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5-HT1A_affinity_prediction_model - Mordred descriptors 2D

Affinity prediction model for 5-HT1A ligands, based on curated database (merged ZINC and ChEMBL databases)

  • QSAR models were obtained with AutoML H2O package.

  • In attached files, there are curated database (information of id, SMILES and pKi - affinity vaue) and two prediction models of pKi affinity for the serotonin 5-HT1A receptor based on 216 and 39 Mordred descriptors.

Descriptions of curated database and model based on 216 descriptors are presented in article: Czub N, Pacławski A, Szlęk J, Mendyk A. Curated Database and Preliminary AutoML QSAR Model for 5-HT1A Receptor. Pharmaceutics. 2021; 13(10):1711. https://doi.org/10.3390/pharmaceutics13101711

The curated database with mordred descriptors is avaiable with this link: https://ujchmura-my.sharepoint.com/:t:/g/personal/natalia_czub_doctoral_uj_edu_pl/EUiNFyevAwdJrQuo_1yMyo0Bxt5BljodIgJjKxbHPo5-rg

Prediction model is avaiable with this link (216 descriptors): https://ujchmura-my.sharepoint.com/:u:/g/personal/natalia_czub_doctoral_uj_edu_pl/EQ8mCwbyIqxEi3rydnrjCVUBS0Hag-VC6FX-T75toyKacw

  • Prediction model with 39 descriptors is in folder: 39in_AutoML_H2O_model

Model based on 39 descriptors is describe in out article according to the OECD Principles of valid QSAR model: Czub N, Pacławski A, Szlęk J, Mendyk A. Do AutoML-Based QSAR Models Fulfill OECD Principles for Regulatory Assessment? A 5-HT1A Receptor Case. Pharmaceutics. 2022; 14(7):1415. https://doi.org/10.3390/pharmaceutics14071415

5-HT1A_affinity_prediction_model - Fingerprints and descriptors

Affinity prediction model for 5-HT1A ligands, based on curated database (merged ZINC and ChEMBL databases). QSAR models were obtained thanks to AutoML tool - mljar (https://github.com/mljar/mljar-supervised)

Due to large size of mljar's models, models are available with links presented below:

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Affinity prediction model for 5-HT1A ligands

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