Computational insights into molecular docking strategies for non-small cell lung cancer drug discovery
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Pharmacy, 2024.
| Huvudupphovsman: | |
|---|---|
| Övriga upphovsmän: | |
| Materialtyp: | Lärdomsprov |
| Språk: | English |
| Publicerad: |
Brac University
2024
|
| Ämnen: | |
| Länkar: | http://hdl.handle.net/10361/23926 |
| id |
10361-23926 |
|---|---|
| record_format |
dspace |
| spelling |
10361-239262024-09-03T10:14:03Z Computational insights into molecular docking strategies for non-small cell lung cancer drug discovery Das, Reshita Omer, Humair Bin MD School of Pharmacy, Brac University Molecular docking NSCLC 5GPG Structure-based drug design Lung cancer Pharmaceutical chemistry. Biomolecules--Structure. Drugs--Design. Lungs--Cancer. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Pharmacy, 2024. Cataloged from the PDF version of thesis. Includes bibliographical references (pages 36-41). This work addresses computational approaches to non-small cell lung cancer (NSCLC) drug discovery, highlighting the vital part that molecular docking plays in the early stages of drug discovery. It demonstrates the effectiveness of molecular docking and structure-based drug design (SBDD) in hit identification while navigating through conventional obstacles. With an emphasis on adenocarcinoma and squamous cell carcinoma, the research sheds light on the genetic complexity of NSCLC. Potential associations between NSCLC, diabetes, hypertension, and cholesterol levels are investigated. The binding affinities of several drug classes with the target protein are examined in a critical investigation that highlights non-covalent interactions such as salt bridges compared to Rapamycin (binding affinity = 19.4 kcal/mol). By providing opportunities for more potentially effective and tailored treatments for NSCLC and other diseases, the significance of the research is that it applies the field of computational drug design in the discovery of new, potential ligands against NSCLC. Reshita Das B. Pharmacy 2024-08-27T09:26:41Z 2024-08-27T09:26:41Z ©2024 2024-02 Thesis ID 20146043 http://hdl.handle.net/10361/23926 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 52 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Molecular docking NSCLC 5GPG Structure-based drug design Lung cancer Pharmaceutical chemistry. Biomolecules--Structure. Drugs--Design. Lungs--Cancer. |
| spellingShingle |
Molecular docking NSCLC 5GPG Structure-based drug design Lung cancer Pharmaceutical chemistry. Biomolecules--Structure. Drugs--Design. Lungs--Cancer. Das, Reshita Computational insights into molecular docking strategies for non-small cell lung cancer drug discovery |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Pharmacy, 2024. |
| author2 |
Omer, Humair Bin MD |
| author_facet |
Omer, Humair Bin MD Das, Reshita |
| format |
Thesis |
| author |
Das, Reshita |
| author_sort |
Das, Reshita |
| title |
Computational insights into molecular docking strategies for non-small cell lung cancer drug discovery |
| title_short |
Computational insights into molecular docking strategies for non-small cell lung cancer drug discovery |
| title_full |
Computational insights into molecular docking strategies for non-small cell lung cancer drug discovery |
| title_fullStr |
Computational insights into molecular docking strategies for non-small cell lung cancer drug discovery |
| title_full_unstemmed |
Computational insights into molecular docking strategies for non-small cell lung cancer drug discovery |
| title_sort |
computational insights into molecular docking strategies for non-small cell lung cancer drug discovery |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/23926 |
| work_keys_str_mv |
AT dasreshita computationalinsightsintomoleculardockingstrategiesfornonsmallcelllungcancerdrugdiscovery |
| _version_ |
1814307376732307456 |