Integrating QSAR models predicting acute contact toxicity and mode of action profiling in honey bees (A. mellifera): Data curation using open source databases, performance testing and validation

This excel file (DOI: https://doi.org/10.5281/zenodo.3755675) provides the collection of raw data used for developing the first integrative Quantitative Structure-Activity Relationship (QSAR) model using EFSA's OpenFoodTox, US-EPA ECOTOX and Pesticide Properties DataBase i) to predict acute contact toxicity (LD50) and ii) to profile the Mode of Action (MoA) of pesticides active substances in honey bees (Apis mellifera). Chemical identifiers (e.g. SMILES, CAS n., InChI) and acute contact toxicity data (LD50) on honey bees were used to develop and validate i) a two-category QSAR model (toxic/non-toxic; n=411) (sensitivity =0.93), specificity =0.85), balanced accuracy =0.90), Matthews correlation coefficient MCC=0.78), and ii) a regression-based model (n=113) (R2=0.74; MAE=0.52). Similarly, current study proposes the first MoA profiling for 113 pesticides active substances and the first harmonised MoA classification scheme for acute contact toxicity in honey bees, including LD50s data points from three different databases such as EFSA's OpenFoodTox, US-EPA ECOTOX and Pesticide Properties DataBase. Such classification allows to further define MoAs and the target site of Plant Protection Products (PPPs) active substances, thus enabling regulators and scientists to refine chemical grouping and toxicity extrapolations for single chemicals and component-based mixture risk assessment of multiple chemicals. The full data collection and analysis of QSAR models, toxicity data (LD50) and Mode of Action (Moa) data are described in Carnesecchi et al., 2020 (DOI: doi.org/10.1016/j.scitotenv.2020.139243). This work was supported by the European Food Safety Authority (EFSA) [contract number: OC/EFSA/SCER/2018/01 and NP/EFSA/AFSCO/2016/02 (Edoardo Carnesecchi)].本Excel文件（DOI：https://doi.org/10.5281/zenodo.3755675）收录了用于开发首个整合型定量构效关系（Quantitative Structure-Activity Relationship, QSAR）模型的原始数据集，该模型依托欧洲食品安全局（European Food Safety Authority, EFSA）的OpenFoodTox数据库、美国环境保护署ECOTOX数据库及农药性质数据库构建，可实现两大功能：一是预测农药活性物质对西方蜜蜂（Apis mellifera）的急性接触毒性（半数致死剂量LD50），二是解析其作用模式（Mode of Action, MoA）。研究中使用了化学标识符（如SMILES、CAS编号、InChI）以及蜜蜂急性接触毒性数据（LD50），分别开发并验证了两类模型：其一为二分类QSAR模型（有毒/无毒；样本量n=411），其灵敏度为0.93、特异度为0.85、平衡准确率为0.90、马修斯相关系数MCC为0.78；其二为基于回归的模型（样本量n=113），其决定系数R²=0.74、平均绝对误差MAE=0.52。本研究首次针对113种农药活性物质开展了作用模式解析，并首次提出了适用于蜜蜂急性接触毒性的标准化作用模式分类体系，该体系整合了EFSA OpenFoodTox、US-EPA ECOTOX及农药性质数据库三类不同来源的LD50数据。该分类体系可进一步明确植物保护产品（Plant Protection Products, PPPs）活性物质的作用模式及其作用靶点，有助于监管机构与科研人员优化单化学品的化学分组与毒性外推方法，同时可为基于组分的多化学品混合物风险评估提供支撑。本数据集的完整收集流程、QSAR模型构建、毒性数据（LD50）及作用模式（MoA）数据分析详情已发表于Carnesecchi等人2020年的研究（DOI：doi.org/10.1016/j.scitotenv.2020.139243）。本研究得到欧洲食品安全局（EFSA）资助，合同编号为OC/EFSA/SCER/2018/01及NP/EFSA/AFSCO/2016/02（Edoardo Carnesecchi）。