Vapor Pressure and Toxicity Prediction for Novichok Agent Candidates Using Machine Learning Model: Preparation for Unascertained Nerve Agents after Chemical Weapons Convention Schedule 1 Update

Abstract

The recent terrorist attacks using Novichok agents and subsequent operations have necessitated an understanding of its physicochemical properties, such as vapor pressure and toxicity, as well as unascertained nerve agent structures. To prevent continued threats from new types of nerve agents, the organization for the prohibition of chemical weapons (OPCW) updated the chemical weapons convention (CWC) schedule 1 list. However, this information is vague and may encompass more than 10 000 possible chemical structures, which makes it almost impossible to synthesize and measure their properties and toxicity. To assist this effort, we successfully developed machine learning (ML) models to predict the vapor pressure to help with escape and removal operations. The model shows robust and high-accuracy performance with promising features for predicting vapor pressure when applied to Novichok materials and accurate predictions with reasonable errors. The ML classification model was successfully built for the swallow globally harmonized system class of organophosphorus compounds (OP) for toxicity predictions. The tuned ML model was used to predict the toxicity of Novichok agents, as described in the CWC list. Although its accuracy and linearity can be improved, this ML model is expected to be a firm basis for developing more accurate models for predicting the vapor pressure and toxicity of nerve agents in the future to help handle future terror attacks with unknown nerve agents.

Precisely predicting the 1H and 13C NMR chemical shifts in new types of nerve agents and building spectra database

“…The functional group was changed along 1–1, 2–1, 3–1, and 4–1 because of the suggested structure, which is denoted as 1A13 and 1A14 in the CWC list update (Supplementary Fig. S15 ) 24 , 25 . The naming strategy for the structures substituted with the alkyl groups is shown in Fig.…”

Theoretical prediction on the hydrolysis rate of the new types of nerve agents: A density functional study

“…These nerve agents are considered the most toxic substances amongst CWAs ever synthesized [17] , [18] , [19] . Although there is an updated CWC list on those materials [20] . [20] , very little reliable information on their physicochemical, electronic, or other properties [7] .…”

“…Although there is an updated CWC list on those materials [20] . [20] , very little reliable information on their physicochemical, electronic, or other properties [7] .…”

DFT–Spectroscopy Integrated Identification Method on Unknown Terrorist Chemical Mixtures by Incorporating Experimental and Theoretical GC-MS, NMR, IR, and DFT-NMR/IR Data

“…NMR/IR Measurement. 1 H NMR experiments were performed at 7 T by using a Bruker Avance III 300 MHz spectrometer. All NMR spectra were obtained at room temperature using 30°pulses.…”

“…During the past few decades, it has been difficult to achieve a comprehensive approach for the determination of unknown chemicals used in terrorist attacks because of the vast number of chemical libraries and the continuous synthesis of new compounds over time. − …”