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In this work, quantitative structure\u2013activity relationship (QSAR) models for identification of putative inhibitors of LRRK2 protein are developed by using an in-house chemical library and several machine learning techniques. The methodology applied in this paper has two steps: first, alternative subsets of molecular descriptors useful for characterizing LRRK2 inhibitors are chosen by a multi-objective feature selection method; secondly, QSAR models are learned by using these subsets and three different strategies for supervised learning. The qualities of all these QSAR models are compared by classical metrics and the best models are discussed in statistical and physicochemical terms.<\/jats:p>","DOI":"10.1515\/jib-2018-0063","type":"journal-article","created":{"date-parts":[[2019,2,14]],"date-time":"2019-02-14T09:01:10Z","timestamp":1550134870000},"source":"Crossref","is-referenced-by-count":16,"title":["QSAR Modelling to Identify LRRK2 Inhibitors for Parkinson\u2019s Disease"],"prefix":"10.1515","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8248-4496","authenticated-orcid":false,"given":"V\u00edctor","family":"Sebasti\u00e1n-P\u00e9rez","sequence":"first","affiliation":[{"name":"Centro de Investigaciones Biol\u00f3gicas (CIB-CSIC) , Ramiro de Maeztu 9 , 28040 Madrid , Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0443-5795","authenticated-orcid":false,"given":"Mar\u00eda Jimena","family":"Mart\u00ednez","sequence":"additional","affiliation":[{"name":"Instituto de Ciencias e Ingenier\u00eda de la Computaci\u00f3n (UNS\u2013CONICET), Departamento de Ciencias e Ingenier\u00eda de la Computaci\u00f3n , Universidad Nacional del Sur (UNS) , Bah\u00eda Blanca , Argentina"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3882-6081","authenticated-orcid":false,"given":"Carmen","family":"Gil","sequence":"additional","affiliation":[{"name":"Centro de Investigaciones Biol\u00f3gicas (CIB-CSIC) , Ramiro de Maeztu 9 , 28040 Madrid , Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9948-2665","authenticated-orcid":false,"given":"Nuria Eugenia","family":"Campillo","sequence":"additional","affiliation":[{"name":"Centro de Investigaciones Biol\u00f3gicas (CIB-CSIC) , Ramiro de Maeztu 9 , 28040 Madrid , Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2707-8110","authenticated-orcid":false,"given":"Ana","family":"Mart\u00ednez","sequence":"additional","affiliation":[{"name":"Centro de Investigaciones Biol\u00f3gicas (CIB-CSIC) , Ramiro de Maeztu 9 , 28040 Madrid , Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6923-9592","authenticated-orcid":false,"given":"Ignacio","family":"Ponzoni","sequence":"additional","affiliation":[{"name":"Instituto de Ciencias e Ingenier\u00eda de la Computaci\u00f3n (UNS\u2013CONICET), Departamento de Ciencias e Ingenier\u00eda de la Computaci\u00f3n , Universidad Nacional del Sur (UNS) , Bah\u00eda Blanca , Argentina"}]}],"member":"374","published-online":{"date-parts":[[2019,2,14]]},"reference":[{"key":"2023033120511948799_j_jib-2018-0063_ref_001_w2aab3b7b1b1b6b1ab1b5b1Aa","doi-asserted-by":"crossref","unstructured":"Zimprich A, Biskup S, Leitner P, Lichtner P, Farrer M, Lincoln S, et al. 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