Common Hits Approach: Combining Pharmacophore Modeling and Molecular Dynamics Simulations.

Anna Maria Almerico, Ugo Perricone, Stefan Boresch, Thierry Langer, Ugo Perricone, Marcus Wieder, Arthur Garon, Thomas Seidel

Risultato della ricerca: Article

11 Citazioni (Scopus)

Abstract

We present a new approach that incorporates flexibility based on extensive MD simulations of protein-ligand complexes into structure-based pharmacophore modeling and virtual screening. The approach uses the 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 rescored 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). The steps between the MD simulation and the final hit-list are performed automatically and without user interaction. 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 (i) median screening performance of all representative pharmacophore models of protein-ligand systems, as well as to the virtual screening performance of (ii) a random classifier, (iii) the pharmacophore model derived from the experimental structure in the PDB, and (iv) 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. The availabilithy of diverse sets of different pharmacophore models is utilized to analyze some additional questions of interest in 3D pharmacophore-based virtual screening.
Lingua originaleEnglish
pagine (da-a)365-385
Numero di pagine21
RivistaJournal of Chemical Information and Modeling
Volume57
Stato di pubblicazionePublished - 2017

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Molecular dynamics
simulation
Screening
Computer simulation
Ligands
Proteins
Classifiers
performance
flexibility
Molecules

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Library and Information Sciences
  • Computer Science Applications
  • Chemical Engineering(all)

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Common Hits Approach: Combining Pharmacophore Modeling and Molecular Dynamics Simulations. / Almerico, Anna Maria; Perricone, Ugo; Boresch, Stefan; Langer, Thierry; Perricone, Ugo; Wieder, Marcus; Garon, Arthur; Seidel, Thomas.

In: Journal of Chemical Information and Modeling, Vol. 57, 2017, pag. 365-385.

Risultato della ricerca: Article

Almerico, Anna Maria ; Perricone, Ugo ; Boresch, Stefan ; Langer, Thierry ; Perricone, Ugo ; Wieder, Marcus ; Garon, Arthur ; Seidel, Thomas. / Common Hits Approach: Combining Pharmacophore Modeling and Molecular Dynamics Simulations. In: Journal of Chemical Information and Modeling. 2017 ; Vol. 57. pagg. 365-385.
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abstract = "We present a new approach that incorporates flexibility based on extensive MD simulations of protein-ligand complexes into structure-based pharmacophore modeling and virtual screening. The approach uses the 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 rescored 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). The steps between the MD simulation and the final hit-list are performed automatically and without user interaction. 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 (i) median screening performance of all representative pharmacophore models of protein-ligand systems, as well as to the virtual screening performance of (ii) a random classifier, (iii) the pharmacophore model derived from the experimental structure in the PDB, and (iv) 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. The availabilithy of diverse sets of different pharmacophore models is utilized to analyze some additional questions of interest in 3D pharmacophore-based virtual screening.",
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AU - Wieder, Marcus

AU - Garon, Arthur

AU - Seidel, Thomas

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