%0 Journal Article %1 Wieder2016DynamicPharmacophoreStability %A Wieder, Marcus %A Perricone, Ugo %A Boresch, Stefan %A Seidel, Thomas %A Langer, Thierry %D 2016 %J Biochemical and Biophysical Research Communications %K dynamic-pharmacophore ligand-binding molecular-dynamics pharmacophore %N 3 %P 685 - 689 %R http://dx.doi.org/10.1016/j.bbrc.2016.01.081 %T Evaluating the stability of pharmacophore features using molecular dynamics simulations %U http://www.sciencedirect.com/science/article/pii/S0006291X1630081X %V 470 %X Abstract Molecular dynamics simulations of twelve protein—ligand systems were used to derive a single, structure based pharmacophore model for each system. These merged models combine the information from the initial experimental structure and from all snapshots saved during the simulation. We compared the merged pharmacophore models with the corresponding \PDB\ pharmacophore models, i.e., the static models generated from an experimental structure in the usual manner. The frequency of individual features, of feature types and the occurrence of features not present in the static model derived from the experimental structure were analyzed. We observed both pharmacophore features not visible in the traditional approach, as well as features which disappeared rapidly during the molecular dynamics simulations and which may well be artifacts of the initial \PDB\ structure-derived pharmacophore model. Our approach helps mitigate the sensitivity of structure based pharmacophore models to the single set of coordinates present in the experimental structure. Further, the frequency with which specific features occur during the \MD\ simulation may aid in ranking the importance of individual features.

@article{Wieder2016DynamicPharmacophoreStability, abstract = {Abstract Molecular dynamics simulations of twelve protein—ligand systems were used to derive a single, structure based pharmacophore model for each system. These merged models combine the information from the initial experimental structure and from all snapshots saved during the simulation. We compared the merged pharmacophore models with the corresponding \{PDB\} pharmacophore models, i.e., the static models generated from an experimental structure in the usual manner. The frequency of individual features, of feature types and the occurrence of features not present in the static model derived from the experimental structure were analyzed. We observed both pharmacophore features not visible in the traditional approach, as well as features which disappeared rapidly during the molecular dynamics simulations and which may well be artifacts of the initial \{PDB\} structure-derived pharmacophore model. Our approach helps mitigate the sensitivity of structure based pharmacophore models to the single set of coordinates present in the experimental structure. Further, the frequency with which specific features occur during the \{MD\} simulation may aid in ranking the importance of individual features. }, added-at = {2016-05-31T23:03:00.000+0200}, author = {Wieder, Marcus and Perricone, Ugo and Boresch, Stefan and Seidel, Thomas and Langer, Thierry}, biburl = {https://www.bibsonomy.org/bibtex/23ccd9ac96c16208139861548d1d5badf/salotz}, description = {Evaluating the stability of pharmacophore features using molecular dynamics simulations}, doi = {http://dx.doi.org/10.1016/j.bbrc.2016.01.081}, interhash = {c9011b07e7a545d185265f62798f4022}, intrahash = {3ccd9ac96c16208139861548d1d5badf}, issn = {0006-291X}, journal = {Biochemical and Biophysical Research Communications }, keywords = {dynamic-pharmacophore ligand-binding molecular-dynamics pharmacophore}, number = 3, pages = {685 - 689}, timestamp = {2016-05-31T23:03:00.000+0200}, title = {Evaluating the stability of pharmacophore features using molecular dynamics simulations }, url = {http://www.sciencedirect.com/science/article/pii/S0006291X1630081X}, volume = 470, year = 2016 }