predictingproteinstructureandbeyond…内容摘要：
a: Brute Force Approach Towards Structure Elucidation Employ battalions of amp。 Postdoctorals Aim to solve about 400 structures a year Largescale expression amp。 crystallization attempts + – Basic strategies remain the same No (known) new tricks * Enhances the statistical base for inferring sequence – structure relationships ―Unrelenting‖ ones will be ignored ? KQFTKCELSQNLYDIDGYGRIALPELICTMFHTSGYDTQAIVENDESTEYGLFQISNALWCKSSQSPQSRNICDITCDKFLDDDITDDIMCAKKILDIKGIDYWIAHKALCTEKLEQWLCEKE Predicting Protein Structure: 1. Comparative Modeling (formerly, homology modeling) Use as template amp。 model 8lyz 1alc KVFGRCELAAAMKRHGLDNYRGYSLGNWVCAAKFESNFNTQATNRNTDGSTDYGILQINSRWWCNDGRTPGSRNLCNIPCSALLSSDITASVNCAKKIVSDGNGMNAWVAWRNRCKGTDVQAWIRGCRL Share Similar Sequence Homologous Structure is much more conserved than sequence during evolution Comparative Modeling Basis * Higher the similarity, higher is the confidence in the modeled structure * Limited applicability A large number of proteins and ORFs have no similarity to proteins with known structure * Predicting Protein Structure: Alternative Methods Threading or Fold Recognition Both these methods depend heavily on the analysis of known protein structures * Ab initio In addition, establishing sequence structure relationship is also important * Input from people trained in statistics, pattern recognition and related areas of puter science is very critical * Statistical Analysis of Protein Structures: Microenvironment Characterization Atom based properties Residue based properties Chemical group Secondary structure Other properties Type, Hydrophobicity, Charge Type, Hydrophobi。阅读剩余 0%
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