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Artigo de periodico
MASSA Algorithm: automated rational sampling of training and test subsets for QSAR modelling (2023)
Veríssimo, Gabriel Corrêa ; Simone Queiroz Panteleão; Gertrudes, Jadson Castro ; Kronenberger, Thales ; Honorio, Kathia Maria ; Maltarollo, Vinícius Gonçalves
Source: Journal of Computer - Aided Molecular Design. Unidade: EACH
Assunto: AMOSTRAGEM
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VERÍSSIMO, Gabriel Corrêa et al. MASSA Algorithm: automated rational sampling of training and test subsets for QSAR modelling. Journal of Computer - Aided Molecular Design, p. 01-26, 2023Tradução . . Disponível em: http://dx.doi.org/10.1007/s10822-023-00536-y. Acesso em: 23 maio 2024.
APA
Veríssimo, G. C., Simone Queiroz Panteleão,, Gertrudes, J. C., Kronenberger, T., Honorio, K. M., & Maltarollo, V. G. (2023). MASSA Algorithm: automated rational sampling of training and test subsets for QSAR modelling. Journal of Computer - Aided Molecular Design, 01-26. doi:10.1007/s10822-023-00536-y
NLM
Veríssimo GC, Simone Queiroz Panteleão, Gertrudes JC, Kronenberger T, Honorio KM, Maltarollo VG. MASSA Algorithm: automated rational sampling of training and test subsets for QSAR modelling [Internet]. Journal of Computer - Aided Molecular Design. 2023 ; 01-26.[citado 2024 maio 23 ] Available from: http://dx.doi.org/10.1007/s10822-023-00536-y
Vancouver
Veríssimo GC, Simone Queiroz Panteleão, Gertrudes JC, Kronenberger T, Honorio KM, Maltarollo VG. MASSA Algorithm: automated rational sampling of training and test subsets for QSAR modelling [Internet]. Journal of Computer - Aided Molecular Design. 2023 ; 01-26.[citado 2024 maio 23 ] Available from: http://dx.doi.org/10.1007/s10822-023-00536-y
Artigo de periodico
The importance of good practices and false hits for QSAR-driven virtual screening real application: a SARS-CoV-2 main protease (Mpro) case study (2023)
Serafim, Mateus Sá Magalhães ; Pantaleão, Simone Queiroz ; Silva, Elany Barbosa da ; McKerrow, James H. ; O’Donoghue, Anthony J. ; Mota, Bruno Eduardo Fernandes; Honorio, Kathia Maria ; Maltarollo, Vinícius Gonçalves
Source: Frontiers in Drug Discovery. Unidade: EACH
Assunto: INIBIÇÃO
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SERAFIM, Mateus Sá Magalhães et al. The importance of good practices and false hits for QSAR-driven virtual screening real application: a SARS-CoV-2 main protease (Mpro) case study. Frontiers in Drug Discovery, v. 3, p. 01-18, 2023Tradução . . Disponível em: https://doi.org/10.3389/fddsv.2023.1237655. Acesso em: 23 maio 2024.
APA
Serafim, M. S. M., Pantaleão, S. Q., Silva, E. B. da, McKerrow, J. H., O’Donoghue, A. J., Mota, B. E. F., et al. (2023). The importance of good practices and false hits for QSAR-driven virtual screening real application: a SARS-CoV-2 main protease (Mpro) case study. Frontiers in Drug Discovery, 3, 01-18. doi:10.3389/fddsv.2023.1237655
NLM
Serafim MSM, Pantaleão SQ, Silva EB da, McKerrow JH, O’Donoghue AJ, Mota BEF, Honorio KM, Maltarollo VG. The importance of good practices and false hits for QSAR-driven virtual screening real application: a SARS-CoV-2 main protease (Mpro) case study [Internet]. Frontiers in Drug Discovery. 2023 ; 3 01-18.[citado 2024 maio 23 ] Available from: https://doi.org/10.3389/fddsv.2023.1237655
Vancouver
Serafim MSM, Pantaleão SQ, Silva EB da, McKerrow JH, O’Donoghue AJ, Mota BEF, Honorio KM, Maltarollo VG. The importance of good practices and false hits for QSAR-driven virtual screening real application: a SARS-CoV-2 main protease (Mpro) case study [Internet]. Frontiers in Drug Discovery. 2023 ; 3 01-18.[citado 2024 maio 23 ] Available from: https://doi.org/10.3389/fddsv.2023.1237655
Artigo de periodico
Recent advances in the prediction of pharmacokinetics properties in drug design studies: a review (2022)
Pantaleão, Simone Queiroz ; Fernandes, Philipe O.; Gonçalves, José Eduardo; Maltarollo, Vinícius Gonçalves ; Honorio, Kathia Maria
Source: ChemMedChem: chemistry enabling drug discovery. Unidade: EACH
Subjects: FARMACOCINÉTICA, PLANEJAMENTO DE FÁRMACOS, TECNOLOGIA FARMACÊUTICA
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PANTALEÃO, Simone Queiroz et al. Recent advances in the prediction of pharmacokinetics properties in drug design studies: a review. ChemMedChem: chemistry enabling drug discovery, v. 17, p. 01-13, 2022Tradução . . Disponível em: https://doi.org/10.1002/cmdc.202100542. Acesso em: 23 maio 2024.
APA
Pantaleão, S. Q., Fernandes, P. O., Gonçalves, J. E., Maltarollo, V. G., & Honorio, K. M. (2022). Recent advances in the prediction of pharmacokinetics properties in drug design studies: a review. ChemMedChem: chemistry enabling drug discovery, 17, 01-13. doi:10.1002/cmdc.202100542
NLM
Pantaleão SQ, Fernandes PO, Gonçalves JE, Maltarollo VG, Honorio KM. Recent advances in the prediction of pharmacokinetics properties in drug design studies: a review [Internet]. ChemMedChem: chemistry enabling drug discovery. 2022 ; 17 01-13.[citado 2024 maio 23 ] Available from: https://doi.org/10.1002/cmdc.202100542
Vancouver
Pantaleão SQ, Fernandes PO, Gonçalves JE, Maltarollo VG, Honorio KM. Recent advances in the prediction of pharmacokinetics properties in drug design studies: a review [Internet]. ChemMedChem: chemistry enabling drug discovery. 2022 ; 17 01-13.[citado 2024 maio 23 ] Available from: https://doi.org/10.1002/cmdc.202100542
Artigo de periodico
Study of the CuII Affinity by Three Chelating Agents of Biological Interest: TPEN, TRIEN and Et2DTC (2021)
Valle, Eliana Maíra Agostini ; Maltarollo, Vinícius Gonçalves ; Princhak, Thiago C.; Honório, Káthia Maria ; Cerchiaro, Giselle
Source: Journal of the Brazilian Chemical Society. Unidade: EACH
Subjects: COBRE, MODELAGEM MOLECULAR, ESPECTROSCOPIA
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VALLE, Eliana Maíra Agostini et al. Study of the CuII Affinity by Three Chelating Agents of Biological Interest: TPEN, TRIEN and Et2DTC. Journal of the Brazilian Chemical Society, v. 32, n. 4, p. 732-740, 2021Tradução . . Disponível em: https://doi.org/10.21577/0103-5053.20200225. Acesso em: 23 maio 2024.
APA
Valle, E. M. A., Maltarollo, V. G., Princhak, T. C., Honório, K. M., & Cerchiaro, G. (2021). Study of the CuII Affinity by Three Chelating Agents of Biological Interest: TPEN, TRIEN and Et2DTC. Journal of the Brazilian Chemical Society, 32( 4), 732-740. doi:10.21577/0103-5053.20200225
NLM
Valle EMA, Maltarollo VG, Princhak TC, Honório KM, Cerchiaro G. Study of the CuII Affinity by Three Chelating Agents of Biological Interest: TPEN, TRIEN and Et2DTC [Internet]. Journal of the Brazilian Chemical Society. 2021 ; 32( 4): 732-740.[citado 2024 maio 23 ] Available from: https://doi.org/10.21577/0103-5053.20200225
Vancouver
Valle EMA, Maltarollo VG, Princhak TC, Honório KM, Cerchiaro G. Study of the CuII Affinity by Three Chelating Agents of Biological Interest: TPEN, TRIEN and Et2DTC [Internet]. Journal of the Brazilian Chemical Society. 2021 ; 32( 4): 732-740.[citado 2024 maio 23 ] Available from: https://doi.org/10.21577/0103-5053.20200225
Artigo de periodico
Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade (2021)
Serafim, Mateus Sá Magalhães; Júnior, Valtair Severino dos Santos; Gertrudes, Jadson Castro; Maltarollo, Vinícius Gonçalves; Honorio, Kathia Maria
Source: EXPERT OPINION ON DRUG DISCOVERY. Unidade: EACH
Subjects: ANTIVIRAIS, PLANEJAMENTO DE FÁRMACOS, COMPUTAÇÃO APLICADA
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SERAFIM, Mateus Sá Magalhães et al. Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade. EXPERT OPINION ON DRUG DISCOVERY, v. 16, n. 9, p. 961-975, 2021Tradução . . Disponível em: https://doi.org/10.1080/17460441.2021.1918098. Acesso em: 23 maio 2024.
APA
Serafim, M. S. M., Júnior, V. S. dos S., Gertrudes, J. C., Maltarollo, V. G., & Honorio, K. M. (2021). Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade. EXPERT OPINION ON DRUG DISCOVERY, 16( 9), 961-975. doi:10.1080/17460441.2021.1918098
NLM
Serafim MSM, Júnior VS dos S, Gertrudes JC, Maltarollo VG, Honorio KM. Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade [Internet]. EXPERT OPINION ON DRUG DISCOVERY. 2021 ; 16( 9): 961-975.[citado 2024 maio 23 ] Available from: https://doi.org/10.1080/17460441.2021.1918098
Vancouver
Serafim MSM, Júnior VS dos S, Gertrudes JC, Maltarollo VG, Honorio KM. Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade [Internet]. EXPERT OPINION ON DRUG DISCOVERY. 2021 ; 16( 9): 961-975.[citado 2024 maio 23 ] Available from: https://doi.org/10.1080/17460441.2021.1918098
Artigo de periodico
Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates (2021)
Serafim, Mateus Sá Magalhães ; Gertrudes, Jadson Castro ; Costa, Debora M.A.; Oliveira, Patrícia Rufino; Maltarollo, Vinícius Gonçalves ; Honório, Káthia Maria
Source: Bioscience Reports. Unidade: EACH
Subjects: COVID-19, INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, PLANEJAMENTO DE FÁRMACOS, QUÍMICA MÉDICA
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SERAFIM, Mateus Sá Magalhães et al. Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates. Bioscience Reports, v. 41, n. 3, p. 01-16, 2021Tradução . . Disponível em: https://doi.org/10.1042/BSR20202616. Acesso em: 23 maio 2024.
APA
Serafim, M. S. M., Gertrudes, J. C., Costa, D. M. A., Oliveira, P. R., Maltarollo, V. G., & Honório, K. M. (2021). Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates. Bioscience Reports, 41( 3), 01-16. doi:10.1042/BSR20202616
NLM
Serafim MSM, Gertrudes JC, Costa DMA, Oliveira PR, Maltarollo VG, Honório KM. Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates [Internet]. Bioscience Reports. 2021 ; 41( 3): 01-16.[citado 2024 maio 23 ] Available from: https://doi.org/10.1042/BSR20202616
Vancouver
Serafim MSM, Gertrudes JC, Costa DMA, Oliveira PR, Maltarollo VG, Honório KM. Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates [Internet]. Bioscience Reports. 2021 ; 41( 3): 01-16.[citado 2024 maio 23 ] Available from: https://doi.org/10.1042/BSR20202616
Artigo de periodico
Advances and Perspectives in Applying Deep Learning for Drug Design and Discovery (2019)
Lipinski, Célio Fernando ; Maltarollo, Vinícius Gonçalves ; Oliveira, Patrícia Rufino; Silva, Alberico Borges Ferreira da ; Honório, Káthia Maria
Source: Frontiers in Robotics and AI. Unidades: IQSC, EACH
Subjects: INTELIGÊNCIA ARTIFICIAL, QUÍMICA MÉDICA, QUÍMICA FARMACÊUTICA, PLANEJAMENTO DE FÁRMACOS
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LIPINSKI, Célio Fernando et al. Advances and Perspectives in Applying Deep Learning for Drug Design and Discovery. Frontiers in Robotics and AI, v. no 2019, p. 01-06, 2019Tradução . . Disponível em: https://doi.org/10.3389/frobt.2019.00108. Acesso em: 23 maio 2024.
APA
Lipinski, C. F., Maltarollo, V. G., Oliveira, P. R., Silva, A. B. F. da, & Honório, K. M. (2019). Advances and Perspectives in Applying Deep Learning for Drug Design and Discovery. Frontiers in Robotics and AI, no 2019, 01-06. doi:10.3389/frobt.2019.00108
NLM
Lipinski CF, Maltarollo VG, Oliveira PR, Silva ABF da, Honório KM. Advances and Perspectives in Applying Deep Learning for Drug Design and Discovery [Internet]. Frontiers in Robotics and AI. 2019 ; no 2019 01-06.[citado 2024 maio 23 ] Available from: https://doi.org/10.3389/frobt.2019.00108
Vancouver
Lipinski CF, Maltarollo VG, Oliveira PR, Silva ABF da, Honório KM. Advances and Perspectives in Applying Deep Learning for Drug Design and Discovery [Internet]. Frontiers in Robotics and AI. 2019 ; no 2019 01-06.[citado 2024 maio 23 ] Available from: https://doi.org/10.3389/frobt.2019.00108
Artigo de periodico
On the relationship of anthranilic derivatives structure and the FXR (Farnesoid X receptor) agonist activity (2018)
Kronenberger, Thales ; Windshügel, Björn ; Wrenger, Carsten ; Honório, Káthia Maria ; Maltarollo, Vinícius Gonçalves
Source: Journal of Biomolecular Structure & Dynamics. Unidades: ICB, EACH
Subjects: PARASITOLOGIA, HOMEOSTASE, DOENÇAS METABÓLICAS
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KRONENBERGER, Thales et al. On the relationship of anthranilic derivatives structure and the FXR (Farnesoid X receptor) agonist activity. Journal of Biomolecular Structure & Dynamics, v. 36, n. 16, p. 4378–4391, 2018Tradução . . Disponível em: https://doi.org/10.1080/07391102.2017.1417161. Acesso em: 23 maio 2024.
APA
Kronenberger, T., Windshügel, B., Wrenger, C., Honório, K. M., & Maltarollo, V. G. (2018). On the relationship of anthranilic derivatives structure and the FXR (Farnesoid X receptor) agonist activity. Journal of Biomolecular Structure & Dynamics, 36( 16), 4378–4391. doi:10.1080/07391102.2017.1417161
NLM
Kronenberger T, Windshügel B, Wrenger C, Honório KM, Maltarollo VG. On the relationship of anthranilic derivatives structure and the FXR (Farnesoid X receptor) agonist activity [Internet]. Journal of Biomolecular Structure & Dynamics. 2018 ; 36( 16): 4378–4391.[citado 2024 maio 23 ] Available from: https://doi.org/10.1080/07391102.2017.1417161
Vancouver
Kronenberger T, Windshügel B, Wrenger C, Honório KM, Maltarollo VG. On the relationship of anthranilic derivatives structure and the FXR (Farnesoid X receptor) agonist activity [Internet]. Journal of Biomolecular Structure & Dynamics. 2018 ; 36( 16): 4378–4391.[citado 2024 maio 23 ] Available from: https://doi.org/10.1080/07391102.2017.1417161
Artigo de periodico
Advances and challenges in drug design of PPARδ ligands (2018)
Maltarollo, Vinícius Gonçalves ; Kronenberger, Thales ; Windshuegel, Bjoern ; Wrenger, Carsten ; Trossini, Gustavo Henrique Goulart ; Honório, Káthia Maria
Source: Current Drug Targets. Unidades: ICB, FCF, EACH
Subjects: DIABETES MELLITUS NÃO INSULINO-DEPENDENTE, SÍNDROME X METABÓLICA, ÁCIDOS GRAXOS, DOENÇAS METABÓLICAS, PARASITOLOGIA
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MALTAROLLO, Vinícius Gonçalves et al. Advances and challenges in drug design of PPARδ ligands. Current Drug Targets, v. 19, n. 2, p. 144-154, 2018Tradução . . Disponível em: https://doi.org/10.2174/1389450118666170414113159. Acesso em: 23 maio 2024.
APA
Maltarollo, V. G., Kronenberger, T., Windshuegel, B., Wrenger, C., Trossini, G. H. G., & Honório, K. M. (2018). Advances and challenges in drug design of PPARδ ligands. Current Drug Targets, 19( 2), 144-154. doi:10.2174/1389450118666170414113159
NLM
Maltarollo VG, Kronenberger T, Windshuegel B, Wrenger C, Trossini GHG, Honório KM. Advances and challenges in drug design of PPARδ ligands [Internet]. Current Drug Targets. 2018 ; 19( 2): 144-154.[citado 2024 maio 23 ] Available from: https://doi.org/10.2174/1389450118666170414113159
Vancouver
Maltarollo VG, Kronenberger T, Windshuegel B, Wrenger C, Trossini GHG, Honório KM. Advances and challenges in drug design of PPARδ ligands [Internet]. Current Drug Targets. 2018 ; 19( 2): 144-154.[citado 2024 maio 23 ] Available from: https://doi.org/10.2174/1389450118666170414113159
Artigo de periodico
Studies of Staphylococcus aureus FabI inhibitors: fragment-based approach based on holographic structure–activity relationship analyses (2017)
Kronenberger, Thales; Asse Junior, Leonardo Rander; Wrenger, Carsten ; Trossini, Gustavo Henrique Goulart ; Honorio, Kathia Maria; Maltarollo, Vinícius Gonçalves
Source: Future Medicinal Chemistry. Unidades: EACH, ICB, FCF
Subjects: STAPHYLOCOCCUS, RELAÇÕES QUANTITATIVAS ENTRE ESTRUTURA QUÍMICA E ATIVIDADE BIOLÓGICA, MODELAGEM MOLECULAR
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KRONENBERGER, Thales et al. Studies of Staphylococcus aureus FabI inhibitors: fragment-based approach based on holographic structure–activity relationship analyses. Future Medicinal Chemistry, v. 9, n. 2, p. 135-151, 2017Tradução . . Disponível em: https://doi.org/10.4155/fmc-2016-0179. Acesso em: 23 maio 2024.
APA
Kronenberger, T., Asse Junior, L. R., Wrenger, C., Trossini, G. H. G., Honorio, K. M., & Maltarollo, V. G. (2017). Studies of Staphylococcus aureus FabI inhibitors: fragment-based approach based on holographic structure–activity relationship analyses. Future Medicinal Chemistry, 9( 2), 135-151. doi:10.4155/fmc-2016-0179
NLM
Kronenberger T, Asse Junior LR, Wrenger C, Trossini GHG, Honorio KM, Maltarollo VG. Studies of Staphylococcus aureus FabI inhibitors: fragment-based approach based on holographic structure–activity relationship analyses [Internet]. Future Medicinal Chemistry. 2017 ; 9( 2): 135-151.[citado 2024 maio 23 ] Available from: https://doi.org/10.4155/fmc-2016-0179
Vancouver
Kronenberger T, Asse Junior LR, Wrenger C, Trossini GHG, Honorio KM, Maltarollo VG. Studies of Staphylococcus aureus FabI inhibitors: fragment-based approach based on holographic structure–activity relationship analyses [Internet]. Future Medicinal Chemistry. 2017 ; 9( 2): 135-151.[citado 2024 maio 23 ] Available from: https://doi.org/10.4155/fmc-2016-0179
Artigo de periodico
Study on molecular structure, spectroscopic properties (FTIR and UV–Vis), NBO, QTAIM, HOMO-LUMO energies and docking studies of 5-fluorouracil, a substance used to treat cancer (2017)
Almeida, Michell O.; Barros, Daiane A.S.; Araujo, Sheila Cruz; Faria, Sérgio Henrique Dias Marques; Maltarollo, Vinícius Gonçalves; Honorio, Káthia Maria
Source: Spectrochimica Acta Part A : Molecular and Biomolecular Spectroscopy. Unidade: EACH
Subjects: MODELAGEM MOLECULAR, RELAÇÕES QUANTITATIVAS ENTRE ESTRUTURA QUÍMICA E ATIVIDADE BIOLÓGICA, NEOPLASIAS
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ALMEIDA, Michell O. et al. Study on molecular structure, spectroscopic properties (FTIR and UV–Vis), NBO, QTAIM, HOMO-LUMO energies and docking studies of 5-fluorouracil, a substance used to treat cancer. Spectrochimica Acta Part A : Molecular and Biomolecular Spectroscopy, v. 184, p. 169-176, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.saa.2017.04.070. Acesso em: 23 maio 2024.
APA
Almeida, M. O., Barros, D. A. S., Araujo, S. C., Faria, S. H. D. M., Maltarollo, V. G., & Honorio, K. M. (2017). Study on molecular structure, spectroscopic properties (FTIR and UV–Vis), NBO, QTAIM, HOMO-LUMO energies and docking studies of 5-fluorouracil, a substance used to treat cancer. Spectrochimica Acta Part A : Molecular and Biomolecular Spectroscopy, 184, 169-176. doi:10.1016/j.saa.2017.04.070
NLM
Almeida MO, Barros DAS, Araujo SC, Faria SHDM, Maltarollo VG, Honorio KM. Study on molecular structure, spectroscopic properties (FTIR and UV–Vis), NBO, QTAIM, HOMO-LUMO energies and docking studies of 5-fluorouracil, a substance used to treat cancer [Internet]. Spectrochimica Acta Part A : Molecular and Biomolecular Spectroscopy. 2017 ; 184 169-176.[citado 2024 maio 23 ] Available from: https://doi.org/10.1016/j.saa.2017.04.070
Vancouver
Almeida MO, Barros DAS, Araujo SC, Faria SHDM, Maltarollo VG, Honorio KM. Study on molecular structure, spectroscopic properties (FTIR and UV–Vis), NBO, QTAIM, HOMO-LUMO energies and docking studies of 5-fluorouracil, a substance used to treat cancer [Internet]. Spectrochimica Acta Part A : Molecular and Biomolecular Spectroscopy. 2017 ; 184 169-176.[citado 2024 maio 23 ] Available from: https://doi.org/10.1016/j.saa.2017.04.070
Artigo de periodico
MD simulations and multivariate studies for modeling the antileishmanial activity of peptides (2017)
Guerra, Mirian Elisa Rodrigues; Fadel, Valmir; Maltarollo, Vinícius Gonçalves; Baldissera, Gisele; Honório, Káthia Maria; Ruggiero, José Roberto; Cabrera, Marcia Perez dos Santos
Source: Chemical Biology and Drug Design. Unidade: EACH
Subjects: RELAÇÕES ESTRUTURA-ATIVIDADE, RELAÇÕES QUANTITATIVAS ENTRE ESTRUTURA QUÍMICA E ATIVIDADE BIOLÓGICA, PEPTÍDEOS
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GUERRA, Mirian Elisa Rodrigues et al. MD simulations and multivariate studies for modeling the antileishmanial activity of peptides. Chemical Biology and Drug Design, p. 1-10, 2017Tradução . . Disponível em: https://doi.org/10.1111/cbdd.12970. Acesso em: 23 maio 2024.
APA
Guerra, M. E. R., Fadel, V., Maltarollo, V. G., Baldissera, G., Honório, K. M., Ruggiero, J. R., & Cabrera, M. P. dos S. (2017). MD simulations and multivariate studies for modeling the antileishmanial activity of peptides. Chemical Biology and Drug Design, 1-10. doi:10.1111/cbdd.12970
NLM
Guerra MER, Fadel V, Maltarollo VG, Baldissera G, Honório KM, Ruggiero JR, Cabrera MP dos S. MD simulations and multivariate studies for modeling the antileishmanial activity of peptides [Internet]. Chemical Biology and Drug Design. 2017 ; 1-10.[citado 2024 maio 23 ] Available from: https://doi.org/10.1111/cbdd.12970
Vancouver
Guerra MER, Fadel V, Maltarollo VG, Baldissera G, Honório KM, Ruggiero JR, Cabrera MP dos S. MD simulations and multivariate studies for modeling the antileishmanial activity of peptides [Internet]. Chemical Biology and Drug Design. 2017 ; 1-10.[citado 2024 maio 23 ] Available from: https://doi.org/10.1111/cbdd.12970
Artigo de periodico
Understanding PPAR-δ affinity and selectivity using hologram quantitative structure–activity modeling, molecular docking and GRID calculations (2016)
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
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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: 23 maio 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-2016-0061
NLM
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 maio 23 ] Available from: https://doi.org/10.4155/fmc-2016-0061
Vancouver
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 maio 23 ] Available from: https://doi.org/10.4155/fmc-2016-0061
Artigo de periodico
Use of machine learning approaches for novel drug discovery (2016)
Lima, Angélica Nakagawa; Philot, Eric Alisson; Trossini, Gustavo Henrique Goulart ; Scott, Luis Paulo Barbour; Maltarollo, Vinícius Gonçalves; Honório, Kathia Maria
Source: Expert Opinion on Drug Discovery. Unidades: FCF, EACH
Subjects: HISTOPLASMA, LEUCÓCITOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LIMA, Angélica Nakagawa et al. Use of machine learning approaches for novel drug discovery. Expert Opinion on Drug Discovery, v. 11, n. 3, p. 225-239, 2016Tradução . . Disponível em: https://doi.org/10.1517/17460441.2016.1146250. Acesso em: 23 maio 2024.
APA
Lima, A. N., Philot, E. A., Trossini, G. H. G., Scott, L. P. B., Maltarollo, V. G., & Honório, K. M. (2016). Use of machine learning approaches for novel drug discovery. Expert Opinion on Drug Discovery, 11( 3), 225-239. doi:10.1517/17460441.2016.1146250
NLM
Lima AN, Philot EA, Trossini GHG, Scott LPB, Maltarollo VG, Honório KM. Use of machine learning approaches for novel drug discovery [Internet]. Expert Opinion on Drug Discovery. 2016 ; 11( 3): 225-239.[citado 2024 maio 23 ] Available from: https://doi.org/10.1517/17460441.2016.1146250
Vancouver
Lima AN, Philot EA, Trossini GHG, Scott LPB, Maltarollo VG, Honório KM. Use of machine learning approaches for novel drug discovery [Internet]. Expert Opinion on Drug Discovery. 2016 ; 11( 3): 225-239.[citado 2024 maio 23 ] Available from: https://doi.org/10.1517/17460441.2016.1146250
Artigo de periodico
In silico studies on the interaction between bioactive ligands and ALK5, a biological target related to the cancer treatment (2016)
Almeida, M. O; Trossini, Gustavo Henrique Goulart ; Maltarollo, Vinícius Gonçalves; Silva, Danielle D; Honório, Kathia Maria
Source: Journal of Biomolecular Structure and Dynamics. Unidades: FCF, EACH
Subjects: ANTI-INFLAMATÓRIOS, LIGANTES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ALMEIDA, M. O et al. In silico studies on the interaction between bioactive ligands and ALK5, a biological target related to the cancer treatment. Journal of Biomolecular Structure and Dynamics, v. 34, n. 9, p. 2045-2053, 2016Tradução . . Disponível em: https://doi.org/10.1080/07391102.2015.1106340. Acesso em: 23 maio 2024.
APA
Almeida, M. O., Trossini, G. H. G., Maltarollo, V. G., Silva, D. D., & Honório, K. M. (2016). In silico studies on the interaction between bioactive ligands and ALK5, a biological target related to the cancer treatment. Journal of Biomolecular Structure and Dynamics, 34( 9), 2045-2053. doi:10.1080/07391102.2015.1106340
NLM
Almeida MO, Trossini GHG, Maltarollo VG, Silva DD, Honório KM. In silico studies on the interaction between bioactive ligands and ALK5, a biological target related to the cancer treatment [Internet]. Journal of Biomolecular Structure and Dynamics. 2016 ; 34( 9): 2045-2053.[citado 2024 maio 23 ] Available from: https://doi.org/10.1080/07391102.2015.1106340
Vancouver
Almeida MO, Trossini GHG, Maltarollo VG, Silva DD, Honório KM. In silico studies on the interaction between bioactive ligands and ALK5, a biological target related to the cancer treatment [Internet]. Journal of Biomolecular Structure and Dynamics. 2016 ; 34( 9): 2045-2053.[citado 2024 maio 23 ] Available from: https://doi.org/10.1080/07391102.2015.1106340
Artigo de periodico
Molecular docking studies and 2D analyses of DPP-4 inhibitors as candidates in the treatment of diabetes (2015)
Pantaleão, Simone Queiroz; Maltarollo, Vinícius Gonçalves; Araujo, Sheila Cruz; Gertrudes, Jadson Castro; Honório, Kathia Maria
Source: Molecular BioSystems. Unidade: EACH
Subjects: DIABETES MELLITUS (TRATAMENTO), MODELAGEM MOLECULAR, RELAÇÕES QUANTITATIVAS ENTRE ESTRUTURA QUÍMICA E ATIVIDADE BIOLÓGICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PANTALEÃO, Simone Queiroz et al. Molecular docking studies and 2D analyses of DPP-4 inhibitors as candidates in the treatment of diabetes. Molecular BioSystems, v. no 2015, n. 11, p. 3188-3193, 2015Tradução . . Disponível em: https://doi.org/10.1039/C5MB00493D. Acesso em: 23 maio 2024.
APA
Pantaleão, S. Q., Maltarollo, V. G., Araujo, S. C., Gertrudes, J. C., & Honório, K. M. (2015). Molecular docking studies and 2D analyses of DPP-4 inhibitors as candidates in the treatment of diabetes. Molecular BioSystems, no 2015( 11), 3188-3193. doi:10.1039/C5MB00493D
NLM
Pantaleão SQ, Maltarollo VG, Araujo SC, Gertrudes JC, Honório KM. Molecular docking studies and 2D analyses of DPP-4 inhibitors as candidates in the treatment of diabetes [Internet]. Molecular BioSystems. 2015 ; no 2015( 11): 3188-3193.[citado 2024 maio 23 ] Available from: https://doi.org/10.1039/C5MB00493D
Vancouver
Pantaleão SQ, Maltarollo VG, Araujo SC, Gertrudes JC, Honório KM. Molecular docking studies and 2D analyses of DPP-4 inhibitors as candidates in the treatment of diabetes [Internet]. Molecular BioSystems. 2015 ; no 2015( 11): 3188-3193.[citado 2024 maio 23 ] Available from: https://doi.org/10.1039/C5MB00493D
Artigo de periodico
Hologram quantitative structure–activity relationship and comparative molecular interaction field analysis of aminothiazole and thiazolesulfonamide as reversible LSD1 inhibitors (2015)
Maltarollo, Vinícius Gonçalves; Honório, Káthia Maria; Emery, Flavio da Silva; Ganesa, Arasu; Trossini, Gustavo Henrique Goulart
Source: Future Medicinal Chemistry. Unidades: EACH, FCFRP, FCF
Subjects: INIBIDORES DE ENZIMAS, ANTINEOPLÁSICOS, HOLOGRAMAS, RELAÇÕES QUANTITATIVAS ENTRE ESTRUTURA QUÍMICA E ATIVIDADE BIOLÓGICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MALTAROLLO, Vinícius Gonçalves et al. Hologram quantitative structure–activity relationship and comparative molecular interaction field analysis of aminothiazole and thiazolesulfonamide as reversible LSD1 inhibitors. Future Medicinal Chemistry, v. 7, n. 11, p. 1381-1394, 2015Tradução . . Disponível em: https://doi.org/10.4155/fmc.15.68. Acesso em: 23 maio 2024.
APA
Maltarollo, V. G., Honório, K. M., Emery, F. da S., Ganesa, A., & Trossini, G. H. G. (2015). Hologram quantitative structure–activity relationship and comparative molecular interaction field analysis of aminothiazole and thiazolesulfonamide as reversible LSD1 inhibitors. Future Medicinal Chemistry, 7( 11), 1381-1394. doi:10.4155/fmc.15.68
NLM
Maltarollo VG, Honório KM, Emery F da S, Ganesa A, Trossini GHG. Hologram quantitative structure–activity relationship and comparative molecular interaction field analysis of aminothiazole and thiazolesulfonamide as reversible LSD1 inhibitors [Internet]. Future Medicinal Chemistry. 2015 ; 7( 11): 1381-1394.[citado 2024 maio 23 ] Available from: https://doi.org/10.4155/fmc.15.68
Vancouver
Maltarollo VG, Honório KM, Emery F da S, Ganesa A, Trossini GHG. Hologram quantitative structure–activity relationship and comparative molecular interaction field analysis of aminothiazole and thiazolesulfonamide as reversible LSD1 inhibitors [Internet]. Future Medicinal Chemistry. 2015 ; 7( 11): 1381-1394.[citado 2024 maio 23 ] Available from: https://doi.org/10.4155/fmc.15.68
Artigo de periodico
Benchmark studies of UV-vis spectra simulation for cinnamates with UV filter profile (2015)
Garcia, Ricardo D'A; Maltarollo, Vinícius Gonçalves; Honório, Kathia Maria; Trossini, Gustavo Henrique Goulart
Source: Journal of Molecular Modeling. Unidades: EACH, FCF
Subjects: MODELAGEM MOLECULAR, ESPECTROSCOPIA ULTRAVIOLETA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GARCIA, Ricardo D'A et al. Benchmark studies of UV-vis spectra simulation for cinnamates with UV filter profile. Journal of Molecular Modeling, v. 21, p. 1-13 art. 150, 2015Tradução . . Disponível em: https://doi.org/10.1007/s00894-015-2689-y. Acesso em: 23 maio 2024.
APA
Garcia, R. D. 'A., Maltarollo, V. G., Honório, K. M., & Trossini, G. H. G. (2015). Benchmark studies of UV-vis spectra simulation for cinnamates with UV filter profile. Journal of Molecular Modeling, 21, 1-13 art. 150. doi:10.1007/s00894-015-2689-y
NLM
Garcia RD'A, Maltarollo VG, Honório KM, Trossini GHG. Benchmark studies of UV-vis spectra simulation for cinnamates with UV filter profile [Internet]. Journal of Molecular Modeling. 2015 ; 21 1-13 art. 150.[citado 2024 maio 23 ] Available from: https://doi.org/10.1007/s00894-015-2689-y
Vancouver
Garcia RD'A, Maltarollo VG, Honório KM, Trossini GHG. Benchmark studies of UV-vis spectra simulation for cinnamates with UV filter profile [Internet]. Journal of Molecular Modeling. 2015 ; 21 1-13 art. 150.[citado 2024 maio 23 ] Available from: https://doi.org/10.1007/s00894-015-2689-y
Artigo de periodico
Applying machine learning techniques for ADME-Tox prediction: a review (2015)
Maltarollo, Vinícius Gonçalves; Gertrudes, Jadson Castro; Oliveira, Patrícia Rufino; Honório, Kathia Maria
Source: Expert Opinion on Drug Metabolism & Toxicology. Unidade: EACH
Subjects: MODELAGEM MOLECULAR, FARMACOCINÉTICA, XENOBIÓTICO, APRENDIZADO COMPUTACIONAL, RELAÇÕES QUANTITATIVAS ENTRE ESTRUTURA QUÍMICA E ATIVIDADE BIOLÓGICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MALTAROLLO, Vinícius Gonçalves et al. Applying machine learning techniques for ADME-Tox prediction: a review. Expert Opinion on Drug Metabolism & Toxicology, v. 11, n. 2, p. 259-271, 2015Tradução . . Disponível em: https://doi.org/10.1517/17425255.2015.980814. Acesso em: 23 maio 2024.
APA
Maltarollo, V. G., Gertrudes, J. C., Oliveira, P. R., & Honório, K. M. (2015). Applying machine learning techniques for ADME-Tox prediction: a review. Expert Opinion on Drug Metabolism & Toxicology, 11( 2), 259-271. doi:10.1517/17425255.2015.980814
NLM
Maltarollo VG, Gertrudes JC, Oliveira PR, Honório KM. Applying machine learning techniques for ADME-Tox prediction: a review [Internet]. Expert Opinion on Drug Metabolism & Toxicology. 2015 ; 11( 2): 259-271.[citado 2024 maio 23 ] Available from: https://doi.org/10.1517/17425255.2015.980814
Vancouver
Maltarollo VG, Gertrudes JC, Oliveira PR, Honório KM. Applying machine learning techniques for ADME-Tox prediction: a review [Internet]. Expert Opinion on Drug Metabolism & Toxicology. 2015 ; 11( 2): 259-271.[citado 2024 maio 23 ] Available from: https://doi.org/10.1517/17425255.2015.980814
Artigo de periodico
Theoretical study of tautomers and photoisomers of avobenzone by DFT methods (2015)
Trossini, Gustavo Henrique Goulart ; Maltarollo, Vinícius Gonçalves; Garcia, Ricardo D’A; Pinto, Claudinéia Aparecida Sales de Oliveira ; Velasco, Maria Valéria Robles ; Honório, Kathia Maria; Baby, André Rolim
Source: Journal of Molecular Modeling. Unidades: EACH, FCF
Subjects: MODELAGEM MOLECULAR, COSMÉTICOS, FILTRO SOLAR, TAUTOMERIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TROSSINI, Gustavo Henrique Goulart et al. Theoretical study of tautomers and photoisomers of avobenzone by DFT methods. Journal of Molecular Modeling, v. 21, n. 12, p. 1-7, 2015Tradução . . Disponível em: https://doi.org/10.1007/s00894-015-2863-2. Acesso em: 23 maio 2024.
APA
Trossini, G. H. G., Maltarollo, V. G., Garcia, R. D. ’A., Pinto, C. A. S. de O., Velasco, M. V. R., Honório, K. M., & Baby, A. R. (2015). Theoretical study of tautomers and photoisomers of avobenzone by DFT methods. Journal of Molecular Modeling, 21( 12), 1-7. doi:10.1007/s00894-015-2863-2
NLM
Trossini GHG, Maltarollo VG, Garcia RD’A, Pinto CAS de O, Velasco MVR, Honório KM, Baby AR. Theoretical study of tautomers and photoisomers of avobenzone by DFT methods [Internet]. Journal of Molecular Modeling. 2015 ; 21( 12): 1-7.[citado 2024 maio 23 ] Available from: https://doi.org/10.1007/s00894-015-2863-2
Vancouver
Trossini GHG, Maltarollo VG, Garcia RD’A, Pinto CAS de O, Velasco MVR, Honório KM, Baby AR. Theoretical study of tautomers and photoisomers of avobenzone by DFT methods [Internet]. Journal of Molecular Modeling. 2015 ; 21( 12): 1-7.[citado 2024 maio 23 ] Available from: https://doi.org/10.1007/s00894-015-2863-2

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