Restricted Research - Award List, Note/Discussion Page
Fiscal Year: 2023
1542 The University of Texas at Arlington (143430)
Principal Investigator: Kwangho Nam,kwangho.nam@uta.edu,(817) 272-1091
Total Amount of Contract, Award, or Gift (Annual before 2011): $ 361,274
Exceeds $250,000 (Is it flagged?): Yes
Start and End Dates: 1/1/23 - 11/30/24
Restricted Research: YES
Academic Discipline: Department of Chemistry and Biochemistry
Department, Center, School, or Institute: none
Title of Contract, Award, or Gift: EnzyDock-based Multistate and Multiscale Tools for Covalent Drug Design
Name of Granting or Contracting Agency/Entity:
National Institutes of Health (NIH)
CFDA Link: HHS
93.859
Program Title:
NIH R21
CFDA Linked: Biomedical Research and Research Training
Note:
(SAM Category 1.1.1.) In recent years, FDA has approved a growing number of drugs that are covalently linked to target biological molecules. To expand the development of covalent inhibitors, technologies more specific to the discovery of covalent inhibitors are needed, as well as to address concerns about off-site reactivity and toxicity associated with covalent drugs. The particular focus of this proposal is to develop multiscale in silico covalent docking approaches by integrating robust quantum mechanical and molecular mechanical (QM/MM) potentials with the EnzyDock docking platform, thus enabling explicit modeling of multi-step chemical events and their energetic contributions during the search for docked poses. The lack of effective docking approaches to perform covalent bond formation in a manner consistent with inhibitor’s non-covalent binding mode as well as the reaction transition state and covalently bonded mode not only hampers the fundamental understanding of warhead-target reactivity, but also poses a technical barrier for advancing in silico docking strategies. Indeed, many existing docking programs offer the capacity to perform covalent docking but in an ad hoc fashion, and they have not considered the covalent docking from the design phase of the program development. With the goal to overcome this technical challenge, two specific aims are: Aim 1 is to develop a multiscale QM/MM/EnzyDock covalent docking method. In this development, EnzyDock will serve as the primary docking platform and robust semiempirical QM/MM potentials will be developed, calibrated for each specific warhead-target reaction type and combined with EnzyDock. In addition, we will develop and implement the generalized Born (GB) solvation model with the QM/MM potential framework to improve the energetics of QM/MM-docked poses. Aim 2 will apply the QM/MM/EnzyDock approach developed in Aim 1 to establish effective workflow for in silico screening of large covalent inhibitor databases. Specifically, two workflows will be explored: The first workflow is based on docking with a predefined covalent attachment site, which is employed in most covalent docking programs. The second workflow entails a dynamic approach to covalent docking, in which covalent attachment sites on the ligand are searched and determined on the fly using cheminformatics analysis and spatial proximity with target residues in the binding pocket. In this research, the study will be limited to the warheads that react only with cysteine residue, and more reaction types and warheads will be considered in the future research to construct a more comprehensive warhead-target reaction database. Thus, the two workflows will be tested and benchmarked against known structures and kinetic/thermodynamic data of drug-Cys covalent systems. It is the hope that the methods developed will make the in silico covalent inhibitor discovery more powerful and help understand warhead-target reactivity for use in warhead design and selection.
Discussion: No discussion notes