Maltarollo, Vinícius Gonçalves; Araujo, Sheila Cruz; Trossini, Gustavo Henrique Goulart 
; Honorio, Káthia Maria
Source: Future Medicinal Chemistry. Unidades: EACH, FCF
Subjects: DIABETES MELLITUS, RELAÇÕES QUANTITATIVAS ENTRE ESTRUTURA QUÍMICA E ATIVIDADE BIOLÓGICA, MODELAGEM MOLECULAR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MALTAROLLO, Vinícius Gonçalves et al. Understanding PPAR-δ affinity and selectivity using hologram quantitative structure–activity modeling, molecular docking and GRID calculations. Future Medicinal Chemistry, v. 8, n. 16, p. 1913-1926, 2016Tradução . . Disponível em: https://doi.org/10.4155/fmc-2016-0061. Acesso em: 08 ago. 2024.APA
Maltarollo, V. G., Araujo, S. C., Trossini, G. H. G., & Honorio, K. M. (2016). Understanding PPAR-δ affinity and selectivity using hologram quantitative structure–activity modeling, molecular docking and GRID calculations. Future Medicinal Chemistry, 8( 16), 1913-1926. doi:10.4155/fmc-2016-0061NLM
Maltarollo VG, Araujo SC, Trossini GHG, Honorio KM. Understanding PPAR-δ affinity and selectivity using hologram quantitative structure–activity modeling, molecular docking and GRID calculations [Internet]. Future Medicinal Chemistry. 2016 ; 8( 16): 1913-1926.[citado 2024 ago. 08 ] Available from: https://doi.org/10.4155/fmc-2016-0061Vancouver
Maltarollo VG, Araujo SC, Trossini GHG, Honorio KM. Understanding PPAR-δ affinity and selectivity using hologram quantitative structure–activity modeling, molecular docking and GRID calculations [Internet]. Future Medicinal Chemistry. 2016 ; 8( 16): 1913-1926.[citado 2024 ago. 08 ] Available from: https://doi.org/10.4155/fmc-2016-0061
