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CLASSIFICATION AND CHARACTERIZATION OF NATURAL PROTEIN INHIBITORS OF PROTEIN KINASES

CLASSIFICATION AND CHARACTERIZATION OF NATURAL PROTEIN INHIBITORS OF PROTEIN KINASES AGATA MEGLICZ 1 , JACEK LELUK 1 , BOGDAN LESYNG 1,2 1 Interdisciplinary Centre for Mathematical and Computational Modelling (ICM), Warsaw University, Poland

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CLASSIFICATION AND CHARACTERIZATION OF NATURAL PROTEIN INHIBITORS OF PROTEIN KINASES

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  1. CLASSIFICATION AND CHARACTERIZATION OF NATURAL PROTEIN INHIBITORS OF PROTEIN KINASES AGATA MEGLICZ1, JACEK LELUK1, BOGDAN LESYNG1,2 1Interdisciplinary Centre for Mathematical and Computational Modelling (ICM), Warsaw University, Poland 2Department of Biophysics, Faculty of Physics, Warsaw University, Poland

  2. Kinase project at ICM • Complex comparative studies at the primary structure level • Construction of molecular phylogenetic trees • Studies on sequence/structure/function relationship • Studies on the mechanisms of correlated mutations and variability • Genetic principles of differentiation within the kinase and kinase inhibitor families

  3. Kinase protein inhibitors – current knowledge status Although various protein kinase families are relatively well described, there is much less known about natural protein inhibitors that control their activities. Protein kinase inhibitors are not sufficiently well classified into homologous families. There is not much known about their mechanisms of inhibition, and especially about structure-function relationships. The mechanisms of their specific recognition processes is still unclear in many cases. This limits the approaches aiming to select inhibitors of desired structural features and specificity.

  4. The comparative study of primary structures of natural protein kinase inhibitors includes: • a thorough classification of this group of proteins • selecting the homologous families • describing of each selected family with respect to their mutational variability, structural properties and select regions that are important for their specificity. Our study started by selecting homologous inhibitor sequences. Multiple alignment was carried out and consensus sequences were constructed with the aid of the programs GEISHA (written by Adam Górecki) and Consensus Constructor (both elaborated at ICM).

  5. Multiple alignment of the „cAMP inhibitor family”

  6. Multiple alignment of the Cip inhibitor family

  7. Multiple alignment of the Ink4 inhibitor family

  8. Multiple alignment of the KCIP-1 inhibitor family (part 1/3)

  9. Multiple alignment of the KCIP-1 inhibitor family (part 2/3)

  10. Multiple alignment of the KCIP-1 inhibitor family (part 3/3)

  11. Multiple alignment of the HIT family

  12. The families of protein kinase inhibitors • KCIP-1 - inhibit Ca dependent kinases • Ink4 – inhibit cyclin dependent kinases • Cip/Kip – inhibit cyclin dependent kinases • cAMP – inhibit cAMP dependent kinases • The HIT family ??? - supposed to inhibit protein kinase C

  13. Consensus sequences KCIP-1 Cip/Kip Ink4

  14. Homology studies • Identity: • KCIP – 1 -> 45 - 82% • Ink4 -> 37 – 50% • Cip/Kip -> 33 – 40% (without the proline rich region) • Similarity (genetic relationships): • KCIP-1 -> 84 - 90% • Ink4 -> 55 - 60% • Cip/Kip -> 50 - 62% • The most conservative regions: • KCIP-1 -> 14.3.3 protein motif: RNLLSVAY(positions: 44-51), YKDSTLIMQLLRDNLTLWTS (positions:211-238) • Ink4 -> Ankyrin motifs – a quadruple repeated motif (positions50-67,81-101,117-134,149-169) • Cip/Kip -> A domainreactingwiththe N-teminal site of the Cdk kinase (31-40,64-68), the NLS motif (255-265,285,289).

  15. Occurrence of six-codon amino acids in KCIP-1 family

  16. Occurrence of six-codon amino acids in Ink4 family

  17. Occurrence of six-codon amino acids in Cip/Kip family

  18. Simplified (planar) diagram of genetic relationships between amino acids In planar diagram the encoding role of the third codon position is ignored. Only first two codon positions are taken into account.

  19. Simplified (planar) diagram of genetic relationships between amino acids The simplified planar diagram emphasizes the special encoding character of six-codon amino acids – Leu, Arg and Ser. The six-codon amino acids may play the role the of „mutational passages” that are not liable to the selection restrictions. These amino acids may influence on the variability range increase. In fact the six-codon amino acids occur unusually frequent at very variable positions. This concerns especially serine, and to lesser extent – arginine. Leucine does not show the correlation between the frequency of occurrence and variability range.

  20. Frequency of six-codon amino acids as a function of position variability in randomly selected proteins of different origin and nature The results for 2686 residues at 606 corresponding positions

  21. Studies on phylogenetic relationshipsProgram SSSS2(Ela Gajewska and Jacek Leluk) • Freely accessible Java application • Contact with the authors • egajewska@grid.icm.edu.pl, lulu@icm.edu.pl • Phylogenetic trees generally reveal correlation with observed similarity

  22. Program SSSS2 The basic criteria used for analysis Contribution of identities (%) significant unsignificant Length of the sequence unsignificant significant • Distribution of identical positions unsignificant significant

  23. Pairwise similarity estimationby program SSSS2(Sequence Similarity Significance Statement v. 2)

  24. Pairwise similarity estimation

  25. Phylograms Cip inhibitor family KCIP inhibitor family

  26. Phylograms Ink4 inhibitor family cAMP inhibitor family

  27. Phylograms HIT inhibitor (?) family

  28. cAMP (PKA) inhibitor family (PKI5-24) Cip inhibitor family Ink4 inhibitor family HIT family KCIP inhibitor family Tertiary structures and correlated mutations within the inhibitor families

  29. Program Corm(written by Adam Górecki)http://tarawa.icm.edu.pl/agorecki/corm Location and characterization of correlated mutations occuring in proteins

  30. Correlated mutations within the Cip/Kip inhibitor family

  31. Correlated mutations within the Ink4 inhibitor family

  32. Correlated mutations within the KCIP-1 inhibitor family

  33. The results of this comparative analysis can be used in the process of the rational drug design against many pathophysiological states caused by wrong functioning of kinases or their inhibitors. This work was supported by European Centre of Excellence for Multi-scale Biomolecular Modelling, Bioinformatics and Applications (project QLRI-CT-2002-90383) and by Interdisciplinary Centre for Mathematical and Computational Modelling, Warsaw University.

  34. Bogdan Lesyng Thank you for your attention ! AgataMeglicz currently at: Leiden University Medical CenterThe Netherlands JacekLeluk

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