| Literature DB >> 28900792 |
Christina Schindler1, Friedrich Rippmann2, Daniel Kuhn2.
Abstract
Physics-based free energy simulations have increasingly become an important tool for predicting binding affinity and the recent introduction of automated protocols has also paved the way towards a more widespread use in the pharmaceutical industry. The D3R 2016 Grand Challenge 2 provided an opportunity to blindly test the commercial free energy calculation protocol FEP+ and assess its performance relative to other affinity prediction methods. The present D3R free energy prediction challenge was built around two experimental data sets involving inhibitors of farnesoid X receptor (FXR) which is a promising anticancer drug target. The FXR binding site is predominantly hydrophobic with few conserved interaction motifs and strong induced fit effects making it a challenging target for molecular modeling and drug design. For both data sets, we achieved reasonable prediction accuracy (RMSD ≈ 1.4 kcal/mol, rank 3-4 according to RMSD out of 20 submissions) comparable to that of state-of-the-art methods in the field. Our D3R results boosted our confidence in the method and strengthen our desire to expand its applications in future in-house drug design projects.Entities:
Keywords: Binding affinity prediction; Computer-aided drug design; D3R; Drug design data resource; Free energy calculations
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Year: 2017 PMID: 28900792 DOI: 10.1007/s10822-017-0064-z
Source DB: PubMed Journal: J Comput Aided Mol Des ISSN: 0920-654X Impact factor: 3.686