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Virtual

Virtual. modelling. of proteins. Jacek Leluk Interdyscyplinarne Centrum Modelowania Matematycznego i Komputerowego, Uniwersytet Warszawski. Main functions of proteins (selected) : Enzymes Immunoglobulins Transport factors ( e.g. hemoglobin) Hormones, neurotransmitters

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Virtual

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  1. Virtual modelling of proteins Jacek Leluk Interdyscyplinarne Centrum Modelowania Matematycznego i Komputerowego, Uniwersytet Warszawski

  2. Main functions of proteins (selected): • Enzymes • Immunoglobulins • Transport factors (e.g.hemoglobin) • Hormones, neurotransmitters • Structural and storage proteins • Contractile proteins (muscles, flagella) Jacek Leluk

  3. Protein – a polymer of amino acids. • Proteins consists of one or more chains. • Some proteins contain other components (sugars, lipids, nucleotides, metal ions, other compounds...) – proteids. • The basic unit of a protein is amino acid. There are 20 biogenic amino acids (genetically encoded). Jacek Leluk

  4. Amino acids Amino acid – organic compound that contains amino group and acidic group (usually it is carboxyl group) General formula Alanine Jacek Leluk

  5. Amino acid – polypeptide – protein Jacek Leluk

  6. Protein chain folding Jacek Leluk

  7. Diversity of proteins Insulin ROP protein Glucagon Jacek Leluk

  8. Diversity of proteins Light „harvesting” protein from purple bacteria Jacek Leluk

  9. Sequence – structure - function At first the central dogma of molecular biology assumed very strict relationship between genetic information, protein structure and function: ? ? ? 1 gene 1 sequence 1 structure 1 function At present this dogma is still valid but not in as strict form as before. These relationships are not strictly univocal. e.g. a protein of the same sequence may reveal different secondary and tertiary structures. Jacek Leluk

  10. Sequence – structure - function All information about protein structure (and function as well) is included in its amino acid sequence, which is unique for each protein. In order to be able to apply these relationships for protein modelling, first we have to learn to read and understand the information „written” in amino acid sequence. The current level of our understanding this „writing” depends on the protein complexity and the prediction accuracy is between 20% and 80%. Jacek Leluk

  11. What do we have? • Biomolecular databases (genomic, protein and bibliographic) • Tools for theoretical analysis of biomolecules • Labs for experimental verification of the results • Knowledge (theories, hypotheses, theoretical models) Jacek Leluk

  12. Regular types of structure (secondary structure) -helix helix Jacek Leluk

  13. Regular types of structure (secondary structure) -chain (-sheet) sheet Jacek Leluk

  14. 3D protein structures Structure-function relationship Sea anemone - toxin Snake - toxin Jacek Leluk

  15. 3D protein structures Structure-function relationship Bacterial RNase Mammalian RNase Rnase inhibitor (inhibits both RNases) Jacek Leluk

  16. Errors (mutations) and resulting implicationsSickle cell anemia Sickle cell anemia – genetic disease caused by a single amino acid substitution in hemoglobin -chain (one of 146). S hemoglobin has Val instead of Glu in -chain. Homozygotes (HbSS) are lethal, heterozygotes (Hb AS) are anemic, but resistant to malaria. Normal hemoglobin –  chain VHLTPEEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLGAFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVANALAHKYH S Hemoglobin –  chain VHLTPVEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLGAFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVANALAHKYH Jacek Leluk

  17. Mutations and resulting implicationsSickle cell anemia Hemoglobin Normal Altered Jacek Leluk

  18. Mutations and resulting implicationsSickle cell anemia Jacek Leluk

  19. Mutations and resulting implicationsSickle cell anemia Jacek Leluk

  20. Glucagon (pig) – hormone, 29 amino acids HSQGTFTSDYSKYLDSRRAQDFVQWLMNT Glucagon (synthetic) – hormone, 29 amino acids HSQGTFTSDYSKYLDSKKAQEFVQWLMNT Jacek Leluk

  21. „Gluca con” modelling Glucagon (pig) – HSQGTFTSDYSKYLDSRRAQDFVQWLMNT Glucagon (synth.) – HSQGTFTSDYSKYLDSKKAQEFVQWLMNT Gluca con LAALIAAVAAAIAAVLRRIAEVLAIVAAL Hydrophobic amino acids: L, I, V, F, M, Y, (W) Jacek Leluk

  22. „Gluca con” design - results Glucagon (pig) – HSQGTFTSDYSKYLDSRRAQDFVQWLMNT Glucagon (synth.) – HSQGTFTSDYSKYLDSKKAQEFVQWLMNT Gluca con – LAALIAAVAAAIAAVLRRIXEVLAIVAAL Jacek Leluk

  23. Can we „improve” the Nature at molecular level? What for? Our goal is to get the knowledge about natural mechanisms and then to apply this knowledge for our needs, but not to alter the evolved mechanisms that naturally occur. Jacek Leluk

  24. Role and significance of theoretical protein modeling and design • Time economy • Money economy • Work and material economy • Increasing our knowledge • Supporting the experimental work Jacek Leluk

  25. The value of virtual protein design = Jacek Leluk

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