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Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function (1998)
| Venue: | J. Comput. Chem |
| Citations: | 379 - 4 self |
BibTeX
@ARTICLE{Morris98automateddocking,
author = {Garrett M. Morris and David S. Goodsell and Robert S. Halliday and Ruth Huey and William E. Hart and Richard K. Belew and Arthur J. Olson},
title = {Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function},
journal = {J. Comput. Chem},
year = {1998},
volume = {19},
pages = {1639--1662}
}
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Abstract
ABSTRACT: A novel and robust automated docking method that predicts the bound conformations of flexible ligands to macromolecular targets has been developed and tested, in combination with a new scoring function that estimates the free energy change upon binding. Interestingly, this method applies a Lamarckian model of genetics, in which environmental adaptations of an individual’s phenotype are reverse transcribed into its genotype and become heritable traits Ž sic.. We consider three search methods, Monte Carlo simulated annealing, a traditional genetic algorithm, and the Lamarckian genetic algorithm, and compare their performance in dockings of seven protein�ligand test systems having known three-dimensional structure. We show that both the traditional and Lamarckian genetic algorithms can handle ligands with more degrees of freedom than the simulated annealing method used in earlier versions of AUTODOCK, and that the Lamarckian genetic algorithm is the most efficient, reliable, and successful of the three. The empirical free energy function was calibrated using a set of 30 structurally known protein�ligand complexes with experimentally determined binding constants. Linear regression analysis of the observed binding constants in terms of a wide variety of structure-derived molecular properties was performed. The final model had a residual standard �1 Ž �1 error of 9.11 kJ mol 2.177 kcal mol. and was chosen as the new energy
Keyphrases
lamarckian genetic algorithm empirical binding free energy function monte carlo protein ligand complex macromolecular target empirical free energy function free energy change individual phenotype structure-derived molecular property kj mol flexible ligand three-dimensional structure environmental adaptation protein ligand test system kcal mol final model traditional genetic algorithm binding constant simulated annealing method search method bound conformation linear regression analysis residual standard observed binding constant lamarckian model wide variety new scoring function heritable trait new energy
