A Python-based Docking Program Utilizing a Receptor Bound Ligand Shape: PythDock
- Title
- A Python-based Docking Program Utilizing a Receptor Bound Ligand Shape: PythDock
- Author
- 하정미
- Keywords
- Initial population; Lead optimization; Molecular docking; Molecular shape; Particle swarm optimization; PythDock; Virtual screening
- Issue Date
- 2011-09
- Publisher
- PHARMACEUTICAL SOC KOREA
- Citation
- ARCHIVES OF PHARMACAL RESEARCH, v. 34, NO. 9, Page. 1451-1458
- Abstract
- PythDock is a heuristic docking program that uses Python programming language with a simple scoring function and a population based search engine. The scoring function considers electrostatic and dispersion/repulsion terms. The search engine utilizes a particle swarm optimization algorithm. A grid potential map is generated using the shape information of a bound ligand within the active site. Therefore, the searching area is more relevant to the ligand binding. To evaluate the docking performance of PythDock, two well-known docking programs (AutoDock and DOCK) were also used with the same data. The accuracy of docked results were measured by the difference of the ligand structure between x-ray structure, and docked pose, i.e., average root mean squared deviation values of the bound ligand were compared for fourteen protein-ligand complexes. Since the number of ligands' rotational flexibility is an important factor affecting the accuracy of a docking, the data set was chosen to have various degrees of flexibility. Although PythDock has a scoring function simpler than those of other programs (AutoDock and DOCK), our results showed that PythDock predicted more accurate poses than both AutoDock4.2 and DOCK6.2. This indicates that PythDock could be a useful tool to study ligand-receptor interactions and could also be beneficial in structure based drug design.
- URI
- https://link.springer.com/article/10.1007%2Fs12272-011-0906-5https://repository.hanyang.ac.kr/handle/20.500.11754/186139
- ISSN
- 0253-6269;1976-3786
- DOI
- 10.1007/s12272-011-0906-5
- Appears in Collections:
- COLLEGE OF PHARMACY[E](약학대학) > PHARMACY(약학과) > Articles
- Files in This Item:
There are no files associated with this item.
- Export
- RIS (EndNote)
- XLS (Excel)
- XML