Statistical and computational physics of biomolecular systems

Group leaders: Gérald KNELLER and Konrad HINSEN

Statistical and computational physics of biomolecular systems
path_for_subdiffusive_fractional_brownian_dynamics_petit-2.jpg
A path for subdiffusive fractional Brownian dynamics

Anomalous relaxation and diffusion processes in biomolecular systems
The internal dynamics of biomolecular systems such as proteins is characterized by a vast spectrum of time scales and most of the dynamical modes are strongly overdamped and diffusive. Their time evolution and corresponding time correlation functions can be modeled by fractional Fokker-Planck equations, which generalize the idea of Markovian, i.e. memoryless small-step diffusion processes to stochastic processes with long-time memory. The keyword “anomalous relaxation” refers here to the strongly non-exponential decay of the corresponding time correlation functions. We have successfully applied and continue to apply such concepts to model quasielastic neutron scattering spectra and NMR relaxation spectra from proteins.

Anomalous diffusion generally refers to unconstrained diffusion process where the mean square displacement exhibits a non-linear growth with time. The underlying mechanisms are the same as for anomalous relaxation, except that the dynamics of the diffusing particles, which maybe anything from single atoms to whole proteins, is not space-limited. We have studied anomalous lateral diffusion if lipid molecules in lipid bilayers and we have also developed a theoretical framework for anomalous diffusion and relaxation in general, which links such processes to the atomistic dynamics in “crowded” molecular systems. Anomalous diffusion is an ubiquitous phenomenon which is also of great importance in other domains of science, such as in solid state physics, in physical chemistry, and in financial mathematics (http://www.smoluchowski.if.uj.edu.pl).

Minimal models for protein structure and dynamics
Based on the concepts of fractional Brownian dynamics and on the general theoretical framework for anomalous diffusion and relaxation processes, we have developed a so-called minimal model for the backbone dynamics of proteins (J. Chem. Phys. Editor’s choice 2012) and more recently a model-free interpretation of quasielastic neutron scattering spectra (QENS) from proteins proteins (J. Chem. Phys. Editor’s choice 2016). The basic features of protein dynamics, in particular its multiscale character, is here captured by essentially two parameters describing, respectively, the form and the scale of a spectrum. In case of the QENS analysis one uses in addition that high-resolution spectrometers can only detect the asymptotic for of the dynamics for long times and small frequencies.

 

screwframe_tube_model_for_myoglobin_petit-2.jpg
ScrewFrame tube model for myoglobin
Another type of minimal protein models, which has been developed in the group, concerns the bigactad.gifcharacterization of their global fold. The ScrewFrame model uses the positions of the Cα-atoms along the backbone of a protein to construct a tube model for the protein under consideration. Such a tube model is essentially characterized by the bending and by the internal torsion of the tube. The model is based on Cα-based Frenet frames, which are constructed from the discrete trace of the Cα-positions, and a sequence of helix motions relating these frames. Current applications concern the structural characterization of “unstructured proteins” and the analysis of electron microscopy clichés.

 

Elastic Network Models for proteins
elastic_network_model_for_lysozyme_petit-2.jpg
Elastic network model for lysozyme

An Elastic Network Model (ENM) describes a protein as a structured elastic object at a coarse-grained level. The most widely used ENMs represent a protein by its Cα atoms connected by springs. We have been developing, evaluating, and applying ENMs for many years, with applications including in particular the interpretation of low-resolution protein structures and the analysis of conformational transitions.

 

Reproducible research
The rapid change in computing technology have made it difficult to reproduce or verify results obtained with the help of computers. The publication of software and electronic datasets are crucial to improve to make such research transparent, but it remains difficult to publish them in such a way that other scientists can easily re-run a computational analysis several years later. We have been publishing most of our work reproducibly in recent years, using the ActivePapers framework that we are developing to support the specific needs of biomolecular simulation.
Scientific data management
A major technical challenge in publishing biomolecular simulation data is the lack of suitable file formats for many data types. Only molecular configurations and sequences of such configurations (trajectories) are well supported by today’s software tools. Other important information, such as molecular systems definitions, including force fields and their parameters, normal modes, or models used in trajectory analysis, are difficult to archive or exchange, and are therefore not published at all. We are working on the development of modular and extensible data model and file formats for all aspects of molecular simulation. Current projects in this field are the MOSAIC data model and the digital scientific notation Leibniz.
Software development
Most of our research is methodological and therefore requires the development of appropriate software. We have made all our research software publicly available, both to allow verification of our work and to provide useful tools to the scientific community. Our most widely used tools are the Molecular Modelling Toolkit (MMTK), a Python library for molecular simulation, and nMOLDYN, an analysis tool for Molecular Dynamics (MD) trajectories and the calculation of MD-based neutron scattering spectra.


102 documents

Article dans une revue

  • Gerald R. Kneller, Konrad Hinsen. Memory effects in a random walk description of protein structure ensembles. Journal of Chemical Physics, American Institute of Physics, 2019, 150 (6), pp.064911. ⟨10.1063/1.5054887⟩. ⟨hal-02117662⟩
  • Konrad Hinsen. Dealing With Software Collapse. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2019, 21 (3), pp.104-108. ⟨10.1109/MCSE.2019.2900945⟩. ⟨hal-02117588⟩
  • Konrad Hinsen. Verifiability in computer-aided research: the role of digital scientific notations at the human-computer interface. PeerJ Computer Science, PeerJ, 2018, 4, pp.e158. ⟨10.7717/peerj-cs.158⟩. ⟨hal-02068574⟩
  • G. Kneller. Model-free Approach to Quasielastic Neutron Scattering from Anomalously Diffusing Quantum Particles. Acta Physica Polonica B, Jagellonian University, Cracow, 2018, 49 (5), pp.893. ⟨hal-01966150⟩
  • Rana Ashkar, Hassina Bilheux, Heliosa Bordallo, Robert Briber, David Callaway, et al.. Neutron scattering in the biological sciences: progress and prospects. Acta crystallographica. Section D, Structural biology, International Union of Crystallography, 2018, 74 (12), pp.1129-1168. ⟨10.1107/S2059798318017503⟩. ⟨hal-01990351⟩
  • Judith Peters, Rana Ashkar, Hassina Bilheux, Heliosa Bordallo, Robert Briber, et al.. Neutron scattering in the biological sciences: progress and prospects. Acta crystallographica. Section D, Structural biology, International Union of Crystallography, 2018, 74 (12), pp.1129-1168. ⟨hal-02001788⟩
  • Konrad Hinsen. Reusable vs. re-editable code. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2018, 20 (3), pp.78-83. ⟨10.1109/MCSE.2018.03202636⟩. ⟨hal-01966146⟩
  • Konrad Hinsen. Domain-Specific Languages in Scientific Computing. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2018, 20 (1), pp.88-92. ⟨10.1109/MCSE.2018.011111130⟩. ⟨hal-01966145⟩
  • Gerald Kneller. Franck–Condon picture of incoherent neutron scattering. Proceedings of the National Academy of Sciences of the United States of America , National Academy of Sciences, 2018, 115 (38), pp.9450-9455. ⟨hal-01966151⟩
  • Gerald Kneller. General framework for constraints in molecular dynamics simulations. Molecular Physics, Taylor & Francis, 2017, 115 (9-12), pp.1352 - 1361. ⟨10.1080/00268976.2017.1297503⟩. ⟨hal-01656448⟩
  • Nicolas Rougier, Konrad Hinsen, Frédéric Alexandre, Thomas Arildsen, Lorena Barba, et al.. Sustainable computational science: the ReScience initiative. PeerJ Computer Science, PeerJ, 2017, 3. ⟨hal-01592078⟩
  • Konrad Hinsen. A Dream of Simplicity: Scientific Computing on Turing Machines. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2017, 19 (3), pp.78 - 85. ⟨10.1109/mcse.2017.39⟩. ⟨hal-01618280⟩
  • Konrad Hinsen. A Dream of Simplicity: Scientific Computing on Turing Machines. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2017, 19 (3), pp.78-85. ⟨10.1109/MCSE.2017.39⟩. ⟨hal-02117720⟩
  • Konrad Hinsen. The Roles of Code in Computational Science. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2017, 19 (1), pp.78 - 82. ⟨10.1109/MCSE.2017.18⟩. ⟨hal-01618279⟩
  • Sarah Cohen-Boulakia, Khalid Belhajjame, Olivier Collin, Jérôme Chopard, Christine Froidevaux, et al.. Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities. Future Generation Computer Systems, Elsevier, 2017, ⟨10.1016/j.future.2017.01.012⟩. ⟨hal-01516082⟩
  • Gerald R. Kneller. Asymptotic neutron scattering laws for anomalously diffusing quantum particles. Journal of Chemical Physics, American Institute of Physics, 2016, 145 (4), pp.044103. ⟨10.1063/1.4959124⟩. ⟨hal-01407912⟩
  • Konrad Hinsen. The Power to Create Chaos. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2016, 18 (4), pp.75-79. ⟨10.1109/MCSE.2016.67⟩. ⟨hal-02071770⟩
  • Gerald Kneller, Konrad Hinsen. Protein secondary-structure description with a coarse-grained model. Acta Crystallographica Section D: Biological Crystallography, International Union of Crystallography, 2015, 71 (7), pp.1411-1422. ⟨10.1107/s1399004715007191⟩. ⟨hal-02072279⟩
  • G. Kneller. Anomalous Diffusion in Biomolecular Systems from the Perspective of Non-equilibrium Statistical Physics. Acta Physica Polonica B, Jagellonian University, Cracow, 2015, 46 (6), pp.1167. ⟨10.5506/APhysPolB.46.1167⟩. ⟨hal-02072278⟩
  • Paolo A. Calligari, Vania Calandrini, Jacques Ollivier, Jean-Baptiste Artero, Michael Härtlein, et al.. Adaptation of Extremophilic Proteins with Temperature and Pressure: Evidence from Initiation Factor 6. Journal of Physical Chemistry B, American Chemical Society, 2015, 119 (25), pp.7860-7873. ⟨10.1021/acs.jpcb.5b02034⟩. ⟨hal-01170680⟩
  • Konrad Hinsen. The Approximation Tower in Computational Science: Why Testing Scientific Software Is Difficult. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2015, 17 (4), pp.72-77. ⟨10.1109/MCSE.2015.75⟩. ⟨hal-01171382⟩
  • Konrad Hinsen. Writing Software Specifications. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2015, 17 (3), pp.54-61. ⟨10.1109/MCSE.2015.64⟩. ⟨hal-01171458⟩
  • Sławomir Stachura, Gerald Kneller. Communication: Probing anomalous diffusion in frequency space. Journal of Chemical Physics, American Institute of Physics, 2015, 143 (19), pp.191103. ⟨10.1063/1.4936129⟩. ⟨hal-02072308⟩
  • Konrad Hinsen, Aurore Vaitinadapoule, Mariano A. Ostuni, Catherine Etchebest, Jean-Jacques Lacapere. Construction and validation of an atomic model for bacterial TSPO from electron microscopy density, evolutionary constraints, and biochemical and biophysical data.. Biochimica et Biophysica Acta:Biomembranes, Elsevier, 2015, 1848 (2), pp.568-580. ⟨10.1016/j.bbamem.2014.10.028.⟩. ⟨hal-01171268⟩
  • Konrad Hinsen. Technical Debt in Computational Science. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2015, 17 (6), pp.103-107. ⟨10.1109/MCSE.2015.113⟩. ⟨hal-02072258⟩
  • Konrad Hinsen. ActivePapers: a platform for publishing and archiving computer-aided research.. F1000Research, Faculty of 1000, 2015, pp.doi:10.12688/f1000research.5773.2. ⟨10.12688/f1000research.5773.2.⟩. ⟨hal-01171263⟩
  • Sławomir Stachura, Gerald R. Kneller. Anomalous lateral diffusion in lipid bilayers observed by molecular dynamics simulations with atomistic and coarse-grained force fields. Molecular Simulation, Taylor & Francis, 2014, 40 (1-3), pp.245-250. ⟨10.1080/08927022.2013.840902⟩. ⟨hal-01180893⟩
  • Gerald R. Kneller. Communication: A scaling approach to anomalous diffusion. Journal of Chemical Physics, American Institute of Physics, 2014, 141 (4), pp.041105. ⟨10.1063/1.4891357⟩. ⟨hal-01179255⟩
  • Konrad Hinsen. MOSAIC: A Data Model and File Formats for Molecular Simulations. Journal of Chemical Information and Modeling, American Chemical Society, 2014, 54 (1), pp.131-137. ⟨10.1021/ci400599y⟩. ⟨hal-01179151⟩
  • Konrad Hinsen. Computational science: shifting the focus from tools to models. F1000Research, Faculty of 1000, 2014, 3, pp.101. ⟨10.12688/f1000research.3978.2⟩. ⟨hal-01175456⟩
  • Konrad Hinsen. A Glimpse of the Future of Scientific Programming. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2013, 15 (1), pp.84-88. ⟨hal-00817458⟩
  • Judith Peters, Gerald Kneller. Motional heterogeneity in human acetylcholinesterase revealed by a non-Gaussian model for elastic incoherent neutron scattering Motional heterogeneity in human acetylcholinesterase revealed by a non-Gaussian model for elastic incoherent neutron scattering. Journal of Chemical Physics, American Institute of Physics, 2013, 139 (16), pp.165102. ⟨10.1063/1.4825199⟩. ⟨hal-01582670⟩
  • Guillaume Chevrot, Konrad Hinsen, Gerald Kneller. Model-free simulation approach to molecular diffusion tensors. Journal of Chemical Physics, American Institute of Physics, 2013, 139 (15), pp.154110. ⟨10.1063/1.4823996⟩. ⟨hal-02070748⟩
  • Konrad Hinsen, Shuangwei Hu, Gerald R. Kneller, Antti J. Niemi. A comparison of reduced coordinate sets for describing protein structure. Journal of Chemical Physics, American Institute of Physics, 2013, 139 (12), pp.124115. ⟨10.1063/1.4821598⟩. ⟨hal-01528424⟩
  • Edvin Fuglebakk, Nathalie Reuter, Konrad Hinsen. Evaluation of Protein Elastic Network Models Based on an Analysis of Collective Motions. Journal of Chemical Theory and Computation, American Chemical Society, 2013, 9 (12), pp.5618-5628. ⟨10.1021/ct400399x⟩. ⟨hal-02070831⟩
  • Konrad Hinsen. Software Development for Reproducible Research. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2013, 15 (4), pp.60-63. ⟨10.1109/MCSE.2013.91⟩. ⟨hal-02070857⟩
  • Konrad Hinsen. Daydreaming about Scientific Programming. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2013, 15 (5), pp.77-79. ⟨10.1109/MCSE.2013.104⟩. ⟨hal-02070862⟩
  • Gerald R Kneller, Konrad Hinsen, Paolo Calligari. Communication: a minimal model for the diffusion-relaxation backbone dynamics of proteins.. Journal of Chemical Physics, American Institute of Physics, 2012, 136 (19), pp.191101. ⟨10.1063/1.4718380⟩. ⟨hal-00726225⟩
  • Konrad Hinsen. Managing State. COMPUTING IN SCIENCE & ENGINEERING, IEEE, 2012, 14 (1), pp.80-86. ⟨10.1109/MCSE.2012.11⟩. ⟨hal-00726599⟩
  • P.A. Calligari, G.R. Kneller. ScrewFit: combining localization and description of protein secondary structure. Acta Crystallographica Section D: Biological Crystallography, International Union of Crystallography, 2012, 68, pp.1690-1693. ⟨hal-00751382⟩
  • Konrad Hinsen. Caring for Your Data. COMPUTING IN SCIENCE & ENGINEERING, IEEE, 2012, 14 (6), pp.70-74. ⟨10.1109/MCSE.2012.108⟩. ⟨hal-00817362⟩
  • Alexandre Giuliani, Aleksandar R Milosavljević, Konrad Hinsen, Francis Canon, Christophe Nicolas, et al.. Structure and Charge-State Dependence of the Gas-Phase Ionization Energy of Proteins.. Angewandte Chemie (English Edition), John Wiley & Sons, 2012, epub ahead of print. ⟨10.1002/anie.201204435⟩. ⟨hal-00727349⟩
  • Paolo A Calligari, Gerald R Kneller. ScrewFit: combining localization and description of protein secondary structure.. Acta Crystallogr D Biol Crystallogr, 2012, 68 ((Pt 12)), pp.1690-3. ⟨10.1107/S0907444912039029⟩. ⟨hal-00766848⟩
  • Christopher Ing, Konrad Hinsen, Jing Yang, Toby Zeng, Hui Li, et al.. A path-integral Langevin equation treatment of low-temperature doped helium clusters.. Journal of Chemical Physics, American Institute of Physics, 2012, 136 (22), pp.224309-224312. ⟨10.1063/1.4726507⟩. ⟨hal-00726222⟩
  • Gerald R Kneller, Guillaume Chevrot. Impact of anisotropic atomic motions in proteins on powder-averaged incoherent neutron scattering intensities.. Journal of Chemical Physics, American Institute of Physics, 2012, 137 (22), pp.225101. ⟨10.1063/1.4769782⟩. ⟨hal-00817098⟩
  • N. Smolin, R. Biehl, G. R. Kneller, D. Richter, J. C. Smith. Functional domain motions in proteins on the ~1-100 ns timescale: comparison of neutron spin-echo spectroscopy of phosphoglycerate kinase with molecular-dynamics simulation.. Biophysical Journal, Biophysical Society, 2012, 102 (5), pp.1108-17. ⟨10.1016/j.bpj.2012.01.002⟩. ⟨hal-00726260⟩
  • Konrad Hinsen, Eric Pellegrini, Sławomir Stachura, Gerald R Kneller. nMoldyn 3: Using task farming for a parallel spectroscopy-oriented analysis of molecular dynamics simulations.. Journal of Computational Chemistry, Wiley, 2012, 33 (25), pp.2043-2048. ⟨10.1002/jcc.23035⟩. ⟨hal-00721865⟩
  • Gerald R. Kneller. Generalized Kubo relations and conditions for anomalous diffusion: Physical insights from a mathematical theorem. Journal of Chemical Physics, American Institute of Physics, 2011, 134 (22), pp.Article Number: 224106. ⟨10.1063/1.3598483⟩. ⟨hal-00614940⟩
  • Guillaume Chevrot, Paolo Calligari, Konrad Hinsen, Gerald R Kneller. Least constraint approach to the extraction of internal motions from molecular dynamics trajectories of flexible macromolecules.. Journal of Chemical Physics, American Institute of Physics, 2011, 135 (8), pp.084110. ⟨10.1063/1.3626275⟩. ⟨hal-00720598⟩
  • Vania Calandrini, E. Pellegrini, Paolo Calligari, Konrad Hinsen, Gerald R. Kneller. nMoldyn - Interfacing spectroscopic experiments, molecular dynamics simulations and models for time correlation functions. Collection SFN, 2011, 12, pp.201-232. ⟨10.1051/sfn/201112010⟩. ⟨hal-00720549⟩
  • Paolo Calligari, Vania Calandrini, Gerald R Kneller, Daniel Abergel. From NMR relaxation to fractional Brownian dynamics in proteins: results from a virtual experiment.. Journal of Physical Chemistry B, American Chemical Society, 2011, 115 ((43)), pp.12370-9. ⟨10.1021/jp205380f⟩. ⟨hal-00688787⟩
  • G.R. Kneller, K. Baczynski, M. Pasenkiewicz-Gierula. Communication: consistent picture of lateral subdiffusion in lipid bilayers: molecular dynamics simulation and exact results. Journal of Chemical Physics, American Institute of Physics, 2011, 135 (14), pp.141105. ⟨10.1063/1.3651800⟩. ⟨hal-00720633⟩
  • Gerald R. Kneller. Comment on "Fast Determination of the Optimal Rotational Matrix for Macromolecular Superpositions" [J. Comp. Chem. 31, 1561 (2010)]. Journal of Computational Chemistry, Wiley, 2011, 32 (1), pp.183-184. ⟨10.1002/jcc.21607⟩. ⟨hal-00602439⟩
  • Konrad Hinsen. Computer code: incentives needed. Nature, Nature Publishing Group, 2010, 468, pp.370. ⟨10.1038/468037b⟩. ⟨hal-00726320⟩
  • Konrad Hinsen. Economic growth: indicators not targets.. Nature, Nature Publishing Group, 2010, 468, pp.897. ⟨10.1038/468897a⟩. ⟨hal-00726312⟩
  • Konrad Hinsen, Edward Beaumont, Bertrand Fournier, Jean-Jacques Lacapère. From electron microscopy maps to atomic structures using normal mode-based fitting. Methods in Molecular Biology, Humana Press/Springer Imprint, 2010, 654, pp.237-258. ⟨10.1007/978-1-60761-762-4_13⟩. ⟨hal-00609503⟩
  • G.K. Thiruvathukal, Konrad Hinsen, Konstantin Laufer, Joe Kaylor. Virtualization for computational scientists. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2010, 12 (4), pp.52-61. ⟨hal-00602510⟩
  • Vania Calandrini, Daniel Abergel, Gerald R Kneller. Fractional protein dynamics seen by nuclear magnetic resonance spectroscopy: Relating molecular dynamics simulation and experiment.. Journal of Chemical Physics, American Institute of Physics, 2010, 133 (14), pp.145101. ⟨10.1063/1.3486195⟩. ⟨hal-00593171⟩
  • Gerald R. Kneller, Vania Calandrini. Self-similar dynamics of proteins under hydrostatic pressure-Computer simulations and experiments. Biochimica et Biophysica Acta Proteins and Proteomics, Elsevier, 2010, 1804 (1), pp.56-62. ⟨10.1016/j.bbapap.2009.05.007⟩. ⟨hal-00529350⟩
  • Konrad Hinsen. A scientific model for free will is impossible. Proceedings of the National Academy of Sciences of the United States of America , National Academy of Sciences, 2010, 107 (38), pp.E149. ⟨10.1073/pnas.1010609107⟩. ⟨hal-00602371⟩
  • Konrad Hinsen. The promises of functional programming. COMPUTING IN SCIENCE & ENGINEERING, IEEE, 2009, 11 (4), pp.86-90. ⟨hal-00522448⟩
  • Vania Calandrini, Godehard Sutmann, Antonio Deriu, Gerald R. Kneller. Rigid Molecule Approximation in Memory Function-based Models for Molecular Liquids: Application to Liquid Water. ZEITSCHRIFT FUR PHYSIKALISCHE CHEMIE-INTERNATIONAL JOURNAL OF RESEARCH IN PHYSICAL CHEMISTRY & CHEMICAL PHYSICS, 2009, 223 (9), pp.957-978. ⟨10.1524/zpch.2009.6063⟩. ⟨hal-00521840⟩
  • Konrad Hinsen, Konstantin Laeufer, K. Thiruvathukal George. Essential tools: version control systems. COMPUTING IN SCIENCE & ENGINEERING, IEEE, 2009, 11 (6), pp.84-90. ⟨hal-00522455⟩
  • Gerald R. Kneller, Konrad Hinsen. Quantitative model for the heterogeneity of atomic position fluctuations in proteins: A simulation study. Journal of Chemical Physics, American Institute of Physics, 2009, 131 (4), pp.045104. ⟨10.1063/1.3170941⟩. ⟨hal-00522467⟩
  • Denis Horváth, Gerald R. Kneller. A least-constraint principle for population dynamics and reaction kinetics: Modeling entropy-controlled chemical hypercycles. Journal of Chemical Physics, American Institute of Physics, 2009, 131 (17), pp.171101. ⟨10.1063/1.3253688⟩. ⟨hal-00522464⟩
  • Paolo A Calligari, Gerald R Kneller, Andrea Giansanti, Paolo Ascenzi, Alessandro Porrello, et al.. Inhibition of viral group-1 and group-2 neuraminidases by oseltamivir: A comparative structural analysis by the ScrewFit algorithm.. Biophysical Chemistry, Elsevier, 2009, 141 ((1)), pp.117-23. ⟨10.1016/j.bpc.2009.01.004⟩. ⟨hal-00773671⟩
  • Paolo Calligari, Gerald R. Kneller, Andrea Giansanti, Paolo Ascenzi, Alessandro (porrello, et al.. Inhibition of viral group-1 and group-2 neuraminidases by oseltamivir: A comparative structural analysis by the ScrewFit algorithm. Biophysical Chemistry, Elsevier, 2009, 141 (1), pp.117-123. ⟨10.1016/j.bpc.2009.01.004⟩. ⟨hal-00521837⟩
  • Konrad Hinsen. Physical arguments for distance-weighted interactions in elastic network models for proteins. Proceedings of the National Academy of Sciences of the United States of America , National Academy of Sciences, 2009, 106 (45), pp.E128. ⟨10.1073/pnas.0909385106⟩. ⟨hal-00522452⟩
  • Gerald Kneller. Eckart axis conditions, Gauss' principle of least constraint, and the optimal superposition of molecular structures. Journal of Chemical Physics, American Institute of Physics, 2008, 128 (19), pp.194101. ⟨10.1063/1.2902290⟩. ⟨hal-00283349⟩
  • Gerald R. Kneller. Eckart axis conditions, Gauss’ principle of least constraint, and the optimal superposition of molecular structures. Journal of Chemical Physics, American Institute of Physics, 2008, 128 (19), pp.194101. ⟨10.1063/1.2902290⟩. ⟨hal-01378837⟩
  • Calandrini, Vania, Daniel Abergel, Gerald R. Kneller. Protein dynamics from a NMR perspective: Networks of coupled rotators and fractional Brownian dynamics.. Journal of Chemical Physics, American Institute of Physics, 2008, 128, pp.145102. ⟨hal-00420311⟩
  • V. Calandrini, V. Hamon, K. Hinsen, P. Calligari, M.-C. Bellissent-Funel, et al.. Relaxation dynamics of lysozyme in solution under pressure: Combining molecular dynamics simulations and quasielastic neutron scattering. Chemical Physics, Elsevier, 2008, 345 (2-3), pp.289-297. ⟨10.1016/j.chemphys.2007.07.018⟩. ⟨hal-00408024⟩
  • Gerald R. Kneller, Konrad Hinsen, Godehard Sutmann, Vania Calandrini. Scaling laws and memory effects in the dynamics of liquids and proteins. Physics of Particles and Nuclei Letters, 2008, 5 (3), pp.189-195. ⟨10.1134/S1547477108030114⟩. ⟨hal-00518138⟩
  • K. Wood, S. Grudinin, B. Kessler, M. Weik, M. Johnson, et al.. Dynamical heterogeneity of specific amino acids in bacteriorhodopsin. Journal of Molecular Biology, Elsevier, 2008, 380 (3), pp.581-591. ⟨10.1016/j.jmb.2008.04.077⟩. ⟨hal-00518913⟩
  • Vania Calandrini, Gerald R. Kneller. Influence of pressure on the low and fast fractional relaxation dynamics in lysozyme: a simulation study. Journal of Chemical Physics, American Institute of Physics, 2008, 128 (6), pp.065102. ⟨10.1063/1.2828769⟩. ⟨hal-00283234⟩
  • Vania Calandrini, Daniel Abergel, Gerald R. Kneller. Protein dynamics from a NMR perspective: networks of coupled rotators and fractional brownian dynamics. Journal of Chemical Physics, American Institute of Physics, 2008, 128 (14), pp.145102. ⟨10.1063/1.2894844⟩. ⟨hal-00283232⟩
  • Konrad Hinsen, Gérald Kneller. Solvent effects in the slow dynamics of proteins. Proteins - Structure, Function and Bioinformatics, Wiley, 2008, 70 (4), pp.1235-1242. ⟨10.1002/prot.21655⟩. ⟨hal-00176279⟩
  • Konrad Hinsen. Structural flexibility in proteins: impact of the crystal environment. Bioinformatics, Oxford University Press (OUP), 2008, 24 (4), pp.521-528. ⟨10.1093/bioinformatics/btm625⟩. ⟨hal-00283340⟩
  • V. Calandrini, V. Hamon, K. Hinsen, P. Calligari, M. Bellissent-Funel, et al.. Relaxation dynamics of lysozyme in solution under pressure: Combining molecular dynamics simulations and quasielastic neutron scattering. Chemical Physics, Elsevier, 2007, 345 (2-3), pp.289-297. ⟨hal-00282389⟩
  • Konrad Hinsen. Parallel scripting with python. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2007, 9 (6), pp.82-89. ⟨hal-00282403⟩
  • Gerald Kneller. Projection formalism for constrained dynamical systems: From Newtonian to Hamiltonian mechanics. Journal of Chemical Physics, American Institute of Physics, 2007, 127, 164114 (5 p.). ⟨10.1063/1.2779326⟩. ⟨hal-00188115⟩
  • Gerald R. Kneller, Vania Calandrini. Estimating the influence of finite instrumental resolution on elastic neutron scattering intensities from proteins. Journal of Chemical Physics, American Institute of Physics, 2007, 126, 125107 (2007) (8 p.). ⟨10.1063/1.2711207⟩. ⟨hal-00159577⟩
  • G.R. Kneller, P. Calligari. Efficient characterization of protein secondary structure in terms of screw motions. Acta Crystallographica Section D: Biological Crystallography, International Union of Crystallography, 2006, 62, pp.302-311. ⟨10.1107/S0907444905042654⟩. ⟨hal-00088869⟩
  • Vania Calandrini, Godehard Sutmann, Antonio Deriu, Gerald R. Kneller. Role of effective atomic masses in memory function-based models for liquids: A simulation study of liquid water. Journal of Chemical Physics, American Institute of Physics, 2006, 125 (23), 236102 (2006) (2 p.). ⟨10.1063/1.2403877⟩. ⟨hal-00166737⟩
  • Gérald Kneller. Hamiltonian formalism for semiflexible molecules in Cartesian coordinates.. Journal of Chemical Physics, American Institute of Physics, 2006, 125, 114107 (10 p.). ⟨10.1063/1.2220037⟩. ⟨hal-00110254⟩
  • Véronique Hamon, Paolo Calligari, Konrad Hinsen, Gerald R. Kneller. Simulation studies of structural changes and relaxation processes in lysozyme under pressure. Journal of Non-Crystalline Solids, Elsevier, 2006, 352, pp.4417-4423. ⟨hal-00388010⟩
  • K. Hinsen, H.P. Langtangen, O. Skavhaug, A. Odegard. Using BSP and Python to simplify parallel programming. Future Generation Computer Systems, Elsevier, 2006, 22, pp.123-157. ⟨10.1016/j.future.2003.09.003⟩. ⟨hal-00088866⟩
  • B. Brutovsky, G.R. Kneller. Linear prediction of force time series to accelerate molecular dynamics simulations. Computer Physics Communications, Elsevier, 2005, 169, pp.339-342. ⟨hal-00088530⟩
  • G.R. Kneller. Simulations moléculaires et leur analyse. Journal de Physique IV Colloque, 2005, 130, pp.155-178. ⟨hal-00088724⟩
  • G.R. Kneller. Quasielastic neutron scattering and relaxation processes in proteins: analytical and simulation-based models. Physical Chemistry Chemical Physics, Royal Society of Chemistry, 2005, 7, pp.2641-2655. ⟨hal-00088607⟩
  • G.R. Kneller. Comment on "Using quaternions to calculate RMSD" [J. Comp. Chem. 25, 1849 (2004)]. Journal of Computational Chemistry, Wiley, 2005, 26, pp.1660-1662. ⟨hal-00088606⟩
  • Gerald Kneller, Konrad Hinsen. Fractional Brownian dynamics in proteins. Journal of Chemical Physics, American Institute of Physics, 2004, 121, pp.10278. ⟨10.1063/1.1806134⟩. ⟨hal-00015422⟩
  • Kneller G.R., G. Sutmann. Scaling of the memory function and Brownian motion. Journal of Chemical Physics, American Institute of Physics, 2004, 120, pp.1667-1669. ⟨hal-00113062⟩
  • B. Brutovsky, T. Mülders, G.R. Kneller. Accelerating molecular dynamics simulations by linear prediction of time series. Journal of Chemical Physics, American Institute of Physics, 2003, 118, pp.6179-6187. ⟨hal-00087705⟩
  • Konrad Hinsen. High-Level Parallel Software Development with Python and BSP. Parallel Processing Letters, World Scientific Publishing, 2003, 13, pp.473. ⟨hal-00015424⟩
  • Nathalie Reuter, Konrad Hinsen, Jean-Jacques Lacapère. Transconformations of the SERCA1 Ca-ATPase: A Normal Mode Study. Biophysical Journal, Biophysical Society, 2003, 85, pp.2186. ⟨hal-00015419⟩
  • K. Hinsen, Petrescu A.J., S. Dellerue, Bellissent-Funel M.C., Kneller Gr.. Liquid-like and solid-like motions in proteins. Journal of Molecular Liquids, Elsevier, 2002, 98-99, pp.383-400. ⟨hal-00114769⟩

Communication dans un congrès

  • Alexandre Giuliani, Alexandre R. Milosavljević, Konrad Hinsen, Francis Canon, Christophe Nicolas, et al.. Ionization energy of gas phase protein cations and its dependence on charge state_and structure. Synchrotron SOLEIL Users Meeting, Jan 2013, Orsay, France. ⟨hal-01573564⟩
  • Konrad Hinsen. A data and code model for reproducible research and executable papers. International Conference on Computational Science, Jun 2011, Singapour, Singapore. pp.579, ⟨10.1016/j.procs.2011.04.061⟩. ⟨hal-00626032⟩

Chapitre d'ouvrage

  • Konrad Hinsen. Problem-Specific Analysis of Molecular Dynamics Trajectories for Biomolecules. Kitzes, J. Turek, D. Deniz, F. The Practice of Reproducible Research : Case Studies and Lessons from the Data-Intensive Sciences, University of California Press, pp.254-260, 2017, 978-0520294752. ⟨hal-02071690⟩
  • Gerald Kneller. Dynamics of biological macromolecules. Salvatore Magazù, Federica Migliardo. Dynamics of Biological Macromolecules by Neutron Scattering, BENTHAM SCIENCE PUBLISHERS, 2012, 978-1608053346. ⟨hal-02071825⟩
  • Konrad Hinsen, Edward Beaumont, Bertrand Fournier, Jean-Jacques Lacapère. From Electron Microscopy Maps to Atomic Structures Using Normal Mode-Based Fitting. Lacapère Jean-Jacques. Membrane Protein Structure Determination: Methods and Protocols, Springer-Verlag, pp.237-258, 2010, Methods in Molecular Biology, ⟨10.1007/978-1-60761-762-4_13⟩. ⟨hal-00610003⟩