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Lessons learned from participating in D3R 2016 Grand Challenge 2: compounds targeting the farnesoid X receptor

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Abstract

D3R 2016 Grand Challenge 2 focused on predictions of binding modes and affinities for 102 compounds against the farnesoid X receptor (FXR). In this challenge, two distinct methods, a docking-based method and a template-based method, were employed by our team for the binding mode prediction. For the new template-based method, 3D ligand similarities were calculated for each query compound against the ligands in the co-crystal structures of FXR available in Protein Data Bank. The binding mode was predicted based on the co-crystal protein structure containing the ligand with the best ligand similarity score against the query compound. For the FXR dataset, the template-based method achieved a better performance than the docking-based method on the binding mode prediction. For the binding affinity prediction, an in-house knowledge-based scoring function ITScore2 and MM/PBSA approach were employed. Good performance was achieved for MM/PBSA, whereas the performance of ITScore2 was sensitive to ligand composition, e.g. the percentage of carbon atoms in the compounds. The sensitivity to ligand composition could be a clue for the further improvement of our knowledge-based scoring function.

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Acknowledgements

Support to XZ from OpenEye Scientific Software Inc. (Santa Fe, NM, http://www.eyesopen.com) is gratefully acknowledged. This work was supported by the NSF CAREER Award DBI-0953839, NIH R01GM109980, and American Heart Association (Midwest Affiliate) 13GRNT16990076 to XZ. The computations were performed on the high performance computing infrastructure supported by NSF CNS-1429294 (PI: Chi-Ren Shyu) and the HPC resources supported by the University of Missouri Bioinformatics Consortium (UMBC).

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  1. Rui Duan and Xianjin Xu have contributed equally to this work.

Authors and Affiliations

  1. Dalton Cardiovascular Research Center, University of Missouri, Columbia, MO, 65211, USA

    Rui Duan, Xianjin Xu & Xiaoqin Zou

  2. Department of Physics and Astronomy, University of Missouri, Columbia, MO, 65211, USA

    Rui Duan, Xianjin Xu & Xiaoqin Zou

  3. Department of Biochemistry, University of Missouri, Columbia, MO, 65211, USA

    Rui Duan, Xianjin Xu & Xiaoqin Zou

  4. Informatics Institute, University of Missouri, Columbia, MO, 65211, USA

    Rui Duan, Xianjin Xu & Xiaoqin Zou

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  1. Rui Duan
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Correspondence to Xiaoqin Zou.

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Duan, R., Xu, X. & Zou, X. Lessons learned from participating in D3R 2016 Grand Challenge 2: compounds targeting the farnesoid X receptor. J Comput Aided Mol Des 32, 103–111 (2018). https://doi.org/10.1007/s10822-017-0082-x

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