1 / 63

Structure Alignment

Structure Alignment. Structure Alignment. +. Content. Motivation Some basics Double Dynamic Programming. PART I: Motivation. Motivation: Conformational changes. Upon ligand binding structures may change Structural alignment can highlight the changes. GEFs. GAPs.

brady-adkins
Download Presentation

Structure Alignment

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Structure Alignment

  2. Structure Alignment +

  3. Content • Motivation • Some basics • Double Dynamic Programming

  4. PART I: Motivation

  5. Motivation: Conformational changes • Upon ligand binding structures may change • Structural alignment can highlight the changes

  6. GEFs GAPs Conformational changes: Small GTPases • Small GTPases act as molecular switches to control and regulate important functions and pathways within in cell • Activated by guanine nucleotide exchange factors (GEF) • Inactivated by GTPase activating proteins (GAP)

  7. G proteins: Conformational change in GTP and GDP bound state

  8. Open and closed conformation of cytrate synthase (1cts,5cts) • Open: oxalacetate, Closed: oxalacetate and co-enzyme A • Loop between two helices moves by 6A and rotates by 28º, some atoms move by 10A

  9. Hinge motion in Lactoferrin (1lfh, 1lfg) • Lactoferrin is an iron-binding protein found in secretions such as milk or tears • Rotation of 54º upon iron-binding

  10. Hinge motion in Lactoferrin (1lfh, 1lfg) • Lactoferrin is an iron-binding protein found in secretions such as milk or tears • Rotation of 54º upon iron-binding

  11. Motivation: (Distant) Relatives • Sequence similarity may be low, but structural similarity can still be high Picture from www.jenner.ac.uk/YBF/DanielleTalbot.ppt

  12. Distant relatives • Globins occur widely • Primary function: binding oxygen • Assembly of helices surrounding haem group

  13. Relatives Sperm whale myoglobin (2lh7) and Lupin leghaemoglobin (1mbd)

  14. Distant Relatives

  15. Relatives • Actinidin (2act) and Papain (9pap) • Sequence identity 49%, rmsd 0.77A • Same family: Papain-like

  16. Relatives • Plastocyanin (5pcy) and azurin (2aza) • Core of structure is conserved

  17. Relatives • Structure classifications like CATH and FSSP use structural alignments to identify superfamilies.

  18. Motivation: Convergent Evolution

  19. Sequence similarity: low >1cse Subtilisin AQTVPYGIPLIKADKVQAQGFKGANVKVAVLDTGIQA SHPDLNVVGGASFVAGEAYNTDGNGHGTHVAGTVAAL DNTTGVLGVAPSVSLYAVKVLNSSGSGSYSGIVSGIE WATTNGMDVINMSLGGASGSTAMKQAVDNAYARGVVV VAAAGNSGNSGSTNTIGYPAKYDSVIAVGAVDSNSNR ASFSSVGAELEVMAPGAGVYSTYPTNTYATLNGTSMA SPHVAGAAALILSKHPNLSASQVRNRLSSTATYLGSS FYYGKGLINVEAAAQ >1acb Chymotrypsin CGVPAIQPVLSGLSRIVNGEEAVPGSWPWQVSLQDKT GFHFCGGSLINENWVVTAAHCGVTTSDVVVAGEFDQG SSSEKIQKLKIAKVFKNSKYNSLTINNDITLLKLSTA ASFSQTVSAVCLPSASDDFAAGTTCVTTGWGLTRYTN ANTPDRLQQASLPLLSNTNCKKYWGTKIKDAMICAGA SGVSSCMGDSGGPLVCKKNGAWTLVGIVSWGSSTCST STPGVYARVTALVNWVQQTLAAN

  20. Structural similarity: low 1CSE:E, 1ACB:E

  21. Convergent Evolution • c.41.1 and b.47.1 share interaction partners d.40.1 CI-2 family of serine protease inhibitors d.58.3Protease propeptides/inhibitors c.41.1 Subtilisin-like b.47.1Trypsin-likeserine proteases d.84.1Subtilisin inhibitor c.56.5 Zn-dependentexopeptidase g.15.1 Ovomucoid/PCI-1 like inhibitor

  22. Convergent Evolution 1oyv Ovomucoid/PCI-1 like inhibitor, g.15.1top Subtilisin like c.41.1bottom 1OYV 4sgb Ovomucoid/PCI-1 like inhibitor, g.15.1, top Trypsin-like serine proteases, b.47.1.2, bottom

  23. Convergent Evolution • Aligned structures 1cse CI-2 family of serine proteases inhitors, d.40.1 top Subtilisin like c.41.1bottom 1acb CI-2 family of serine proteases inhitors, d.40.1 top Trypsin-like serine proteases, b.47.1.2, bottom

  24. Catalytic Triad >1cse Subtilisin AQTVPYGIPLIKADKVQAQGFKGANVKVAVLDTGIQA SHPDLNVVGGASFVAGEAYNTDGNGHGTHVAGTVAAL DNTTGVLGVAPSVSLYAVKVLNSSGSGSYSGIVSGIE WATTNGMDVINMSLGGASGSTAMKQAVDNAYARGVVV VAAAGNSGNSGSTNTIGYPAKYDSVIAVGAVDSNSNR ASFSSVGAELEVMAPGAGVYSTYPTNTYATLNGTSMA SPHVAGAAALILSKHPNLSASQVRNRLSSTATYLGSS FYYGKGLINVEAAAQ >1acb Chymotrypsin CGVPAIQPVLSGLSRIVNGEEAVPGSWPWQVSLQDKT GFHFCGGSLINENWVVTAAHCGVTTSDVVVAGEFDQG SSSEKIQKLKIAKVFKNSKYNSLTINNDITLLKLSTA ASFSQTVSAVCLPSASDDFAAGTTCVTTGWGLTRYTN ANTPDRLQQASLPLLSNTNCKKYWGTKIKDAMICAGA SGVSSCMGDSGGPLVCKKNGAWTLVGIVSWGSSTCST STPGVYARVTALVNWVQQTLAAN

  25. B C C Convergent evolution A and B are native, C is viral A B C A A’ Henschel et al., Bioinformatics 2006

  26. HIV Nef mimics kinase in binding SH3 • Comparison of Nef-SH3 and intra-chain interaction of catalytic domain and SH3 of Hck, PDBs: 1efn and 2hck • No evidence of homology between Nef and Kinase Kinase (Src Haematopoeitic cell kinase, Catalytic domain) HIV1-Nef Fyn-SH3/Hck-SH3 Henschel et al., Bioinformatics 2006

  27. Automatic calculation of equivalent residues Nef Kinase • Apart from PxxP motif matches: Arg71/Lys249, Phe90/His289 • Residues with equivalents are strictly conserved in HIV-Nef Henschel et al., Bioinformatics 2006

  28. Mimickry of baculovirus p35 and human inhibitor of apoptosis • Caspase (red) • P35 (yellow) • IAP (green) • Upon infection cell starts apoptosis programme, p35 tries to stop it Henschel et al., Bioinformatics 2006

  29. Mimickry of Capsids and Cyclophilin • HIV capsid protein (yellow) • Cyclophilin (red, green) • Cyclophilin A restricts HIV infectivity • Upon mutation of cyclophilin or inhibition with cyclophorin, infectivity goes up >100(Towers, Nature Medicine, 2003) Henschel et al., Bioinformatics 2006

  30. PART II: Some basics

  31. What do we need? • To main operations to align structures: • Translation • Rotation • How to evaluate a structural alignment? • Root mean square deviation, rmsd

  32. Basic Operations: Translation

  33. Basic Operations: Translation

  34. Basic Operations: Translation

  35. Basic Operations: Rotation

  36. a b Root Mean Square Deviation • What is the distance between two points a with coordinates xa and ya and b with coordinates xb and yb? • Euclidean distance:d(a,b) = √(xa--xb )2 + (ya -yb )2 • And in 3D?

  37. Root Mean Square Deviation • In a structure alignment the score measures how far the aligned atoms are from each other on average • Given the distances di between n aligned atoms, the root mean square deviation is defined as rmsd = √ 1/n ∑ di2

  38. Quality of Alignment and Example • Unit of RMSD => e.g. Ångstroms • Identical structures => RMSD = “0” • Similar structures => RMSD is small (1 – 3 Å) • Distant structures => RMSD > 3 Å

  39. PART III: Dynamic Programming

  40. A very simple algorithm… • …to align identical structures with conformational changes • Generate a sequence alignment (not necessary if both sequences are really 100% identical) • Compute center of mass for both structures • Move both structures so that the centers of mass are the origin • Compute the angle between all aligned residues • Rotate structure by median of all angles

  41. A very simple algorithm… • …to align identical structures with conformational changes • Generate a sequence alignment (not necessary if both sequences are really 100% identical) • Compute center of mass for both structures • Move both structures so that the centers of mass are the origin • Compute the angle between all aligned residues • Rotate structure by median of all angles Question: How? Assume n atoms (x1,y1,z1) to (xn,yn,zn) (for one structure)

  42. A very simple algorithm… Question: How?Assume n atoms(x1,y1,z1) to (xn,yn,zn:) Center of mass (xCoM,yCoM,zCoM) = (1/n ni=1 xi , 1/n ni=1 yi 1/n ni=1 zi ) • …to align identical structures with conformational changes • Generate a sequence alignment (not necessary if both sequences are really 100% identical) • Compute center of mass for both structures • Move both structures so that the centers of mass are the origin • Compute the angle between all aligned residues • Rotate structure by median of all angles Question: How?

  43. A very simple algorithm… Question: How?Assume n atoms (x1,y1,z1) to (xn,yn,zn:) Center of mass (xCoM,yCoM,zCoM) = (1/n ni=1 xi , 1/n ni=1 yi 1/n ni=1 zi • …to align identical structures with conformational changes • Generate a sequence alignment (not necessary if both sequences are really 100% identical) • Compute center of mass for both structures • Move both structures so that the centers of mass are the origin • Compute the angle between all aligned residues • Rotate structure by median of all angles For all i: do xi:= xi-xCoM, yi:= yi-yCoM, yi:= yi-yCoM,

  44. A very simple algorithm… • …to align identical structures with conformational changes • Generate a sequence alignment (not necessary if both sequences are really 100% identical) • Compute center of mass for both structures • Move both structures so that the centers of mass are the origin • Compute the angle between all aligned residues • Rotate structure by median of all angles Why median and not mean?

  45. A refinement: Alternating alignment and superposition • 1. P = initial alignment (e.g. based on sequence alignment) • 2. Superpose structures A and B based on P • 3. Generate distance-based scoring matrix R from superposition • 4. Use dynamic programming to align A and B using scoring matrix R • 5. P‘ = new alignment derived from dynamic programming step • 6. If P‘ is different from P then go to step 2 again

  46. Distance-based scoring matrix • Let d(Ai, Bj) be the Euclidean distance between Aiand Bj • Let t be the upper distance limit for residues to be rewarded • The scoring matrix R is defined as follows:R(Ai, Bj) = 1 / d(Ai, Bj) - 1 / t if R(Ai, Bj) > max. score then R(Ai, Bj) = max. score • The gap/mismatch penalty is set to 0

  47. Distance-based scoring matrix • Let d(Ai, Bj) be the Euclidean distance between Aiand Bj • Let t be the upper distance limit for residues to be rewarded • The scoring matrix R is defined as follows:R(Ai, Bj) = 1 / d(Ai, Bj) - 1 / t if R(Ai, Bj) > max. score then R(Ai, Bj) = max. score • The gap/mismatch penalty is set to 0 What size doesPAM have? What size doesR have?

  48. Example • R(Ai, Bj) = 1/d(Ai, Bj) - 1/t for t=1/10 and max. score =2

More Related