| アイテムタイプ |
会議発表用資料 / Presentation(1) |
| 公開日 |
2025-10-27 |
| タイトル |
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|
タイトル |
Structure-based and AI-accelerated Drug Screening with Enhanced Accuracy |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6670 |
|
資源タイプ |
conference poster |
| 著者 |
Kun-Lin Tsai
Nikhil Pathak
Sakuraba Shun
Lee-wei Yang
|
| 抄録 |
|
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内容記述 |
Structure-based virtual screening (SBVS) remains one of the most widely adopted strategies in modern computer-aided drug discovery, yet it continues to suffer from high false-positive rates due to imprecise scoring functions and limited scalability. To address these challenges, we developed a statistical re-scoring framework based on Log-Odds (LOD) scores that quantifies the probability of a docking pose being a “true binder” versus a “decoy”. By integrating this with an AI accelerator, we aim to eliminate the need for exhaustive docking simulations for SBVS in the future. |
| 会議概要（会議名, 開催地, 会期, 主催者等） |
|
|
内容記述 |
第12回「富岳」を中核とするHPCIシステム利用研究課題 成果報告会 |
| 発表年月日 |
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|
日付 |
2025-10-24 |
