Toxicology in the 21st Century Program (Tox21) - Computational Toxicology

Tox 21计划的联邦合作伙伴包括环境保护局（EPA）、食品药品监督管理局（FDA）和NIH，并由NCATS和国家环境健康科学研究所（NIEHS）的国家毒理学计划（NTP）领导。这些机构共同努力推进体外毒理学测试。Tox 21计划可以分为三个NCATS团队：系统毒理学，基因组毒理学和计算毒理学。Tox 21计算毒理学团队增强了Tox 21合作伙伴访问彼此数据时经常使用的各种工具。该团队对由Tox 21系统毒理学团队鉴定、开发、优化和/或筛选的15种检测方法以及Tox 21基因组毒理学团队生成的基因表达数据进行了数据分析。这些活动包括标准化和校正、拟合浓度-响应曲线以生成效价和疗效指标、基于一组标准（包括拟合显著性）对曲线进行分类（通过p值测量）、拟合的完整性和功效，通过数据再现性评价测定性能，数据驱动选择用于后续研究的化合物，以及识别涉及细胞对化学暴露的反应的基因和途径。此外，Tox 21计算毒理学团队更新了基于网络的自动化结构-活性关系（SAR）分析工具，以便系统毒理学团队对所有10 K库屏幕进行SAR分析。Tox 21计算毒理学团队还更新了Tox 21测定跟踪系统，该系统存储了所有Tox 21测定的测定注释和详细的实验条件和筛选方案。截至2019财年筛选的所有检测的10 K数据已在PubChem中公开，共计223个检测条目（AID）和超过9900万个数据点。 Tox 21公共数据浏览器已更新了来自10 K文库筛选的最新测定结果，共计72个测定。该浏览器为公众提供Tox 21 qHTS数据的可视化，包括浓度-响应曲线、曲线拟合结果和不同的活性指标沿着化学结构和分析QC结果。数据可通过分析和/或化学品进行检索。多个检测和/或化学品的结果可以重叠，以便于比较。所有数据以及分析描述和详细的筛选方案（SLP）可供下载。Tox 21计算毒理学团队继续与Tox 21化学工作组合作，更新Tox 21 10 K库化学QC结果，包括4个月化合物稳定性试验结果。所有QC结果均已在公共Tox 21浏览器（https：//tripod.nih.gov/tox21/）中发布，并更新了浏览器，链接至EPA CompTox化学品仪表板。在2020财年，Tox 21计算毒理学团队一直在与其他NCATS团队合作，更新NCATS药物收藏（NPC），这是Tox 21 10 K化合物库的一部分，近年来批准的药物包括所有批准药物的最新列表。此外，这些团队一直在努力构建一系列经过临床测试的化合物，以补充2020财年的NPC。Tox 21计算毒理学团队还领导了Tox 21跨合作伙伴项目之一，即通过Tox 21高通量筛选试验扩大途径覆盖范围，以更好地预测药物不良反应，该项目利用NCATS BioPlanet（https：//tripod.nih.gov/bioplanet/）作为定义生物空间和确定筛选试验的工具。该项目产生的数据将用于建立计算模型，以预测肝脏和心脏毒性。此外，Tox 21计算毒理学团队继续与Tox 21基因组毒理学团队合作，完善浓度响应基因表达数据分析方法，包括出发点（PoD）确定策略，以及毒物和调节剂的组合筛选数据分析（ToxMatrix）。已经开发了一个用于浓度反应基因表达数据可视化和分析的网络版软件平台，并将在适当时候公布。 在2020财年，Tox 21计算毒理学团队一直与TDB生物和化学团队合作开发基于生物活性的建模（BABM）方法，该方法已成功验证并应用于识别可开发为潜在抗COVID-19药物先导的新型抗SARS-CoV-2化合物。描述BABM方法的文章已于2020财年在Nature Biotechnology上发表。此外，Tox 21计算毒理学团队与Tox 21系统毒理学团队以及ETB和TDB生物学团队合作，评估现有的抗SARS-CoV-2 HTS检测方法，并通过数据驱动方法确定潜在的新抗SARS-CoV-2靶标和途径。这些合作努力促成了2020财年分别在《今日药物发现》和《科学报告》上发表的两篇论文。

The Tox21 Programs federal partners include the Environmental Protection Agency (EPA), the Food and Drug Administration (FDA) and NIH, with leadership from NCATS and the National Toxicology Program (NTP) at the National Institute of Environmental Health Sciences (NIEHS). These agencies work together to advance in vitro toxicological testing. The Tox21 Program can be separated into three NCATS teams: Systems Toxicology, Genomic Toxicology, and Computational Toxicology. The Tox21 Computational Toxicology team has enhanced a variety of tools that are routinely used by Tox21 partners to access each others data. The team performed data analysis of 15 assays that were identified, developed, optimized, and/or screened by the Tox21 systems toxicology team and gene expression data generated by the Tox21 Genomic Toxicology team. These activities include normalization and correction, fitting of concentration-response curves to generate potency and efficacy measures, classification of curves based on a set of criteria that included significance of fit (measured by p-values), completeness of fit, and efficacy, evaluation of assay performance by data reproducibility, data driven selection of compounds for follow up studies, and identification of genes and pathways involved in cell responses to chemical exposure. In addition, the Tox21 Computational Toxicology team has updated the web-based, automated structure-activity relationship (SAR) analysis tool for the systems toxicology team to conduct SAR analysis on all 10K library screens. The Tox21 Computational Toxicology team has also updated the Tox21 Assay Tracking System that stores the assay annotations and detailed experimental conditions and screening protocols for all the Tox21 assays. The 10K data from all assays screened up to FY19 have been made public in PubChem totaling 223 assay entries (AIDs) and over 99 million data points. The Tox21 public data browser has been updated with the latest assay results from the 10K library screens totaling 72 assays. This browser provides the public with visualization of Tox21 qHTS data including concentration-response curves, curve fitting results and different activity metrics along with chemical structure and analytical QC results. Data are searchable by assay and/or chemical. Results from multiple assays and/or chemicals can be overlaid for ease of comparison. All data as well as assay descriptions and detailed screening protocols (SLPs) are available for download. The Tox21 Computational Toxicology team has continued to work with the Tox21 chemical working group to update the Tox21 10K library chemical QC results, including the 4-month compound stability test results. All QC results have been released in the public Tox21 Browser (https://tripod.nih.gov/tox21/) and the Browser was updated with links to the EPA CompTox Chemicals Dashboard. In FY20, the Tox21 Computational Toxicology team has been working with other NCATS teams to update the NCATS Pharmaceutical Collection (NPC), which is part of the Tox21 10K compound library, with drugs approved in recent years to include an up-to-date list of all approved drugs. In addition, the teams have been working on constructing a collection of clinically tested compounds to complement the NPC in FY20. The Tox21 Computational Toxicology team is also leading one of the Tox21 cross-partner projects Expansion of Pathway Coverage by Tox21 High-Throughput Screening Assays for Better Prediction of Adverse Drug Effects, which utilizes the NCATS BioPlanet (https://tripod.nih.gov/bioplanet/) as a tool to define the biological space and identify assays for screening. The data generated from this project will be used to build computational models to predict liver and cardiotoxicity. In addition, the Tox21 Computational Toxicology team has continued to work with the Tox21 Genomic Toxicology team to refine methods for concentration response gene expression data analysis including strategies for point-of-departure (PoD) determination, as well as combination screening data analysis of toxicants and modulators (the ToxMatrix). A web version of the software platform for visualization and analysis of concentration response gene expression data has been developed and will be made public in due course. In FY20, the Tox21 Computational Toxicology team has been collaborating with the TDB biology and chemistry teams to develop a biological activity-based modeling (BABM) approach that has been successfully validated and applied to identify novel anti-SARS-CoV-2 compounds that could be developed as potential anti-COVID-19 drug leads. An article describing the BABM approach has been published in Nature Biotechnology in FY20. Moreover, the Tox21 Computational Toxicology team collaborated with the Tox21 Systems Toxicology team and the ETB and TDB biology teams to evaluate the existing anti-SARS-CoV-2 HTS assays and identify potential new anti-SARS-CoV-2 targets and pathways through data-driven approaches. These collaborative efforts have resulted in two papers published in Drug Discovery Today and Scientific Reports, respectively, in FY20.