Comparing pharmacophore models derived from crystallography and NMR ensembles

Abstract

NMR and X-ray crystallography are the two most widely used methods for determining protein structures. Our previous study examining NMR versus X-Ray sources of protein conformations showed improved performance with NMR structures when used in our Multiple Protein Structures (MPS) method for receptor-based pharmacophores (Damm, Carlson, J Am Chem Soc 129:8225-8235, 2007). However, that work was based on a single test case, HIV-1 protease, because of the rich data available for that system. New data for more systems are available now, which calls for further examination of the effect of different sources of protein conformations. The MPS technique was applied to Growth factor receptor bound protein 2 (Grb2), Src SH2 homology domain (Src-SH2), FK506-binding protein 1A (FKBP12), and Peroxisome proliferator-activated receptor-γ (PPAR-γ). Pharmacophore models from both crystal and NMR ensembles were able to discriminate between high-affinity, low-affinity, and decoy molecules. As we found in our original study, NMR models showed optimal performance when all elements were used. The crystal models had more pharmacophore elements compared to their NMR counterparts. The crystal-based models exhibited optimum performance only when pharmacophore elements were dropped. This supports our assertion that the higher flexibility in NMR ensembles helps focus the models on the most essential interactions with the protein. Our studies suggest that the "extra" pharmacophore elements seen at the periphery in X-ray models arise as a result of decreased protein flexibility and make very little contribution to model performance.

Applications of Virtual Screening in Bioprospecting: Facts, Shifts, and Perspectives to Explore the Chemo-Structural Diversity of Natural Products

“…Regarding structure-based pharmacophore modeling, the use of experimental structures to build the models must prioritize some structural features obtained from both methods; as an example, it has been demonstrated that a higher flexibility obtained in structures elucidated by nuclear magnetic resonance (NMR) spectroscopy helps to focus the models on the most essential interactions with the receptor due to the presence of structural flexibility of the complexes evidenced by the method. On the other hand, models obtained by X-ray crystallography had more pharmacophore elements compared to those obtained by NMR spectroscopy (Ghanakota and Carlson, 2017 ).…”

PyRod Enables Rational Homology Model‐based Virtual Screening Against MCHR1

“…Molecular dynamics (MD) simulation can be used to address such artifacts and additionally, provide valuable information about the flexibility and thermodynamic properties of the system . PyRod, a free and open‐source Python software, combines the strength of MD simulations with structure‐based 3D pharmacophore searches by analyzing the protein environment of water molecules in protein binding pockets and subsequently generates pharmacophore features for virtual screening …”