QSAR-Co-X: an open source toolkit for multitarget QSAR modelling

• Tipo: Artigo em Revista Científica Internacional
• Data: 2021

Autores

Halder, AK (Autor) Outra; Natalia N D S Cordeiro (Autor) FCUP

Revista

A Revista está pendente de validação pelos Serviços Administrativos.

Título: JOURNAL OF CHEMINFORMATICS

Vol. 13

ISSN: 1758-2946

Indexação

ISI Web of Knowledge - 11 Citações

Scopus - 12 Citações

Outras Informações

ID Authenticus: P-00T-V3M

DOI: 10.1186/s13321-021-00508-0

Abstract (EN): Quantitative structure activity relationships (QSAR) modelling is a well-known computational tool, often used in a wide variety of applications. Yet one of the major drawbacks of conventional QSAR modelling is that models are set up based on a limited number of experimental and/or theoretical conditions. To overcome this, the so-called multitasking or multitarget QSAR (mt-QSAR) approaches have emerged as new computational tools able to integrate diverse chemical and biological data into a single model equation, thus extending and improving the reliability of this type of modelling. We have developed QSAR-Co-X, an open source python-based toolkit (available to download at ) for supporting mt-QSAR modelling following the Box-Jenkins moving average approach. The new toolkit embodies several functionalities for dataset selection and curation plus computation of descriptors, for setting up linear and non-linear models, as well as for a comprehensive results analysis. The workflow within this toolkit is guided by a cohort of multiple statistical parameters and graphical outputs onwards assessing both the predictivity and the robustness of the derived mt-QSAR models. To monitor and demonstrate the functionalities of the designed toolkit, four case-studies pertaining to previously reported datasets are examined here. We believe that this new toolkit, along with our previously launched QSAR-Co code, will significantly contribute to make mt-QSAR modelling widely and routinely applicable.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 18