• Corpus ID: 227151667

Lipophilicity Prediction with Multitask Learning and Molecular Substructures Representation

@article{Lukashina2020LipophilicityPW,
  title={Lipophilicity Prediction with Multitask Learning and Molecular Substructures Representation},
  author={Nina Lukashina and Alisa Alenicheva and Elizaveta M. Vlasova and Artem Kondiukov and Aigul Khakimova and Emil Magerramov and Nikita Churikov and Aleksei Shpilman},
  journal={ArXiv},
  year={2020},
  volume={abs/2011.12117}
}
Lipophilicity is one of the factors determining the permeability of the cell membrane to a drug molecule. Hence, accurate lipophilicity prediction is an essential step in the development of new drugs. In this paper, we introduce a novel approach to encoding additional graph information by extracting molecular substructures. By adding a set of generalized atomic features of these substructures to an established Direct Message Passing Neural Network (D-MPNN) we were able to achieve a new state-of… 

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