Name
Title | ||
|---|---|---|
SARS-CoV protease inhibitors design using virtual screening method from natural products libraries. |
Abstract | ||
|---|---|---|
Two natural products databases, the marine natural products database (MNPD) and the traditional Chinese medicines database (TCMD), were used to find novel structures of potent SARS-CoV protease inhibitors through virtual screening. Before the procedure, the databases were filtered by Lipinski's ROF and Xu's extension rules. The results were analyzed by statistic methods to eliminate the bias in target-based database screening toward higher molecular weight compounds for enhancing the hit rate. Eighteen lead compounds were recommended by the screening procedure. They were useful for experimental scientists in prioritizing drug candidates and studying the interaction mechanism. The binding mechanism was also analyzed between the best screening compound and the SARS protein. (c) 2005 Wiley Periodicals, Inc. I Comput Chem 26: 484-490, 2005. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1002/jcc.20186 | JOURNAL OF COMPUTATIONAL CHEMISTRY |
Keywords | Field | DocType |
SARS,virtual screening,molecular docking,marine natural products,traditional Chinese medicines | Hit rate,Docking (molecular),Mathematical optimization,Combinatorial chemistry,Chemistry,Protease,Computational biology,Virtual screening | Journal |
Volume | Issue | ISSN |
26.0 | 5 | 0192-8651 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bing Liu | 1 | 56 | 11.41 |
| Jiaju Zhou | 2 | 40 | 8.09 |