合成子
化学空间
虚拟筛选
萨斯
计算机科学
相似性(几何)
质量(理念)
空格(标点符号)
人工智能
化学
立体化学
生物信息学
万维网
生物
药物发现
物理
量子力学
图像(数学)
操作系统
作者
Chen Cheng,Paul Beroza
标识
DOI:10.1021/acs.jcim.3c01865
摘要
Virtual screening of large-scale chemical libraries has become increasingly useful for identifying high-quality candidates for drug discovery. While it is possible to exhaustively screen chemical spaces that number on the order of billions, indirect combinatorial approaches are needed to efficiently navigate larger, synthon-based virtual spaces. We describe Shape-Aware Synthon Search (SASS), a synthon-based virtual screening method that carries out shape similarity searches in the synthon space instead of the enumerated product space. SASS can replicate results from exhaustive searches in ultralarge, combinatorial spaces with high recall on a variety of query molecules while only scoring a small subspace of possible enumerated products, thereby significantly accelerating large-scale, shape-based virtual screening.
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