Protein and Water Modeling in Computer-Aided Drug Discovery

<p>The field of Computer-Aided Drug Design (CADD) is continuously evolving to improve protein modeling, a crucial step in the drug discovery process. However, limitations exist in how CADD accounts for the various configurations a protein can adopt due to different rotamer and protonation states of its residues. This thesis explores advancements in CADD to address this challenge, focusing on protein modeling and water interactions.</p> <p>In Chapter 1, I introduce the drug discovery process with a brief overview of its history, the purpose of FDA clinical trials, and the cost and time duration for bringing a drug to the market. I then introduce the workflow of Computer-Aided Drug Design and how it’s incorporated in drug projects in a pharmaceutical setting. I conclude the chapter by highlighting water modeling in biological systems as well as the importance of rotamer and protonation state assignment in protein modeling.</p> <p>In Chapter 2, I introduce our novel Rotamer and Protonation state Assignment (RAPA) tool. Unlike existing methods, RAPA analyzes local hydrogen bonding environments to identify a broader range of energetically favorable configurations, each with a unique protonation and rotamer assignment for every residue. This approach significantly improves the accuracy of protein modeling for CADD applications, potentially identifying a greater number of viable candidate drug molecules. The chapter further discusses the validation of RAPA's findings through simulations and emphasizes that each configuration remains energetically consistent with the experimental structure.</p> <p>In Chapter 3, I give an overview of water modeling and structural and thermodynamic mapping by the SSTMap tool. I then explain the HSA program in SSTMap, and I introduce the water orientational code which I have written to analyze the most probable water orientations in high density water clusters.</p> <p>In Chapter 4, I discuss the contributions we made towards making publicly available solvation thermodynamic and structural maps of SARS-CoV-2 targets. This work was intended to aid as a resource to the academic and industrial drug design community in their pursuit of identifying small molecule treatments for COVID-19.</p>

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Chemistry

Grantor

The Graduate School and University Center of The City University of New York

Year dc:date.available

2024

Author dc:creator

• Ghattas, Mossa

Advisor dc:contributor.advisor

• Thomas Kurtzman

Committee members dc:contributor.committeemember

• Ranajeet Ghose
• Amedee des Georges
• Daniel McKay

• Computational Chemistry
• Medicinal-Pharmaceutical Chemistry

Repository record dc:identifier

https://academicworks.cuny.edu/gc_etds/5977

OAI identifier oai:identifier

oai:academicworks.cuny.edu:gc_etds-7097