Name
Abstract | ||
|---|---|---|
Discovering new drugs for emerging diseases has been a challenging task. There are numerous drug design techniques including fragment-based and diversity-oriented methods but their accuracies and efficiencies are low. By incorporating visualisation, biomedical experts can interact with the process to produce drug-like ligands more efficiently. The paper presents an interactive drug design algorithm which generates lead candidates against a protein. A set of drug candidates, created by an in house fragment-based method and docked on the target protein, are visualised in the virtual reality settings. Biomedical experts can investigate and select some of the ligands for further processing, aided with distance and bonding information. It also assists the user to drag and rotate the ligand to the binding site they find suitable. The algorithm runs iteratively and improves the quality of lead candidates every step. The paper compares the quality of resulting ligands between interactive and automatic approaches. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IV.2011.72 | IV |
Keywords | Field | DocType |
interactive drug design,drug-like ligands,fragment based methods,diseases,physicochemical properties,virtual reality,numerous drug design technique,automatic approach,protein,proteins,lead candidate,drug candidate,biochemistry,molecular biophysics,data visualisation,diversity-oriented methods,house fragment-based method,biomedical expert,target protein,ligands,medical computing,visualisation,new drug,interactive drug design algorithm,drug candidates,drugs,visualization,evolutionary computation,drug design,algorithm design and analysis | Data visualization,Algorithm design,Virtual reality,Visualization,Simulation,Evolutionary computation,Human–computer interaction,Engineering | Conference |
ISSN | ISBN | Citations |
1550-6037 | 978-1-4577-0868-8 | 2 |
PageRank | References | Authors |
0.45 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ching-Man Tse | 1 | 2 | 0.45 |
| Hongjian Li | 2 | 64 | 6.26 |
| Kwong-Sak Leung | 3 | 1887 | 205.58 |
| Kin-Hong Lee | 4 | 257 | 26.27 |
| Man Hon Wong | 5 | 814 | 233.13 |