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Computational Studies of Protein Systems as Prospective Drug Targets

He, Yiran
http://orcid.org/0000-0002-4933-9035
http://rave.ohiolink.edu/etdc/view?acc_num=osu1711722981373852

Abstract Details

2024, Doctor of Philosophy, Ohio State University, Chemistry.
Molecular docking and molecular dynamics simulations are two commonly used computational techniques for the in silico evaluation of receptor-ligand binding and characterization of biomacromolecules. This work presents two independent projects to elucidate the molecular interactions in different prospective protein targets and provide physical insights into structure-based drug design. The focus of the first part is the “interacts-with-Spt6” protein (IWS1), a eukaryotic transcription elongation factor present in the RNAP II polymerase (RNAP II) complexes. IWS1 is gaining increasing attention as recent works revealed its collaborative actions with many formerly identified transcription factors of known regulatory effects and its direct interaction with the catalytic alpha subunit of RNAP II (RPB1). However, having about 70% of residues in human IWS1 being intrinsically disordered, its structure and function are not fully understood. Motivated by the recently discovered connection between IWS1 and liposarcoma (LPS), a cancer that can grow and spread aggressively, we initiated the effort of finding drug molecules targeting IWS1 to suppress transcriptional activities in cancer cells. To begin with, we analyzed the supermolecular arrangement, the protein interactions within the structured core, and the potential interactions with chromatin in the intrinsically disordered region of hIWS1 based on various recent studies of the structures and biological functions of IWS1. We then identified a potential binding pocket on IWS1’s interface with Spt6 for a drug molecule to act as a competitive inhibitor that downregulates the transcriptional activity of RNAP II by diminishing the association of IWS1/Spt6. Next, we designed and performed a series of molecular docking calculations. Among the top-ranked compounds from the virtual screening of FDA-approved drugs, Ketotifen and Desloratadine were selected for experimental validation and were shown to reduce the association of IWS1/Spt6 in treated cells. To find the consensus among the top-ranked FDA-approved drugs and natural products, we developed a topology-based encoding method to discriminate and classify polycyclic chemical scaffolds by the arrangements and types of rings. Furthermore, to discover alternate scaffolds from the ZINC ligand database, we applied an efficient subgraph search method based on the ring topologies. Following the selection of scaffolds, we conducted the virtual screening of over 10,000 ligands with diverse chemical structures and similar topologies to Ketotifen and Desloratadine. The top candidates are ranked in Appendix A for future investigations. The second part of this work is centered on serine hydrolase, acetylcholinesterase (AChE). AChE has long been an intriguing protein target for electrostatics and mechanistic studies due to its unique charge distribution and surprisingly fast turnover rate. Being a potent nucleophile, the catalytic Ser203 in human AChE can be covalently modified by organophosphorus pesticides and nerve agents, leading to potentially lethal consequences. To decipher the conformational and electrostatic interactions between the nonnatural phosphoryl component and the active site residues, we designed a hierarchical approach consisting of parameter refinement, fast enumeration of residue protonation states, and advanced dynamics simulations with variable protonation states, including the constant pH MD simulations and alchemical free energy calculations with soft-core potentials.
Christopher Hadad (Advisor)
Rafael Bruschweiler (Committee Member)
Alexander Sokolov (Committee Member)
195 p.
Chemistry
computational chemistry; structure-based drug design; virtual screening; chemical graph theory; molecular dynamics; alchemical free energy calculation

Recommended Citations

Citations

  • He, Y. (2024). Computational Studies of Protein Systems as Prospective Drug Targets [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1711722981373852

    APA Style (7th edition)

  • He, Yiran. Computational Studies of Protein Systems as Prospective Drug Targets. 2024. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1711722981373852.

    MLA Style (8th edition)

  • He, Yiran. "Computational Studies of Protein Systems as Prospective Drug Targets." Doctoral dissertation, Ohio State University, 2024. http://rave.ohiolink.edu/etdc/view?acc_num=osu1711722981373852

    Chicago Manual of Style (17th edition)

osu1711722981373852
© 2024, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.