| Type of Material: | Thesis |
| 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: | Col Allam Appa Rao |
| Department: | Department of Computer Science and Engineering |
| Publisher: | Acharya Nagarjuna University, Guntur |
| Place: | Guntur |
| Year: | 2011 |
| Language: | English |
| Subject: | Computer Science | Computer Aided drug Design | Computer Science and Information Technology | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Department of Computer Science and Engineering, Acharya Nagarjuna University, Guntur, Guntur; 2011; Y9CSR061 |
| Fulltext: | Shodhganga |
| 000 | 00000ntm a2200000ua 4500 | |
| 001 | 454579 | |
| 003 | IN-AhILN | |
| 005 | 2024-09-17 15:40:10 | |
| 008 | __ | 240917t2011||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_454579 |
| 040 | __ | |aNGJN_522510|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aPatchikolla Satheesh|eResearcher |
| 110 | __ | |aDepartment of Computer Science and Engineering|bAcharya Nagarjuna University, Guntur|dGuntur|ein |
| 245 | __ | |aComputer aided drug design: an in silico analysis of structure prediction and ligand binding for glutathione S-transferase (GST) protein |
| 260 | __ | |aGuntur|bAcharya Nagarjuna University, Guntur|c2011 |
| 300 | __ | |a157p.|c-|dNone |
| 500 | __ | |aBibliography p.148-157 |
| 502 | __ | |cDepartment of Computer Science and Engineering, Acharya Nagarjuna University, Guntur, Guntur|d2011|oY9CSR061|bPhD |
| 518 | __ | |oDate of Award|dn.d. |
| 518 | __ | |oDate of Registration|dn.d. |
| 520 | __ | |aThe 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 pr |
| 650 | __ | |aComputer Science and Information Technology|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aComputer Science |
| 653 | __ | |aComputer Aided drug Design |
| 700 | __ | |eGuide|aCol Allam Appa Rao |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/8277|yShodhganga |
| 905 | __ | |afromsg |
User Feedback Comes Under This section.