Getting Docking into Shape Using Negative Image-Based Rescoring
Kurkinen, S. T., Lätti, S., Pentikäinen, O. T., & Postila, P. A. (2019). Getting Docking into Shape Using Negative Image-Based Rescoring. Journal of Chemical Information and Modeling, 59(8), 3584-3599. https://doi.org/10.1021/acs.jcim.9b00383
Julkaistu sarjassa
Journal of Chemical Information and ModelingPäivämäärä
2019Tekijänoikeudet
© 2019 American Chemical Society
The failure of default scoring functions to ensure virtual screening enrichment is a persistent problem for the
molecular docking algorithms used in the structure-based drug discovery. To remedy this problem, elaborate rescoring and post-processing schemes have been developed with a varying degree of success, specificity, and cost. The negative imagebased rescoring (R-NiB) has been shown to improve the flexible docking performance markedly with a variety of drug targets.The yield improvement is achieved by comparing the alternative docking poses against the negative image of the target protein’s ligand-binding cavity. In other words, the shape and electrostatics of the binding pocket is directly used in the similarity comparison to rank the explicit docking poses. Here, the PANTHER/ShaEP-based R-NiB methodology is tested with six popular docking software, including GLIDE, PLANTS, GOLD, DOCK, AUTODOCK, and AUTODOCK VINA, using five validated benchmark sets. Overall, the results indicate that the R-NiB outperforms the default docking scoring consistently and inexpensively; i.e., demonstrating that the methodology is ready for wide-scale virtual screening usage.
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Julkaisija
American Chemical SocietyISSN Hae Julkaisufoorumista
1549-9596Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/32108459
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Lisätietoja rahoituksesta
The Turku University Foundation and Finnish Cultural Foundation are acknowledged for personal grant to STK. The Finnish IT Center for Science (CSC) is acknowledged for generous computational resources (OTP; Project Nos. jyy2516 and jyy2585). Visual Molecular Dynamics (VMD) was developed by the Theoretical and Computational Biophysics Group in the Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign. ...Lisenssi
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