A Comprehensive Collection of Pain and Opioid Use Disorder Compounds for High-Throughput Screening and Artificial Intelligence-Driven Drug Discovery

Xin Hu*, Paul Shinn, Zina Itkin, Lin Ye, Ya-Qin Zhang, Min Shen, Stephanie Ford-Scheimer and Matthew D. Hall*, 
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Abstract

As part of the NIH Helping to End Addiction Long-term (HEAL) Initiative, the National Center for Advancing Translational Sciences is dedicated to the development of new pharmacological tools and investigational drugs for managing and treating pain as well as the prevention and treatment of opioid misuse and addiction. In line with these objectives, we created a comprehensive, annotated small molecule library including drugs, probes, and tool compounds that act on published pain- and addiction-relevant targets. Nearly 3000 small molecules associated with approximately 200 known and hypothesized HEAL targets have been assembled, curated, and annotated in one collection. Physical samples of the library compounds have been acquired and plated in 1536-well format, enabling a rapid and efficient high-throughput screen against a wide range of assays. The creation of the HEAL Targets and Compounds Library, coupled with an integrated computational platform for AI-driven machine learning, structural modeling, and virtual screening, provides a valuable source for strategic drug repurposing, innovative profiling, and hypothesis testing of novel targets related to pain and opioid use disorder (OUD). The library is available to investigators for screening pain and OUD-relevant phenotypes.

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用于高通量筛选和人工智能驱动药物发现的疼痛和阿片类药物使用障碍化合物综合汇编
作为美国国立卫生研究院(NIH)"帮助戒除毒瘾长期计划"(HEAL)的一部分,美国国家转化科学促进中心(National Center for Advancing Translational Sciences)致力于开发新的药理学工具和研究药物,用于控制和治疗疼痛以及预防和治疗阿片类药物滥用和成瘾。根据这些目标,我们创建了一个全面的、附有注释的小分子化合物库,其中包括作用于已公布的疼痛和成瘾相关靶点的药物、探针和工具化合物。与大约 200 个已知和假设的 HEAL 靶点相关的近 3000 种小分子化合物已被收集、整理和注释在一个集合中。该化合物库的物理样本已采集完毕,并以 1536 孔的格式进行了培养,从而能够针对各种检测方法进行快速、高效的高通量筛选。HEAL 靶点和化合物库的建立,加上人工智能驱动的机器学习、结构建模和虚拟筛选的集成计算平台,为疼痛和阿片类药物使用障碍 (OUD) 相关新靶点的战略药物再利用、创新性分析和假设检验提供了宝贵的资源。研究人员可利用该库筛选与疼痛和阿片类药物使用障碍相关的表型。
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来源期刊
ACS Pharmacology and Translational Science
ACS Pharmacology and Translational Science Medicine-Pharmacology (medical)
CiteScore
10.00
自引率
3.30%
发文量
133
期刊介绍: ACS Pharmacology & Translational Science publishes high quality, innovative, and impactful research across the broad spectrum of biological sciences, covering basic and molecular sciences through to translational preclinical studies. Clinical studies that address novel mechanisms of action, and methodological papers that provide innovation, and advance translation, will also be considered. We give priority to studies that fully integrate basic pharmacological and/or biochemical findings into physiological processes that have translational potential in a broad range of biomedical disciplines. Therefore, studies that employ a complementary blend of in vitro and in vivo systems are of particular interest to the journal. Nonetheless, all innovative and impactful research that has an articulated translational relevance will be considered. ACS Pharmacology & Translational Science does not publish research on biological extracts that have unknown concentration or unknown chemical composition. Authors are encouraged to use the pre-submission inquiry mechanism to ensure relevance and appropriateness of research.
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