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Rob Russell Cell Networks University of Heidelberg

Interactions and Modules: the how and why of molecular interactions. Rob Russell Cell Networks University of Heidelberg. Proteins are modular.

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Rob Russell Cell Networks University of Heidelberg

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  1. Interactions and Modules: the how and why of molecular interactions Rob Russell Cell Networks University of Heidelberg

  2. Proteins are modular Since the early 1970s it has been observed that protein structures are divided into discrete elements or domains that appear to fold, function and evolve independently.

  3. “Low sequence complexity” (Linker regions? Flexible? Junk? Signal peptide (secreted or membrane attached) Transmembrane segment (crosses the membrane) Tyrosine kinase (phosphorylates Tyr) Immunoglobulin domains (bind ligands?) Domains on a sequence SMART domain ‘bubblegram’ for human fibroblast growth factor (FGF) receptor 1 (type P11362 into web site: smart.embl.de)

  4. Finding domains in a sequence

  5. A library of protein domains for signaling Pawson & Nash, Science, 2003

  6. Domains assemble to form higher-order structures Pawson & Nash, Science, 2003

  7. How proteins interact

  8. homology homology Modelling interactions by homology Protein A Protein C X (e.g.) Two-hybrid interaction Protein D Protein B Can we use the C/D structure to predict an interaction between A & B?

  9. Can structure help solve the specificity problem? Family A Family B ?

  10. InterPreTS Interaction Prediction through Tertiary Structure Structure Interface pair potentials Phe Asp + + Phe Arg Asp - - Score Phe Significance (Do RHO4 & YFE7 interact?) Side-chain to side-chain Side-chain to main-chain Alignments 1tx4A PIVLRETVAYLQA-------HALTTE ... YFE7_YEAST PLIISSIFSYMDKIYPDLPNDKVR-T ... 1tx4B KLVIVGDGACGKTCLLIVNSKDQF-- ... RHO4_YEAST KIVVVGDGAVGKTCLLISYVQGTFPT ... Aloy & Russell, PNAS, 99, 5896, 2002. Aloy & Russell, Bioinformatics.19, 161, 2003.

  11. How proteins interact

  12. Domain peptide interactions Recognition of ligands or targeting signals Post-translational modifications

  13. “instance” “motif” “perpetrator” “victim” Linear motifs Peptides interacting with a common domain often show a common pattern or motif usually 3-8 aas. 3BP1_MOUSE/528-537 APTMPPPLPP PTN8_MOUSE/612-629 IPPPLPERTP SOS1_HUMAN/1149-1157 VPPPVPPRRR NCF1_HUMAN/359-390 SKPQPAVPPRPSA PEXE_YEAST/85-94 MPPTLPHRDW SH3-interacting motif PxxP Puntervol et al, NAR, 2003; www.elm.org (Eukaryotic Linear Motif DB)

  14. Linear motifs versus domains Domains: large globular segments of the proteome that fold into discrete structures and belong in sequence families. Linear motifs: small, non-globular segments that do not adopt a regular structure, and aren’t homologous to each other in the way domains are. Motifs lie in the disordered part of the proteome.

  15. Intrinsically unstructured or disordered proteins or protein fragments

  16. Disorder predictors (IUPred, RONN, DisORPred, etc)

  17. Linear motif mediated interactions are everywhere • Include motifs for: • Targeting – e.g. KDEL • Modifications – e.g. phosphorylation • Signaling – e.g. SH3 • About 200 are currently known, likely many more still to be discovered Neduva & Russell, Curr. Opin. Biotech, 2006

  18. Finding peptides or linear motifs in a sequence See: elm.eu.org Finding these modules much harder than for domains. Domains are long (>30 AA) and belong to sequence families that help detect new family members Linear motifs are typically < 8 amino acids long and have simple patterns e.g. PxxP will occur in most sequences randomly and these are not SH3 domains

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