Construction of a generic reaction knowledge base by reaction data mining.
As synthesis by combinatorial chemistry and high throughput screening have become well-established strategies in the drug discovery process, chemists face increased challenges in managing large amounts of data and using these data to design more diverse and focused libraries. As synthesis is an intuitive and empirical process, however, the classical approaches to computer-assisted synthesis planning do not fully satisfy the needs of the synthetic chemist. We describe a novel computational technique for extracting reaction data and building a generic reaction knowledge base (GRKB) to provide chemists with useful and well-organized knowledge. The method consists of three key steps: (1) the automatic recognition of reaction centers, (2) the definition of a hierarchy of reaction patterns, and (3) the organization of the generic reaction knowledge. Significant reaction knowledge has been discovered via mining a subset of the InfoChem Reaction database. A frame system has been constructed to store and retrieve the GRKB. Applications of this GRKB to synthesis planning are illustrated.
Wang
K
K
Laboratory of Computer Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 354 Fenglin Lu, Shanghai 200032, China.
Wang
L
L
Yuan
Q
Q
Luo
S
S
Yao
J
J
Yuan
S
S
Zheng
C
C
Brandt
J
J
D001185:Artificial Intelligence; D016208:Databases, Factual; D015195:Drug Design