
  50. (2004). Matching problems for unlabelled configurations,
  51. (2003). Matching unlabelled configurationsusing theEM algorithm,
  52. (1990). Mechanism of action of organophosphorus and carbamate insecticides, doi
  53. (1997). Melanie II - a third-generation software package for analysis of two-dimensional electrophoresis images: doi
  54. (1997). Melanie II - a third-generation software package for analysis of two-dimensional electrophoresis images: I. Features and user interface, doi
  55. model of the acetylcholinesterase catalytic cavity probed by stereospecific organophosphorous inhibitors, doi
  56. (1993). Molecular and cellular biology of cholinesterases, doi
  57. (2006). Molecular markers of prostate cancer, doi
  58. (1999). New algorithmic approaches to protein spot detection and pattern matching in two-dimensional electrophoresis gel databases, doi
  59. (1997). Osta, Computer analysisof two-dimensionalelectrophoresisgels: A newsegmentationand modeling algorithm, doi
  60. (2009). Pdquest 2-d analysis software,
  61. (2005). Pesticide toxicology and international regulation (current toxicology series), doi
  62. (2001). Prediction of organophosphorus acetylcholinesterase inhibition using three-dimensional Quantitative StructureActivity Relationship (3D-QSAR) methods, doi
  63. (2001). Prediction of potential toxicity and side effect protein targets of a small molecule by a ligand-protein inverse docking approach, doi
  64. (1998). Principles and applications of stereochemistry, doi
  65. (2006). Protein image alignment via piecewise affine transformations, doi
  66. (1975). Protein mapping by combined isoelectric focusing and electrophoresis of mouse tissues. A novel approach to testing for induced point mutations in mammals,
  67. (2006). Protein-ligand docking: Current status and future challenges, doi
  68. (1997). Proteome research: New frontiers in functional genomics, doi
  69. (2000). Proteomics: new perspectives, new biomedical opportunities, doi
  70. (2002). Quantitative comparison and evaluation of two commercially available, two-dimensional electrophoresis image analysis software packages, doi
  71. (2002). Quantitative evaluation of proteins in oneand two-dimensional polyacrylamide gels using a fluorescent stain, doi
  72. (2007). Quantitative Structure-Activity Relationships (QSAR) for pesticide regulatory purposes, Elsevier, doi
  73. (2005). Real spherical harmonic expansion coefficients as 3D shape descriptors for protein binding pocket and ligand comparisons, doi
  74. (2006). Receptor-based computational screening of compound databases: The main docking-scoring engines, doi
  75. (1999). Robust, non-parametric and automatic methods for matching spatial point patterns,
  76. (2002). Shape matching and object recognition using shape contexts, doi
  77. (2005). Software-induced variance in two-dimensional gel electrophoresis image analysis, doi
  78. (2007). Statistical analysis of unlabeled point sets: comparing molecules in chemoinformatics, doi
  79. (1998). Statistical shape analysis, doi
  80. (2003). Stereoselective inactivation of torpedo californica acetylcholinesterase by isomalathion: InhibitoryBIBLIOGRAPHY 173 reactions with (1R)- and (1S)-isomers proceed by different mechanisms, doi
  81. (1997). Structure of acetylcholinesterase complexed with the nootropic alkaloid, doi
  82. (1992). Superimposing two-dimensional gels to study genetic variation in malaria parasites, doi
  83. (2005). The Amber biomolecular simulation programs, doi
  84. (2003). The role of bioinformatics in twodimensional gel electrophoresis, doi
  85. (1981). The TYCHO system for computer analysis of two-dimensional gel electrophoresis patterns,
  86. (2008). Understanding bioinformatics, Garland Science, doi
  87. (2002). α-methylacyl coenzyme a racemase as a tissue biomarker for prostate cancer, doi

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