Computer simulations allow us to validate the structure, predict properties, and study the reactivity of proteins. In many areas of research, they are well integrated as they are used for structure validation and calculations of spectroscopic properties. In this chapter, we describe a simulation protocol that starts from a protein structure of a cyanobacteriochrome. The procedure to prepare the structure for classical molecular dynamics simulations is explained and broken down into single steps. After the classical simulation, it is shown how spectroscopic properties can be obtained by quantum chemical calculations which are part of a multiscale model. The high dimensionality of the protein environment in the calculation of excitation energies is an issue for the calculation of excitation energies, because a single representative geometry cannot be selected. To alleviate this problem, we explain the conformational sampling and compare it to the optimization procedure.

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Computational Protocols to Study Phytochromes

  • Probal Nag,
  • Chongyao Wei,
  • Megan J. Mackintosh,
  • Igor Schapiro

摘要

Computer simulations allow us to validate the structure, predict properties, and study the reactivity of proteins. In many areas of research, they are well integrated as they are used for structure validation and calculations of spectroscopic properties. In this chapter, we describe a simulation protocol that starts from a protein structure of a cyanobacteriochrome. The procedure to prepare the structure for classical molecular dynamics simulations is explained and broken down into single steps. After the classical simulation, it is shown how spectroscopic properties can be obtained by quantum chemical calculations which are part of a multiscale model. The high dimensionality of the protein environment in the calculation of excitation energies is an issue for the calculation of excitation energies, because a single representative geometry cannot be selected. To alleviate this problem, we explain the conformational sampling and compare it to the optimization procedure.