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Convex-PL: a novel knowledge-based potential for protein-ligand interactions deduced from structural databases using convex optimization

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Abstract

We present a novel optimization approach to train a free-shape distance-dependent protein-ligand scoring function called Convex-PL. We do not impose any functional form of the scoring function. Instead, we decompose it into a polynomial basis and deduce the expansion coefficients from the structural knowledge base using a convex formulation of the optimization problem. Also, for the training set we do not generate false poses with molecular docking packages, but use constant RMSD rigid-body deformations of the ligands inside the binding pockets. This allows the obtained scoring function to be generally applicable to scoring of structural ensembles generated with different docking methods. We assess the Convex-PL scoring function using data from D3R Grand Challenge 2 submissions and the docking test of the CASF 2013 study. We demonstrate that our results outperform the other 20 methods previously assessed in CASF 2013. The method is available at http://team.inria.fr/nano-d/software/Convex-PL/.

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Acknowledgements

The authors thank Georgy Cheremovskiy from Moscow Institute of Physics and Technology for the initial development of the potential, and Georgy Derevyanko from Concordia University who proposed the initial formulation of the optimization problem. The authors also thank Valentin Gordeliy from IBS Grenoble, and Vladimir Chupin and Petr Popov from MIPT Moscow for fruitful discussions during this work. This work was partially supported by RSF research Project 14-14-00995.

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Authors and Affiliations

  1. LJK, University of Grenoble Alpes, 38000, Grenoble, France

    Maria Kadukova & Sergei Grudinin

  2. LJK, CNRS, 38000, Grenoble, France

    Maria Kadukova & Sergei Grudinin

  3. Inria, 38000, Grenoble, France

    Maria Kadukova & Sergei Grudinin

  4. Moscow Institute of Physics and Technology, Dolgoprudniy, Russia, 141700

    Maria Kadukova

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  1. Maria Kadukova
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Correspondence to Sergei Grudinin.

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Kadukova, M., Grudinin, S. Convex-PL: a novel knowledge-based potential for protein-ligand interactions deduced from structural databases using convex optimization. J Comput Aided Mol Des 31, 943–958 (2017). https://doi.org/10.1007/s10822-017-0068-8

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