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1
Self-assembly of phosphocholine derivatives using the ELBA coarse-grained model micelles, bicelles, and reverse micelles
Self-assembly of phosphocholine derivatives using the ELBA coarse-grained model micelles, bicelles, and reverse micelles
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Self-assembly of phosphocholine derivatives using the ELBA coarse-grained model micelles, bicelles, and reverse micelles

Rafael Maglia de Souza Rafael Henrique Ratochinski; Mikko Karttunen; Luis Gustavo Dias

Journal of Chemical Information and Modeling Washington v. 60, n. 2, p. 522-536, 2020

Washington 2020

Localização: FFCLRP - Fac. Fil. Ciên. Let. de R. Preto    (pcd 3090763 Acervo Digital )(Acessar)

2
Combined experimental and molecular simulation study of insulin–chitosan complexation driven by electrostatic interactions
Combined experimental and molecular simulation study of insulin–chitosan complexation driven by electrostatic interactions
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Combined experimental and molecular simulation study of insulin–chitosan complexation driven by electrostatic interactions

Cecilia Prudkin-Silva Oscar E Pérez; Karina D Martínez; Fernando Luís Barroso da Silva

Journal of Chemical Information and Modeling Washington v. 60, n. 2, p. 854-865, 2020

Washington 2020

Localização: FCFRP - Fac. Ciên. Farm. Ribeirão Preto    (pcd 3090228 Acervo Digital )(Acessar)

3
Celebrating diversity, equity, inclusion, and respect in computational and theoretical chemistry [Editorial]
Celebrating diversity, equity, inclusion, and respect in computational and theoretical chemistry [Editorial]
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Celebrating diversity, equity, inclusion, and respect in computational and theoretical chemistry [Editorial]

Zoe Cournia Thereza A Soares; Habibah A Wahab; Rommie E Amaro

Journal of Chemical Information and Modeling Washington v. 62, n. 24, p. 6287-6291, 2022

Washington 2022

Localização: FFCLRP - Fac. Fil. Ciên. Let. de R. Preto    (pcd 3138581 Acervo Digital )(Acessar)

4
Transition Metal Ion Interactions with Disordered Amyloid‑β Peptides in the Pathogenesis of Alzheimer’s Disease: Insights from Computational Chemistry Studies
Transition Metal Ion Interactions with Disordered Amyloid‑β Peptides in the Pathogenesis of Alzheimer’s Disease: Insights from Computational Chemistry Studies
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Transition Metal Ion Interactions with Disordered Amyloid‑β Peptides in the Pathogenesis of Alzheimer’s Disease: Insights from Computational Chemistry Studies

Strodel, Birgit ; Coskuner-Weber, Orkid

Journal of chemical information and modeling, 2019-05, Vol.59 (5), p.1782-1805 [Periódico revisado por pares]

United States: American Chemical Society

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5
Drug Design in the Exascale Era: A Perspective from Massively Parallel QM/MM Simulations
Drug Design in the Exascale Era: A Perspective from Massively Parallel QM/MM Simulations
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Drug Design in the Exascale Era: A Perspective from Massively Parallel QM/MM Simulations

Raghavan, Bharath ; Paulikat, Mirko ; Ahmad, Katya ; Callea, Lara ; Rizzi, Andrea ; Ippoliti, Emiliano ; Mandelli, Davide ; Bonati, Laura ; De Vivo, Marco ; Carloni, Paolo

Journal of chemical information and modeling, 2023-06, Vol.63 (12), p.3647-3658 [Periódico revisado por pares]

United States: American Chemical Society

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6
Assessing the Performance of the MM/PBSA and MM/GBSA Methods. 1. The Accuracy of Binding Free Energy Calculations Based on Molecular Dynamics Simulations
Assessing the Performance of the MM/PBSA and MM/GBSA Methods. 1. The Accuracy of Binding Free Energy Calculations Based on Molecular Dynamics Simulations
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Assessing the Performance of the MM/PBSA and MM/GBSA Methods. 1. The Accuracy of Binding Free Energy Calculations Based on Molecular Dynamics Simulations

Hou, Tingjun ; Wang, Junmei ; Li, Youyong ; Wang, Wei

Journal of chemical information and modeling, 2011-01, Vol.51 (1), p.69-82 [Periódico revisado por pares]

Washington, DC: American Chemical Society

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7
RosENet: Improving Binding Affinity Prediction by Leveraging Molecular Mechanics Energies with an Ensemble of 3D Convolutional Neural Networks
RosENet: Improving Binding Affinity Prediction by Leveraging Molecular Mechanics Energies with an Ensemble of 3D Convolutional Neural Networks
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RosENet: Improving Binding Affinity Prediction by Leveraging Molecular Mechanics Energies with an Ensemble of 3D Convolutional Neural Networks

Hassan-Harrirou, Hussein ; Zhang, Ce ; Lemmin, Thomas

Journal of chemical information and modeling, 2020-06, Vol.60 (6), p.2791-2802 [Periódico revisado por pares]

United States: American Chemical Society

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8
Structure and Dynamics of the CRISPR–Cas9 Catalytic Complex
Structure and Dynamics of the CRISPR–Cas9 Catalytic Complex
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Structure and Dynamics of the CRISPR–Cas9 Catalytic Complex

Palermo, Giulia

Journal of chemical information and modeling, 2019-05, Vol.59 (5), p.2394-2406 [Periódico revisado por pares]

United States: American Chemical Society

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9
Leveraging DFT and Molecular Fragmentation for Chemically Accurate pKa Prediction Using Machine Learning
Leveraging DFT and Molecular Fragmentation for Chemically Accurate pKa Prediction Using Machine Learning
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Leveraging DFT and Molecular Fragmentation for Chemically Accurate pKa Prediction Using Machine Learning

Sanchez, Alec J ; Maier, Sarah ; Raghavachari, Krishnan

Journal of chemical information and modeling, 2024-02, Vol.64 (3), p.712-723 [Periódico revisado por pares]

Washington: American Chemical Society

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10
Multiscale Workflow for Modeling Ligand Complexes of Zinc Metalloproteins
Multiscale Workflow for Modeling Ligand Complexes of Zinc Metalloproteins
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Multiscale Workflow for Modeling Ligand Complexes of Zinc Metalloproteins

Yang, Zongfan ; Twidale, Rebecca M ; Gervasoni, Silvia ; Suardíaz, Reynier ; Colenso, Charlotte K ; Lang, Eric J. M ; Spencer, James ; Mulholland, Adrian J

Journal of chemical information and modeling, 2021-11, Vol.61 (11), p.5658-5672 [Periódico revisado por pares]

United States: American Chemical Society

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