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Hydrogen bonds in Rosetta: a phenomonological study Jack Snoeyink Dept. of Computer Science UNC Chapel Hill.

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Presentation on theme: "Hydrogen bonds in Rosetta: a phenomonological study Jack Snoeyink Dept. of Computer Science UNC Chapel Hill."— Presentation transcript:

1 Hydrogen bonds in Rosetta: a phenomonological study Jack Snoeyink Dept. of Computer Science UNC Chapel Hill

2 Key points  My biases  Hydrogen bonds in Rosetta Structure-derived potential of KMB03 Existing definition/scoring Comparing natives & decoys Proposed recategorization  Bad smells in code  Open questions

3 Phenomenology defined:  Movement originated by E. Husserl in 1905  A philosophy based on the premise that reality consists of objects and events as they are perceived or understood in human consciousness and not of anything independent of human consciousness.

4 Phenomenology defined:  Movement originated by E. Husserl in 1905  A philosophy based on the premise that reality consists of objects and events as they are perceived or understood in human consciousness and not of anything independent of human consciousness.

5 Structure-derived potential KMB03  Energy from observed structures: distance dependence for helix

6 Structure-derived potential KMB03  Energy from observed structures: statistically derived energies…

7 Structure-derived potential KMB03  Energy from observed structures: as implemented in Rosetta…

8 Three tasks in Hbond scoring  Identify pairs of atoms that Hbond  Classify Hbond types  Evaluate energies for Hbonds Rosetta++ mixes these tasks together…

9 Three tasks in Hbond scoring As described in KMB03  Identify pairs of atoms that Hbond Params: AH distance, ,   Classify Hbond types BB: helix, strand, other; AH distance SS,BS,SB: acceptor hybridization; AH dist  Evaluate energies for Hbonds Sum three potentials on AH distance, , ,  Amino acid weights Residue neighbors for donor/acceptor

10 Three tasks in Hbond scoring As implemented in Rosetta++  Identify pairs of atoms that Hbond Params: AH distance, ,   Classify Hbond types BB: separation short |sep|≤4; long range SS,BS,SB: acceptor hybridization; AH dist  Evaluate energies for Hbonds Sum three potentials on AH distance, ,  Amino acid weights OR Residue neighbors for donor/acceptor

11 SS bonds: native & decoy sp 2 ED QN bb sp 3 TS Y ring H dist 

12 SS bonds: native & decoy sp 2 ED QN bb sp 3 TS Y ring H dist   Natives: Dunbrack set of 3157 structures some pdb errors  Decoys: Best 20 for each of Rhiju’s ab initio runs on 62 structures small proteins few parallel beta strands  Rosetta places Hs & determines Hbonds  Filter energies < -0.1  Visualization: Tufte’s small multiples  Normalization Express counts as fraction of all Hbonds to support comparison of colors in each plot Plot with common x axis; scale y to max height

13 Energy distribution of bonds involving a sidechain atom before/after filtering

14 Number (and percentage) of bonds under the existing classification CountsPercentage NativeDecoysNativeDecoys BB Helix (+/-4) 185,204 38, Turn (+/-3) 79,110 8, Other 150,945 19, S sp2 ED QB bb 132,522 6, sp3 TS Y 23,641 2, ring H 2, TOTALS 573,747 75,

15 Observations  Rosetta does well at optimizing what it is told.  Decoy distributions are more sharply peaked than natives.  Relax preserves more non-helix bonds than ab initio, but produces same shapes for param distrib’ns. To test changes, it suffices to run relax.

16 SS bonds: native & decoy sp 2 ED QN bb sp 3 TS Y ring H dist 

17 SS bonds: native & decoy sp 2 ED QN bb sp 3 TS Y ring H dist 

18 SS,BS,SB bonds: native & decoy sp 2 ED QN bb sp 3 TS Y ring H dist 

19 AH Distance NB: donor effects small # omit C bimodal H R & QNacc

20 Theta A-H-D angle NB: small #s width R N E &N H

21 Psi AHD angle NB: R E & EDacc

22 Chi A 2 -A torsion NB: Polar & charged prefs

23 __ H-D torsion NB: Polar & charged prefs

24 Three tasks in Hbond scoring Proposed changes  Identify pairs of atoms that Hbond Params: AH distance, ,   Classify Hbond types BB: finer separation (Beta?) SS,BS,SB: finer don/acc chemical types  Evaluate energies for Hbonds: options 1. Sum three potentials on AH distance, ,  2. Potential on three variables AH distance, ,  3. Add neighbors 4. Add a torsion as 4 th or 5 th variable Weights for tuning different terms

25 Backbone bonds AH distance

26 Backbone bonds theta

27 Parallel vs Anti-parallel beta The standard figures are misleading; parallel and anti-parallel form similar distance, ,  distributions.

28 Backbone bonds psi

29 Backbone bonds chi torsion

30 Backbone bonds AH-DD 2 torsion

31 Refactoring Hbonds  Recategorizing should eliminate long-range & short-range Hbonds; which are used outside of hbonds.cc – they shouldn’t need to be.  Duplicated code in minimizers needs to be brought back into hbonds.cc

32 Refactoring  In code, a function should do one thing well.  When a function you work with is doing too many things, split it.  Duplicating code indicates that something is designed wrong.  Avoid magic numbers.


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