Characterizing the Mutational Landscape and Ligand Activity of Some Lysosomal Storage Disorders Using Computational Pipeline
| dc.contributor.guide | Magesh,R | |
| dc.coverage.spatial | Biotechnology Mutational analysis Molecular dynamics | |
| dc.creator.researcher | Priyanka K | |
| dc.date.accessioned | 2025-06-20T09:24:22Z | |
| dc.date.available | 2025-06-20T09:24:22Z | |
| dc.date.awarded | 2025 | |
| dc.date.completed | 2025 | |
| dc.date.registered | 2018 | |
| dc.description.abstract | Lysosomal storage disorders LSDs are a class of genetic diseases affected by inherited modifications in genetic material that leads to a cause in lysosomal function leading to the collection of undegraded macromolecules within lysosomes The specific clinical phenotypes of LSDs depend on the type of substrate accumulating within lysosomes In this work selected classification of LSDs are utilized like GM1 gangliosidosis GLB1 Niemann Pick disease type C NPC1 Pycnodysostosis CTSK Neuronal ceroid lipofuscinosis TPP1 Mucolipidosis type IV MCOLN1 mucopolysaccharidosis type IIIB NAGLU Niemann Pick disease type A SMPD1 to study the sequence and structural functions with respect to its mutant proteins In this study we retrieved a mutational dataset screening for the listed proteins from various databases ClinVar NCBI UniProt and HGMD An aggregate of 689 mutations in GLB1 263 mutations from NPC1 protein 44 mutations from CTSK 56 mutations from TPP1 23 mutations from MCOLN1 162 mutations from NAGLU and 177 mutations from SMPD1 with missense mutants were enumerated with computational methods to perceive the most significant mutants and correlated with clinical and literature data After which a structure based screening methods were carried out to understand protein ligand interaction via molecular docking analysis with respective drugs Miglustat Itraconazole Relacatib, Gemfibrozil MLSA1 NAG and Desipramine and the docking procedure was performed for the native and mutant structures with their respective drugs and showed better interaction profiling with the mutant protein structure Finally molecular dynamics simulation and free binding energy calculations were analyzed to understand the flexibility stability compactness hydrogen bond formation This study assists in comprehending the mutational significance and ligand activity and further experimental studies can validate the drug activity to improve the LSD conditions newline | |
| dc.description.note | Chapter 1 Introduction p.1-7 Chapter 2 Review of Literature p.8-33 Chapter 3 Aim and objectives p.34-35 Chapter 4 Methodology p.36-44 Chapter 5 Results p.45-77 Chapter 6 Discussion p.76-87 Chapter 7 Summary and Conclusion p.88-89 | |
| dc.format.accompanyingmaterial | None | |
| dc.format.dimensions | 15 cms | |
| dc.format.extent | 1-89 | |
| dc.identifier.researcherid | ||
| dc.identifier.uri | http://hdl.handle.net/10603/647616 | |
| dc.language | English | |
| dc.publisher.institution | College of Biomedical Sciences | |
| dc.publisher.place | Chennai | |
| dc.publisher.university | Sri Ramachandra Institute of Higher Education and Research | |
| dc.relation | ||
| dc.rights | self | |
| dc.source.university | University | |
| dc.subject.keyword | Genetics and Heredity | |
| dc.subject.keyword | Life Sciences | |
| dc.subject.keyword | Molecular Biology and Genetics | |
| dc.title | Characterizing the Mutational Landscape and Ligand Activity of Some Lysosomal Storage Disorders Using Computational Pipeline | |
| dc.title.alternative | ||
| dc.type.degree | Ph.D. |
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