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Chemical Shift Restraints Tools and Methods Andrea Cavalli Overview Overview • Methods Overview • Methods • Details Overview • Methods • Details • Results/Discussion Methods Methods Cheshire base solid-state Methods Cheshire base solid-state CamShift new predictor Monte Carlo/Molecular Dynamics Methods Cheshire base solid-state CamShift new predictor Monte Carlo/Molecular Dynamics CamDock protein-protein docking About CHESHIRE: CHEmical SHifts REstraints About CHESHIRE: CHEmical SHifts REstraints 3D structure determination from NMR chemical shifts. About CHESHIRE: CHEmical SHifts REstraints 3D structure determination from NMR chemical shifts. • Chemical shifts are “easy” to measure About CHESHIRE: CHEmical SHifts REstraints 3D structure determination from NMR chemical shifts. • • Chemical shifts are “easy” to measure Can be measured with great accuracy About CHESHIRE: CHEmical SHifts REstraints 3D structure determination from NMR chemical shifts. • • • Chemical shifts are “easy” to measure Can be measured with great accuracy Contain a lot of structural informations (CSI, TALOS,...) About CHESHIRE: CHEmical SHifts REstraints 3D structure determination from NMR chemical shifts. • • • • Chemical shifts are “easy” to measure Can be measured with great accuracy Contain a lot of structural informations (CSI, TALOS,...) In some cases they are the “only” available data About CHESHIRE: CHEmical SHifts REstraints 3D structure determination from NMR chemical shifts. • • • • Chemical shifts are “easy” to measure Can be measured with great accuracy Contain a lot of structural informations (CSI, TALOS,...) In some cases they are the “only” available data but ... NOE-NMR vs CHESHIRE NOE-NMR vs CHESHIRE • NOEs have a direct structural interpretation as distances NOE-NMR vs CHESHIRE • • NOEs have a direct structural interpretation as distances Chemical shifts values are indirectly related to geometry (SHIFTX, CamShift) NOE-NMR vs CHESHIRE • • • NOEs have a direct structural interpretation as distances Chemical shifts values are indirectly related to geometry (SHIFTX, CamShift) NOEs have long-range information NOE-NMR vs CHESHIRE • • • • NOEs have a direct structural interpretation as distances Chemical shifts values are indirectly related to geometry (SHIFTX, CamShift) NOEs have long-range information Chemical shifts are local NOE-NMR vs CHESHIRE • • • • • NOEs have a direct structural interpretation as distances Chemical shifts values are indirectly related to geometry (SHIFTX, CamShift) NOEs have long-range information Chemical shifts are local NOEs are redundant NOE-NMR vs CHESHIRE • • • • • • NOEs have a direct structural interpretation as distances Chemical shifts values are indirectly related to geometry (SHIFTX, CamShift) NOEs have long-range information Chemical shifts are local NOEs are redundant There is only one chemical shift per atom NOE-NMR vs CHESHIRE • • • • • • • NOEs have a direct structural interpretation as distances Chemical shifts values are indirectly related to geometry (SHIFTX, CamShift) NOEs have long-range information Chemical shifts are local NOEs are redundant There is only one chemical shift per atom Clear quality control (number of assigned NOEs, NOEs violation) NOE-NMR vs CHESHIRE • • • • • • • • NOEs have a direct structural interpretation as distances Chemical shifts values are indirectly related to geometry (SHIFTX, CamShift) NOEs have long-range information Chemical shifts are local NOEs are redundant There is only one chemical shift per atom Clear quality control (number of assigned NOEs, NOEs violation) Weak Q-factor Idea Idea Force field -920 Free Energy -940 -960 -980 -1000 0 2 4 6 Cα-RMSD 8 10 Idea Chemical shifts -920 -420 -940 -440 Chemical Shift Free Energy Force field -960 -460 -980 -480 -1000 -500 0 2 4 6 Cα-RMSD 8 10 0 2 4 6 Cα-RMSD 8 10 Idea Combined score Chemical shifts -420 -420 -940 -440 -440 -960 Chemical Shift -920 Chemical Shift Free Energy Force field -460 -980 -460 -480 -1000 -480 -500 0 2 4 6 Cα-RMSD 8 10 -500 0 2 4 6 Cα-RMSD 8 10 0 2 4 6 Cα-RMSD 8 10 Idea Combined score Chemical shifts -420 -420 -940 -440 -440 -960 Chemical Shift -920 Chemical Shift Free Energy Force field -460 -980 -460 -480 -1000 -480 -500 0 2 4 6 Cα-RMSD 8 10 -500 0 2 4 6 Cα-RMSD 8 10 0 2 4 6 8 10 Cα-RMSD Structures have to be very close to the native one in order to “feel” chemical shifts score. CHESHIRE Determination or prediction? Experiment Theory CHESHIRE Determination or prediction? NMR X-ray Experiment Theory CHESHIRE Determination or prediction? NMR X-ray ab initio Experiment Theory CHESHIRE Determination or prediction? NMR X-ray Experiment Homology modeling > 50 % Homology modeling < 50 % ab initio Theory CHESHIRE Determination or prediction? NMR X-ray Experiment Homology modeling > 50 % CHESHIRE Homology modeling < 50 % ab initio Theory CHESHIRE Determination or prediction? Jigsaw puzzle Steps Chemical shifts Prediction of local geometry Database Fragment selection Fragment assembly Refinement SCOP domains SHIFX Energy function Local structure 1 Prediction of local geometry Chemical shifts Database Secondary structure prediction P3(S1, S2, S3|AA1, AA2, AA3), Pcs(S|Hα, N,Cα,Cβ, AA) N N i=1 i=1 E = − ∑ log P3(i) − Kcs ∑ log Pcs(i) Secondary structure propensity NS P(S|A) = N Local structure 2 Chemical shifts Prediction of local geometry Database Torsion angle prediction S(Φi, Ψi|A,CS) = Sym(B, A) + Sym(∆CSA, ∆CSB) + Sym(SA, SB) Three best scoring cluster centers are taken as prediction. Fragment selection Chemical shifts Fragment selection Database Fragments of length 3 and 9 aa N N i=1 i=1 E = ∑ Ecs(Ai, ∆CSA, Bi, ∆CSB) + Ktor ∑ Etar (Φi, Ψi, B) Performance Protein 3Pred TOPOS Ubiquitin 0.75 0.93 FF domain 0.90 0.86 Calbindin 0.85 0.95 HPR 0.87 0.86 Fold Fragment assembly Energy function Fold Fragment assembly Energy function Refinement 1 Chemical shifts Refinement Energy function Energy function Ere f = E f f / log(1 −Ccs) where Ccs = ∑ χ∈{Hα,N,Cα,Cβ} Kχ(1 −Cχ), Cχcorrelation of CS type χ Refinement 2 Refinement 2 • Structure with large Rg are discarded Refinement 2 • Structure with large Rg are discarded • Side-chains are added Refinement 2 • Structure with large Rg are discarded • Side-chains are added • Initial ranking Refinement 2 Takes one structure at random from the best-list. New structure generated by simulated annealing. • Structure with large Rg are discarded • Side-chains are added • Initial ranking Keeps a list of the 100 best structures Results Results The largest The largest 2GW6, 123 aa 1.72 Å backbone RMSD The smallest The smallest 1PV0, 46 aa 1.37 Å backbone RMSD Solid-State NMR of protein G Solid-State NMR of protein G Solid-State NMR of protein G Structure RMSD N (5.5 Å) Q (RDC) 1P7F 0.40 0 0.03 3GB1 0.59 0 0.16 2GB1 0.97 1 0.37 2JU6 1.86 5 0.48 2K0P 1.04 3 0.40 Failures Failures 0 S = 48.09-4.2458*NA, R=-0.9794 Score -200 -400 -600 -800 60 80 100 120 140 Number of Amino Acids 160 180 200 Failures 1ZGG -400 0 S = 48.09-4.2458*NA, R=-0.9794 -450 Refined Structures Refined Native Structure Expected Score -200 Score -400 -550 -450 -600 Score Score -500 -600 -650 -500 -550 0 -800 60 10 20 30 C!-RMSD 80 100 120 140 Number of Amino Acids 160 180 200 -700 0 5 10 15 20 C!-RMSD 25 30 35 40 Failures 1ZGG -400 0 S = 48.09-4.2458*NA, R=-0.9794 -450 Refined Structures Refined Native Structure Expected Score -200 Score -400 -550 -450 -600 Score Score -500 -600 -650 -500 -550 0 -800 60 10 20 30 C!-RMSD 80 100 120 140 Number of Amino Acids 160 180 200 -700 0 5 10 15 20 C!-RMSD 25 30 35 Why? Usually because the assembly stage does not generate low RMSD models. 40 CamShift CamShift • Chemical shifts are predicted using distances to neighboring atoms R N C H H C O R N C H H C O CamShift • Chemical shifts are predicted using distances to neighboring atoms • Accurate as ShiftX or Sparta and orders of magnitude faster R N C H H C O R N C H H C O CamShift • Chemical shifts are predicted using distances to neighboring atoms • Accurate as ShiftX or Sparta and orders of magnitude faster R N C H H O R • CamShift with physical force field and ReX molecular dynamics C N C H H C O CamShift • Chemical shifts are predicted using distances to neighboring atoms • Accurate as ShiftX or Sparta and orders of magnitude faster R N C H H • ~ 1 Å from unfolded for small proteins (1uzc, 1ubq, ..) O R • CamShift with physical force field and ReX molecular dynamics C N C H H C O CamShift-MD 2jvw: 61 residues Lowest Energy Structure 1.41Å RMSD 2jva: 108 residues Lowest Energy Structure 1.98 Å RMSD CamShift Full No Long range Sparta HN 0.53 0.61 0.57 HA 0.29 0.37 0.27 N 3.10 3.18 2.52 CA 1.18 1.20 0.98 CB 1.43 1.48 1.07 CO 1.16 1.27 1.08 Conclusions Conclusions •Protein structure determination with chemical shifts is possible... Conclusions •Protein structure determination with chemical shifts is possible... •but difficult... very difficult... Conclusions •Protein structure determination with chemical shifts is possible... •but difficult... very difficult... •CHESHIRE works (at the moment) for proteins up to ~100 aa. Conclusions •Protein structure determination with chemical shifts is possible... •but difficult... very difficult... •CHESHIRE works (at the moment) for proteins up to ~100 aa. •results are stable ~1.0-2.0 Å Cα RMSD. Conclusions •Protein structure determination with chemical shifts is possible... •but difficult... very difficult... •CHESHIRE works (at the moment) for proteins up to ~100 aa. •results are stable ~1.0-2.0 Å Cα RMSD. •self-consistent criterion to (maybe) detect failures of the method. Conclusions •Protein structure determination with chemical shifts is possible... •but difficult... very difficult... •CHESHIRE works (at the moment) for proteins up to ~100 aa. •results are stable ~1.0-2.0 Å Cα RMSD. •self-consistent criterion to (maybe) detect failures of the method. •can be used for complexes and with solid-state CS. Conclusions •Protein structure determination with chemical shifts is possible... •but difficult... very difficult... •CHESHIRE works (at the moment) for proteins up to ~100 aa. •results are stable ~1.0-2.0 Å Cα RMSD. •self-consistent criterion to (maybe) detect failures of the method. •can be used for complexes and with solid-state CS. • http://www.open-almost.org Acknowledgments Michele Vendruscolo Chris Dobson Xavier Salvatella Kai Kohlhof Paul Robustelli Danny Hsu Rinaldo Wander Montalvao