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A Fast and Interpretable Deep Learning Approach for Accurate Electrostatics-Driven pKa Predictions in Proteins.
Reis, Pedro B P S; Bertolini, Marco; Montanari, Floriane; Rocchia, Walter; Machuqueiro, Miguel; Clevert, Djork-Arné.
Affiliation
  • Reis PBPS; Machine Learning Research, Bayer A.G., Berlin 13353, Germany.
  • Bertolini M; Machine Learning Research, Bayer A.G., Berlin 13353, Germany.
  • Montanari F; Machine Learning Research, Bayer A.G., Berlin 13353, Germany.
  • Rocchia W; CONCEPT Lab, Istituto Italiano di Tecnologia (IIT), Via Melen 83, B Block, Genoa 16152, Italy.
  • Machuqueiro M; Biosystems and Integrative Sciences Institute (BioISI), Faculty of Sciences, University of Lisboa, Campo Grande, Lisboa 1749-016, Portugal.
  • Clevert DA; Machine Learning Research, Bayer A.G., Berlin 13353, Germany.
J Chem Theory Comput ; 18(8): 5068-5078, 2022 Aug 09.
Article in En | MEDLINE | ID: mdl-35837736
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: J Chem Theory Comput Year: 2022 Document type: Article Affiliation country: Alemania Country of publication: Estados Unidos
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: J Chem Theory Comput Year: 2022 Document type: Article Affiliation country: Alemania Country of publication: Estados Unidos