Abstract
In this paper, we present a multi-scale optimization model and an entropy-based genetic algorithm for molecular docking. In this model, we introduce to the refined docking design a concept of residue groups based on induced-fit and adopt a combination of conformations in different scales. A new iteration scheme, in conjunction with multi-population evolution strategy, entropy-based searching technique with narrowing down space and the quasi-exact penalty function, is developed to address the optimization problem for molecular docking. A new docking program that accounts for protein flexibility has also been developed. The docking results indicate that the method can be efficiently employed in structure-based drug design.
| Original language | English |
|---|---|
| Pages (from-to) | 182-198 |
| Number of pages | 17 |
| Journal | Journal of Mathematical Chemistry |
| Volume | 46 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jun 2009 |
| Externally published | Yes |
Keywords
- Genetic algorithm
- Information entropy
- Molecular docking
- Multi-scale optimization model
- Residue groups