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Journal of Chemical Theory and Computation|September 1, 2023
Perspectives on Ligand/Protein Binding Kinetics Simulations: Force Fields, Machine Learning, Sampling, and User-FriendlinessPaolo Conflitti, Stefano Raniolo, Vittorio Limongelli
Nature Protocols|August 21, 2020
Ligand binding free-energy calculations with funnel metadynamicsStefano Raniolo, Vittorio Limongelli
Frontiers in Molecular Biosciences|December 30, 2021
Improving Small-Molecule Force Field Parameters in Ligand Binding StudiesStefano Raniolo, Vittorio Limongelli
The Journal of Chemical Physics|August 19, 2025
HEroBM: A deep equivariant graph neural network for high-fidelity backmapping from coarse-grained to all-atom structuresDaniele Angioletti, Stefano Raniolo, Vittorio Limongelli
Communications Chemistry|January 25, 2023
Transferring chemical and energetic knowledge between molecular systems with machine learningSajjad Heydari, Stefano Raniolo, Lorenzo Livi, et al.
Nature Communications|July 26, 2020
Protein-ligand binding with the coarse-grained Martini modelPaulo C T Souza, Sebastian Thallmair, Paolo Conflitti, et al.
Journal of Chemical Theory and Computation|April 17, 2018
The Molecular Mechanism Underlying Ligand Binding to the Membrane-Embedded Site of a G-Protein-Coupled ReceptorXiaojing Yuan, Stefano Raniolo, Vittorio Limongelli, et al.
Bioinformatics (Oxford, England)|July 16, 2019
DDT - Drug Discovery Tool: a fast and intuitive graphics user interface for docking and molecular dynamics analysisSimone Aureli, Daniele Di Marino, Stefano Raniolo, et al.
Communications Chemistry|November 7, 2023
Conformational plasticity and allosteric communication networks explain Shelterin protein TPP1 binding to human telomeraseSimone Aureli, Vince Bart Cardenas, Stefano Raniolo, et al.
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