Application of Associative Neural Networks for Prediction of Lipophilicity in ALOGPS 2.1 Program

By Igor V. Tetko, V. Tanchuk. Journal of chemical information and computer sciences, 2002

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The development of models to predict melting and pyrolysis point data associated with several hundred thousand compounds mined from PATENTS (2016, methodology): “1 program [79], which is also available as part of the OCHEM descriptors.”
A renaissance of neural networks in drug discovery (2016, methodology): “For example, the ALOGPS 2.1 program was initially developed to predict octanol/ water partition coefficients using organic molecules only [68].”
DrugBank: a knowledgebase for drugs, drug actions and drug targets (2007, background): “Specifically, these new data fields include: (i) a primary accession number; (ii) a secondary accession number; (iii) drug synonyms; (iv) a compound description; (v) drug brand names; (vi) SwissProt name (if the drug is a peptide/protein drug); (vii) monoisotopic molecular weight; (viii) isomeric SM”
Can we estimate the accuracy of ADME-Tox predictions? (2006, methodology): “A similarity function between molecules is then introduced as a rank correlation between these vectors (see also ref. [ 51 ] for other measures).”
In silico methods and tools for drug discovery (2021, methodology): “These models include PreADMET [213], ALOGPS [214], SwissADME [215], and DrugMint [216].”