Filtros : "Journal of Chemical Information and Modeling" "Financiamento CAPES" Removido: "Andricopulo, Adriano Defini" Limpar

Filtros



Refine with date range


  • Source: Journal of Chemical Information and Modeling. Unidade: IQ

    Subjects: BIOQUÍMICA INORGÂNICA, MOLÉCULA, PEPTÍDEOS, PROTEÍNAS

    Versão PublicadaAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • 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: 19 nov. 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 nov. 19 ] 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 nov. 19 ] Available from: https://dx.doi.org/10.1021/acs.jcim.5c00655
  • Source: Journal of Chemical Information and Modeling. Unidade: IFSC

    Subjects: INTELIGÊNCIA ARTIFICIAL, MODELAGEM MOLECULAR, MOLÉCULA

    Versão PublicadaAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • 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: 19 nov. 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 nov. 19 ] 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 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.4c01876
  • Source: Journal of Chemical Information and Modeling. Unidade: IFSC

    Subjects: ZIKA VÍRUS, PLANEJAMENTO DE FÁRMACOS, ANTIVIRAIS

    PrivadoAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • 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: 19 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. 19 ] 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. 19 ] Available from: https://doi.org/10.1021/acs.jcim.2c00596
  • Source: Journal of Chemical Information and Modeling. Unidade: IQSC

    Subjects: AMINOÁCIDOS, MECÂNICA QUÂNTICA, ENERGIA

    PrivadoAcesso à fonteDOIHow to cite
    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: 19 nov. 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 nov. 19 ] 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 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.2c00466
  • Source: Journal of Chemical Information and Modeling. Unidade: IFSC

    Subjects: APRENDIZADO COMPUTACIONAL, FÁRMACOS (ESTUDO;DESENVOLVIMENTO)

    PrivadoAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • 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: 19 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. 19 ] 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. 19 ] Available from: https://doi.org/10.1021/acs.jcim.2c00695
  • Source: Journal of Chemical Information and Modeling. Unidade: IQSC

    Subjects: ENERGIA, MOLÉCULA

    PrivadoAcesso à fonteDOIHow to cite
    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: 19 nov. 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 nov. 19 ] 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 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.1c01573
  • Source: Journal of Chemical Information and Modeling. Unidades: FFCLRP, IQSC

    Subjects: ÍONS ELETRÔNICOS, ESTRUTURA ATÔMICA (QUÍMICA TEÓRICA), ENERGIA

    PrivadoAcesso à fonteDOIHow to cite
    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: 19 nov. 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 nov. 19 ] 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 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.2c00748
  • Source: Journal of Chemical Information and Modeling. Unidades: FCFRP, Interunidades em Bioinformática

    Subjects: ZIKA VÍRUS, VIRULÊNCIA, FLAVIVIRUS

    PrivadoAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      POVEDA CUEVAS, Sergio Alejandro e SILVA, Fernando Luís Barroso da e ETCHEBEST, Catherine. How the strain origin of Zika Virus NS1 protein impacts its dynamics and implications to their differential virulence. Journal of Chemical Information and Modeling, v. 61, n. 3, p. 1516-1530, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.0c01377. Acesso em: 19 nov. 2025.
    • APA

      Poveda Cuevas, S. A., Silva, F. L. B. da, & Etchebest, C. (2021). How the strain origin of Zika Virus NS1 protein impacts its dynamics and implications to their differential virulence. Journal of Chemical Information and Modeling, 61( 3), 1516-1530. doi:10.1021/acs.jcim.0c01377
    • NLM

      Poveda Cuevas SA, Silva FLB da, Etchebest C. How the strain origin of Zika Virus NS1 protein impacts its dynamics and implications to their differential virulence [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 3): 1516-1530.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.0c01377
    • Vancouver

      Poveda Cuevas SA, Silva FLB da, Etchebest C. How the strain origin of Zika Virus NS1 protein impacts its dynamics and implications to their differential virulence [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 3): 1516-1530.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.0c01377
  • Source: Journal of Chemical Information and Modeling. Unidade: IQSC

    Subjects: METAIS, ADSORÇÃO, FÍSICO-QUÍMICA

    PrivadoAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      BATISTA, Krys E. A. et al. Energy Decomposition to Access the Stability Changes Induced by CO Adsorption on Transition-Metal 13-Atom Clusters. Journal of Chemical Information and Modeling, v. 61, n. 5, p. 2294–2301, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00097. Acesso em: 19 nov. 2025.
    • APA

      Batista, K. E. A., Soares, M. D., Quiles, M. G., Piotrowski, M. J., & Da Silva, J. L. F. (2021). Energy Decomposition to Access the Stability Changes Induced by CO Adsorption on Transition-Metal 13-Atom Clusters. Journal of Chemical Information and Modeling, 61( 5), 2294–2301. doi:10.1021/acs.jcim.1c00097
    • NLM

      Batista KEA, Soares MD, Quiles MG, Piotrowski MJ, Da Silva JLF. Energy Decomposition to Access the Stability Changes Induced by CO Adsorption on Transition-Metal 13-Atom Clusters [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 5): 2294–2301.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.1c00097
    • Vancouver

      Batista KEA, Soares MD, Quiles MG, Piotrowski MJ, Da Silva JLF. Energy Decomposition to Access the Stability Changes Induced by CO Adsorption on Transition-Metal 13-Atom Clusters [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 5): 2294–2301.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.1c00097
  • Source: Journal of Chemical Information and Modeling. Unidade: IQSC

    Subjects: QUÍMICA QUÂNTICA, ALGORITMOS

    PrivadoAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      AZEVEDO, Luis Cesar de et al. Systematic Investigation of Error Distribution in Machine Learning Algorithms Applied to the Quantum-Chemistry QM9 Data Set Using the Bias and Variance Decomposition. Journal of Chemical Information and Modeling, v. 61, p. 4210−4223, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00503. Acesso em: 19 nov. 2025.
    • APA

      Azevedo, L. C. de, Pinheiro, G. A., Quiles, M. G., Silva, J. L. F. da, & Prati, R. C. (2021). Systematic Investigation of Error Distribution in Machine Learning Algorithms Applied to the Quantum-Chemistry QM9 Data Set Using the Bias and Variance Decomposition. Journal of Chemical Information and Modeling, 61, 4210−4223. doi:10.1021/acs.jcim.1c00503
    • NLM

      Azevedo LC de, Pinheiro GA, Quiles MG, Silva JLF da, Prati RC. Systematic Investigation of Error Distribution in Machine Learning Algorithms Applied to the Quantum-Chemistry QM9 Data Set Using the Bias and Variance Decomposition [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61 4210−4223.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.1c00503
    • Vancouver

      Azevedo LC de, Pinheiro GA, Quiles MG, Silva JLF da, Prati RC. Systematic Investigation of Error Distribution in Machine Learning Algorithms Applied to the Quantum-Chemistry QM9 Data Set Using the Bias and Variance Decomposition [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61 4210−4223.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.1c00503
  • Source: Journal of Chemical Information and Modeling. Unidade: IQSC

    Subjects: MEDICAMENTO, ENZIMAS

    PrivadoAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      BONATTO, Vinícius et al. Predicting the Relative Binding Affinity for Reversible Covalent Inhibitors by Free Energy Perturbation Calculations. Journal of Chemical Information and Modeling, v. 61, p. 4733−4744, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00515. Acesso em: 19 nov. 2025.
    • APA

      Bonatto, V., Shamim, A., Rocho, F. dos R., Leitão, A., Luque, F. J., & Montanari, C. A. (2021). Predicting the Relative Binding Affinity for Reversible Covalent Inhibitors by Free Energy Perturbation Calculations. Journal of Chemical Information and Modeling, 61, 4733−4744. doi:10.1021/acs.jcim.1c00515
    • NLM

      Bonatto V, Shamim A, Rocho F dos R, Leitão A, Luque FJ, Montanari CA. Predicting the Relative Binding Affinity for Reversible Covalent Inhibitors by Free Energy Perturbation Calculations [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61 4733−4744.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.1c00515
    • Vancouver

      Bonatto V, Shamim A, Rocho F dos R, Leitão A, Luque FJ, Montanari CA. Predicting the Relative Binding Affinity for Reversible Covalent Inhibitors by Free Energy Perturbation Calculations [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61 4733−4744.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.1c00515
  • Source: Journal of Chemical Information and Modeling. Unidade: FFCLRP

    Subjects: CANABINOIDES, SIMULAÇÃO, TRANSTORNOS RELACIONADOS AO USO DE SUBSTÂNCIAS

    PrivadoAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      CASTRO, Jade Simões de e RODRIGUES, Caio Henrique Pinke e BRUNI, Aline Thaís. In silico infrared characterization of synthetic cannabinoids by quantum chemistry and chemometrics. Journal of Chemical Information and Modeling, v. 60, n. 4, p. 2100-2114, 2020Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.9b00871. Acesso em: 19 nov. 2025.
    • APA

      Castro, J. S. de, Rodrigues, C. H. P., & Bruni, A. T. (2020). In silico infrared characterization of synthetic cannabinoids by quantum chemistry and chemometrics. Journal of Chemical Information and Modeling, 60( 4), 2100-2114. doi:10.1021/acs.jcim.9b00871
    • NLM

      Castro JS de, Rodrigues CHP, Bruni AT. In silico infrared characterization of synthetic cannabinoids by quantum chemistry and chemometrics [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 4): 2100-2114.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.9b00871
    • Vancouver

      Castro JS de, Rodrigues CHP, Bruni AT. In silico infrared characterization of synthetic cannabinoids by quantum chemistry and chemometrics [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 4): 2100-2114.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.9b00871
  • Source: Journal of Chemical Information and Modeling. Unidades: Interunidades em Bioinformática, FCFRP

    Subjects: ANTÍGENOS, IMUNOLOGIA, FLAVIVIRUS

    PrivadoAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      POVEDA CUEVAS, Sergio Alejandro e ETCHEBEST, Catherine e SILVA, Fernando Luís Barroso da. Identification of electrostatic epitopes in flavivirus by computer simulations: the PROCEEDpKa method. Journal of Chemical Information and Modeling, v. 60, n. 2, p. 944-963, 2019Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.9b00895. Acesso em: 19 nov. 2025.
    • APA

      Poveda Cuevas, S. A., Etchebest, C., & Silva, F. L. B. da. (2019). Identification of electrostatic epitopes in flavivirus by computer simulations: the PROCEEDpKa method. Journal of Chemical Information and Modeling, 60( 2), 944-963. doi:10.1021/acs.jcim.9b00895
    • NLM

      Poveda Cuevas SA, Etchebest C, Silva FLB da. Identification of electrostatic epitopes in flavivirus by computer simulations: the PROCEEDpKa method [Internet]. Journal of Chemical Information and Modeling. 2019 ; 60( 2): 944-963.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.9b00895
    • Vancouver

      Poveda Cuevas SA, Etchebest C, Silva FLB da. Identification of electrostatic epitopes in flavivirus by computer simulations: the PROCEEDpKa method [Internet]. Journal of Chemical Information and Modeling. 2019 ; 60( 2): 944-963.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.9b00895

Digital Library of Intellectual Production of Universidade de São Paulo     2012 - 2025