6533b829fe1ef96bd128b002

RESEARCH PRODUCT

Evaluating the stability of pharmacophore features using molecular dynamics simulations.

Stefan BoreschUgo PerriconeMarcus WiederThierry LangerThomas Seidel

subject

0301 basic medicineProtein FlexibilityProtein ConformationBiophysicsStability (learning theory)Molecular Dynamics SimulationLigands01 natural sciencesBiochemistryLigandScoutSet (abstract data type)03 medical and health sciencesMolecular dynamicsComputational chemistryFeature (machine learning)Pharmacophore ModelingSensitivity (control systems)Molecular BiologyBinding Sites010405 organic chemistryChemistryStructure-based Pharmacophore ModelingMolecular DynamicProteinsHydrogen BondingCell Biology0104 chemical sciences030104 developmental biologyRankingModels ChemicalDrug DesignPharmacophoreBiological systemProtein Binding

description

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.

10.1016/j.bbrc.2016.01.081https://pubmed.ncbi.nlm.nih.gov/26785387