Estimating the synthetic accessibility of molecules with building block and reaction-aware SAScore
2024 · Journal of Cheminformatics
저자
Shuan Chen, 정유성 (Yousung Jung)
연구주제
Computational Drug Discovery Methods · Machine Learning in Materials Science
NTIS 과학기술표준분류
가장 가까운 분류(전기/전자 > 디스플레이 > 디스플레이 소재/부품)가 화학·화공 범위 밖이다. 배정 근거: 논문을 지원한 과제의 분류.
AI 연구 키워드·방법
building block synthesis planning synthetic accessibility score
키워드 (OpenAlex)
synthetic accessibility building blocks chemical reactions synthesis planning fragment analysis computer-aided molecular design
초록
Synthetic accessibility prediction is a task to estimate how easily a given molecule might be synthesizable in the laboratory, playing a crucial role in computer-aided molecular design. Although synthesis planning programs can determine synthesis routes, their slow processing times make them impractical for large-scale molecule screening. On the other hand, existing rapid synthesis accessibility estimation methods offer speed but typically lack integration with actual synthesis routes and building block information. In this work, we introduce BR-SAScore, an enhanced version of SAScore that integrates the available building block information (B) and reaction knowledge (R) from synthesis planning programs into the scoring process. In particular, we differentiate fragments inherent in building blocks and fragments to be derived from synthesis (reactions) when scoring synthetic accessibility…
이 논문을 지원한 국가R&D 과제 (NTIS 성과)
| 연도 | 과제 | 부처 | 사업 | 수행기관 | NTIS 분류(1순위) |
|---|---|---|---|---|---|
| 2024 | 디스플레이용 High T1(≥2.9eV, Blue)호스트의 AI기반 개발 | 산업통상자원부 | 소재부품기술개발 | 엘티소재(주) | 범위 밖 |
| 2024 | 인공지능대학원지원(서울대학교) | 과학기술정보통신부 | 정보통신방송혁신인재양성(R&D) | 서울대학 | – |
인접 그래프
노드 hover = 이웃 강조 · 1회 클릭 = 고정 · 고정된 노드 다시 클릭 = 페이지 이동