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Artigo de periodico
Flexibility and hydration of the Qo site determine multiple pathways for proton transfer in cytochrome bc1 (2025)
Camilo, Sofia Rodrigues Guedes; Arantes, Guilherme Menegon
Fonte: Journal of Chemical Information and Modeling. Unidade: IQ
Assuntos: BIOQUÍMICA INORGÂNICA, MOLÉCULA, PEPTÍDEOS, PROTEÍNAS
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ABNT
CAMILO, Sofia Rodrigues Guedes e ARANTES, Guilherme Menegon. Flexibility and hydration of the Qo site determine multiple pathways for proton transfer in cytochrome bc1. Journal of Chemical Information and Modeling, v. 65, n. 12, p. 6184-6197, 2025Tradução . . Disponível em: https://dx.doi.org/10.1021/acs.jcim.5c00655. Acesso em: 08 out. 2025.
APA
Camilo, S. R. G., & Arantes, G. M. (2025). Flexibility and hydration of the Qo site determine multiple pathways for proton transfer in cytochrome bc1. Journal of Chemical Information and Modeling, 65( 12), 6184-6197. doi:10.1021/acs.jcim.5c00655
NLM
Camilo SRG, Arantes GM. Flexibility and hydration of the Qo site determine multiple pathways for proton transfer in cytochrome bc1 [Internet]. Journal of Chemical Information and Modeling. 2025 ; 65( 12): 6184-6197.[citado 2025 out. 08 ] Available from: https://dx.doi.org/10.1021/acs.jcim.5c00655
Vancouver
Camilo SRG, Arantes GM. Flexibility and hydration of the Qo site determine multiple pathways for proton transfer in cytochrome bc1 [Internet]. Journal of Chemical Information and Modeling. 2025 ; 65( 12): 6184-6197.[citado 2025 out. 08 ] Available from: https://dx.doi.org/10.1021/acs.jcim.5c00655
Artigo de periodico
Redox activated proton transfer through a redundant network in the Qo site of Cytochrome bc1 (2025)
Arantes, Guilherme Menegon
Fonte: Journal of Chemical Information and Modeling. Unidade: IQ
Assuntos: MECÂNICA QUÂNTICA, OXIDAÇÃO, REDUÇÃO
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ABNT
ARANTES, Guilherme Menegon. Redox activated proton transfer through a redundant network in the Qo site of Cytochrome bc1. Journal of Chemical Information and Modeling, v. 65, n. 5, p. 2660−2669, 2025Tradução . . Disponível em: https://dx.doi.org/10.1021/acs.jcim.4c02361. Acesso em: 08 out. 2025.
APA
Arantes, G. M. (2025). Redox activated proton transfer through a redundant network in the Qo site of Cytochrome bc1. Journal of Chemical Information and Modeling, 65( 5), 2660−2669. doi:10.1021/acs.jcim.4c02361
NLM
Arantes GM. Redox activated proton transfer through a redundant network in the Qo site of Cytochrome bc1 [Internet]. Journal of Chemical Information and Modeling. 2025 ; 65( 5): 2660−2669.[citado 2025 out. 08 ] Available from: https://dx.doi.org/10.1021/acs.jcim.4c02361
Vancouver
Arantes GM. Redox activated proton transfer through a redundant network in the Qo site of Cytochrome bc1 [Internet]. Journal of Chemical Information and Modeling. 2025 ; 65( 5): 2660−2669.[citado 2025 out. 08 ] Available from: https://dx.doi.org/10.1021/acs.jcim.4c02361
Artigo de periodico
Fuzz testing molecular representation using deep variational anomaly generation (2025)
Nogueira, Victor Henrique Rabesquine ; Sharma, Rishabh; Guido, Rafael Victorio Carvalho ; Keiser, Michael James
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: INTELIGÊNCIA ARTIFICIAL, MODELAGEM MOLECULAR, MOLÉCULA
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ABNT
NOGUEIRA, Victor Henrique Rabesquine et al. Fuzz testing molecular representation using deep variational anomaly generation. Journal of Chemical Information and Modeling, v. 65, n. 4, p. 1911-1927 + supporting information, 2025Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.4c01876. Acesso em: 08 out. 2025.
APA
Nogueira, V. H. R., Sharma, R., Guido, R. V. C., & Keiser, M. J. (2025). Fuzz testing molecular representation using deep variational anomaly generation. Journal of Chemical Information and Modeling, 65( 4), 1911-1927 + supporting information. doi:10.1021/acs.jcim.4c01876
NLM
Nogueira VHR, Sharma R, Guido RVC, Keiser MJ. Fuzz testing molecular representation using deep variational anomaly generation [Internet]. Journal of Chemical Information and Modeling. 2025 ; 65( 4): 1911-1927 + supporting information.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.4c01876
Vancouver
Nogueira VHR, Sharma R, Guido RVC, Keiser MJ. Fuzz testing molecular representation using deep variational anomaly generation [Internet]. Journal of Chemical Information and Modeling. 2025 ; 65( 4): 1911-1927 + supporting information.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.4c01876
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: 08 out. 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 out. 08 ] 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 out. 08 ] 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: 08 out. 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 out. 08 ] 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 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.4c01560
Artigo de periodico
Decoding Van der Waals Impact on Chirality Transfer in Perovskite Structures: Density Functional Theory Insights (2024)
González, José E.; Besse, Rafael; Lima, Matheus P.; Silva, Juarez Lopes Ferreira da
Fonte: Journal of Chemical Information and Modeling. Unidade: IQSC
Assuntos: ENERGIA, QUÍMICA TEÓRICA
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ABNT
GONZÁLEZ, José E. et al. Decoding Van der Waals Impact on Chirality Transfer in Perovskite Structures: Density Functional Theory Insights. Journal of Chemical Information and Modeling, v. 64, n. 4, p. 1306–1318, 2024Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.3c01895. Acesso em: 08 out. 2025.
APA
González, J. E., Besse, R., Lima, M. P., & Silva, J. L. F. da. (2024). Decoding Van der Waals Impact on Chirality Transfer in Perovskite Structures: Density Functional Theory Insights. Journal of Chemical Information and Modeling, 64( 4), 1306–1318. doi:10.1021/acs.jcim.3c01895
NLM
González JE, Besse R, Lima MP, Silva JLF da. Decoding Van der Waals Impact on Chirality Transfer in Perovskite Structures: Density Functional Theory Insights [Internet]. Journal of Chemical Information and Modeling. 2024 ;64( 4): 1306–1318.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.3c01895
Vancouver
González JE, Besse R, Lima MP, Silva JLF da. Decoding Van der Waals Impact on Chirality Transfer in Perovskite Structures: Density Functional Theory Insights [Internet]. Journal of Chemical Information and Modeling. 2024 ;64( 4): 1306–1318.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.3c01895
Artigo de periodico-carta/editorial
Enhancing coarse-grained models through machine learning. [Editorial] (2024)
Karmakar, Tarak; Soares, Thereza Amélia ; Merz Jr, Kenneth M
Fonte: Journal of Chemical Information and Modeling. Unidade: FFCLRP
Assuntos: APRENDIZADO COMPUTACIONAL, SIMULAÇÃO, MODELAGEM MOLECULAR, NANOPARTÍCULAS
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ABNT
KARMAKAR, Tarak e SOARES, Thereza Amélia e MERZ JR, Kenneth M. Enhancing coarse-grained models through machine learning. [Editorial]. Journal of Chemical Information and Modeling. Washington: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1021/acs.jcim.4c00537. Acesso em: 08 out. 2025. , 2024
APA
Karmakar, T., Soares, T. A., & Merz Jr, K. M. (2024). Enhancing coarse-grained models through machine learning. [Editorial]. Journal of Chemical Information and Modeling. Washington: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1021/acs.jcim.4c00537
NLM
Karmakar T, Soares TA, Merz Jr KM. Enhancing coarse-grained models through machine learning. [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64( 8): 2931-2932.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.4c00537
Vancouver
Karmakar T, Soares TA, Merz Jr KM. Enhancing coarse-grained models through machine learning. [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64( 8): 2931-2932.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.4c00537
Artigo de periodico
The Impact of Interdisciplinary, Gender and Geographic Distributions on the Citation Patterns of the Journal of Chemical Information and Modeling (2024)
Prati, Ronaldo C.; Rodrigues, Bruno S. M.; Aragão, Iberis; Silva, Thereza Amélia Soares da; Quiles, Marcos Gonçalves ; Silva, Juarez Lopes Ferreira da
Fonte: Journal of Chemical Information and Modeling. Unidades: IQSC, FFCLRP
Assuntos: BIOENGENHARIA, BIOTECNOLOGIA, BIOLOGIA, MATERIAIS
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ABNT
PRATI, Ronaldo C. et al. The Impact of Interdisciplinary, Gender and Geographic Distributions on the Citation Patterns of the Journal of Chemical Information and Modeling. Journal of Chemical Information and Modeling, v. 64, n. 4, p. 1107–1111, 2024Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.3c02014. Acesso em: 08 out. 2025.
APA
Prati, R. C., Rodrigues, B. S. M., Aragão, I., Silva, T. A. S. da, Quiles, M. G., & Silva, J. L. F. da. (2024). The Impact of Interdisciplinary, Gender and Geographic Distributions on the Citation Patterns of the Journal of Chemical Information and Modeling. Journal of Chemical Information and Modeling, 64( 4), 1107–1111. doi:10.1021/acs.jcim.3c02014
NLM
Prati RC, Rodrigues BSM, Aragão I, Silva TAS da, Quiles MG, Silva JLF da. The Impact of Interdisciplinary, Gender and Geographic Distributions on the Citation Patterns of the Journal of Chemical Information and Modeling [Internet]. Journal of Chemical Information and Modeling. 2024 ;64( 4): 1107–1111.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.3c02014
Vancouver
Prati RC, Rodrigues BSM, Aragão I, Silva TAS da, Quiles MG, Silva JLF da. The Impact of Interdisciplinary, Gender and Geographic Distributions on the Citation Patterns of the Journal of Chemical Information and Modeling [Internet]. Journal of Chemical Information and Modeling. 2024 ;64( 4): 1107–1111.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.3c02014
Artigo de periodico
Dissecting reaction mechanisms and catalytic contributions in Flavoprotein fumarate Reductases (2023)
Curtolo, Felipe ; Arantes, Guilherme Menegon
Fonte: Journal of Chemical Information and Modeling. Unidade: IQ
Assuntos: PROTEÍNAS, PEPTÍDEOS
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ABNT
CURTOLO, Felipe e ARANTES, Guilherme Menegon. Dissecting reaction mechanisms and catalytic contributions in Flavoprotein fumarate Reductases. Journal of Chemical Information and Modeling, v. 63, p. 3510−3520, 2023Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.3c00292. Acesso em: 08 out. 2025.
APA
Curtolo, F., & Arantes, G. M. (2023). Dissecting reaction mechanisms and catalytic contributions in Flavoprotein fumarate Reductases. Journal of Chemical Information and Modeling, 63, 3510−3520. doi:10.1021/acs.jcim.3c00292
NLM
Curtolo F, Arantes GM. Dissecting reaction mechanisms and catalytic contributions in Flavoprotein fumarate Reductases [Internet]. Journal of Chemical Information and Modeling. 2023 ; 63 3510−3520.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.3c00292
Vancouver
Curtolo F, Arantes GM. Dissecting reaction mechanisms and catalytic contributions in Flavoprotein fumarate Reductases [Internet]. Journal of Chemical Information and Modeling. 2023 ; 63 3510−3520.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.3c00292
Artigo de periodico
Molecular dynamics simulations of the human ecto-5′-nucleotidase (h-ecto-5′-NT, CD73): insights into protein flexibility and binding site dynamics (2023)
Viviani, Lucas Gasparello ; Kokh, Daria B ; Wade, Rebecca C ; Amaral, Antonia Tavares do
Fonte: Journal of Chemical Information and Modeling. Unidade: IQ
Assuntos: ESTRUTURA QUÍMICA, PROTEÍNAS
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ABNT
VIVIANI, Lucas Gasparello et al. Molecular dynamics simulations of the human ecto-5′-nucleotidase (h-ecto-5′-NT, CD73): insights into protein flexibility and binding site dynamics. Journal of Chemical Information and Modeling, v. 63, n. 15, p. 4691-4707, 2023Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.3c01068. Acesso em: 08 out. 2025.
APA
Viviani, L. G., Kokh, D. B., Wade, R. C., & Amaral, A. T. do. (2023). Molecular dynamics simulations of the human ecto-5′-nucleotidase (h-ecto-5′-NT, CD73): insights into protein flexibility and binding site dynamics. Journal of Chemical Information and Modeling, 63( 15), 4691-4707. doi:10.1021/acs.jcim.3c01068
NLM
Viviani LG, Kokh DB, Wade RC, Amaral AT do. Molecular dynamics simulations of the human ecto-5′-nucleotidase (h-ecto-5′-NT, CD73): insights into protein flexibility and binding site dynamics [Internet]. Journal of Chemical Information and Modeling. 2023 ; 63( 15): 4691-4707.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.3c01068
Vancouver
Viviani LG, Kokh DB, Wade RC, Amaral AT do. Molecular dynamics simulations of the human ecto-5′-nucleotidase (h-ecto-5′-NT, CD73): insights into protein flexibility and binding site dynamics [Internet]. Journal of Chemical Information and Modeling. 2023 ; 63( 15): 4691-4707.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.3c01068
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: 08 out. 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 out. 08 ] 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 out. 08 ] 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: 08 out. 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 out. 08 ] 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 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00596
Artigo de periodico
Bias amplification in gender, gender identity, and geographical affiliation (2022)
Cascella, Michele; Silva, Thereza Amélia Soares da
Fonte: Journal of Chemical Information and Modeling. Unidade: FFCLRP
Assuntos: PRECONCEITO, PESQUISA CIENTÍFICA
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ABNT
CASCELLA, Michele e SILVA, Thereza Amélia Soares da. Bias amplification in gender, gender identity, and geographical affiliation. Journal of Chemical Information and Modeling, v. 62, n. 24, p. 6297-6301, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00533. Acesso em: 08 out. 2025.
APA
Cascella, M., & Silva, T. A. S. da. (2022). Bias amplification in gender, gender identity, and geographical affiliation. Journal of Chemical Information and Modeling, 62( 24), 6297-6301. doi:10.1021/acs.jcim.2c00533
NLM
Cascella M, Silva TAS da. Bias amplification in gender, gender identity, and geographical affiliation [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 24): 6297-6301.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00533
Vancouver
Cascella M, Silva TAS da. Bias amplification in gender, gender identity, and geographical affiliation [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 24): 6297-6301.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00533
Artigo de periodico
Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape (2022)
Santos, Denys ; Coutinho, Kaline Rabelo ; Silva, Thereza Amélia Soares da
Fonte: Journal of Chemical Information and Modeling. Unidades: IF, FFCLRP
Assuntos: FÍSICO-QUÍMICA, FÍSICA MOLECULAR, SOFTWARE ESTATÍSTICO PARA MICROCOMPUTADORES, LIPÍDEOS DA MEMBRANA
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ABNT
SANTOS, Denys e COUTINHO, Kaline Rabelo e SILVA, Thereza Amélia Soares da. Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape. Journal of Chemical Information and Modeling, v. 62, n. 19, p. 4690-4701, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00673. Acesso em: 08 out. 2025.
APA
Santos, D., Coutinho, K. R., & Silva, T. A. S. da. (2022). Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape. Journal of Chemical Information and Modeling, 62( 19), 4690-4701. doi:10.1021/acs.jcim.2c00673
NLM
Santos D, Coutinho KR, Silva TAS da. Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 19): 4690-4701.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00673
Vancouver
Santos D, Coutinho KR, Silva TAS da. Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 19): 4690-4701.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00673
Artigo de periodico
Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces (2022)
Santos, Alberto M. Dos; Oliveira, Amanda Ruslana Santana; Costa, Clauber H. S. da; Kenny, Peter W.; Montanari, Carlos Alberto ; Varela Júnior, Jaldyr de Jesus G.; Lameira, Jerônimo
Fonte: Journal of Chemical Information and Modeling. Unidade: IQSC
Assuntos: AMINOÁCIDOS, MECÂNICA QUÂNTICA, ENERGIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Alberto M. Dos et al. Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces. Journal of Chemical Information and Modeling, v. 62, p. 4083-4094, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00466. Acesso em: 08 out. 2025.
APA
Santos, A. M. D., Oliveira, A. R. S., Costa, C. H. S. da, Kenny, P. W., Montanari, C. A., Varela Júnior, J. de J. G., & Lameira, J. (2022). Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces. Journal of Chemical Information and Modeling, 62, 4083-4094. doi:10.1021/acs.jcim.2c00466
NLM
Santos AMD, Oliveira ARS, Costa CHS da, Kenny PW, Montanari CA, Varela Júnior J de JG, Lameira J. Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62 4083-4094.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00466
Vancouver
Santos AMD, Oliveira ARS, Costa CHS da, Kenny PW, Montanari CA, Varela Júnior J de JG, Lameira J. Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62 4083-4094.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00466
Artigo de periodico
Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder (2022)
Oliveira, Andre F ; Silva, Juarez Lopes Ferreira da ; Quiles, Marcos Gonçalves
Fonte: Journal of Chemical Information and Modeling. Unidade: IQSC
Assuntos: ENERGIA, MOLÉCULA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Andre F e SILVA, Juarez Lopes Ferreira da e QUILES, Marcos Gonçalves. Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder. Journal of Chemical Information and Modeling, v. 62, p. 817−828, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c01573. Acesso em: 08 out. 2025.
APA
Oliveira, A. F., Silva, J. L. F. da, & Quiles, M. G. (2022). Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder. Journal of Chemical Information and Modeling, 62, 817−828. doi:10.1021/acs.jcim.1c01573
NLM
Oliveira AF, Silva JLF da, Quiles MG. Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62 817−828.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c01573
Vancouver
Oliveira AF, Silva JLF da, Quiles MG. Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62 817−828.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c01573
Artigo de periodico-carta/editorial
The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial] (2022)
Soares, Thereza A. ; Alves, Ariane Ferreira Nunes; Mazzolari, Angelica; Ruggiu, Fiorella; Wei, Guo-Wei; Merz, Kenneth
Fonte: Journal of Chemical Information and Modeling. Unidade: FFCLRP
Assuntos: APRENDIZADO COMPUTACIONAL, MODELOS MATEMÁTICOS, ESTRUTURA MOLECULAR (QUÍMICA TEÓRICA)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOARES, Thereza A. et al. The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial]. Journal of Chemical Information and Modeling. Washington: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1021/acs.jcim.2c01422. Acesso em: 08 out. 2025. , 2022
APA
Soares, T. A., Alves, A. F. N., Mazzolari, A., Ruggiu, F., Wei, G. -W., & Merz, K. (2022). The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial]. Journal of Chemical Information and Modeling. Washington: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1021/acs.jcim.2c01422
NLM
Soares TA, Alves AFN, Mazzolari A, Ruggiu F, Wei G-W, Merz K. The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 22): 5317-5320.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c01422
Vancouver
Soares TA, Alves AFN, Mazzolari A, Ruggiu F, Wei G-W, Merz K. The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 22): 5317-5320.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c01422
Artigo de periodico
SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning (2022)
Pinheiro, Gabriel A.; Silva, Juarez Lopes Ferreira da ; Quiles, Marcos Gonçalves
Fonte: Journal of Chemical Information and Modeling. Unidade: IQSC
Assuntos: MODELAGEM MOLECULAR, MOLÉCULA, QUÍMICA TEÓRICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PINHEIRO, Gabriel A. e SILVA, Juarez Lopes Ferreira da e QUILES, Marcos Gonçalves. SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning. Journal of Chemical Information and Modeling, v. 62, n. 17, p. 3948–3960, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00521. Acesso em: 08 out. 2025.
APA
Pinheiro, G. A., Silva, J. L. F. da, & Quiles, M. G. (2022). SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning. Journal of Chemical Information and Modeling, 62( 17), 3948–3960. doi:10.1021/acs.jcim.2c00521
NLM
Pinheiro GA, Silva JLF da, Quiles MG. SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 17): 3948–3960.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00521
Vancouver
Pinheiro GA, Silva JLF da, Quiles MG. SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 17): 3948–3960.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00521
Artigo de periodico
Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining (2022)
Moraes, Alex S.; Pinheiro, Gabriel A.; Lourenço, Tuanan da Costa ; Lopes, Mauro C.; Quiles, Marcos G.; Dias, Luis G. ; Silva, Juarez Lopes Ferreira da
Fonte: Journal of Chemical Information and Modeling. Unidades: FFCLRP, IQSC
Assuntos: ÍONS ELETRÔNICOS, ESTRUTURA ATÔMICA (QUÍMICA TEÓRICA), ENERGIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MORAES, Alex S. et al. Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining. Journal of Chemical Information and Modeling, v. 62, n. 19, p. 4702–4712, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00748. Acesso em: 08 out. 2025.
APA
Moraes, A. S., Pinheiro, G. A., Lourenço, T. da C., Lopes, M. C., Quiles, M. G., Dias, L. G., & Silva, J. L. F. da. (2022). Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining. Journal of Chemical Information and Modeling, 62( 19), 4702–4712. doi:10.1021/acs.jcim.2c00748
NLM
Moraes AS, Pinheiro GA, Lourenço T da C, Lopes MC, Quiles MG, Dias LG, Silva JLF da. Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 19): 4702–4712.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00748
Vancouver
Moraes AS, Pinheiro GA, Lourenço T da C, Lopes MC, Quiles MG, Dias LG, Silva JLF da. Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 19): 4702–4712.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00748
Artigo de periodico
Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles (2022)
Mendonça, João Paulo A. de ; Calderan, Felipe V.; Lourenço, Tuanan da Costa ; Quiles, Marcos G.; Silva, Juarez Lopes Ferreira da
Fonte: Journal of Chemical Information and Modeling. Unidade: IQSC
Assuntos: COMBUSTÍVEIS, COBRE, NANOCOMPOSITOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MENDONÇA, João Paulo A. de et al. Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles. Journal of Chemical Information and Modeling, v. 27, p. 5503-5512, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00957. Acesso em: 08 out. 2025.
APA
Mendonça, J. P. A. de, Calderan, F. V., Lourenço, T. da C., Quiles, M. G., & Silva, J. L. F. da. (2022). Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles. Journal of Chemical Information and Modeling, 27, 5503-5512. doi:10.1021/acs.jcim.2c00957
NLM
Mendonça JPA de, Calderan FV, Lourenço T da C, Quiles MG, Silva JLF da. Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles [Internet]. Journal of Chemical Information and Modeling. 2022 ; 27 5503-5512.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00957
Vancouver
Mendonça JPA de, Calderan FV, Lourenço T da C, Quiles MG, Silva JLF da. Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles [Internet]. Journal of Chemical Information and Modeling. 2022 ; 27 5503-5512.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00957

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