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Artigo de periodico
Machine learning-based virtual screening of antibacterial agents against methicillin-susceptible and resistant staphylococcus aureus (2024)
Fernandes, Philipe Oliveira ; Dias, Anna Letícia Teotonio; Santos Júnior, Valtair Severino dos ; Serafim, Mateus Sá Magalhães ; Sousa, Yamara Viana; Monteiro, Gustavo Claro ; Coutinho, Isabel Duarte ; Valli, Marilia ; Verzola, Marina Mol Sena Andrade; Ottoni, Flaviano Melo; Pádua, Rodrigo Maia de; Oda, Fernando Bombarda ; Santos, André Gonzaga dos ; Andricopulo, Adriano Defini ; Bolzani, Vanderlan da Silva ; Mota, Bruno Eduardo Fernandes; Alves, Ricardo José; Oliveira, Renata Barbosa de ; Kronenberger, Thales ; Maltarollo, Vinícius Gonçalves
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: BACTÉRIAS, AGENTES ANTIMICROBIANOS, CRISTALOGRAFIA
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ABNT
FERNANDES, Philipe Oliveira et al. Machine learning-based virtual screening of antibacterial agents against methicillin-susceptible and resistant staphylococcus aureus. Journal of Chemical Information and Modeling, v. 64, n. 6, p. 1932-1944 + supporting information, 2024Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.4c00087. Acesso em: 17 nov. 2025.
APA
Fernandes, P. O., Dias, A. L. T., Santos Júnior, V. S. dos, Serafim, M. S. M., Sousa, Y. V., Monteiro, G. C., et al. (2024). Machine learning-based virtual screening of antibacterial agents against methicillin-susceptible and resistant staphylococcus aureus. Journal of Chemical Information and Modeling, 64( 6), 1932-1944 + supporting information. doi:10.1021/acs.jcim.4c00087
NLM
Fernandes PO, Dias ALT, Santos Júnior VS dos, Serafim MSM, Sousa YV, Monteiro GC, Coutinho ID, Valli M, Verzola MMSA, Ottoni FM, Pádua RM de, Oda FB, Santos AG dos, Andricopulo AD, Bolzani V da S, Mota BEF, Alves RJ, Oliveira RB de, Kronenberger T, Maltarollo VG. Machine learning-based virtual screening of antibacterial agents against methicillin-susceptible and resistant staphylococcus aureus [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64( 6): 1932-1944 + supporting information.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.4c00087
Vancouver
Fernandes PO, Dias ALT, Santos Júnior VS dos, Serafim MSM, Sousa YV, Monteiro GC, Coutinho ID, Valli M, Verzola MMSA, Ottoni FM, Pádua RM de, Oda FB, Santos AG dos, Andricopulo AD, Bolzani V da S, Mota BEF, Alves RJ, Oliveira RB de, Kronenberger T, Maltarollo VG. Machine learning-based virtual screening of antibacterial agents against methicillin-susceptible and resistant staphylococcus aureus [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64( 6): 1932-1944 + supporting information.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.4c00087
Artigo de periodico
Latin american natural product database (LANaPDB): an update (2024)
Garcia, Alejandro Gomez ; Jiménez, Daniel A. Acuña; Zamora, William J. ; Ccahuana, Haruna L. Barazorda; Fumagalli, Miguel Angel Chávez ; Valli, Marilia ; Andricopulo, Adriano Defini ; Bolzani, Vanderlan da Silva ; Olmedo, Dionisio Antonio ; Solis, Pablo N. ; Nuñez, Marvin J. ; Pérez, Johny Roberto Rodríguez ; Sánchez, Hoover A. Valencia; Hernández, Héctor Fabio Cortés ; Martinez, Oscar Marino Mosquera; Franco, José L. Medina
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: PRODUTOS NATURAIS, FÁRMACOS, CRISTALOGRAFIA
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ABNT
GARCIA, Alejandro Gomez et al. Latin american natural product database (LANaPDB): an update. Journal of Chemical Information and Modeling, v. No 2024, n. 22, p. 8495-8509, 2024Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.4c01560. Acesso em: 17 nov. 2025.
APA
Garcia, A. G., Jiménez, D. A. A., Zamora, W. J., Ccahuana, H. L. B., Fumagalli, M. A. C., Valli, M., et al. (2024). Latin american natural product database (LANaPDB): an update. Journal of Chemical Information and Modeling, No 2024( 22), 8495-8509. doi:10.1021/acs.jcim.4c01560
NLM
Garcia AG, Jiménez DAA, Zamora WJ, Ccahuana HLB, Fumagalli MAC, Valli M, Andricopulo AD, Bolzani V da S, Olmedo DA, Solis PN, Nuñez MJ, Pérez JRR, Sánchez HAV, Hernández HFC, Martinez OMM, Franco JLM. Latin american natural product database (LANaPDB): an update [Internet]. Journal of Chemical Information and Modeling. 2024 ; No 2024( 22): 8495-8509.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.4c01560
Vancouver
Garcia AG, Jiménez DAA, Zamora WJ, Ccahuana HLB, Fumagalli MAC, Valli M, Andricopulo AD, Bolzani V da S, Olmedo DA, Solis PN, Nuñez MJ, Pérez JRR, Sánchez HAV, Hernández HFC, Martinez OMM, Franco JLM. Latin american natural product database (LANaPDB): an update [Internet]. Journal of Chemical Information and Modeling. 2024 ; No 2024( 22): 8495-8509.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.4c01560
Artigo de periodico
Artificial intelligence agents for materials sciences (2023)
Oliveira Junior, Osvaldo Novais de ; Christino, Leonardo Milhomem Franco; Oliveira, Maria Cristina Ferreira de ; Paulovich, Fernando Vieira
Fonte: Journal of Chemical Information and Modeling. Unidades: IFSC, ICMC
Assuntos: ALGORITMOS, APRENDIZADO COMPUTACIONAL, GENÔMICA
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ABNT
OLIVEIRA JUNIOR, Osvaldo Novais de et al. Artificial intelligence agents for materials sciences. Journal of Chemical Information and Modeling, v. 63, n. 24, p. 7605-7609, 2023Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.3c01778. Acesso em: 17 nov. 2025.
APA
Oliveira Junior, O. N. de, Christino, L. M. F., Oliveira, M. C. F. de, & Paulovich, F. V. (2023). Artificial intelligence agents for materials sciences. Journal of Chemical Information and Modeling, 63( 24), 7605-7609. doi:10.1021/acs.jcim.3c01778
NLM
Oliveira Junior ON de, Christino LMF, Oliveira MCF de, Paulovich FV. Artificial intelligence agents for materials sciences [Internet]. Journal of Chemical Information and Modeling. 2023 ; 63( 24): 7605-7609.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.3c01778
Vancouver
Oliveira Junior ON de, Christino LMF, Oliveira MCF de, Paulovich FV. Artificial intelligence agents for materials sciences [Internet]. Journal of Chemical Information and Modeling. 2023 ; 63( 24): 7605-7609.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.3c01778
Artigo de periodico
Discovery of new Zika protease and polymerase inhibitors through the open science collaboration Project OpenZika (2022)
Mottin, Melina ; Sousa, Bruna Katiele de Paula ; Mesquita, Nathalya Cristina de Moraes Roso; Oliveira, Ketllyn Irene Zagato de; Noske, Gabriela Dias; Sartori, Geraldo Rodrigues ; Albuquerque, Aline de Oliveira; Urbina, Fabio; Puhl, Ana C. ; Moreira Filho, José Teófilo; Souza, Guilherme Eduardo de ; Guido, Rafael Victorio Carvalho ; Muratov, Eugene ; Neves, Bruno Junior ; Silva, João Hermínio Martins da ; Clark, Alex E.; Siqueira Neto, Jair L. ; Perryman, Alexander L.; Oliva, Glaucius ; Ekins, Sean ; Andrade, Carolina Horta
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: ZIKA VÍRUS, PLANEJAMENTO DE FÁRMACOS, ANTIVIRAIS
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ABNT
MOTTIN, Melina et al. Discovery of new Zika protease and polymerase inhibitors through the open science collaboration Project OpenZika. Journal of Chemical Information and Modeling, v. 62, n. 24, p. 6825-6843, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00596. Acesso em: 17 nov. 2025.
APA
Mottin, M., Sousa, B. K. de P., Mesquita, N. C. de M. R., Oliveira, K. I. Z. de, Noske, G. D., Sartori, G. R., et al. (2022). Discovery of new Zika protease and polymerase inhibitors through the open science collaboration Project OpenZika. Journal of Chemical Information and Modeling, 62( 24), 6825-6843. doi:10.1021/acs.jcim.2c00596
NLM
Mottin M, Sousa BK de P, Mesquita NC de MR, Oliveira KIZ de, Noske GD, Sartori GR, Albuquerque A de O, Urbina F, Puhl AC, Moreira Filho JT, Souza GE de, Guido RVC, Muratov E, Neves BJ, Silva JHM da, Clark AE, Siqueira Neto JL, Perryman AL, Oliva G, Ekins S, Andrade CH. Discovery of new Zika protease and polymerase inhibitors through the open science collaboration Project OpenZika [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 24): 6825-6843.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.2c00596
Vancouver
Mottin M, Sousa BK de P, Mesquita NC de MR, Oliveira KIZ de, Noske GD, Sartori GR, Albuquerque A de O, Urbina F, Puhl AC, Moreira Filho JT, Souza GE de, Guido RVC, Muratov E, Neves BJ, Silva JHM da, Clark AE, Siqueira Neto JL, Perryman AL, Oliva G, Ekins S, Andrade CH. Discovery of new Zika protease and polymerase inhibitors through the open science collaboration Project OpenZika [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 24): 6825-6843.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.2c00596
Artigo de periodico
Prioritizing virtual screening with interpretable interaction Fingerprints (2022)
Fassio, Alexandre Victor ; Shub, Laura ; Ponzoni, Luca ; McKinley, Jessica ; O’Meara, Matthew J. ; Ferreira, Rafaela S.; Keiser, Michael J. ; Minardi, Raquel C. de Melo
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: APRENDIZADO COMPUTACIONAL, FÁRMACOS (ESTUDO;DESENVOLVIMENTO)
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ABNT
FASSIO, Alexandre Victor et al. Prioritizing virtual screening with interpretable interaction Fingerprints. Journal of Chemical Information and Modeling, v. 62, n. 18, p. 4300-4318, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00695. Acesso em: 17 nov. 2025.
APA
Fassio, A. V., Shub, L., Ponzoni, L., McKinley, J., O’Meara, M. J., Ferreira, R. S., et al. (2022). Prioritizing virtual screening with interpretable interaction Fingerprints. Journal of Chemical Information and Modeling, 62( 18), 4300-4318. doi:10.1021/acs.jcim.2c00695
NLM
Fassio AV, Shub L, Ponzoni L, McKinley J, O’Meara MJ, Ferreira RS, Keiser MJ, Minardi RC de M. Prioritizing virtual screening with interpretable interaction Fingerprints [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 18): 4300-4318.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.2c00695
Vancouver
Fassio AV, Shub L, Ponzoni L, McKinley J, O’Meara MJ, Ferreira RS, Keiser MJ, Minardi RC de M. Prioritizing virtual screening with interpretable interaction Fingerprints [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 18): 4300-4318.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.2c00695
Artigo de periodico
Differences in gluco and galacto substrate-binding interactions in a dual 6Pβ-Glucosidase/6Pβ-Galactosidase glycoside hydrolase 1 enzyme from Bacillus licheniformis (2021)
Veldman, Wayde ; Liberato, Marcelo Vizoná; Souza, Valquiria P; Almeida, Vitor M; Marana, Sandro Roberto ; Bishop, Ozlem Tastan ; Polikarpov, Igor
Fonte: Journal of Chemical Information and Modeling. Unidades: IQ, IFSC
Assuntos: CRISTALOGRAFIA, PEPTÍDEOS, PROTEÍNAS, LIGANTES
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ABNT
VELDMAN, Wayde et al. Differences in gluco and galacto substrate-binding interactions in a dual 6Pβ-Glucosidase/6Pβ-Galactosidase glycoside hydrolase 1 enzyme from Bacillus licheniformis. Journal of Chemical Information and Modeling, v. 61, n. 9, p. 4554-4570, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00413. Acesso em: 17 nov. 2025.
APA
Veldman, W., Liberato, M. V., Souza, V. P., Almeida, V. M., Marana, S. R., Bishop, O. T., & Polikarpov, I. (2021). Differences in gluco and galacto substrate-binding interactions in a dual 6Pβ-Glucosidase/6Pβ-Galactosidase glycoside hydrolase 1 enzyme from Bacillus licheniformis. Journal of Chemical Information and Modeling, 61( 9), 4554-4570. doi:10.1021/acs.jcim.1c00413
NLM
Veldman W, Liberato MV, Souza VP, Almeida VM, Marana SR, Bishop OT, Polikarpov I. Differences in gluco and galacto substrate-binding interactions in a dual 6Pβ-Glucosidase/6Pβ-Galactosidase glycoside hydrolase 1 enzyme from Bacillus licheniformis [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 9): 4554-4570.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.1c00413
Vancouver
Veldman W, Liberato MV, Souza VP, Almeida VM, Marana SR, Bishop OT, Polikarpov I. Differences in gluco and galacto substrate-binding interactions in a dual 6Pβ-Glucosidase/6Pβ-Galactosidase glycoside hydrolase 1 enzyme from Bacillus licheniformis [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 9): 4554-4570.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.1c00413
Artigo de periodico
Quantum machine learning algorithms for drug discovery applications (2021)
Batra, Kushal; Zorn, Kimberley M.; Foil, Daniel H.; Minerali, Eni; Gawriljuk, Victor Oliveira; Lane, Thomas R.; Ekins, Sean
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: PLANEJAMENTO DE FÁRMACOS, COMPUTAÇÃO APLICADA, INTELIGÊNCIA ARTIFICIAL
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ABNT
BATRA, Kushal et al. Quantum machine learning algorithms for drug discovery applications. Journal of Chemical Information and Modeling, v. 61, n. 6, p. 2641-2647, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00166. Acesso em: 17 nov. 2025.
APA
Batra, K., Zorn, K. M., Foil, D. H., Minerali, E., Gawriljuk, V. O., Lane, T. R., & Ekins, S. (2021). Quantum machine learning algorithms for drug discovery applications. Journal of Chemical Information and Modeling, 61( 6), 2641-2647. doi:10.1021/acs.jcim.1c00166
NLM
Batra K, Zorn KM, Foil DH, Minerali E, Gawriljuk VO, Lane TR, Ekins S. Quantum machine learning algorithms for drug discovery applications [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 6): 2641-2647.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.1c00166
Vancouver
Batra K, Zorn KM, Foil DH, Minerali E, Gawriljuk VO, Lane TR, Ekins S. Quantum machine learning algorithms for drug discovery applications [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 6): 2641-2647.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.1c00166
Artigo de periodico
Development of machine learning models and the discovery of a new antiviral compound against yellow fever virus (2021)
Oliveira, Victor Gawriljuk Ferraro; Foil, Daniel H.; Puhl, Ana C. ; Zorn, Kimberley M.; Lane, Thomas R.; Riabova, Olga; Makarov, Vadim; Godoy, Andre Schutzer de ; Oliva, Glaucius ; Ekins, Sean
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: FEBRE AMARELA, APRENDIZADO COMPUTACIONAL, PLANEJAMENTO DE FÁRMACOS, ANTIVIRAIS
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ABNT
OLIVEIRA, Victor Gawriljuk Ferraro et al. Development of machine learning models and the discovery of a new antiviral compound against yellow fever virus. Journal of Chemical Information and Modeling, v. 61, n. 8, p. 3804-3813, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00460. Acesso em: 17 nov. 2025.
APA
Oliveira, V. G. F., Foil, D. H., Puhl, A. C., Zorn, K. M., Lane, T. R., Riabova, O., et al. (2021). Development of machine learning models and the discovery of a new antiviral compound against yellow fever virus. Journal of Chemical Information and Modeling, 61( 8), 3804-3813. doi:10.1021/acs.jcim.1c00460
NLM
Oliveira VGF, Foil DH, Puhl AC, Zorn KM, Lane TR, Riabova O, Makarov V, Godoy AS de, Oliva G, Ekins S. Development of machine learning models and the discovery of a new antiviral compound against yellow fever virus [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 8): 3804-3813.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.1c00460
Vancouver
Oliveira VGF, Foil DH, Puhl AC, Zorn KM, Lane TR, Riabova O, Makarov V, Godoy AS de, Oliva G, Ekins S. Development of machine learning models and the discovery of a new antiviral compound against yellow fever virus [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 8): 3804-3813.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.1c00460
Artigo de periodico
Investigation of the stability mechanisms of eight-atom binary metal clusters using DFT calculations and k‑means clustering algorithm (2021)
Morais, Felipe Orlando; Andriani, Karla Furtado ; Silva, Juarez Lopes Ferreira da
Fonte: Journal of Chemical Information and Modeling. Unidades: IQSC, IFSC
Assunto: METAIS
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ABNT
MORAIS, Felipe Orlando e ANDRIANI, Karla Furtado e SILVA, Juarez Lopes Ferreira da. Investigation of the stability mechanisms of eight-atom binary metal clusters using DFT calculations and k‑means clustering algorithm. Journal of Chemical Information and Modeling, v. 61, n. 7, p. 3411-3420, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00253. Acesso em: 17 nov. 2025.
APA
Morais, F. O., Andriani, K. F., & Silva, J. L. F. da. (2021). Investigation of the stability mechanisms of eight-atom binary metal clusters using DFT calculations and k‑means clustering algorithm. Journal of Chemical Information and Modeling, 61( 7), 3411-3420. doi:10.1021/acs.jcim.1c00253
NLM
Morais FO, Andriani KF, Silva JLF da. Investigation of the stability mechanisms of eight-atom binary metal clusters using DFT calculations and k‑means clustering algorithm [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 7): 3411-3420.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.1c00253
Vancouver
Morais FO, Andriani KF, Silva JLF da. Investigation of the stability mechanisms of eight-atom binary metal clusters using DFT calculations and k‑means clustering algorithm [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 7): 3411-3420.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.1c00253
Artigo de periodico
Machine learning models identify inhibitors of SARS-CoV2 (2021)
Oliveira, Victor Gawriljuk Ferraro; Zin, Phyo Phyo Kyaw; Puhl, Ana C. ; Zorn, Kimberley M.; Foil, Daniel H.; Lane, Thomas R.; Hurst, Brett; Tavella, Tatyana Almeida; Costa, Fabio Trindade Maranhão; Lakshmanane, Premkumar; Bernatchez, Jean; Godoy, Andre Schutzer de ; Oliva, Glaucius ; Siqueira-Neto, Jair L.; Madrid, Peter B.; Ekins, Sean
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: CORONAVIRUS, COVID-19, APRENDIZADO COMPUTACIONAL, PLANEJAMENTO DE FÁRMACOS, ANTIVIRAIS
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ABNT
OLIVEIRA, Victor Gawriljuk Ferraro et al. Machine learning models identify inhibitors of SARS-CoV2. Journal of Chemical Information and Modeling, v. 61, n. 9, p. 4224-4235, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00683. Acesso em: 17 nov. 2025.
APA
Oliveira, V. G. F., Zin, P. P. K., Puhl, A. C., Zorn, K. M., Foil, D. H., Lane, T. R., et al. (2021). Machine learning models identify inhibitors of SARS-CoV2. Journal of Chemical Information and Modeling, 61( 9), 4224-4235. doi:10.1021/acs.jcim.1c00683
NLM
Oliveira VGF, Zin PPK, Puhl AC, Zorn KM, Foil DH, Lane TR, Hurst B, Tavella TA, Costa FTM, Lakshmanane P, Bernatchez J, Godoy AS de, Oliva G, Siqueira-Neto JL, Madrid PB, Ekins S. Machine learning models identify inhibitors of SARS-CoV2 [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 9): 4224-4235.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.1c00683
Vancouver
Oliveira VGF, Zin PPK, Puhl AC, Zorn KM, Foil DH, Lane TR, Hurst B, Tavella TA, Costa FTM, Lakshmanane P, Bernatchez J, Godoy AS de, Oliva G, Siqueira-Neto JL, Madrid PB, Ekins S. Machine learning models identify inhibitors of SARS-CoV2 [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 9): 4224-4235.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.1c00683
Artigo de periodico
X-ray structure, bioinformatics analysis, and substrate specificity of a 6-phospho-β-glucosidase glycoside hydrolase 1 enzyme from Bacillus licheniformis (2020)
Veldman, Wayde ; Liberato, Marcelo Vizoná; Almeida, Vitor Medeiros ; Souza, Valquiria P; Frutuoso, Maira Artischeff; Marana, Sandro Roberto ; Moses, Vuyani; Bishop, Ozlem Tastan ; Polikarpov, Igor
Fonte: Journal of Chemical Information and Modeling. Unidades: IQ, IFSC, FO
Assuntos: RAIOS X, BIOINFORMÁTICA
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ABNT
VELDMAN, Wayde et al. X-ray structure, bioinformatics analysis, and substrate specificity of a 6-phospho-β-glucosidase glycoside hydrolase 1 enzyme from Bacillus licheniformis. Journal of Chemical Information and Modeling, v. 60, n. 12, p. 6392-6407, 2020Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.0c00759. Acesso em: 17 nov. 2025.
APA
Veldman, W., Liberato, M. V., Almeida, V. M., Souza, V. P., Frutuoso, M. A., Marana, S. R., et al. (2020). X-ray structure, bioinformatics analysis, and substrate specificity of a 6-phospho-β-glucosidase glycoside hydrolase 1 enzyme from Bacillus licheniformis. Journal of Chemical Information and Modeling, 60( 12), 6392-6407. doi:10.1021/acs.jcim.0c00759
NLM
Veldman W, Liberato MV, Almeida VM, Souza VP, Frutuoso MA, Marana SR, Moses V, Bishop OT, Polikarpov I. X-ray structure, bioinformatics analysis, and substrate specificity of a 6-phospho-β-glucosidase glycoside hydrolase 1 enzyme from Bacillus licheniformis [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 12): 6392-6407.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.0c00759
Vancouver
Veldman W, Liberato MV, Almeida VM, Souza VP, Frutuoso MA, Marana SR, Moses V, Bishop OT, Polikarpov I. X-ray structure, bioinformatics analysis, and substrate specificity of a 6-phospho-β-glucosidase glycoside hydrolase 1 enzyme from Bacillus licheniformis [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 12): 6392-6407.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.0c00759
Artigo de periodico
Discovery of potent, reversible, and competitive cruzain inhibitors with trypanocidal activity: a structure-based drug design approach (2020)
Souza, Mariana Laureano de; Rezende Junior, Celso de Oliveira; Ferreira, Rafaela S. ; Chávez, Rocio Marisol Espinoza; Ferreira, Leonardo Luiz Gomes ; Slafer, Brian W.; Magalhães, Luma Godoy; Andricopulo, Renata Krogh; Oliva, Glaucius ; Cruz, Fabio Cardoso; Dias, Luiz Carlos; Andricopulo, Adriano Defini
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: TRIPANOSSOMICIDAS, PLANEJAMENTO DE FÁRMACOS, INIBIDORES QUÍMICOS
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ABNT
SOUZA, Mariana Laureano de et al. Discovery of potent, reversible, and competitive cruzain inhibitors with trypanocidal activity: a structure-based drug design approach. Journal of Chemical Information and Modeling, v. 60, n. 2, p. 1028-1041, 2020Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.9b00802. Acesso em: 17 nov. 2025.
APA
Souza, M. L. de, Rezende Junior, C. de O., Ferreira, R. S., Chávez, R. M. E., Ferreira, L. L. G., Slafer, B. W., et al. (2020). Discovery of potent, reversible, and competitive cruzain inhibitors with trypanocidal activity: a structure-based drug design approach. Journal of Chemical Information and Modeling, 60( 2), 1028-1041. doi:10.1021/acs.jcim.9b00802
NLM
Souza ML de, Rezende Junior C de O, Ferreira RS, Chávez RME, Ferreira LLG, Slafer BW, Magalhães LG, Andricopulo RK, Oliva G, Cruz FC, Dias LC, Andricopulo AD. Discovery of potent, reversible, and competitive cruzain inhibitors with trypanocidal activity: a structure-based drug design approach [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 2): 1028-1041.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.9b00802
Vancouver
Souza ML de, Rezende Junior C de O, Ferreira RS, Chávez RME, Ferreira LLG, Slafer BW, Magalhães LG, Andricopulo RK, Oliva G, Cruz FC, Dias LC, Andricopulo AD. Discovery of potent, reversible, and competitive cruzain inhibitors with trypanocidal activity: a structure-based drug design approach [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 2): 1028-1041.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.9b00802
Artigo de periodico
Chemical space and diversity of the NuBBE database: a chemoinformatic characterization (2019)
Saldívar-González, Fernanda I.; Valli, Marilia; Andricopulo, Adriano Defini ; Bolzani, Vanderlan S.; Medina-Franco, José L.
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: ANTINEOPLÁSICOS, PRODUTOS NATURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SALDÍVAR-GONZÁLEZ, Fernanda I. et al. Chemical space and diversity of the NuBBE database: a chemoinformatic characterization. Journal of Chemical Information and Modeling, v. 59, n. Ja 2019, p. 74-85, 2019Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.8b00619. Acesso em: 17 nov. 2025.
APA
Saldívar-González, F. I., Valli, M., Andricopulo, A. D., Bolzani, V. S., & Medina-Franco, J. L. (2019). Chemical space and diversity of the NuBBE database: a chemoinformatic characterization. Journal of Chemical Information and Modeling, 59( Ja 2019), 74-85. doi:10.1021/acs.jcim.8b00619
NLM
Saldívar-González FI, Valli M, Andricopulo AD, Bolzani VS, Medina-Franco JL. Chemical space and diversity of the NuBBE database: a chemoinformatic characterization [Internet]. Journal of Chemical Information and Modeling. 2019 ; 59( Ja 2019): 74-85.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.8b00619
Vancouver
Saldívar-González FI, Valli M, Andricopulo AD, Bolzani VS, Medina-Franco JL. Chemical space and diversity of the NuBBE database: a chemoinformatic characterization [Internet]. Journal of Chemical Information and Modeling. 2019 ; 59( Ja 2019): 74-85.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.8b00619
Artigo de periodico
Discovery of new inhibitors of Mycobacterium tuberculosis InhA enzyme using virtual screening and a 3D-pharmacophore-based approach (2013)
Pauli, Ivani; Santos, Ricardo N. dos; Rostirolla, Diana C.; Martinelli, Leonardo K.; Ducati, Rodrigo G.; Timmers, Luís F. S. M.; Basso, Luiz A.; Santos, Diogenes S.; Guido, Rafael Victorio Carvalho ; Andricopulo, Adriano Defini ; Souza, Osmar Norberto de
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: TUBERCULOSE (TRATAMENTO), ENZIMAS, LIGANTES
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ABNT
PAULI, Ivani et al. Discovery of new inhibitors of Mycobacterium tuberculosis InhA enzyme using virtual screening and a 3D-pharmacophore-based approach. Journal of Chemical Information and Modeling, v. 53, n. 9, p. 2390-2401, 2013Tradução . . Disponível em: https://doi.org/10.1021/ci400202t. Acesso em: 17 nov. 2025.
APA
Pauli, I., Santos, R. N. dos, Rostirolla, D. C., Martinelli, L. K., Ducati, R. G., Timmers, L. F. S. M., et al. (2013). Discovery of new inhibitors of Mycobacterium tuberculosis InhA enzyme using virtual screening and a 3D-pharmacophore-based approach. Journal of Chemical Information and Modeling, 53( 9), 2390-2401. doi:10.1021/ci400202t
NLM
Pauli I, Santos RN dos, Rostirolla DC, Martinelli LK, Ducati RG, Timmers LFSM, Basso LA, Santos DS, Guido RVC, Andricopulo AD, Souza ON de. Discovery of new inhibitors of Mycobacterium tuberculosis InhA enzyme using virtual screening and a 3D-pharmacophore-based approach [Internet]. Journal of Chemical Information and Modeling. 2013 ; 53( 9): 2390-2401.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/ci400202t
Vancouver
Pauli I, Santos RN dos, Rostirolla DC, Martinelli LK, Ducati RG, Timmers LFSM, Basso LA, Santos DS, Guido RVC, Andricopulo AD, Souza ON de. Discovery of new inhibitors of Mycobacterium tuberculosis InhA enzyme using virtual screening and a 3D-pharmacophore-based approach [Internet]. Journal of Chemical Information and Modeling. 2013 ; 53( 9): 2390-2401.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/ci400202t
Artigo de periodico
Discovery of new inhibitors of Schistosoma mansoni PNP by pharmacophore-based virtual screening (2010)
Postigo, Matheus P.; Guido, Rafael Victorio Carvalho ; Oliva, Glaucius ; Castilho, Marcelo S.; Pitta, Ivan R.; Albuquerque, Julianna F. C. de; Andricopulo, Adriano Defini
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: ESQUISTOSSOMOSE (ESTUDO;TRATAMENTO), DOENÇAS PARASITÁRIAS, FÁRMACOS (DESENVOLVIMENTO), ENZIMAS, LIGANTES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
POSTIGO, Matheus P. et al. Discovery of new inhibitors of Schistosoma mansoni PNP by pharmacophore-based virtual screening. Journal of Chemical Information and Modeling, v. 50, n. 9, p. 1693-1705, 2010Tradução . . Disponível em: https://doi.org/10.1021/ci100128k. Acesso em: 17 nov. 2025.
APA
Postigo, M. P., Guido, R. V. C., Oliva, G., Castilho, M. S., Pitta, I. R., Albuquerque, J. F. C. de, & Andricopulo, A. D. (2010). Discovery of new inhibitors of Schistosoma mansoni PNP by pharmacophore-based virtual screening. Journal of Chemical Information and Modeling, 50( 9), 1693-1705. doi:10.1021/ci100128k
NLM
Postigo MP, Guido RVC, Oliva G, Castilho MS, Pitta IR, Albuquerque JFC de, Andricopulo AD. Discovery of new inhibitors of Schistosoma mansoni PNP by pharmacophore-based virtual screening [Internet]. Journal of Chemical Information and Modeling. 2010 ; 50( 9): 1693-1705.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/ci100128k
Vancouver
Postigo MP, Guido RVC, Oliva G, Castilho MS, Pitta IR, Albuquerque JFC de, Andricopulo AD. Discovery of new inhibitors of Schistosoma mansoni PNP by pharmacophore-based virtual screening [Internet]. Journal of Chemical Information and Modeling. 2010 ; 50( 9): 1693-1705.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/ci100128k
Artigo de periodico
Role of halogen bonds in thyroid hormone receptor selectivity: pharmacophore-based 3D-QSSR studies (2009)
Valadares, Napoleão F.; Salum, Lívia B.; Polikarpov, Igor ; Andricopulo, Adriano Defini ; Garratt, Richard Charles
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: RELAÇÕES QUANTITATIVAS ENTRE ESTRUTURA QUÍMICA E ATIVIDADE BIOLÓGICA (ESTUDO), HORMÔNIOS TIREOIDIANOS, RECEPTORES HORMONAIS, PLANEJAMENTO DE FÁRMACOS, LIGANTES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
VALADARES, Napoleão F. et al. Role of halogen bonds in thyroid hormone receptor selectivity: pharmacophore-based 3D-QSSR studies. Journal of Chemical Information and Modeling, v. No 2009, n. 11, p. 2606-2616, 2009Tradução . . Disponível em: https://doi.org/10.1021/ci900316e. Acesso em: 17 nov. 2025.
APA
Valadares, N. F., Salum, L. B., Polikarpov, I., Andricopulo, A. D., & Garratt, R. C. (2009). Role of halogen bonds in thyroid hormone receptor selectivity: pharmacophore-based 3D-QSSR studies. Journal of Chemical Information and Modeling, No 2009( 11), 2606-2616. doi:10.1021/ci900316e
NLM
Valadares NF, Salum LB, Polikarpov I, Andricopulo AD, Garratt RC. Role of halogen bonds in thyroid hormone receptor selectivity: pharmacophore-based 3D-QSSR studies [Internet]. Journal of Chemical Information and Modeling. 2009 ; No 2009( 11): 2606-2616.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/ci900316e
Vancouver
Valadares NF, Salum LB, Polikarpov I, Andricopulo AD, Garratt RC. Role of halogen bonds in thyroid hormone receptor selectivity: pharmacophore-based 3D-QSSR studies [Internet]. Journal of Chemical Information and Modeling. 2009 ; No 2009( 11): 2606-2616.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/ci900316e
Artigo de periodico
Structure-based approach for the study of estrogen receptor binding affinity and subtype selectivity (2008)
Salum, Lívia de Barros; Polikarpov, Igor ; Andricopulo, Adriano Defini
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: RELAÇÕES QUANTITATIVAS ENTRE ESTRUTURA QUÍMICA E ATIVIDADE BIOLÓGICA, ESTRÓGENOS (ESTRUTURA), RECEPTORES HORMONAIS, PLANEJAMENTO DE FÁRMACOS, TERAPIA DE REPOSIÇÃO DE ESTRÓGENOS, MULHERES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SALUM, Lívia de Barros e POLIKARPOV, Igor e ANDRICOPULO, Adriano Defini. Structure-based approach for the study of estrogen receptor binding affinity and subtype selectivity. Journal of Chemical Information and Modeling, v. No 2008, n. 11, p. 2243-2253, 2008Tradução . . Disponível em: https://doi.org/10.1021/ci8002182. Acesso em: 17 nov. 2025.
APA
Salum, L. de B., Polikarpov, I., & Andricopulo, A. D. (2008). Structure-based approach for the study of estrogen receptor binding affinity and subtype selectivity. Journal of Chemical Information and Modeling, No 2008( 11), 2243-2253. doi:10.1021/ci8002182
NLM
Salum L de B, Polikarpov I, Andricopulo AD. Structure-based approach for the study of estrogen receptor binding affinity and subtype selectivity [Internet]. Journal of Chemical Information and Modeling. 2008 ; No 2008( 11): 2243-2253.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/ci8002182
Vancouver
Salum L de B, Polikarpov I, Andricopulo AD. Structure-based approach for the study of estrogen receptor binding affinity and subtype selectivity [Internet]. Journal of Chemical Information and Modeling. 2008 ; No 2008( 11): 2243-2253.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/ci8002182
Artigo de periodico
Structural basis for selective inhibition of trypanosomatid glyceraldehyde-3-phosphate dehydrogenase: molecular docking and 3D QSAR studies (2008)
Guido, Rafael Victorio Carvalho ; Oliva, Glaucius ; Montanari, Carlos Alberto ; Andricopulo, Adriano Defini
Fonte: Journal of Chemical Information and Modeling. Unidades: IFSC, IQSC
Assuntos: PLANEJAMENTO DE FÁRMACOS, TRYPANOSOMA CRUZI, LEISHMANIA, DOENÇAS PARASITÁRIAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GUIDO, Rafael Victorio Carvalho et al. Structural basis for selective inhibition of trypanosomatid glyceraldehyde-3-phosphate dehydrogenase: molecular docking and 3D QSAR studies. Journal of Chemical Information and Modeling, v. 48, n. 4, p. 918-929, 2008Tradução . . Acesso em: 17 nov. 2025.
APA
Guido, R. V. C., Oliva, G., Montanari, C. A., & Andricopulo, A. D. (2008). Structural basis for selective inhibition of trypanosomatid glyceraldehyde-3-phosphate dehydrogenase: molecular docking and 3D QSAR studies. Journal of Chemical Information and Modeling, 48( 4), 918-929.
NLM
Guido RVC, Oliva G, Montanari CA, Andricopulo AD. Structural basis for selective inhibition of trypanosomatid glyceraldehyde-3-phosphate dehydrogenase: molecular docking and 3D QSAR studies. Journal of Chemical Information and Modeling. 2008 ; 48( 4): 918-929.[citado 2025 nov. 17 ]
Vancouver
Guido RVC, Oliva G, Montanari CA, Andricopulo AD. Structural basis for selective inhibition of trypanosomatid glyceraldehyde-3-phosphate dehydrogenase: molecular docking and 3D QSAR studies. Journal of Chemical Information and Modeling. 2008 ; 48( 4): 918-929.[citado 2025 nov. 17 ]

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