A Comprehensive Collection of Pain and Opioid Use Disorder Compounds for High-Throughput Screening and Artificial Intelligence-Driven Drug Discovery
Xin HuiD, Paul ShinniD, Zina ItkiniD, Lin Ye, Ya-Qin ZhangiD, Min SheniD, Stephanie L. Ford‐Scheimer, Matthew D. HalliD
Abstract
As part of the NIH Helping to End Addiction Long-term (HEAL) Initiative, the National Center for Advancing Translational Sciences (NCATS) 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 3,000 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 rapid and efficient high throughput screen (HTS) 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 (ML), structural modeling, and virtual screening (VS), 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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