Cell Painting and Chemical Structure Read-Across Can Complement Each Other for Rat Acute Oral Toxicity Prediction in Chemical Early Derisking

体内 毒性 急性毒性 训练集 化学结构 化学毒性 体外 化学 毒理 计算生物学 计算机科学 人工智能 生物化学 生物 生物技术 有机化学
作者
F. Camilleri,J. Wenda,C. Pecoraro-Mercier,Jean‐Paul Comet,David Rouquié
出处
期刊:Chemical Research in Toxicology [American Chemical Society]
卷期号:37 (11): 1851-1866 被引量:4
标识
DOI:10.1021/acs.chemrestox.4c00169
摘要

Early derisking decisions in the development of new chemical compounds enable the identification of novel chemical candidates with improved safety profiles. In vivo studies are traditionally conducted in the early assessment of acute oral toxicity of crop protection products to avoid compounds, which are considered "very acutely toxic", with an in vivo lethal dose of 50% (LD50) ≤ 60 mg/kg body weight. Those studies are lengthy and costly and raise ethical concerns, catalyzing the use of nonanimal alternatives. The objective of our analysis was to assess the predictive efficacy of read-across approaches for acute oral toxicity in rats, comparing the use of chemical structure information, in vitro biological data derived from the Cell Painting profiling assay on U2OS cells, or the combination of both. Our findings indicate that the classification of compounds as very acute oral toxic (LD50 ≤ 60 mg/kg) or not is possible using a read-across approach, with chemical structure information, morphological profiles, or a combination of both. When classifying compounds structurally similar to those in the training set, the chemical structure was more predictive (balanced accuracy of 0.82). Conversely, when the compounds to be classified were structurally different from those in the training set, the morphological profiles were more predictive (balanced accuracy of 0.72). Combining the two models allowed for the classification of compounds structurally similar to those in the training set to slightly improve the predictions (balanced accuracy of 0.85).
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
2315235给2315235的求助进行了留言
1秒前
1秒前
漂亮的芷巧完成签到,获得积分10
2秒前
2秒前
柚子完成签到,获得积分10
2秒前
Ava应助三途采纳,获得10
2秒前
充电宝应助科研小吴采纳,获得10
4秒前
JIN发布了新的文献求助10
4秒前
泽豫完成签到,获得积分20
4秒前
科研通AI6.4应助Desamin采纳,获得10
4秒前
韦德德完成签到,获得积分10
5秒前
huilin完成签到 ,获得积分20
5秒前
hhh完成签到,获得积分10
5秒前
科研通AI6.4应助猪猪hero采纳,获得10
5秒前
FeCl发布了新的文献求助10
6秒前
7秒前
7秒前
zz发布了新的文献求助10
7秒前
7秒前
8秒前
8秒前
ding应助影流采纳,获得10
9秒前
RockRedfoo完成签到,获得积分10
9秒前
凪启发布了新的文献求助10
10秒前
小蘑菇应助李光辉采纳,获得10
10秒前
Fay关闭了Fay文献求助
10秒前
初景应助悦子采纳,获得20
10秒前
11秒前
XA完成签到,获得积分20
11秒前
领导范儿应助车恩池采纳,获得10
11秒前
苹果代天应助dd采纳,获得10
11秒前
青柠完成签到 ,获得积分10
12秒前
王sir完成签到,获得积分10
12秒前
大力的灵雁应助zzz采纳,获得10
13秒前
魑魅裕哥发布了新的文献求助10
13秒前
星辰大海应助flame采纳,获得10
13秒前
huhuiya发布了新的文献求助10
13秒前
13秒前
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Cowries - A Guide to the Gastropod Family Cypraeidae 1200
Quality by Design - An Indispensable Approach to Accelerate Biopharmaceutical Product Development 800
Pulse width control of a 3-phase inverter with non sinusoidal phase voltages 777
Signals, Systems, and Signal Processing 610
Research Methods for Applied Linguistics 500
Chemistry and Physics of Carbon Volume 15 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6396187
求助须知:如何正确求助?哪些是违规求助? 8211534
关于积分的说明 17394407
捐赠科研通 5449627
什么是DOI,文献DOI怎么找? 2880549
邀请新用户注册赠送积分活动 1857131
关于科研通互助平台的介绍 1699454