Structure prediction

Structure prediction is the prediction of the three-dimensional structure of materials, such as crystals, proteins or small molecules. Structure prediction commonly uses a combination of microscopy, spectroscopy, scattering and computational techniques, such as electron microscopy, nuclear magnetic resonance spectroscopy, X-ray scattering and molecular dynamics.

Latest Research and Reviews

News and Comment

  • News & Views |

    Machine learning algorithms are fast surpassing human abilities in multiple tasks, from image recognition to medical diagnostics. Now, machine learning algorithms have been shown to be capable of accurately predicting the folded structures of proteins.

    • Cecilia Clementi
    Nature Chemistry 13, 1032-1034
  • Comments & Opinion
    | Open Access

    The Hückel rule defines that monocyclic and planar conjugated systems containing [4n + 2] π electrons are aromatic. Here, the authors highlight boron species that feature a globally 4n π system, defying the Hückel rule, but nonetheless exhibit aromaticity.

    • Kei Ota
    •  & Rei Kinjo
  • Research Highlights |

    Models for polyhedral clusters with different symmetries enable us to understand their electronic structures and predict the formation of new clusters.

    • David Schilter
  • News & Views |

    A comprehensive chemical space of potential inorganic ternary metal nitrides has been explored by computational methods as a guideline for their experimental synthesis and discovery.

    • Ralf Riedel
    •  & Zhaoju Yu
    Nature Materials 18, 664-665
  • Research Highlights |

    Particle swarm optimization allows one to search vast compositional space for new viable species. Additionally, simulating high pressures has enabled the prediction of hypervalent species such as IF8.

    • David Schilter