Abstract
In this paper we evaluate the design of the hybrid EAs that are currently used to perform flexible ligand binding in the AutoDock docking software. Hybrid evolutionary algorithms (EAs) incorporate specialized operators that exploit domain-specific features to accelerate an EA’s search. We consider hybrid EAs that use an integrated local search operator to refine individuals within each iteration of the search. We evaluate several factors that impact the efficacy of a hybrid EA, and we propose new hybrid EAs that provide more robust convergence to low-energy docking configurations than the methods currently available in AutoDock.
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Hart, W.E., Rosin, C., Belew, R.K., Morris, G.M. (2000). Improved Evolutionary Hybrids for Flexible Ligand Docking in AutoDock. In: Floudas, C.A., Pardalos, P.M. (eds) Optimization in Computational Chemistry and Molecular Biology. Nonconvex Optimization and Its Applications, vol 40. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3218-4_12
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DOI: https://doi.org/10.1007/978-1-4757-3218-4_12
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