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

    Subjects: ELÉTRONS, PEPTÍDEOS, PROTEÍNAS

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    • ABNT

      CAMILO, Sofia Rodrigues Guedes; CURTOLO, Felipe; GALASSI, Vanesa V; ARANTES, Guilherme Menegon. Tunneling and nonadiabatic effects on a proton-coupled electron transfer model for the Qo site in cytochrome bc1. Journal of Chemical Information and Modeling, Washington, v. 61, p. 1840−1849, 2021. Disponível em: < http://dx.doi.org/10.1021/acs.jcim.1c00008 > DOI: 10.1021/acs.jcim.1c00008.
    • APA

      Camilo, S. R. G., Curtolo, F., Galassi, V. V., & Arantes, G. M. (2021). Tunneling and nonadiabatic effects on a proton-coupled electron transfer model for the Qo site in cytochrome bc1. Journal of Chemical Information and Modeling, 61, 1840−1849. doi:10.1021/acs.jcim.1c00008
    • NLM

      Camilo SRG, Curtolo F, Galassi VV, Arantes GM. Tunneling and nonadiabatic effects on a proton-coupled electron transfer model for the Qo site in cytochrome bc1 [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61 1840−1849.Available from: http://dx.doi.org/10.1021/acs.jcim.1c00008
    • Vancouver

      Camilo SRG, Curtolo F, Galassi VV, Arantes GM. Tunneling and nonadiabatic effects on a proton-coupled electron transfer model for the Qo site in cytochrome bc1 [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61 1840−1849.Available from: http://dx.doi.org/10.1021/acs.jcim.1c00008
  • Source: Journal of Chemical Information and Modeling. Unidade: IQSC

    Subjects: METAIS, ADSORÇÃO, FÍSICO-QUÍMICA

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      BATISTA, Krys E. A.; PIOTROWSKI, Maurício J.; DA SILVA, Juarez Lopes Ferreira; SOARES, Marinalva D.; QUILES, Marcos G. Energy Decomposition to Access the Stability Changes Induced by CO Adsorption on Transition-Metal 13-Atom Clusters. Journal of Chemical Information and Modeling, Washington, v. 61, n. 5, p. 2294–2301, 2021. Disponível em: < https://doi.org/10.1021/acs.jcim.1c00097 > DOI: 10.1021/acs.jcim.1c00097.
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      Batista, K. E. A., Piotrowski, M. J., Da Silva, J. L. F., Soares, M. D., & Quiles, M. G. (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, Piotrowski MJ, Da Silva JLF, Soares MD, Quiles MG. 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.Available from: https://doi.org/10.1021/acs.jcim.1c00097
    • Vancouver

      Batista KEA, Piotrowski MJ, Da Silva JLF, Soares MD, Quiles MG. 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.Available from: https://doi.org/10.1021/acs.jcim.1c00097
  • Source: Journal of Chemical Information and Modeling. Unidade: IFSC

    Subjects: PLANEJAMENTO DE FÁRMACOS, COMPUTAÇÃO APLICADA, INTELIGÊNCIA ARTIFICIAL

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      BATRA, Kushal; ZORN, Kimberley M.; FOIL, Daniel H.; MINERALI, Eni; GAWRILJUK, Victor Oliveira. Quantum machine learning algorithms for drug discovery applications. Journal of Chemical Information and Modeling, Washington, DC, v. 61, n. 6, p. 2641-2647, 2021. Disponível em: < http://dx.doi.org/10.1021/acs.jcim.1c00166 > DOI: 10.1021/acs.jcim.1c00166.
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      Batra, K., Zorn, K. M., Foil, D. H., Minerali, E., & Gawriljuk, V. O. (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. Quantum machine learning algorithms for drug discovery applications [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 6): 2641-2647.Available from: http://dx.doi.org/10.1021/acs.jcim.1c00166
    • Vancouver

      Batra K, Zorn KM, Foil DH, Minerali E, Gawriljuk VO. Quantum machine learning algorithms for drug discovery applications [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 6): 2641-2647.Available from: http://dx.doi.org/10.1021/acs.jcim.1c00166
  • Source: Journal of Chemical Information and Modeling. Unidade: IQSC

    Subjects: QUÍMICA QUÂNTICA, MINERAÇÃO DE DADOS, FRAMEWORKS

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      MUCELINI, Johnatan; QUILES, Marcos Gonçalves; PRATI, Ronaldo Cristiano; SILVA, Juarez Lopes Ferreira da. Correlation-based framework for extraction of insights from quantum chemistry databases: Applications for nanoclusters. Journal of Chemical Information and Modeling, Washington, DC, American Chemical Society, v. 61, p. 1125-1135, 2021. Disponível em: < https://doi.org/10.1021/acs.jcim.0c01267 > DOI: 10.1021/acs.jcim.0c01267.
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      Mucelini, J., Quiles, M. G., Prati, R. C., & Silva, J. L. F. da. (2021). Correlation-based framework for extraction of insights from quantum chemistry databases: Applications for nanoclusters. Journal of Chemical Information and Modeling, 61, 1125-1135. doi:10.1021/acs.jcim.0c01267
    • NLM

      Mucelini J, Quiles MG, Prati RC, Silva JLF da. Correlation-based framework for extraction of insights from quantum chemistry databases: Applications for nanoclusters [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61 1125-1135.Available from: https://doi.org/10.1021/acs.jcim.0c01267
    • Vancouver

      Mucelini J, Quiles MG, Prati RC, Silva JLF da. Correlation-based framework for extraction of insights from quantum chemistry databases: Applications for nanoclusters [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61 1125-1135.Available from: https://doi.org/10.1021/acs.jcim.0c01267
  • Source: Journal of Chemical Information and Modeling. Unidade: IQSC

    Subjects: QUÍMICA QUÂNTICA, ALGORITMOS

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      AZEVEDO, Luis Cesar de; SILVA, Juarez Lopes Ferreira da; PRATI, Ronaldo C.; QUILES, Marcos G.; PINHEIRO, Gabriel A. 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, Washington, 2021. Disponível em: < https://doi.org/10.1021/acs.jcim.1c00503 > DOI: 10.1021/acs.jcim.1c00503.
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      Azevedo, L. C. de, Silva, J. L. F. da, Prati, R. C., Quiles, M. G., & Pinheiro, G. A. (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. doi:10.1021/acs.jcim.1c00503
    • NLM

      Azevedo LC de, Silva JLF da, Prati RC, Quiles MG, Pinheiro GA. 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 ;Available from: https://doi.org/10.1021/acs.jcim.1c00503
    • Vancouver

      Azevedo LC de, Silva JLF da, Prati RC, Quiles MG, Pinheiro GA. 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 ;Available from: https://doi.org/10.1021/acs.jcim.1c00503
  • Source: Journal of Chemical Information and Modeling. Unidades: IQSC, IFSC

    Assunto: METAIS

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      MORAIS, Felipe Orlando; ANDRIANI, Karla Furtado; 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, Washington, DC, v. 61, n. 7, p. 3411-3420, 2021. Disponível em: < https://doi.org/10.1021/acs.jcim.1c00253 > DOI: 10.1021/acs.jcim.1c00253.
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      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.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.Available from: https://doi.org/10.1021/acs.jcim.1c00253
  • Source: Journal of Chemical Information and Modeling. Unidade: IFSC

    Subjects: FEBRE AMARELA, APRENDIZADO COMPUTACIONAL, PLANEJAMENTO DE FÁRMACOS, ANTIVIRAIS

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      OLIVEIRA, Victor Gawriljuk Ferraro; FOIL, Daniel H.; PUHL, Ana C.; 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, Washington, DC, v. 61, n. 8, p. 3804-3813, 2021. Disponível em: < http://dx.doi.org/10.1021/acs.jcim.1c00460 > DOI: 10.1021/acs.jcim.1c00460.
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      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.Available from: http://dx.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.Available from: http://dx.doi.org/10.1021/acs.jcim.1c00460
  • Source: Journal of Chemical Information and Modeling. Unidade: IQSC

    Subjects: MEDICAMENTO, ENZIMAS

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      BONATTO, Vinícius; SHAMIM, Anwar; ROCHO, Fernanda dos Reis; et al. Predicting the Relative Binding Affinity for Reversible Covalent Inhibitors by Free Energy Perturbation Calculations. Journal of Chemical Information and Modeling, Washington, 2021. Disponível em: < https://doi.org/10.1021/acs.jcim.1c00515 > DOI: 10.1021/acs.jcim.1c00515.
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      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. 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 ;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 ;Available from: https://doi.org/10.1021/acs.jcim.1c00515
  • Source: Journal of Chemical Information and Modeling. Unidade: IQ

    Subjects: PEPTÍDEOS, PROTEÍNAS, BIOINFORMÁTICA, INIBIDORES DE ENZIMAS

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      MATOS, Isaac de Araújo; MEOTTI, Flavia Carla; COSTA JÚNIOR, Nivan Bezerra da. Integration of an inhibitor-like rule and structure-based virtual screening for the discovery of novel myeloperoxidase inhibitors. Journal of Chemical Information and Modeling, Washington, v. 60, p. 6408−6418, 2020. Disponível em: < http://dx.doi.org/10.1021/acs.jcim.0c00813 > DOI: 10.1021/acs.jcim.0c00813.
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      Matos, I. de A., Meotti, F. C., & Costa Júnior, N. B. da. (2020). Integration of an inhibitor-like rule and structure-based virtual screening for the discovery of novel myeloperoxidase inhibitors. Journal of Chemical Information and Modeling, 60, 6408−6418. doi:10.1021/acs.jcim.0c00813
    • NLM

      Matos I de A, Meotti FC, Costa Júnior NB da. Integration of an inhibitor-like rule and structure-based virtual screening for the discovery of novel myeloperoxidase inhibitors [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60 6408−6418.Available from: http://dx.doi.org/10.1021/acs.jcim.0c00813
    • Vancouver

      Matos I de A, Meotti FC, Costa Júnior NB da. Integration of an inhibitor-like rule and structure-based virtual screening for the discovery of novel myeloperoxidase inhibitors [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60 6408−6418.Available from: http://dx.doi.org/10.1021/acs.jcim.0c00813
  • Source: Journal of Chemical Information and Modeling. Unidade: IQ

    Subjects: RESSONÂNCIA MAGNÉTICA NUCLEAR, PROTEÍNAS

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      REIS, André Anversa Oliveira; SAYEGH, Raphael Santa Rosa; MARANA, Sandro Roberto; ARANTES, Guilherme Menegon. Combining free energy simulations and NMR chemical-shift perturbation to identify transient cation−π contacts in proteins. Journal of Chemical Information and Modeling, Washington, v. 60, n. 2, p. 890–897, 2020. Disponível em: < https://dx.doi.org/10.1021/acs.jcim.9b00859 > DOI: 10.1021/acs.jcim.9b00859.
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      Reis, A. A. O., Sayegh, R. S. R., Marana, S. R., & Arantes, G. M. (2020). Combining free energy simulations and NMR chemical-shift perturbation to identify transient cation−π contacts in proteins. Journal of Chemical Information and Modeling, 60( 2), 890–897. doi:10.1021/acs.jcim.9b00859
    • NLM

      Reis AAO, Sayegh RSR, Marana SR, Arantes GM. Combining free energy simulations and NMR chemical-shift perturbation to identify transient cation−π contacts in proteins [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 2): 890–897.Available from: https://dx.doi.org/10.1021/acs.jcim.9b00859
    • Vancouver

      Reis AAO, Sayegh RSR, Marana SR, Arantes GM. Combining free energy simulations and NMR chemical-shift perturbation to identify transient cation−π contacts in proteins [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 2): 890–897.Available from: https://dx.doi.org/10.1021/acs.jcim.9b00859
  • Source: Journal of Chemical Information and Modeling. Unidades: IQ, IFSC, FO

    Subjects: RAIOS X, BIOINFORMÁTICA

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      VELDMAN, Wayde; LIBERATO, Marcelo Vizoná; ALMEIDA, Vitor Medeiros; 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, Washington, DC, v. 60, n. 12, p. 6392-6407, 2020. Disponível em: < http://dx.doi.org/10.1021/acs.jcim.0c00759 > DOI: 10.1021/acs.jcim.0c00759.
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      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.Available from: http://dx.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.Available from: http://dx.doi.org/10.1021/acs.jcim.0c00759
  • Source: Journal of Chemical Information and Modeling. Unidade: IQ

    Subjects: ÁTOMOS DE HIDROGÊNIO, OXIDAÇÃO

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      CURTOLO, Felipe; ARANTES, Guilherme Menegon. Mechanisms for Flavin-mediated oxidation: hydride or hydrogen-atom transfer? Journal of Chemical Information and Modeling, Washington, v. 60, n. 12, p. 6282–6287, 2020. Disponível em: < http://dx.doi.org//10.1021/acs.jcim.0c00945 > DOI: /10.1021/acs.jcim.0c00945.
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      Curtolo, F., & Arantes, G. M. (2020). Mechanisms for Flavin-mediated oxidation: hydride or hydrogen-atom transfer? Journal of Chemical Information and Modeling, 60( 12), 6282–6287. doi:/10.1021/acs.jcim.0c00945
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      Curtolo F, Arantes GM. Mechanisms for Flavin-mediated oxidation: hydride or hydrogen-atom transfer? [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 12): 6282–6287.Available from: http://dx.doi.org//10.1021/acs.jcim.0c00945
    • Vancouver

      Curtolo F, Arantes GM. Mechanisms for Flavin-mediated oxidation: hydride or hydrogen-atom transfer? [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 12): 6282–6287.Available from: http://dx.doi.org//10.1021/acs.jcim.0c00945
  • Source: Journal of Chemical Information and Modeling. Unidade: IQ

    Subjects: ÍONS, SAIS

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      MORTARA, Laura; CHAIMOVICH GURALNIK, Hernan; CUCCOVIA, Iolanda Midea; HORINEK, Dominik; LIMA, Filipe S. Dehydration determines hydrotropic ion affinity for zwitterionic micelles. Journal of Chemical Information and Modeling, Washington, v. 60, p. 604−610, 2020. Disponível em: < http://dx.doi.org/10.1021/acs.jcim.9b00870 > DOI: 10.1021/acs.jcim.9b00870.
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      Mortara, L., Chaimovich Guralnik, H., Cuccovia, I. M., Horinek, D., & Lima, F. S. (2020). Dehydration determines hydrotropic ion affinity for zwitterionic micelles. Journal of Chemical Information and Modeling, 60, 604−610. doi:10.1021/acs.jcim.9b00870
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      Mortara L, Chaimovich Guralnik H, Cuccovia IM, Horinek D, Lima FS. Dehydration determines hydrotropic ion affinity for zwitterionic micelles [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60 604−610.Available from: http://dx.doi.org/10.1021/acs.jcim.9b00870
    • Vancouver

      Mortara L, Chaimovich Guralnik H, Cuccovia IM, Horinek D, Lima FS. Dehydration determines hydrotropic ion affinity for zwitterionic micelles [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60 604−610.Available from: http://dx.doi.org/10.1021/acs.jcim.9b00870
  • Source: Journal of Chemical Information and Modeling. Unidade: IQSC

    Assunto: QUÍMICA MÉDICA

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      COSTA, Clauber H. S; BONATTO, Vinícius; SANTOS, Alberto M. dos; et al. Evaluating QM/MM Free Energy Surfaces for Ranking Cysteine Protease Covalent Inhibitors. Journal of Chemical Information and Modeling, Washington, DC, p. 880-889, 2020. Disponível em: < https://pubs.acs.org/doi/10.1021/acs.jcim.9b00847 > DOI: 10.1021/acs.jcim.9b00847.
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      Costa, C. H. S., Bonatto, V., Santos, A. M. dos, Lameira, J., Leitão, A., & Montanari, C. A. (2020). Evaluating QM/MM Free Energy Surfaces for Ranking Cysteine Protease Covalent Inhibitors. Journal of Chemical Information and Modeling, 880-889. doi:10.1021/acs.jcim.9b00847
    • NLM

      Costa CHS, Bonatto V, Santos AM dos, Lameira J, Leitão A, Montanari CA. Evaluating QM/MM Free Energy Surfaces for Ranking Cysteine Protease Covalent Inhibitors [Internet]. Journal of Chemical Information and Modeling. 2020 ; 880-889.Available from: https://pubs.acs.org/doi/10.1021/acs.jcim.9b00847
    • Vancouver

      Costa CHS, Bonatto V, Santos AM dos, Lameira J, Leitão A, Montanari CA. Evaluating QM/MM Free Energy Surfaces for Ranking Cysteine Protease Covalent Inhibitors [Internet]. Journal of Chemical Information and Modeling. 2020 ; 880-889.Available from: https://pubs.acs.org/doi/10.1021/acs.jcim.9b00847
  • Source: Journal of Chemical Information and Modeling. Unidade: IF

    Subjects: FÍSICO-QUÍMICA, ÍONS ELETRÔNICOS, ÓPTICA NÃO LINEAR, MECÂNICA QUÂNTICA

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      RAMOS, Tárcius; CANUTO, Sylvio; CHAMPAGNE, Benoît. Unraveling the Electric Field-Induced Second Harmonic Generation Responses of Stilbazolium Ion Pairs Complexes in Solution Using a Multiscale Simulation Method. Journal of Chemical Information and Modeling, Washington, v. 60, n. 10, p. 4817–4826, 2020. Disponível em: < https://doi.org/10.1021/acs.jcim.9b01161 > DOI: 10.1021/acs.jcim.9b01161.
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      Ramos, T., Canuto, S., & Champagne, B. (2020). Unraveling the Electric Field-Induced Second Harmonic Generation Responses of Stilbazolium Ion Pairs Complexes in Solution Using a Multiscale Simulation Method. Journal of Chemical Information and Modeling, 60( 10), 4817–4826. doi:10.1021/acs.jcim.9b01161
    • NLM

      Ramos T, Canuto S, Champagne B. Unraveling the Electric Field-Induced Second Harmonic Generation Responses of Stilbazolium Ion Pairs Complexes in Solution Using a Multiscale Simulation Method [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 10): 4817–4826.Available from: https://doi.org/10.1021/acs.jcim.9b01161
    • Vancouver

      Ramos T, Canuto S, Champagne B. Unraveling the Electric Field-Induced Second Harmonic Generation Responses of Stilbazolium Ion Pairs Complexes in Solution Using a Multiscale Simulation Method [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 10): 4817–4826.Available from: https://doi.org/10.1021/acs.jcim.9b01161
  • Source: Journal of Chemical Information and Modeling. Unidade: IQSC

    Assunto: DOENÇA DE CHAGAS

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      SILVA, JoséRogerio A.; LAMEIRA, Jerônimo; MONTANARI, Carlos Alberto; et al. Assessment of the Cruzain Cysteine Protease Reversible and Irreversible Covalent Inhibition Mechanism. Journal of Chemical Information and Modeling, Washington, DC, v. 60, n. 3, p. 1666-1677, 2020. Disponível em: < https://doi.org/10.1021/acs.jcim.9b01138 > DOI: 10.1021/acs.jcim.9b01138.
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      Silva, J. R. A., Lameira, J., Montanari, C. A., Cianni, L., Araujo, D., Batista, P. H. J., et al. (2020). Assessment of the Cruzain Cysteine Protease Reversible and Irreversible Covalent Inhibition Mechanism. Journal of Chemical Information and Modeling, 60( 3), 1666-1677. doi:10.1021/acs.jcim.9b01138
    • NLM

      Silva JRA, Lameira J, Montanari CA, Cianni L, Araujo D, Batista PHJ, Vita D de, Rosini F, Leitão A. Assessment of the Cruzain Cysteine Protease Reversible and Irreversible Covalent Inhibition Mechanism [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 3): 1666-1677.Available from: https://doi.org/10.1021/acs.jcim.9b01138
    • Vancouver

      Silva JRA, Lameira J, Montanari CA, Cianni L, Araujo D, Batista PHJ, Vita D de, Rosini F, Leitão A. Assessment of the Cruzain Cysteine Protease Reversible and Irreversible Covalent Inhibition Mechanism [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 3): 1666-1677.Available from: https://doi.org/10.1021/acs.jcim.9b01138
  • Source: Journal of Chemical Information and Modeling. Unidade: IQ

    Subjects: ANTICORPOS, IMUNIDADE, INIBIDORES DE ENZIMAS

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    • ABNT

      VIVIANI, Lucas Gasparello; PICCIRILLO, Erika; ULRICH, Henning; AMARAL, Antonia Tavares do. Virtual screening approach for the identification of hydroxamic acids as novel human ecto-5'-nucleotidase inhibitors. Journal of Chemical Information and Modeling, Washington, v. 60, n. 2, p. 621-630, 2020. Disponível em: < https://dx.doi.org/10.1021/acs.jcim.9b00884 > DOI: 10.1021/acs.jcim.9b00884.
    • APA

      Viviani, L. G., Piccirillo, E., Ulrich, H., & Amaral, A. T. do. (2020). Virtual screening approach for the identification of hydroxamic acids as novel human ecto-5'-nucleotidase inhibitors. Journal of Chemical Information and Modeling, 60( 2), 621-630. doi:10.1021/acs.jcim.9b00884
    • NLM

      Viviani LG, Piccirillo E, Ulrich H, Amaral AT do. Virtual screening approach for the identification of hydroxamic acids as novel human ecto-5'-nucleotidase inhibitors [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 2): 621-630.Available from: https://dx.doi.org/10.1021/acs.jcim.9b00884
    • Vancouver

      Viviani LG, Piccirillo E, Ulrich H, Amaral AT do. Virtual screening approach for the identification of hydroxamic acids as novel human ecto-5'-nucleotidase inhibitors [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 2): 621-630.Available from: https://dx.doi.org/10.1021/acs.jcim.9b00884
  • Source: Journal of Chemical Information and Modeling. Unidade: FFCLRP

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

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      CASTRO, Jade Simões de; RODRIGUES, Caio Henrique Pinke; BRUNI, Aline Thaís. In silico infrared characterization of synthetic cannabinoids by quantum chemistry and chemometrics. Journal of Chemical Information and Modeling, Washington, v. 60, p. 2100-2114, 2020. Disponível em: < https://doi.org/10.1021/acs.jcim.9b00871 > DOI: 10.1021/acs.jcim.9b00871.
    • 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, 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 2100-2114.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 2100-2114.Available from: https://doi.org/10.1021/acs.jcim.9b00871
  • Source: Journal of Chemical Information and Modeling. Unidade: IQ

    Subjects: HIDRÓLISE, FERRO, ENXOFRE

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      TEIXEIRA, Murilo Hoias; CURTOLO, Felipe; CAMILO, Sofia Rodrigues Guedes; et al. Modeling the hydrolysis of iron–sulfur clusters. Journal of Chemical Information and Modeling, Washington, v. 60, p. 653−660, 2020. Disponível em: < http://dx.doi.org/10.1021/acs.jcim.9b00881 > DOI: 10.1021/acs.jcim.9b00881.
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      Teixeira, M. H., Curtolo, F., Camilo, S. R. G., Field, M. J., Zheng, P., Li, H., & Arantes, G. M. (2020). Modeling the hydrolysis of iron–sulfur clusters. Journal of Chemical Information and Modeling, 60, 653−660. doi:10.1021/acs.jcim.9b00881
    • NLM

      Teixeira MH, Curtolo F, Camilo SRG, Field MJ, Zheng P, Li H, Arantes GM. Modeling the hydrolysis of iron–sulfur clusters [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60 653−660.Available from: http://dx.doi.org/10.1021/acs.jcim.9b00881
    • Vancouver

      Teixeira MH, Curtolo F, Camilo SRG, Field MJ, Zheng P, Li H, Arantes GM. Modeling the hydrolysis of iron–sulfur clusters [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60 653−660.Available from: http://dx.doi.org/10.1021/acs.jcim.9b00881
  • Source: Journal of Chemical Information and Modeling. Unidade: IQSC

    Assunto: CLUSTERS

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      BATISTA, Krys Elly de Araújo; RESTREPO, Vivianne k; SOARES, Marinalva Dias; et al. Ab Initio Investigation of CO2 Adsorption on 13-Atom 4d Clusters. Journal of Chemical Information and Modeling, Washington, DC, v. 60, p. 537-545, 2020. Disponível em: < https://pubs-acs-org.ez67.periodicos.capes.gov.br/doi/10.1021/acs.jcim.9b00792 > DOI: 10.1021/acs.jcim.9b00792.
    • APA

      Batista, K. E. de A., Restrepo, V. k, Soares, M. D., Quiles, M. G., Piotrowski, M. J., & Silva, J. L. F. da. (2020). Ab Initio Investigation of CO2 Adsorption on 13-Atom 4d Clusters. Journal of Chemical Information and Modeling, 60, 537-545. doi:10.1021/acs.jcim.9b00792
    • NLM

      Batista KE de A, Restrepo V k, Soares MD, Quiles MG, Piotrowski MJ, Silva JLF da. Ab Initio Investigation of CO2 Adsorption on 13-Atom 4d Clusters [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60 537-545.Available from: https://pubs-acs-org.ez67.periodicos.capes.gov.br/doi/10.1021/acs.jcim.9b00792
    • Vancouver

      Batista KE de A, Restrepo V k, Soares MD, Quiles MG, Piotrowski MJ, Silva JLF da. Ab Initio Investigation of CO2 Adsorption on 13-Atom 4d Clusters [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60 537-545.Available from: https://pubs-acs-org.ez67.periodicos.capes.gov.br/doi/10.1021/acs.jcim.9b00792

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