We present a new method that incorporates flexibility based on extensive MD simulations of protein-ligand complexes into structure based pharmacophore modeling and virtual screening. The approach uses multiple coordinate sets saved during the MD simulations and generates for each frame a pharmacophore model. Pharmacophore models with the same pharmacophore features are pooled. In this way the high number of pharmacophore models that results from the MD simulation is reduced to only a few hundred representative pharmacophore models. Virtual screening runs are performed with every representative pharmacophore model; the screening results are combined and re-scored to generate a single hit-list. The score for a particular molecule is calculated based on the number of representative pharmacophore models which classified it as active. Hence, the method is called common hits approach (CHA). We test the performance of CHA for virtual screening using screening databases with active and inactive compounds for 40 protein--ligand systems. The results of the CHA are compared to the virtual screening performance of (i) a random classifier, (ii) the pharmacophore model derived from the experimental structure in the PDB and (iii) the representative pharmacophore model appearing most frequently during the MD simulation. For the 34 (out of 40) protein--ligand complexes, for which at least one of the approaches was able to perform better than a random classifier, the highest enrichment was achieved using CHA in 68% of the cases, compared to 12% for the PDB pharmacophore model and 20% for the representative pharmacophore model appearing most frequently.

Common hits approach: Combining pharmacophore modeling and molecular dynamics simulations

253rd National Meeting (2017)

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