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  1. Advancing Regulatory Science

Development of computational methods to inform public health decisions for newly emerging opioids

CERSI Collaborators: Jana Shen, PhD

FDA Collaborators: Lidiya Stavitskaya, PhD

Project Start: June 8, 2024

Regulatory Science Challenge

This project is expected to advance the development of a technology to directly measure drug substance crystal structure continuously during the manufacturing process (crystallization process) using an X-ray based online probe. This way, drug substance abnormalities can be found and corrected rapidly as the drug substances are made - enabling automated quality control resulting in greater efficiencies and reduced costs.

Project Description and Goals

The goal of the project is to develop a molecular dynamics-based procedure to predict the binding characteristics (described by kinetic parameters) of nitazenes at the mu (μ) opioid receptor [1,2,3]. To accomplish this goal, the first objective is to obtain accurate binding poses of the nitazenes in the mu-opioid receptor using docking tools, and the second objective is to calculate the unbinding rate constants of nitazenes using an accelerated molecular dynamics simulation technique known as meta dynamics. Investigators will validate their procedure by comparing these calculated values to previously described measurements, and if differences exist, parameters in the computational procedure will be adjusted until alignment is reached. The refined procedure will then be used to predict other nitazenes for which experimental measurements are unavailable and determine whether the currently available naloxone doses are sufficient to reverse drug overdose of all nitazene derivatives.

The goals of this project are to: (1) compare the accuracy of the new technology (an X-ray based online probe) to traditional x-ray equipment in tests of the quality of drug substances; and (2) optimize the performance of the new technology to yield the best possible accuracy in the most efficient way.

[1] Vo QN, Mahinthichaichan P, Shen J*, and Ellis CR*. How μ-opioid receptor recognizes fentanyl. Nat Commun 12: 984, 2021. 
[2] Mahinthichaichan P, Vo Q, Ellis CR, and Shen J*. Kinetics and Mechanism of Fentanyl Dissociation from the mu-Opioid Receptor. JACS Au 1: 2208–2215, 2021.
[3] Mahinthichaichan P, Liu R, Vo QN, Ellis CR, Stavitskaya L*, and Shen J*. Structure-Kinetics Relationships of Opioids from Molecular Dynamics Simulations and Machine Learning. J Chem Inf Model 63: 2196–2206, 2023.

Anticipated Outcomes/Impact

The researchers intend for this research to yield a useful computational tool which can be used to predict kinetic unbinding rate constants of nitazenes, a novel class of opioids. The comparison between the rate constants of novel nitazenes and naloxone (rescue agent) will help regulatory decision making by providing information regarding naloxone dosing for overdose reversal of nitazenes. This research will also lead to new scientific knowledge which will be reported to the FDA and published as peer-reviewed journal articles for public dissemination.

 

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