预测药物筛选中能否测出有效浓度,提升高成本测试的效率。
Predicting Quantifiability from Primary Screens to Prioritize Dose-Response Profiling
- 从初筛数据预测后续能否获得可用的剂量反应结果,独立于生物活性判断。
- 初筛信号强度和实验背景决定能否量化效力,预测准确率高。
- 适合药企或研究机构优化药物筛选流程,减少无效测试投入。
高通量药物筛选依赖低成本初筛来挑选化合物进行更昂贵的剂量反应分析,以最终确定效力。现有策略主要关注识别在后续验证中表现出生物活性的化合物,隐含假设是生物活性即意味着可量化效力。然而,初筛中确认的活性并不一定转化为可报告的剂量反应结果,因为部分活性化合物仍无法产生有效的效力估计。为此,本文提出一个建模框架,将“可量化性”——即后续测试能否获得可用效力估计——作为一个与生物活性分离的筛选目标。结果显示,可量化性可由前期低代价初筛数据高度预测,大部分预测信息来自观察到的筛选特征而非分子结构。基于响应的预测模型在未见过的化学骨架上依然稳健,并在排除的靶点机制类别间具有良好泛化能力;而成功量化概率强烈依赖于响应幅度和实验上下文。这些发现表明,实验可测量性是一种可预测的筛选结果属性,且具备可量化性的筛选策略能显著提升高成本剂量反应测试资源的分配效率。
原文摘要 · Abstract (English)
High-throughput drug screening relies on low-cost primary assays to prioritize compounds for more expensive dose-response profiling, where potency is ultimately quantified. Current screening strategies largely focus on identifying compounds that will confirm biological activity on follow-up, implicitly assuming that confirmed activity will also yield a usable potency estimate. However, confirmed biological activity in screening does not necessarily translate into a quantifiable potency, because active compounds can still fail to produce a reportable dose-response estimate. We therefore present a framework for modeling quantifiability, whether follow-up testing will yield a usable potency estimate, as a distinct triage objective from biological activity. Quantifiability was strongly predictable from the preceding low-cost screen, with most predictive information arising from the observed screening features rather than molecular structure. Response-based predictors remained robust on previously unseen chemical scaffolds and generalized across held-out assay-mechanism families, while the probability of successful quantification varied strongly with response amplitude and assay context. These findings establish experimental measurability, distinct from biological activity, as a predictable property of screening outcomes and show that quantifiability-aware triage can improve the allocation of costly dose-response profiling capacity.
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