Abstract

There is a growing need for medications to fight deep-rooted and new diseases because of their socioeconomic consequences, as evidenced by the COVID-19 epidemic which slowed down the economy and affected the social life of mankind globally. This work is a step among many other steps undertaken by research around the world in order to achieve this objective. Asthma is one of the diseases that causes the death of thousands of lives every year. This work aims at the development of novel anti-inflammatory asthma drugs where the quantum chemical descriptors of eleven anti-inflammatory asthma drugs including Ambroxol, Amoxicillin, Budesonide, Fluticasone, Formoterol, Glycopyrrolate, Guaifenesin, Montelukast, Salbutamol, Silymarin, and Theophylline, were computed using B3LYP/6-311G++(d,p) level of theory implementing the geometry optimization. The physicochemical descriptors of these drugs were computed for evaluation against ADME and were found to satisfy bioavailability rules. The anti-inflammatory biological activity of the drugs was measured on RAW246.7 cell lines which was used with both descriptors for the establishment of the QSAR regression model. Molecular docking simulation of the binding between the eleven drugs and human serum albumin (1AO6). The drug with the highest biding energy (-6.05 kcal/mol) was Fluticasone, the drug with the highest inhibition constant was Montelukast (1.1μM) and Theophylline had the highest ligand efficiency of 29%. The model predicted a correlation between the anti-inflammatory biological activity with dipole moment, chemical hardness, hydrogen bond acceptors, number of rotatable bonds, hydration energy, electrophilicity, polar surface area, LogD7.4, and polarizability. Based on the model, substitutions (change in structure) would lead to a change in the predicted biological activity and molecular docking results. 9-substitutions were proposed on Theophylline’s position number 8 where nitroso and bromo substituted Theophylline had promising results based on the proposed model.

School

School of Sciences and Engineering

Department

Chemistry Department

Degree Name

MS in Chemistry

Graduation Date

Spring 6-21-2023

Submission Date

5-21-2023

First Advisor

Dr. Hassan Mohamed El-Said Azzazy

Second Advisor

Dr. Mohamed Elsayed Elshakre

Committee Member 1

Dr. Ismail Awadallah Salama

Committee Member 2

Dr. Eslam Mohamed Dabbish

Extent

167 p.

Document Type

Master's Thesis

Institutional Review Board (IRB) Approval

Approval has been obtained for this item

Available for download on Tuesday, May 20, 2025

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