Computer-aided synthesis planning (CASP) integrates intuition of chemists and reliability of computers.As an in-between of unique creativities of hu-man beings and unparalleled calculational capability of computers,CASP has become an important tool used in academic and industrial research.With explosion of novel chemical reactions,increasing of computer performance,and revolution of algorithms,CASP will play more significant roles in the synthetic chemistry field,inspiring novel and highly efficient syntheses of natural products and drug candidates.In this article,we review the progress in computational analysis of synthetic planning from rule-based programs (e.g.,LHASA and SECS) in the early stage to machine learning (e.g.,neural networks and seq2seq methods) in more recent years.
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