Dataset Information

Prediction of chemical warfare agents based on cholinergic array type meta-predictors.

ABSTRACT: Molecular insights into chemical safety are very important for sustainable development as well as risk assessment. This study considers how to manage future upcoming harmful agents, especially potentially cholinergic chemical warfare agents (CWAs). For this purpose, the structures of known cholinergic agents were encoded by molecular descriptors. And then each drug target interaction (DTI) was learned from the encoded structures and their cholinergic activities to build DTI classification models for five cholinergic targets with reliable statistical validation (ensemble-AUC: up to 0.790, MCC: up to 0.991, accuracy: up to 0.995). The collected classifiers were transformed into 2D or 3D array type meta-predictors for multi-task: (1) cholinergic prediction and (2) CWA detection. The detection ability of the array classifiers was verified under the imbalanced dataset between CWAs and none CWAs (area under the precision-recall curve: up to 0.997, MCC: up to 0.638, F1-score of none CWAs: up to 0.991, F1-score of CWAs: up to 0.585).

SUBMITTER: Kumar S

PROVIDER: S-EPMC9537167 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Prediction of chemical warfare agents based on cholinergic array type meta-predictors.

Kumar Surendra S Kumari Chandni C Ahn Sangjin S Kim Hyoungrae H Kim Mi-Hyun MH

Scientific reports 20221006 1

Molecular insights into chemical safety are very important for sustainable development as well as risk assessment. This study considers how to manage future upcoming harmful agents, especially potentially cholinergic chemical warfare agents (CWAs). For this purpose, the structures of known cholinergic agents were encoded by molecular descriptors. And then each drug target interaction (DTI) was learned from the encoded structures and their cholinergic activities to build DTI classification models ...[more]

PMID: 36203081

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Project description:The organophosphorus chemical warfare agents were initially synthesized in the 1930's and are some of the most toxic compounds ever discovered. The standard means of decontamination are either harsh chemical hydrolysis or high temperature incineration. Given the continued use of chemical warfare agents there are ongoing efforts to develop gentle environmentally friendly means of decontamination and medical counter measures to chemical warfare agent intoxication. Enzymatic decontamination offers the benefits of extreme specificity and mild conditions, allowing their use for both environmental and medical applications. The most promising enzyme for decontamination of the organophosphorus chemical warfare agents is the enzyme phosphotriesterase from Pseudomonas diminuta. However, the catalytic activity of the wild-type enzyme with the chemical warfare agents falls far below that seen with its best substrates, and its stereochemical preference is for the less toxic enantiomer of the chiral phosphorus center found in most chemical warfare agents. Rational design efforts have succeeded in the dramatic improvement of the stereochemical preference of PTE for the more toxic enantiomers. Directed evolution experiments, including site-saturation mutagenesis, targeted error-prone PCR, computational design, and quantitative library analysis, have systematically improved the catalytic activity against the chemical warfare nerve agents. These efforts have resulted in greater than 4-orders of magnitude improvement in catalytic activity and have led to the identification of variants that are highly effective at detoxifying both G-type and V-type nerve agents. The best of these variants have the ability to prevent intoxication when delivered as a post-exposure treatment for VX and as a pre-exposure treatment for G-agent intoxication with observed protective factors up to 60-fold. Combining the best variant, H257Y/L303T, with a PCB polymer coating has enabled the development of a long lasting circulating prophylactic treatment that is highly effective against sarin.

Dataset Information

Prediction of chemical warfare agents based on cholinergic array type meta-predictors.

Publications

Prediction of chemical warfare agents based on cholinergic array type meta-predictors.

Similar Datasets

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