ReP USP - Resultado da busca

Artigo de periodico
Advances and challenges in molecular docking applied to neglected tropical diseases (2025)
Angelo, Rafaela Molina de ; Nascimento, Lucas Alex; Encide, João Pedro Portilho; Silva, Henrique Borges da ; Lago, João Henrique Ghilardi ; Emery, Flavio da Silva ; Honorio, Kathia Maria
Fonte: Current Medicinal Chemistry. Unidades: FCFRP, EACH
Assunto: DOENÇAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ANGELO, Rafaela Molina de et al. Advances and challenges in molecular docking applied to neglected tropical diseases. Current Medicinal Chemistry, n. Ja 2025, p. 01-21, 2025Tradução . . Disponível em: http://dx.doi.org/10.2174/0109298673327352240930040103. Acesso em: 12 nov. 2025.
APA
Angelo, R. M. de, Nascimento, L. A., Encide, J. P. P., Silva, H. B. da, Lago, J. H. G., Emery, F. da S., & Honorio, K. M. (2025). Advances and challenges in molecular docking applied to neglected tropical diseases. Current Medicinal Chemistry, ( Ja 2025), 01-21. doi:10.2174/0109298673327352240930040103
NLM
Angelo RM de, Nascimento LA, Encide JPP, Silva HB da, Lago JHG, Emery F da S, Honorio KM. Advances and challenges in molecular docking applied to neglected tropical diseases [Internet]. Current Medicinal Chemistry. 2025 ;( Ja 2025): 01-21.[citado 2025 nov. 12 ] Available from: http://dx.doi.org/10.2174/0109298673327352240930040103
Vancouver
Angelo RM de, Nascimento LA, Encide JPP, Silva HB da, Lago JHG, Emery F da S, Honorio KM. Advances and challenges in molecular docking applied to neglected tropical diseases [Internet]. Current Medicinal Chemistry. 2025 ;( Ja 2025): 01-21.[citado 2025 nov. 12 ] Available from: http://dx.doi.org/10.2174/0109298673327352240930040103
Artigo de periodico
Machine learning models for the identification of natural products with anti-schistosomiasis activity (2025)
Angelo, Rafaela Molina de ; Maltarollo, Vinícius Gonçalves ; Lago, João Henrique Ghilardi ; Honorio, Kathia Maria
Fonte: Journal Brazilian Chemical Society. Unidade: EACH
Assunto: ESQUISTOSSOMOSE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ANGELO, Rafaela Molina de et al. Machine learning models for the identification of natural products with anti-schistosomiasis activity. Journal Brazilian Chemical Society, v. 36, n. 8, p. 01-18, 2025Tradução . . Disponível em: http://dx.doi.org/10.21577/0103-5053.20250070. Acesso em: 12 nov. 2025.
APA
Angelo, R. M. de, Maltarollo, V. G., Lago, J. H. G., & Honorio, K. M. (2025). Machine learning models for the identification of natural products with anti-schistosomiasis activity. Journal Brazilian Chemical Society, 36( 8), 01-18. doi:10.21577/0103-5053.20250070
NLM
Angelo RM de, Maltarollo VG, Lago JHG, Honorio KM. Machine learning models for the identification of natural products with anti-schistosomiasis activity [Internet]. Journal Brazilian Chemical Society. 2025 ; 36( 8): 01-18.[citado 2025 nov. 12 ] Available from: http://dx.doi.org/10.21577/0103-5053.20250070
Vancouver
Angelo RM de, Maltarollo VG, Lago JHG, Honorio KM. Machine learning models for the identification of natural products with anti-schistosomiasis activity [Internet]. Journal Brazilian Chemical Society. 2025 ; 36( 8): 01-18.[citado 2025 nov. 12 ] Available from: http://dx.doi.org/10.21577/0103-5053.20250070
Artigo de periodico
Computational and experimental studies to discover a promising lead compound, chemically related to natural acetylene acetogenins from Porcelia macrocarpa, against amastigotes of Leishmania (L.) infantum (2025)
Encide, João Pedro Portilho; Brito, Ivanildo A. de; Amaral, Maiara; Tempone, Andre Gustavo; Lago, João Henrique Ghilardi; Honorio, Kathia Maria
Fonte: Journal of Computer - Aided Molecular Design. Unidade: EACH
Assunto: METABÓLITOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ENCIDE, João Pedro Portilho et al. Computational and experimental studies to discover a promising lead compound, chemically related to natural acetylene acetogenins from Porcelia macrocarpa, against amastigotes of Leishmania (L.) infantum. Journal of Computer - Aided Molecular Design, v. 39, n. 88, p. 01-12, 2025Tradução . . Disponível em: http://dx.doi.org/10.1007/s10822-025-00659-4. Acesso em: 12 nov. 2025.
APA
Encide, J. P. P., Brito, I. A. de, Amaral, M., Tempone, A. G., Lago, J. H. G., & Honorio, K. M. (2025). Computational and experimental studies to discover a promising lead compound, chemically related to natural acetylene acetogenins from Porcelia macrocarpa, against amastigotes of Leishmania (L.) infantum. Journal of Computer - Aided Molecular Design, 39( 88), 01-12. doi:10.1007/s10822-025-00659-4
NLM
Encide JPP, Brito IA de, Amaral M, Tempone AG, Lago JHG, Honorio KM. Computational and experimental studies to discover a promising lead compound, chemically related to natural acetylene acetogenins from Porcelia macrocarpa, against amastigotes of Leishmania (L.) infantum [Internet]. Journal of Computer - Aided Molecular Design. 2025 ; 39( 88): 01-12.[citado 2025 nov. 12 ] Available from: http://dx.doi.org/10.1007/s10822-025-00659-4
Vancouver
Encide JPP, Brito IA de, Amaral M, Tempone AG, Lago JHG, Honorio KM. Computational and experimental studies to discover a promising lead compound, chemically related to natural acetylene acetogenins from Porcelia macrocarpa, against amastigotes of Leishmania (L.) infantum [Internet]. Journal of Computer - Aided Molecular Design. 2025 ; 39( 88): 01-12.[citado 2025 nov. 12 ] Available from: http://dx.doi.org/10.1007/s10822-025-00659-4
Artigo de periodico
Andrographolide: a diterpenoid from cymbopogon schoenanthus identified as a new hit compound against trypanosoma cruzi using machine learning and experimental approaches (2024)
Barbosa, Henrique ; Espinoza, Gabriel Zarzana; Amaral, Maiara; Levatti, Erica Valadares de Castro ; Abiuzi, Mariana Babberg ; Veríssimo, Gabriel Corrêa ; Fernandes, Philipe Oliveira ; Maltarollo, Vinícius Gonçalves ; Tempone, Andre Gustavo ; Honorio, Kathia Maria ; Lago, João Henrique Ghilardi
Fonte: Journal of Chemical Information and Modeling. Unidade: EACH
Assunto: DOENÇA DE CHAGAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BARBOSA, Henrique et al. Andrographolide: a diterpenoid from cymbopogon schoenanthus identified as a new hit compound against trypanosoma cruzi using machine learning and experimental approaches. Journal of Chemical Information and Modeling, v. 64, p. 2565−2576, 2024Tradução . . Disponível em: http://dx.doi.org/10.1021/acs.jcim.3c01410. Acesso em: 12 nov. 2025.
APA
Barbosa, H., Espinoza, G. Z., Amaral, M., Levatti, E. V. de C., Abiuzi, M. B., Veríssimo, G. C., et al. (2024). Andrographolide: a diterpenoid from cymbopogon schoenanthus identified as a new hit compound against trypanosoma cruzi using machine learning and experimental approaches. Journal of Chemical Information and Modeling, 64, 2565−2576. doi:10.1021/acs.jcim.3c01410
NLM
Barbosa H, Espinoza GZ, Amaral M, Levatti EV de C, Abiuzi MB, Veríssimo GC, Fernandes PO, Maltarollo VG, Tempone AG, Honorio KM, Lago JHG. Andrographolide: a diterpenoid from cymbopogon schoenanthus identified as a new hit compound against trypanosoma cruzi using machine learning and experimental approaches [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64 2565−2576.[citado 2025 nov. 12 ] Available from: http://dx.doi.org/10.1021/acs.jcim.3c01410
Vancouver
Barbosa H, Espinoza GZ, Amaral M, Levatti EV de C, Abiuzi MB, Veríssimo GC, Fernandes PO, Maltarollo VG, Tempone AG, Honorio KM, Lago JHG. Andrographolide: a diterpenoid from cymbopogon schoenanthus identified as a new hit compound against trypanosoma cruzi using machine learning and experimental approaches [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64 2565−2576.[citado 2025 nov. 12 ] Available from: http://dx.doi.org/10.1021/acs.jcim.3c01410
Artigo de periodico
Identification of inhibitors as drug candidates against Chagas disease (2023)
Araujo, Sheila Cruz; Angelo, Rafaela Molina de; Barbosa, Henrique; Silva, Thais Alves Costa; Tempone, André Gustavo; Lago, João Henrique Ghilardi; Honorio, Kathia Maria
Fonte: European Journal of Medicinal Chemistry. Unidade: EACH
Assunto: DOENÇA DE CHAGAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ARAUJO, Sheila Cruz et al. Identification of inhibitors as drug candidates against Chagas disease. European Journal of Medicinal Chemistry, v. 248, p. 01-17, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.ejmech.2022.115074. Acesso em: 12 nov. 2025.
APA
Araujo, S. C., Angelo, R. M. de, Barbosa, H., Silva, T. A. C., Tempone, A. G., Lago, J. H. G., & Honorio, K. M. (2023). Identification of inhibitors as drug candidates against Chagas disease. European Journal of Medicinal Chemistry, 248, 01-17. doi:10.1016/j.ejmech.2022.115074
NLM
Araujo SC, Angelo RM de, Barbosa H, Silva TAC, Tempone AG, Lago JHG, Honorio KM. Identification of inhibitors as drug candidates against Chagas disease [Internet]. European Journal of Medicinal Chemistry. 2023 ; 248 01-17.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1016/j.ejmech.2022.115074
Vancouver
Araujo SC, Angelo RM de, Barbosa H, Silva TAC, Tempone AG, Lago JHG, Honorio KM. Identification of inhibitors as drug candidates against Chagas disease [Internet]. European Journal of Medicinal Chemistry. 2023 ; 248 01-17.[citado 2025 nov. 12 ] Available from: https://doi.org/10.1016/j.ejmech.2022.115074

Unidades USP

ReP

Filtros

Autores

Afiliação dos autores externos não normalizada