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Development of automatic score to simulate manual assessment for CASP FM targets Qian Cong from Grishin lab.

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Presentation on theme: "Development of automatic score to simulate manual assessment for CASP FM targets Qian Cong from Grishin lab."— Presentation transcript:

1 Development of automatic score to simulate manual assessment for CASP FM targets Qian Cong from Grishin lab

2 Tesla: curiosity driven Me: laziness driven Qian Cong from Grishin lab Development of automatic score to simulate manual assessment for CASP FM targets

3 Tesla: curiosity driven Me: laziness driven Qian Cong from Grishin lab 36 targets (whole chain + domain) around 18000 models Development of automatic score to simulate manual assessment for CASP FM targets

4 Inspiration from expert’s manual analysis Expert: global features + local features Local feature: secondary structure assignment of each residue Global feature: global positions of each Secondary Structure Elements (SSEs) packing and interactions between SSEs

5 Inspiration from expert’s manual analysis Expert: global features + local features Local feature: secondary structure assignment of each residue Global feature: global positions of each Secondary Structure Elements (SSEs) packing and interactions between SSEs Develop a score to “mimic” expert inspection: check each secondary structure element, and inspect their packing and interactions.

6 Overview of features get considered Measurements on single secondary structure element or residue The global position of each SSE The length of each SSE The residue DSSP assignment Measurements on secondary structure pairs or residue pairs The angle between SSE pair The interactions between SSE pair The residue contact score (used for CASP8)

7 Overview of features get considered Measurements on single secondary structure element or residue The global position of each SSE The length of each SSE The residue DSSP assignment Measurements on secondary structure pairs or residue pairs The angle between SSE pair The interactions between SSE pair The residue contact score (used for CASP8) Local features as modulator

8 Step 1.1: Get SSE definition and vector set for target T0531

9 Step 1.1: Get SSE definition and vector set for target I.Majumdar et al. (2005) BMC Bioinformatics HELIX SER 26 PRO 32 7 SHEET GLU 14 CYS 19 6 SHEET GLU 19 CYS 24 6 SHEET GLU 39 CYS 43 5 SHEET GLY 43 SER 48 6 SHEET SER 49 CYS 57 9 Type Start End Length PALSSE T0531

10 Step 1.1: Get SSE definition and vector set for target I.Majumdar et al. (2005) BMC Bioinformatics HELIX SER 26 PRO 32 7 SHEET GLU 14 CYS 19 6 SHEET GLU 19 CYS 24 6 SHEET GLU 39 CYS 43 5 SHEET GLY 43 SER 48 6 SHEET SER 49 CYS 57 9 Type Start End Length PALSSE T0531

11 Step 1.1: Get SSE definition and vector set for target I.Majumdar et al. (2005) BMC Bioinformatics HELIX SER 26 PRO 32 7 SHEET GLU 14 CYS 19 6 SHEET GLU 19 CYS 24 6 SHEET GLU 39 CYS 43 5 SHEET GLY 43 SER 48 6 SHEET SER 49 CYS 57 9 Type Start End Length PALSSE T0531

12 Step 1.2: Get the interacting residue pairs Interactions criteria: 1. The shortest distance of central part of two SSEs 2. Below 8.5 Å T0531

13 Step 1.2: Get the interacting residue pairs 15, 46 15, 52 17, 42 20, 44 21, 42 21, 55 23, 29 32, 41 32, 54 42, 52 45, 55 Interactions criteria: 1. The shortest distance of central part of two SSEs 2. Below 8.5 Å T0531

14 Step 1.2: Get the interacting residue pairs 15, 46 15, 52 17, 42 20, 44 21, 42 21, 55 23, 29 32, 41 32, 54 42, 52 45, 55 Interactions criteria: 1. The shortest distance of central part of two SSEs 2. Below 8.5 Å T0531

15 Step 1.2: Get the interacting residue pairs 15, 46 15, 52 17, 42 20, 44 21, 42 21, 55 23, 29 32, 41 32, 54 42, 52 45, 55 Interactions criteria: 1. The shortest distance of central part of two SSEs 2. Below 8.5 Å T0531

16 Step 2: Simplify models into vectors and key points The SSE definition and interacting residue pair definition are propagated to models, and thus models are simplified as a set of vectors and point pairs too.

17 Step 2: Simplify models into vectors and key points TS490_2 TS399_4 The SSE definition and interacting residue pair definition are propagated to models, and thus models are simplified as a set of vectors and point pairs too.

18 Step 2: Simplify models into vectors and key points TS490_2 TS399_4 The SSE definition and interacting residue pair definition are propagated to models, and thus models are simplified as a set of vectors and point pairs too.

19 What should we look at? TargetA good model A “bad” model

20 Definition of global position: the distance between the geometry center of SSE and the center of the whole protein Step 3.1: compare the global position of SSE vectors

21 Definition of global position: the distance between the geometry center of SSE and the center of the whole protein Step 3.1: compare the global position of SSE vectors

22 Definition of global position: the distance between the geometry center of SSE and the center of the whole protein Step 3.1: compare the global position of SSE vectors

23 Definition of global position: the distance between the geometry center of SSE and the center of the whole protein Step 3.1: compare the global position of SSE vectors

24 Definition of global position: the distance between the geometry center of SSE and the center of the whole protein Step 3.1: compare the global position of SSE vectors

25 Assumption: wrong SS prediction and improper break of SSE will result in difference from target in vector length Step 3.2: compare the length of SSE vectors

26 Assumption: wrong SS prediction and improper break of SSE will result in difference from target in vector length Step 3.2: compare the length of SSE vectors

27 Assumption: wrong SS prediction and improper break of SSE will result in difference from target in vector length Step 3.2: compare the length of SSE vectors

28 Assumption: wrong SS prediction and improper break of SSE will result in difference from target in vector length Step 3.2: compare the length of SSE vectors Too broad a measurement for secondary structure quality measurement

29 Percent agreement of DSSP assignment reflects the detailed quality of secondary structures Step 3.3: compare DSSP assignment Target:CCCCCCCCSTTTSCEEEEEEEEECCHHHHHHCGGGTTTCEEEEEEETTTTEEEEEECCHHHHSCC Model1:CCHHHHSHHHHTTCEECCCCCSGGGCSSCSSCCCCGGGTCCEEEEETTTTEEEEESSCHHHHTCC Model2:CCCCSSSTTSSTTHHHHTTSCSSCSSCCSSCCCCCCSSCCCCEEEETTTTEEEECCCSCHHHHHC

30 Step 3.4: compare the angle between SSE vector pairs

31 Step 3.5: compare the interactions between SSE pairs Motivation: some key interactions defined the general packing of elements, they should be emphasized more

32 C-alpha contact score is added as a modulator for key SSE interaction score Step 3.6: compare all C-alpha contact score Define all alpha contact at a cut off of 8.44 Å, similar program is proved to be good measurement by CASP8 assessors Shuoyong ShiShuoyong Shi, Jimin Pei, Ruslan I. Sadreyev, Lisa N. Kinch, Indraneel Majumdar, Jing Tong, Hua Cheng, Bong-Hyun Kim, Nick V. Grishin. Analysis of CASP8 targets, predictions and assessment methods. Database: The Journal of Biological Database and Curation (2009).Nick V. GrishinDatabase: The Journal of Biological Database and Curation

33 Let’s sum up all the scores

34 superimposition independent global and local comparison manual analysis simulating score SIGLACMASS ?

35 Let’s sum up all the scores superimposition independent global and local comparison manual analysis simulating score SIGLACMASS ? Qian Cong score = QCS

36 Let’s sum up all the scores superimposition independent global and local comparison manual analysis simulating score SIGLACMASS ? Qian Cong score = QCS = Quality control score

37 Global view: Correlations

38 Optimization on weight??? Correlation improve 2%

39 Global view: Correlations

40 Most cases, the top models selected by GDT generally agree with top models selected by QCS and manual assessment Go to individual: Top picks

41 Most cases, the top models selected by GDT generally agree with top models selected by QCS and manual assessment There are cases where QCS reveals features we like Go to individual: Top picks

42 324_5 382_5 Example where QCS reveals better model TS324_5 QCS: 67.4 GDT: 39.4 TS382_5 QCS: 80.7 GDT: 30.9 Target 561

43 324_5 382_5 T0561 QCS reveals good global topology TS324_5 QCS: 67.4 GDT: 39.4

44 324_5 382_5 T0561 QCS reveals good global topology TS324_5 QCS: 67.4 GDT: 39.4

45 324_5 382_5 T0561 QCS reveals good global topology TS324_5 QCS: 67.4 GDT: 39.4

46 324_5 QCS reveals good global topology T0561 TS382_5 QCS: 80.7 GDT: 30.9

47 QCS reveals model with good interactions

48 Get all 3 key SSE interactions

49 Get only 1 key SSE interactions QCS reveals model with good interactions Get all 3 key SSE interactions

50 Being lazy cannot be a final solution To assess CASP need a lot of diligent, efficient and smart and careful analysis in a large scale

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