Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/8277
Title: Computer aided drug design: an in silico analysis of structure prediction and ligand binding for glutathione S-transferase (GST) protein
Researcher: Patchikolla Satheesh
Guide(s): Col Allam Appa Rao
Keywords: Computer Science
Upload Date: 23-Apr-2013
University: Acharya Nagarjuna University
Completed Date: 2011
Abstract: The prediction of protein in large databases is one of the major research objectives in structural and functional proteomics. This can significantly contribute to the elucidation of the functional diversity of homologous proteins. To achieve this, its amino acid sequence is compared with the sequences of structural database using computational techniques. This would be needed in order to design drugs for diseases which are being caused by proteins whose structure is unknown. Every protein has some sequences of patterns which will be matched using an algorithm and classified using sequences of those proteins. Experimental procedures for protein structure prediction are inherently fewer and are thus unable to annotate an irrelevant portion of proteins that are becoming available due to rapid advances in genome sequencing technology. This has led to the development of computational techniques that utilize these experimental data for protein prediction. It has been proven that the structure and function of a protein can be effectively predicted by computational approaches that compel advanced experimental assays. To detect protein residues, algorithms should take into account all the similarity relationships in a given random set of sequences, a process that is different from sequence finding . This approach is usually based on homologous proteins. The major objective of this work was to predict the structure to Glutathione S transferases based on the sequence similarities and design a drug by using computer aided drug designing (CADD). This will reduce the time spent in synthesizing compounds and further experimental procedures on these designed compounds would lead to effective compounds for cancer treatment. Because, polymorphisms in Glutathione-S- transferase genes (GST-M1, GST-T1 and GST-P1) are thought to increase susceptibility for prostate cancer among male smokers [42]. Polymorphisms of Genotypes GSTM1, GSTT1, and GSTP1 inGlutathione S-transferase have also been shown to increase susceptibility Pancreatic
Pagination: 157p.
URI: http://hdl.handle.net/10603/8277
Appears in Departments:Department of Computer Science & Engineering

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01_title.pdfAttached File47.27 kBAdobe PDFView/Open
02_declaration.pdf37.26 kBAdobe PDFView/Open
03_certificate.pdf149.46 kBAdobe PDFView/Open
04_acknowledgements.pdf43.64 kBAdobe PDFView/Open
05_abstract.pdf128.46 kBAdobe PDFView/Open
06_contents.pdf167.52 kBAdobe PDFView/Open
07_list of publications.pdf275.91 kBAdobe PDFView/Open
08_list of tables.pdf128.2 kBAdobe PDFView/Open
09_list of figures.pdf149.56 kBAdobe PDFView/Open
10_nomenclature.pdf128.43 kBAdobe PDFView/Open
11_chapter 1.pdf598.7 kBAdobe PDFView/Open
12_chapter 2.pdf288.56 kBAdobe PDFView/Open
13_chapter 3.pdf618.39 kBAdobe PDFView/Open
14_chapter 4.pdf1.88 MBAdobe PDFView/Open
15_chapter 5.pdf1.82 MBAdobe PDFView/Open
16_chapter 6.pdf211.21 kBAdobe PDFView/Open
17_bibliography.pdf241.13 kBAdobe PDFView/Open


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