| Promoting transparency and reproducibility in enhanced molecular simulations M Bonomi, G Bussi, C Camilloni, GA Tribello, P Banįš, A Barducci, ... Nature methods 16 (8), 670-673, 2019 | 633 | 2019 |
| Cooperative supramolecular block copolymerization for the synthesis of functional axial organic heterostructures A Sarkar, T Behera, R Sasmal, R Capelli, C Empereur-Mot, J Mahato, ... Journal of the American Chemical Society 142 (26), 11528-11539, 2020 | 81 | 2020 |
| Exhaustive search of ligand binding pathways via volume-based metadynamics R Capelli, P Carloni, M Parrinello The journal of physical chemistry letters 10 (12), 3495-3499, 2019 | 67 | 2019 |
| Controlling the length of porphyrin supramolecular polymers via coupled equilibria and dilution-induced supramolecular polymerization E Weyandt, L Leanza, R Capelli, GM Pavan, G Vantomme, EW Meijer Nature Communications 13 (1), 248, 2022 | 56 | 2022 |
| Porous covalent organic nanotubes and their assembly in loops and toroids K Koner, S Karak, S Kandambeth, S Karak, N Thomas, L Leanza, ... Nature Chemistry 14 (5), 507-514, 2022 | 49 | 2022 |
| Chasing the full free energy landscape of neuroreceptor/ligand unbinding by metadynamics simulations R Capelli, A Bochicchio, GM Piccini, R Casasnovas, P Carloni, ... Journal of chemical theory and computation 15 (5), 3354-3361, 2019 | 49 | 2019 |
| Swarm-CG: Automatic Parametrization of Bonded Terms in MARTINI-Based Coarse-Grained Models of Simple to Complex Molecules via Fuzzy Self-Tuning … C Empereur-Mot, L Pesce, G Doni, D Bochicchio, R Capelli, C Perego, ... ACS omega 5 (50), 32823-32843, 2020 | 48 | 2020 |
| Accuracy of Molecular Simulation-Based Predictions of koff Values: A Metadynamics Study R Capelli, W Lyu, V Bolnykh, S Meloni, JMH Olsen, U Rothlisberger, ... The journal of physical chemistry letters 11 (15), 6373-6381, 2020 | 46 | 2020 |
| Enhanced-sampling simulations for the estimation of ligand binding kinetics: current status and perspective K Ahmad, A Rizzi, R Capelli, D Mandelli, W Lyu, P Carloni Frontiers in molecular biosciences 9, 899805, 2022 | 30 | 2022 |
| Enhancing antibody serodiagnosis using a controlled peptide coimmobilization strategy L Sola, P Gagni, I D’Annessa, R Capelli, C Bertino, A Romanato, F Damin, ... ACS Infectious Diseases 4 (6), 998-1006, 2018 | 28 | 2018 |
| A data-driven dimensionality reduction approach to compare and classify lipid force fields R Capelli, A Gardin, C Empereur-Mot, G Doni, GM Pavan The Journal of Physical Chemistry B 125 (28), 7785-7796, 2021 | 24 | 2021 |
| The subtle trade-off between evolutionary and energetic constraints in protein–protein interactions F Marchetti, R Capelli, F Rizzato, A Laio, G Colombo The Journal of Physical Chemistry Letters 10 (7), 1489-1497, 2019 | 23 | 2019 |
| An implementation of the maximum-caliber principle by replica-averaged time-resolved restrained simulations R Capelli, G Tiana, C Camilloni The Journal of Chemical Physics 148 (18), 2018 | 16 | 2018 |
| BPSL1626: Reverse and Structural Vaccinology Reveal a Novel Candidate for Vaccine Design against Burkholderia pseudomallei R Capelli, C Peri, R Villa, A Nithichanon, O Conchillo-Solé, D Yero, ... Antibodies 7 (3), 26, 2018 | 15 | 2018 |
| Automatic Optimization of Lipid Models in the Martini Force Field Using SwarmCG C Empereur-Mot, KB Pedersen, R Capelli, M Crippa, C Caruso, ... Journal of chemical information and modeling 63 (12), 3827-3838, 2023 | 14 | 2023 |
| Ephemeral ice-like local environments in classical rigid models of liquid water R Capelli, F Muniz-Miranda, GM Pavan The Journal of Chemical Physics 156 (21), 2022 | 13* | 2022 |
| Enhanced sampling approach to the induced-fit docking problem in protein–ligand binding: the case of mono-ADP-ribosylation hydrolase inhibitors Q Zhao, R Capelli, P Carloni, B Luscher, J Li, G Rossetti Journal of chemical theory and computation 17 (12), 7899-7911, 2021 | 13 | 2021 |
| SAGE: a fast computational tool for linear epitope grafting onto a foreign protein scaffold R Capelli, F Marchetti, G Tiana, G Colombo Journal of Chemical Information and Modeling 57 (1), 6-10, 2017 | 13 | 2017 |
| MonteGrappa: an iterative Monte Carlo program to optimize biomolecular potentials in simplified models G Tiana, F Villa, Y Zhan, R Capelli, C Paissoni, P Sormanni, E Heard, ... Computer Physics Communications 186, 93-104, 2015 | 13 | 2015 |
| Automatic multi-objective optimization of coarse-grained lipid force fields using SwarmCG C Empereur-Mot, R Capelli, M Perrone, C Caruso, G Doni, GM Pavan The Journal of Chemical Physics 156 (2), 2022 | 12 | 2022 |
