当前位置: X-MOL 学术Chem. Sci. › 论文详情
Efficient prediction of reaction paths through molecular graph and reaction network analysis
Chemical Science ( IF 9.063 ) Pub Date : 2017-12-12 , DOI: 10.1039/C7SC03628K
Yeonjoon Kim, Jin Woo Kim, Zeehyo Kim, Woo Youn Kim

Despite remarkable advances in computational chemistry, prediction of reaction mechanisms is still challenging, because investigating all possible reaction pathways is computationally prohibitive due to the high complexity of chemical space. A feasible strategy for efficient prediction is to utilize chemical heuristics. Here, we propose a novel approach to rapidly search reaction paths in a fully automated fashion by combining chemical theory and heuristics. A key idea of our method is to extract a minimal reaction network composed of only favorable reaction pathways from the complex chemical space through molecular graph and reaction network analysis. This can be done very efficiently by exploring the routes connecting reactants and products with minimum dissociation and formation of bonds. Finally, the resulting minimal network is subjected to quantum chemical calculations to determine kinetically the most favorable reaction path at the predictable accuracy. As example studies, our method was able to successfully find the accepted mechanisms of Claisen ester condensation and cobalt-catalyzed hydroformylation reactions.
更新日期:2018-01-24

 

分享到
评论: 0
期刊列表
深圳大学可拉伸电子研究中心招聘专职研究员
中科大微尺度国家科学中心龚流柱教授课题组招博士后
天合科研
【问答】请问酰胺和卤代烃是否可以发生化学反应?
2017年中科院JCR分区化学大类列表
试剂库存管理
化合物查询
down
wechat
bug