AI Article Synopsis
- The study introduces a Lamarckian genetic algorithm (LGA) variant designed for flexible ligand-receptor docking, effectively managing multiple degrees of freedom.
- This hybrid method combines LGA with a gradient-based optimization technique for improved molecular complex fitting.
- Results demonstrate that the new algorithm outperforms traditional non-gradient search methods, achieving superior outcomes and faster run times, particularly with complex ligands that have numerous rotatable bonds.
Article Abstract
We present a Lamarckian genetic algorithm (LGA) variant for flexible ligand-receptor docking which allows to handle a large number of degrees of freedom. Our hybrid method combines a multi-deme LGA with a recently published gradient-based method for local optimization of molecular complexes. We compared the performance of our new hybrid method to two non gradient-based search heuristics on the Astex diverse set for flexible ligand-receptor docking. Our results show that the novel approach is clearly superior to other LGAs employing a stochastic optimization method. The new algorithm features a shorter run time and gives substantially better results, especially with increasing complexity of the ligands. Thus, it may be used to dock ligands with many rotatable bonds with high efficiency.
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| http://dx.doi.org/10.1002/jcc.21478 | DOI Listing |
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