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Jiménez-Luna J, Cuzzolin A, Bolcato G, et al. A Deep-Learning Approach toward Rational Molecular Docking Protocol Selection. Molecules. 2020;25(11)doi: 10.3390/molecules25112487.
Jiménez-Luna, J., Cuzzolin, A., Bolcato, G., Sturlese, M., & Moro, S. (2020). A Deep-Learning Approach toward Rational Molecular Docking Protocol Selection. Molecules (Basel, Switzerland), 25(11), . https://doi.org/10.3390/molecules25112487
Jiménez-Luna, José, et al. "A Deep-Learning Approach toward Rational Molecular Docking Protocol Selection." Molecules (Basel, Switzerland) vol. 25,11 (2020). doi: https://doi.org/10.3390/molecules25112487
Jiménez-Luna J, Cuzzolin A, Bolcato G, Sturlese M, Moro S. A Deep-Learning Approach toward Rational Molecular Docking Protocol Selection. Molecules. 2020 May 27;25(11). doi: 10.3390/molecules25112487. PMID: 32471211; PMCID: PMC7321124.
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Molecules. 2020 May 27;25(11). doi: 10.3390/molecules25112487.

A Deep-Learning Approach toward Rational Molecular Docking Protocol Selection.

Molecules (Basel, Switzerland)

José Jiménez-Luna, Alberto Cuzzolin, Giovanni Bolcato, Mattia Sturlese, Stefano Moro

Affiliations

  1. Department of Chemistry and Applied Biosciences, RETHINK, ETH Zuerich, Vladimir-Prelog-Weg 4, 8093 Zuerich, Switzerland.
  2. Institute for Pure & Applied Mathematics, University California Los Angeles, 460 Portola Plaza, Los Angeles, CA 90095-7121, USA.
  3. Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padova, 35131 Padova, Italy.

PMID: 32471211 PMCID: PMC7321124 DOI: 10.3390/molecules25112487

Abstract

While a plethora of different protein-ligand docking protocols have been developed over the past twenty years, their performances greatly depend on the provided input protein-ligand pair. In this study, we developed a machine-learning model that uses a combination of convolutional and fully connected neural networks for the task of predicting the performance of several popular docking protocols given a protein structure and a small compound. We also rigorously evaluated the performance of our model using a widely available database of protein-ligand complexes and different types of data splits. We further open-source all code related to this study so that potential users can make informed selections on which protocol is best suited for their particular protein-ligand pair.

Keywords: chemoinformatics; deep learning; molecular docking; structural biology

References

  1. Nucleic Acids Res. 2004 Jan 1;32(Database issue):D138-41 - PubMed
  2. J Cheminform. 2017 Jun 12;9(1):37 - PubMed
  3. J Med Chem. 2004 Mar 25;47(7):1739-49 - PubMed
  4. J Comput Aided Mol Des. 2016 Sep;30(9):773-789 - PubMed
  5. J Chem Inf Model. 2013 Apr 22;53(4):783-90 - PubMed
  6. Chem Sci. 2019 Oct 16;10(47):10911-10918 - PubMed
  7. J Chem Inf Model. 2019 Mar 25;59(3):1205-1214 - PubMed
  8. J Chem Theory Comput. 2016 Apr 12;12(4):1845-52 - PubMed
  9. J Chem Inf Model. 2017 Apr 24;57(4):942-957 - PubMed
  10. J Chem Inf Model. 2020 Mar 3;: - PubMed
  11. Int J Mol Sci. 2019 Jul 20;20(14): - PubMed
  12. Chemistry. 2017 May 2;23(25):5966-5971 - PubMed
  13. J Chem Inf Model. 2009 Jan;49(1):84-96 - PubMed
  14. J Comput Aided Mol Des. 2018 Jan;32(1):251-264 - PubMed
  15. Nature. 2015 May 28;521(7553):436-44 - PubMed
  16. Proteins. 2006 Oct 1;65(1):15-26 - PubMed
  17. Bioinformatics. 2020 Apr 1;36(7):2113-2118 - PubMed
  18. Bioinformatics. 2015 Feb 1;31(3):405-12 - PubMed
  19. Chem Cent J. 2008 Mar 09;2:5 - PubMed
  20. Proteins. 2003 Sep 1;52(4):609-23 - PubMed
  21. Bioinformatics. 2017 Oct 1;33(19):3036-3042 - PubMed
  22. Chem Sci. 2017 Oct 31;9(2):513-530 - PubMed
  23. Molecules. 2015 May 29;20(6):9977-93 - PubMed
  24. J Comput Aided Mol Des. 2018 Jan;32(1):1-20 - PubMed
  25. Curr Top Med Chem. 2008;8(18):1555-72 - PubMed
  26. J Chem Inf Model. 2014 Aug 25;54(8):2243-54 - PubMed
  27. Nature. 2018 Mar 28;555(7698):604-610 - PubMed
  28. J Med Chem. 2004 Jun 3;47(12):2977-80 - PubMed
  29. J Comput Chem. 2010 Jan 30;31(2):455-61 - PubMed
  30. J Chem Inf Model. 2019 Mar 25;59(3):1172-1181 - PubMed
  31. J Chem Inf Model. 2010 Nov 22;50(11):1961-9 - PubMed
  32. J Chem Inf Model. 2010 May 24;50(5):742-54 - PubMed
  33. Nat Rev Drug Discov. 2004 Nov;3(11):935-49 - PubMed
  34. J Comput Aided Mol Des. 2016 Sep;30(9):651-668 - PubMed
  35. Proteins. 2003 Nov 15;53(3):693-707 - PubMed
  36. J Comput Aided Mol Des. 2016 Aug;30(8):595-608 - PubMed
  37. ACS Cent Sci. 2018 Feb 28;4(2):268-276 - PubMed
  38. ACS Cent Sci. 2018 Nov 28;4(11):1520-1530 - PubMed
  39. J Mol Recognit. 1996 Jan-Feb;9(1):1-5 - PubMed
  40. J Comput Aided Mol Des. 2019 Jan;33(1):1-18 - PubMed

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