SNU CBE

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)

연도과제부처사업수행기관NTIS 분류(1순위)
2024디스플레이용 High T1(≥2.9eV, Blue)호스트의 AI기반 개발산업통상자원부소재부품기술개발엘티소재(주)범위 밖
2024인공지능대학원지원(서울대학교)과학기술정보통신부정보통신방송혁신인재양성(R&D)서울대학–

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교수 1

정유성

연구주제 1

Computational Drug Discovery Methods