Selected article for: "ab initio and hybrid model"
Author: D. Molodenskiy; H. Mertens; D. Svergun
Title: An automated data processing and analysis pipeline for transmembrane proteins in detergent solutions
  • Document date: 2019_7_24
    • ID: lhriiv4u_29
    Snippet: Expectedly, the automatically generated Aquaporin0 models display more adequate structural details with increasing amount of a priori information. The single phase based model generated ab initio by DAMMIF (Fig. 6C) provides only the overall shape roughly approximating that of the protein-detergent complex. This reflects the limitation of the ab initio shape determination procedure, which must assume constant density inside the particle. The more.....
    Document: Expectedly, the automatically generated Aquaporin0 models display more adequate structural details with increasing amount of a priori information. The single phase based model generated ab initio by DAMMIF (Fig. 6C) provides only the overall shape roughly approximating that of the protein-detergent complex. This reflects the limitation of the ab initio shape determination procedure, which must assume constant density inside the particle. The more information-rich multi-phase MONSA and MEMPROT models (Fig. 6B, A) display a good level of similarity, with the hybrid model generated using the latter program being more detailed and arguably having a higher resolution. For the multi-phase MONSA modeling path the starting cylindrical search volume used for protein-solvent phases was considerably larger than the final model and contains a spherical core with the fixed protein phase (green area shown in Figure 5B ). However, after the minimization procedure the volume occupied by the protein phase becomes only slightly larger than the central fixed spherical volume, and the MONSA models do display protrusions resembling the four α-helical "legs" expected for Aquaporin0. These models are similar to those generated using the hybrid modeling path with MEMPROT, where the protein structure is assumed to be known.

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