IlliGAL Blogging

The New England Journal of Medicine reports the use of a genetic algorithm in better understanding a form of lung cancer. In an article entitled EGFR Mutation and Resistance of Non–Small-Cell Lung Cancer to Gefitinib, the authors report using GAs fairly routinely as part of structural modeling procedures:

The crystallographic structure of the EGFR tyrosine kinase domain, solved in complex with erlotinib, was used as a model for the prediction of kinase-inhibitor binding (Protein Data Bank accession code 1M17 [PDB] ).14 The inhibitor and solvent were stripped from the model. We used the AutoDock program, version 3.0,15 to predict binding, first using a model of erlotinib, made by means of the JME molecular-editing feature of the online resource PRODRG.16 The erlotinib test yielded a model for ligand binding highly similar to that seen in the crystal structure. Using the AutoDockTools interface, we used a grid spacing of 0.375Å and 60x50x40 points centered around the catalytic cleft of the enzyme for docking and adopted the genetic algorithm with local search using default settings. Gefitinib and CL-387,785 were then docked with the use of the same protocol. To illustrate potential inhibitor clashes with the T790M mutant, we prepared figures in which threonine at position 790 (T790) is mutated to methionine. We then chose the lowest free-energy cluster that overlapped in the quinazoline moiety with the crystallographic coordinates found for erlotinib binding.

This work cites earlier work in the following reference:

Morris GM, Goodsell DS, Halliday RS, et al. Automated docking using a Lamarckian genetic algorithm and empirical binding free energy function. J Comput Chem 1998;19:1639-1662.

Additional details are available here.