Browsing by Author "De Fabritiis, Gianni"

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  • Herrera Nieto, Pablo (Universitat Pompeu Fabra, 2020-11-30)
    Over the last decades molecular dynamics simulations have been successfully applied to relevant biological problems such as protein-ligand, protein-protein binding as well as protein folding. A perfect challenge for molecular ...
  • Doerr, Stefan (Universitat Pompeu Fabra, 2018-01-11)
    Molecular dynamics has established itself over the last years as a strong tool for structure-based molecular investigation in biology. Stefan Doerr's thesis concerns the application of machine learning methods to molecular ...
  • Martínez Rosell, Gerard (Universitat Pompeu Fabra, 2019-01-23)
    In this thesis we apply molecular dynamics (MD) simulations and other in silico techniques in drug discovery. Specifically, (a) we developed an algorithm to detect cryptic pockets based on MD simulations of the protein ...
  • Herrera Nieto, Pablo; Pérez, Adrià; De Fabritiis, Gianni (American Chemical Society (ACS), 2023)
    Intrinsically disordered proteins participate in many biological processes by folding upon binding to other proteins. However, coupled folding and binding processes are not well understood from an atomistic point of view. ...
  • Herrera Nieto, Pablo, 1992-; Pérez, Adrià; De Fabritiis, Gianni (Nature Research, 2020)
    The exploration of intrinsically disordered proteins in isolation is a crucial step to understand their complex dynamical behavior. In particular, the emergence of partially ordered states has not been explored in depth. ...
  • Skalic, Miha (Universitat Pompeu Fabra, 2019-09-19)
    Designing novel drugs is a complex process which requires finding molecules in a vast chemical space that bind to a specific biomolecular target and have favorable physio-chemical properties. Machine learning methods can ...
  • Jiménez Luna, José, 1993-; Pérez Benito, Laura; Martínez Rosell, Gerard, 1990-; Sciabola, Simone; Torella, Rubben; Tresadern, Gary; De Fabritiis, Gianni (Royal Society of Chemistry, 2019)
    The capability to rank different potential drug molecules against a protein target for potency has always been a fundamental challenge in computational chemistry due to its importance in drug design. While several ...
  • Ferruz Capapey, Noelia 1988-; Doerr, Stefan, 1987-; Vanase Frawley, Michelle A.; Zou, Yaozhong; Chen, Xiaomin; Marr, Eric S.; Nelson, Robin T.; Kormos, Bethany L.; Wager, Travis T.; Hou, Xinjun J.; Villalobos, Anabella; Sciabola, Simone; De Fabritiis, Gianni (Nature Publishing Group, 2018)
    The recent increase in the number of X-ray crystal structures of G-protein coupled receptors (GPCRs) has been enabling for structure-based drug design (SBDD) efforts. These structures have revealed that GPCRs are highly ...
  • Kapoor, Abhijeet; Martínez Rosell, Gerard, 1990-; Provasi, Davide; De Fabritiis, Gianni; Filizola, Marta (Nature Publishing Group, 2017)
    While the therapeutic effect of opioids analgesics is mainly attributed to µ-opioid receptor (MOR) activation leading to G protein signaling, their side effects have mostly been linked to β-arrestin signaling. To shed light ...
  • Sabanés Zariquiey, Francesc; Galvelis, Raimondas; Gallicchio, Emilio; Chodera, John D.; Markland, Thomas E.; De Fabritiis, Gianni (American Chemical Society (ACS), 2024)
    This letter gives results on improving protein-ligand binding affinity predictions based on molecular dynamics simulations using machine learning potentials with a hybrid neural network potential and molecular mechanics ...
  • Cremer, Julian; Medrano Sandonas, Leonardo; Tkatchenko, Alexandre; Clevert, Djork-Arné; De Fabritiis, Gianni (American Chemical Society (ACS), 2023)
    Predictive modeling of toxicity is a crucial step in the drug discovery pipeline. It can help filter out molecules with a high probability of failing in the early stages of de novo drug design. Thus, several machine learning ...
  • Stanley, Nathaniel H., 1983-; De Fabritiis, Gianni (SpringerOpen, 2015)
    Molecular dynamics simulations hold the promise to be an important tool for biological research and drug discovery. Historically, however, there were several obstacles for it to become a practical research tool. Limitations ...
  • Pérez Hernández, Guillermo; Paul, Fabian; Giorgino, Toni; De Fabritiis, Gianni (American Institute of Physics (AIP), 2013)
    A goal in the kinetic characterization of a macromolecular system is the description of its slow relaxation processes via (i) identification of the structural changes involved in these processes and (ii) estimation of the ...
  • Varela Rial, Alejandro (2022-02-25)
    The affinity of a drug to its target protein is one of the key properties of a drug. Although there are experimental methods to measure the binding affinity, they are expensive and relatively slow. Hence, accurately ...
  • Selent, Jana; Sanz, Ferran; Pastor Maeso, Manuel; De Fabritiis, Gianni (Public Library of Science (PLoS), 2010)
    G-protein coupled receptors, the largest family of proteins in the human genome, are involved in many complex signal transduction pathways, typically activated by orthosteric ligand binding and subject to allosteric ...
  • Buch Mundó, Ignasi (Universitat Pompeu Fabra, 2013-02-04)
    Investigation of protein-ligand interactions has been a long-standing application for molecular dynamics (MD) simulations given its importance to drug design. However, relevant timescales for biomolecular motions are orders ...
  • Pérez Culubret, Adrià (2022-02-02)
    Caracteritzar la dinàmica de les proteïnes és essencial per tal d'entendre la connexió entre seqüència i funció. La simulació de dinàmiques moleculars és una de les tècniques principals per a estudiar la dinàmica de proteïnes ...
  • Majewski, Maciej; Pérez, Adrià; Thölke, Philipp; Doerr, Stefan, 1987-; Charron, Nicholas E.; Giorgino, Toni; Husic, Brooke E.; Clementi, Cecilia; Noé, Frank; De Fabritiis, Gianni (Nature Research, 2023)
    A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. ...
  • Jiménez Luna, José (Universitat Pompeu Fabra, 2019-10-28)
    Deep learning approaches have become increasingly popular in the last years thanks to their state-of the-art performance in fields such as computer vision and natural language understanding. The first goal of this thesis ...
  • Wang, Jiang; Olsson, Simon; Wehmeyer, Christoph; Pérez, Adrià; Charron, Nicholas E.; De Fabritiis, Gianni; Noé, Frank; Clementi, Cecilia (American Chemical Society (ACS), 2019)
    Atomistic or ab initio molecular dynamics simulations are widely used to predict thermodynamics and kinetics and relate them to molecular structure. A common approach to go beyond the time- and length-scales accessible ...

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