Title |
Ring system-based chemical graph generation for de novo molecular design
|
---|---|
Published in |
Perspectives in Drug Discovery and Design, June 2016
|
DOI | 10.1007/s10822-016-9916-1 |
Pubmed ID | |
Authors |
Tomoyuki Miyao, Hiromasa Kaneko, Kimito Funatsu |
Abstract |
Generating chemical graphs in silico by combining building blocks is important and fundamental in virtual combinatorial chemistry. A premise in this area is that generated structures should be irredundant as well as exhaustive. In this study, we develop structure generation algorithms regarding combining ring systems as well as atom fragments. The proposed algorithms consist of three parts. First, chemical structures are generated through a canonical construction path. During structure generation, ring systems can be treated as reduced graphs having fewer vertices than those in the original ones. Second, diversified structures are generated by a simple rule-based generation algorithm. Third, the number of structures to be generated can be estimated with adequate accuracy without actual exhaustive generation. The proposed algorithms were implemented in structure generator Molgilla. As a practical application, Molgilla generated chemical structures mimicking rosiglitazone in terms of a two dimensional pharmacophore pattern. The strength of the algorithms lies in simplicity and flexibility. Therefore, they may be applied to various computer programs regarding structure generation by combining building blocks. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
China | 1 | 4% |
Unknown | 23 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 8 | 33% |
Student > Master | 5 | 21% |
Student > Doctoral Student | 2 | 8% |
Student > Ph. D. Student | 2 | 8% |
Lecturer | 1 | 4% |
Other | 4 | 17% |
Unknown | 2 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 6 | 25% |
Chemistry | 6 | 25% |
Chemical Engineering | 3 | 13% |
Materials Science | 3 | 13% |
Physics and Astronomy | 1 | 4% |
Other | 2 | 8% |
Unknown | 3 | 13% |