Date of Publication
7-2022
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Premed Physics
Subject Categories
Physics
College
College of Science
Department/Unit
Physics
Honor/Award
Outstanding Thesis Award
Thesis Advisor
Romeric F. Pobre
Defense Panel Chair
Glenn G. Oyong
Defense Panel Member
Michelle T. Natividad
Belinda Dancel-San Juan
Abstract/Summary
We performed an in-silico approach in determining which aptamers would exhibit the strongest binding affinity to cortisol and compared it to the reference receptor Glucocorticoid receptor by analyzing the intermolecular forces (e.g. electrostatic forces and Van der Waals forces) of both enthalpic and entropic hydrophilicity using mFold, RNAComposer, Autodock Tools, Autodock Vina, PyMOL and Discovery Studio Visualizer application software programs. Since the molecules (i.e. ligand and receptor molecule) are nucleic acids and steroid hormone, respectively, molecular dynamics simulation for these types of molecules were prohibitive in terms of computer resources (e.g. memory size and processor speed) and computer access that requires a high performance computer grade facility. The aptamers were observed to fold into stacked pairs, interior loops, and external loops, among other structural components. Molecular docking analysis revealed that the Glucocorticoid Receptor (PDBID 6NWK) has a binding energy of -11.3 kcal/mol and Aptamer 8 had the strongest binding affinity to cortisol (-9.3 kcal/mol). Discovery Studio Visualizer identified that the hydrogen bonding interaction dominated among other interactions between Aptamer 8 and Cortisol, which is an important factor in establishing stability in the complex structure of both molecules. As Aptamer 8 exhibited the strongest binding affinity, it may be considered an alternative receptor for a Glucocorticoid receptor for cortisol detection in designing new sensors for medical instrumentation applications.
Keywords: In-silico, Analysis, Aptamers, Cortisol, Glucocorticoid, Receptor, Nucleic Acids, Hormone, Intermolecular Forces, Molecular Docking
Abstract Format
html
Language
English
Format
Electronic
Physical Description
xiii, 111 leaves
Keywords
Hydrocortisone; Glucocorticoids—Receptors
Recommended Citation
Inoncillo, M. C., Manuel, E. P., & Redoble, B. S. (2022). In silico analysis of aptamer for cortisol detection on biosensing applications. Retrieved from https://animorepository.dlsu.edu.ph/etdb_physics/19
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Embargo Period
7-18-2022
