Treatment of individuals who have been exposed to a nerve agent in the form of a gas (e.g. VX, GB or sarin) involves the use of an injection of DuoDote, which contains Atropine, and an acetylcholinesterase (AChE) reactivator, such as 2-PAM (Pralidoxime). Due to the charged nature of the reactivator (2-PAM), traversing the BBB in order to restore AChE activity is minimally successful, its success is dependent upon large and often times multiple doses that must be administered.
Development of neutral oximes has been a focus of nerve agent toxicity antidotes in recent years. Due to their inherent neutrality, the newly developed oximes possess superior BBB penetrating abilities compared to standard marketed AChE reactivators. Enhanced BBB permeability results in faster restoration of AChE activity leading to heightened and lasting brain function protection.
Currently, the state-of-the-art treatment of individuals affected by nerve agent poisoning involves the use of charged oximes such as 2-PAM and HI-6, but these, as effective as they are, do not readily cross the BBB.
LLNL’s Forensic Science Center (FSC) is currently the only facility in the United States that is accredited to accept samples and analyze them for the possible presence of chemical weapons under the Chemical Weapons Convention. FSC scientists are global experts in chemical, nuclear, and biological counterterrorism and their work leads to innovative tools and therapies with biosecurity and public health applications. Working with LLNL computational biologists, and utilizing LLNL’s supercomputing infrastructure, FSC chemists recently identified a class of novel, neutral, cyclic oximes with increased blood brain barrier permeability serving as optimal antidotes against nerve agent poisoning. Cyclic oximes from this class show drastically increased permeability over HI-6 for the reactivation of acetylcholinesterase.
Membrane permeability is a key property to consider in drug design, especially when the drugs in question need to cross the BBB. A comprehensive in vivo assessment of the BBB permeability of a drug takes considerable time and financial resources. A current, simplified in vitro model to investigate drug permeability is a Parallel Artificial Membrane Permeability Assay (PAMPA) that generally provides higher throughput and initial quantification of a drug’s passive permeability. Computational methods can also be used to predict drug permeability. These methods are highly advantageous as they do not require the synthesis of the desired drug, and can be implemented rapidly using high-performance computing.
LLNL scientists used umbrella sampling Molecular Dynamics (MD) methods to assess the passive permeability of a range of compounds through a lipid bilayer. Furthermore, the permeability of these compounds was comprehensively quantified using the PAMPA assay to calibrate and validate the MD methodology. After demonstrating a firm correlation between the two approaches, the scientists then implemented MD methods to quantitatively predict the most permeable potential drug from a series of potential scaffolds. This permeability was then confirmed by the in vitro PAMPA methodology.
Refer to list of publications below for additional technical information
A Method to Predict Blood-Brain Barrier Permeability of Drug-Like Compounds Using Molecular Dynamics Simulations
A New Model for Pharmaceutical – Supercomputing-based modeling may help validate and accelerate drug research
A Wrench in the Works of Human Acetylcholinesterase: Soman Induced Conformational Changes Revealed by Molecular Dynamics Simulations
Large-Scale First-Principles Molecular Dynamics Simulations with Electrostatic Embedding: Application to Acetylcholinesterase Catalysis
Oximes have been historically used as reactivator molecules to restore acetylcholinesterase (AChE) activity in individuals (e.g. Armed forces or civilians targeted with nerve gas attacks) that have been exposed to nerve agents. Select oximes may have therapeutic potential as nicotine agonists, as well as environmental remediation applications.