Publications

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  • A Kapoor, G Martinez-Rosell, D Provasi, G Fabritiis, M Filizola, Dynamic and Kinetic Elements of µ-Opioid Receptor Functional Selectivity, Scientific Reports 7 (1), 11255. pdf
  • S Doerr, T Giorgino, G Martinez-Rosell, JM Damas, G De Fabritiis, High-throughput automated preparation and simulation of membrane proteins with HTMD, Journal of Chemical Theory and Computation 13 (9), 4003-4011.pdf
  • G Martinez-Rosell, T Giorgino, G De Fabritiis, PlayMolecule ProteinPrepare: A Web Application for Protein Preparation for Molecular Dynamics Simulations, J. Chem. Inf. Model., 2017, 57 (7), pp 1511–1516. pdf
  • N Plattner, S Doerr, G De Fabritiis, F Noé, Complete protein–protein association kinetics in atomic detail revealed by molecular dynamics simulations and Markov modelling, Nature Chemistry 9, 1005–1011 (2017).
  • J Jiménez, S Doerr, G Martínez-Rosell, AS Rose, G De Fabritiis, DeepSite: Protein binding site predictor using 3D-convolutional neural networks, Bioinformatics, Volume 33, Issue 19, 1 October 2017, Pages 3036–3042. pdf
  • G Martínez-Rosell, T Giorgino, MJ Harvey, G de Fabritiis, Drug Discovery and Molecular Dynamics: Methods, Applications and Perspective Beyond the Second Timescale, Curr Top Med Chem. 2017;17(23):2617-2625. pdf
  • N Ferruz, G Tresadern, A Pineda-Lucena, G De Fabritiis, Multibody cofactor and substrate molecular recognition in the myo-inositol monophosphatase enzyme, Scientific Reports 6, Article number: 30275 (2016) pdf.
  • N Ferruz, G De Fabritiis, Binding Kinetics in Drug Discovery, Molecular Informatics, Volume 35, Issue 6-7, pages 216–226, July 2016, pdf .
  • *** S. Doerr , M.J. Harvey, F. Noé ,G. De Fabritiis, HTMD: High-throughput molecular dynamics for molecular discovery, J. Chem. Theory Comput., 2016, 12 (4), pp 1845–1852 pdf
  • *** N Stanley, L Pardo, G De Fabritiis, The pathway of ligand entry from the membrane bilayer to a lipid G protein-coupled receptor, Scientific Reports 6, Article number: 22639 (2016) pdf.
  • *** N Ferruz, M Harvey, J Mestres, G De Fabritiis, Insights from Fragment Hit Binding Assays by Molecular Simulations, J. Chem. Inf. Model., 2015, 55 (10), pp 2200–2205. pdf
  • G. Khelashvili , N. Stanley , M. A. Sahai , J. Medina , M. V. Levine , L. Shi , G. De Fabritiis and H. Weinstein, Spontaneous inward opening of the dopamine transporter is triggered by PIP2-regulated dynamics of the N-terminus, ACS Chem. Neurosci., 2015, 6 (11), pp 1825–1837. pdb
  • ** M. J. Harvey and G. De Fabritiis, Acecloud: Molecular Dynamics Simulations in the Cloud, J. Chem. Inf. Model., 2015, 55 (5), pp 909–914. pdf
  • Nathaniel Stanley, Santiago Esteban-Martín, Gianni De Fabritiis, Progress in studying intrinsically disordered proteins with atomistic simulations, Progress in Biophysics and Molecular Biology, Volume 119, Issue 1, October 2015, Pages 47-52.
  • N. Stanley and G. De Fabritiis, High throughput molecular dynamics for drug discovery, In Silico Pharmacology 2015, 3:3. pdf
  • Maria Marti-Solano, Alba Iglesias, Gianni de Fabritiis, Ferran Sanz, Jose Brea, M Isabel Loza, Manuel Pastor, Jana Selent, Detection of New Biased Agonists for the Serotonin 5-HT2A Receptor: Modeling and Experimental Validation, Mol Pharmacol. 2015 87(4) 740.
  • S. Arena et al., Emergence of multiple EGFR extracellular mutations during cetuximab treatment in colorectal cancer, Clin Cancer Res. 2015 21(9) 2157.
  • *** N. Stanley, S. Esteban and G. De Fabritiis, Kinetic modulation of a disordered protein domain by phosphorylation, Nat. Commun. 5, 5272 (2014). pdf
  • G. Lauro, N. Ferruz, S. Fulle, M. J. Harvey, P. W. Finn, and G. De Fabritiis,Reranking Docking Poses Using Molecular Simulations and Approximate Free Energy Methods, J. Chem. Inf. Model., 2014, 54 (8), pp 2185–2189.pdf
  • *** S. Doerr and G. De Fabritiis, On-the-fly learning and sampling of ligand binding by high-throughput molecular simulations, J. Chem. Theory Comput. 10 (5), pp 2064–2069(2014).pdf
  • P. Bisignano, S. Doerr, M. J. Harvey, A. Favia, A. Cavalli and G. De Fabritiis, Kinetic characterization of fragment binding in AmpC β-lactamase by high-throughput molecular simulations, J. Chem. Inf. Model., 2014, 54 (2), pp 362–366. pdf
  • X. Huang and G. De Fabritiis, Understanding Molecular Recognition by Kinetic Network Models Constructed from Molecular Dynamics Simulations, Adv Exp Med Biol 2014; 797: 107-114. pdf
  • ** E. Dainese, G. De Fabritiis, A. Sabatucci, S. Oddi, C. Angelucci, C. Di Pancrazio, T. Giorgino, N. Stanley, B. Cravatt, and M. Maccarrone, Membrane lipids are key-modulators of the endocannabinoid-hydrolase FAAH, Biochem J. 2014 Feb 1;457(3):463-72. pdf
  • I. Buch, N. Ferruz and G. De Fabritiis, Computational modeling of an EGFR single-mutation resistance to cetuximab in colorectal cancer treatment, J. Chem. Inf. Model., 2013, 53 (12), pp 3123–3126. pdf
  • ** G. Pérez-Hernández, F. Paul, T. Giorgino, G. De Fabritiis, and F. Noé, Identification of slow molecular order parameters for Markov model construction, J. Chem. Phys. 139, 015102 (2013). pdf
  • T. Venken, A. Voet, M. De Maeyer, G. De Fabritiis, K. Sadiq, Rapid conformational fluctuations of disordered HIV-1 fusion peptide in solution, J. Chem. Theory Comput. 9, 2870 (2013).pdf
  • S. K. Sadiq, R. Guixà-González, E. Dainese, M. Pastor, G. De Fabritiis, and J. Selent,Molecular modeling and simulation of membrane lipid-mediated effects on GPCRs, Current medicinal chemistry 20 (1), 22-38(2013).pdf
  • D. W. Wright, S. K. Sadiq, G. De Fabritiis and P. V. Coveney, Thumbs down for HIV: Domain level rearrangements do occur in the NNRTI bound HIV-1 Reverse Transcriptase, J. Am. Chem. Soc., 2012, 134 (31), pp 12885–12888 (2012).pdf
  • A Bruno, G Costantino , G De Fabritiis, M Pastor, J Selent, Membrane-Sensitive Conformational States of Helix 8 in the Metabotropic Glu2 Receptor, a Class C GPCR, PLoS ONE 7(8): e42023 (2012). pdf
  • *** S. K. Sadiq, F. Noe and G. De Fabritiis, Kinetic characterization of the critical step in HIV-1 protease maturation, PNAS 109 (50) 20449-20454 (2012). pdf
  • M. J. Harvey and G. De Fabritiis, A Survey of Computational Molecular Science using Graphics Processing Units, WIREs Comput Mol Sci 2012, 2: 734-742. doi: 10.1002/wcms.1101 pdf
  • ** M. J. Harvey and G. De Fabritiis, High-throughput molecular dynamics: The powerful new tool for drug discovery, Drug Discovery Today, 17, 1059–1062 (2012). pdf
  • ** T. Giorgino, I. Buch and G. De Fabritiis, Visualizing the induced binding of SH2-phosphopeptide, J. Chem. Theory Comput.,8, 1171–1175 (2012).[pdf] pdf
  • **I. Buch, S. K. Sadiq and G. De Fabritiis, Optimized potential of mean force calculations of standard binding free energy, J. Chem. Theory Comput., 7, 1765–1772 (2011). pdf
  • T. Giorgino and G. De Fabritiis, A high-throughput steered molecular dynamics study on the free energy profile of ion permeation through gramicidin A, J. Chem. Theory Comput., 7 , 1943–1950 (2011). pdf
  • ***I. Buch, T. Giorgino and G. De Fabritiis,Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations, PNAS 108, 10184-10189 (2011). pdf
  • M. J. Harvey and G. De Fabritiis, Swan: A tool for porting CUDA programs to OpenCL, Comp. Phys. Commun. 182, 1093 (2010). pdf
  • *** J. Selent, F. Sanz, M. Pastor and G. De Fabritiis, Induced Effects of Sodium Ions on Dopaminergic G-Protein Coupled Receptors, PLOS Computational Biology, 6, e1000884 (2010) pdf.
  • S. K. Sadiq and G. De Fabritiis,Explicit solvent dynamics and energetics of HIV-1 protease flap-opening and closing, Proteins 78, 2873 (2010) pdf. Supplementary PDB of the conformations PDBs.
  • J Cooper,F Cervenansky, G De Fabritiis, J Fenner, D Friboulet, T Giorgino, S Manos, Y Martelli, J Villa-Freixa, S Zasada, S Lloyd, K Mccormack and P V Coveney, The Virtual Physiological Human Toolkit, Phil. Trans. R. Soc. A 368(1925) 3925-3936 (2010).pdf
  • **T. Giorgino, M. J. Harvey and G. De Fabritiis, Distributed computing as a virtual supercomputer: Tools to run and manage large-scale BOINC simulations, Comp. Phys. Commun. 181, 1402 (2010).pdf
  • **I. Buch, M. J. Harvey, T. Giorgino, D. P. Anderson and G. De Fabritiis, High-throughput all-atom molecular dynamics simulations using distributed computing, J. Chem. Inf. and Mod. 50, 397 (2010). pdf
  • A. Lopez Garcıa de Lomana, Q. K. Beg, G. De Fabritiis and J. Villa-Freixa, Global Connectivity and Activity Distributions in Cellular Networks, J. Comp. Bio. 17(7), 869 (2010). pdf
  • ** M. J. Harvey and G. De Fabritiis, An implementation of the smooth particle-mesh Ewald (PME) method on GPU hardware, J. Chem. Theory Comput., 5, 2371–2377 (2009).pdf
  • *** M. Harvey, G. Giupponi and G. De Fabritiis, ACEMD: Accelerated molecular dynamics simulations in the microseconds timescale, J. Chem. Theory and Comput. 5, 1632 (2009). pdf
  • ** F. X. Guix, G. Ill-Raga, R. Bravo, T. Nakaya, G. De Fabritiis, M. Coma, G. P. Miscione, J. Villà-Freixa, T. Suzuki, X. Fernàndez-Busquets, M. A. Valverde, B. de Strooper and F. J. Muñoz, Amyloid-dependent triosephosphate isomerase nitrotyrosination induces glycation and tau fibrillation, Brain 132, 1335 (2009).pdf
  • Notes:
    • Andrea Rinaldi. Science wikinomics. Mass networking through the web creates new forms of scientific collaboration, EMBO reports 10, 5, 439–443 (2009) doi:10.1038/embor.2009.79
    • Play me a molecule, Science 12 September 2008, Vol. 321. no. 5895, p. 14251
  • *** G. Giupponi, M. Harvey and G. De Fabritiis, The impact of accelerator processors for high-throughput molecular modeling and simulation, Drug Discovery Today 13, 1052 (2008). pdf
  • M. Harvey, G. De Fabritiis and G. Giupponi, Accuracy of the Lattice Boltzmann method on the Cell processor, Phys. Rev. E 78, 056702 (2008). pdf (http://www.multiscalelab.org/CellLB)
  • *** G. De Fabritiis, S. Geroult, P. V. Coveney and G. Waksman, Insights from the energetics of water binding at the domain-ligand interface of the Src SH2 domain, 72, 1290 Proteins (2008). pdf
  • R. Delgado-Buscalioni, P. V. Coveney and G. De Fabritiis _ Towards multiscale modelling of complex liquids_, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 222, 769 (2008). pdf
  • ** G. De Fabritiis, P. V. Coveney and J. Villa-Freixa, _ Energetics of K+ permeability through Gramicidin A by forward-reverse steered molecular dynamics_, 73, 184 Proteins (2008).pdf
  • STEP Consortium. Seeding the Euro Physiome: A Roadmap to the Virtual Physiological Human. [Online] 5 July 2007, editor and expert.pdf
  • R. Delgado-Buscalioni and G. De Fabritiis, _ Embedding molecular dynamics within fluctuating hydrodynamics in multiscale simulations of liquids_, Phys. Rev. E 76, 036709 (2007).pdf
  • ** M. Harvey, G. Giupponi, J. Villa-Freixa and G. De Fabritiis, _ PS3GRID.NET: Building a distributed supercomputer using the Playstation 3_, Distributed & Grid Computing - Science Made Transparent for Everyone. Principles, Applications and Supporting Communities (2007).pdf
  • G. Giupponi, G. De Fabritiis and P. V. Coveney, _Hybrid method coupling fluctuating hydrodynamics and molecular dynamics for the simulation of macromolecules _, J. Chem. Phys. 126, 154903 (2007). pdf
  • *** G. De Fabritiis, Performance of the Cell processor for biomolecular simulations, Comp. Phys. Commun. 176, 670 (2007).pdf
  • G. De Fabritiis and J. Villa-Freixa and P. V. Coveney, _Multiscale modelling of permeation through membrane channels using pregenerated molecular dynamics trajectories _, Int. J. Mod. Phys. C, 18, 511 (2007).pdf
  • G. Giupponi, G. De Fabritiis and P. V. Coveney, A coupled molecular-continuum hybrid model for the simulation of macromolecular dynamics, Int. J. Mod. Phys. C, 18, 520 (2007).pdf
  • ** G. De Fabritiis, M. Serrano, R. Delgado-Buscalioni and P. V. Coveney, Fluctuating hydrodynamic modelling of fluids at the nanoscale, Phys. Rev. E 75, 026307 (2007).pdf
  • S. Lloyd, D. Gavaghan, A. Simpson, M. Mascord, C. Seneurine, G. Williams, J. Pitt-Francis, D. Boyd, D. M. Randal, L. Sastry, S. Nagella, K. Weeks, R. Fowler,D. Hanlon, J. Handley, G. De Fabritiis, _ Integrative Biology: The Challenges of Developing a Collaborative Research Environment for Heart and Cancer Modelling_, Future Generation Computer Systems, 23, 457-465 (2007).
  • *** G. De Fabritiis, R. Delgado-Buscalioni and P. V. Coveney, Multiscale Modeling of Liquids with Molecular Specificity, Phys. Rev. Lett. 97, 134501 (2006). pdf
  • P. V. Coveney, G. De Fabritiis, M. Harvey, S. Pickles and A. Porter, _ Coupling applications on distributed resources_, Comp. Phys. Commun. 175, 389 (2006). pdf
  • M. Serrano, G. De Fabritiis, P. Espanol and P. V. Coveney, _ A stochastic Trotter integration scheme for dissipative particle dynamics_, Math. Comput. Simul. 72, 190 (2006).pdf
  • ** G. De Fabritiis, M. Serrano, P. Espanol and P. V. Coveney, Efficient numerical integrators for stochastic models, Physica A 361, 429 (2006). pdf
  • P. V. Coveney, G. De Fabritiis, M. Harvey, S. Pickles and A. Porter, On steering coupled models, proceedings of UK e-science AHM2005, (2005).pdf
  • R. Delgado-Buscalioni, G. De Fabritiis, P. V. Coveney, Determination of the chemical potential using energy biased sampling, J. Chem. Phys. 123, 054105 (2005).pdf
  • ** G. De Fabritiis, R. Delgado-Buscalioni and P. V. Coveney, Energy controlled insertion of polar molecules in dense fluids, J. Chem. Phys. 121, 12139 (2004). Selected for the Virtual Journal of Biological Physics Research, December 15, 2004 Volume 8, Issue 12.pdf
  • *** G. De Fabritiis, F. Pammolli and M. Riccaboni, _ On size and growth of business firms,_ Physica A 324, 38-44 (2003). pdf
  • ** G. De Fabritiis and P. V. Coveney,_ Dynamical geometry for multiscale dissipative particle dynamics,_ Computer Physics Communications, 153(2), 209-226 (2003). pdf
  • M. Serrano, G. De Fabritiis, P. Espanol, E. G. Flekkøy and P. V. Coveney, Mesoscopic dynamics of Voronoi fluid particles, J. Phys. A: Math. Gen. 35, 1605 (2002); pdf
  • G. De Fabritiis, P. V. Coveney and E.G. Flekkøy, Multiscale dissipative particle dynamics, Phil. Trans. R. Soc. Lond. A 360, 317 (2002). pdf
  • G. De Fabritiis, S. Succi and P. V. Coveney, Electronic structure calculations using Voronoi multiscale basis functions, J. Stat. Phys. 107, 159 (2002). pdf
  • ** E.G. Flekkøy, P.V. Coveney and G. De Fabritiis, Foundations of Dissipative Particle Dynamics, Phys. Rev. E 62, 2140 (2000). pdf
  • R.Gorenflo, G. De Fabritiis and F. Mainardi, Discrete random walk models for symmetric Levy-Feller diffusion processes, Physica A 269, 79-89 (1999). pdf
  • G. De Fabritiis, A. Mancini, D. Mansutti and S. Succi, Mesoscopic models of liquid/solid phase transitions, Int. J. Mod. Phys. C 9, 1405-1415 (1998). pdf
  • P.V.Coveney, G. De Fabritiis, E.G. Flekkøy and J. Christopher, From Molecular Dynamics to Dissipative Particle Dynamics, SIMU newsletter, 1, 73-98 (2000).
  • G. De Fabritiis, P.V. Coveney and E.G. Flekkøy, Multiscale modelling of complex fluids, Proceedings of 5th European SGI/Cray MPP Workshop, Bologna, Italy (1999).
  • G. Bellanca, P. bassi, G. Erbacci, G. De Fabritiis and R. Roccari, Bringing home HPCN: implementation of a FD-TD code for microwave ovens design on a PC cluster, 7th Inter. Conf. on Microwave and High Frequency heating, Valencia, Spain (1999).
  • G.Bellanca, P.Bassi, G.Erbacci, G. De Fabritiis and R.Roccari,_ Supercomputer optimized micro-wave domestic oven design via FD-TD,_ Proceedings of VEC-PAR98 Porto, Portugal (1998).
  • G. De Fabritiis, Stochastic dynamics of mesoscopic fluids, Ph.D. thesis (2002).
  • G. De Fabritiis, Cellular Automata in Fluid Dynamics, tesi di laurea (in Italian) 1997.