Overview Information-driven modeling of biomolecular complexes ! Introduction ! Information sources ! General aspects of docking ! Information-driven docking with HADDOCK ! Incorporating biophysical data into docking ! Multiple choice topics... ! Challenges ! Conclusions & perspectives Prof. Alexandre M.J.J. Bonvin Bijvoet Center for Biomolecular Research Faculty of Science, Utrecht University the Netherlands a.m.j.j.bonvin@uu.nl The network of life… Biomolecular interactions Protein-protein interaction + Cellular interactome !"#$%"$&'()*&+,),&-)(('.& Applications Our current knowledge [ Faculty of Science Chemistry]
What can we learn from 3D Study of biomolecular complexes structures (models) of complexes? • Classical NMR & X-ray crystallography approaches can be time-consuming • Models provide structural insight into function and mechanism of • Problems arise with “bad behaving”, weak and/or action transient complexes! • Models can drive and guide • Complementary computational methods are experimental studies needed! • Models can help understand and “docking” prediction of the structure of a complex based on the structures of its constituents rationalize the effect of disease- related mutations • Models provide a starting point for drug design “Critical assessment of predicted interactions” http://capri.ebi.ac.uk [ Faculty of Science [ Faculty of Science Chemistry] Chemistry] Data-driven docking Related reviews • van Dijk ADJ, Boelens R and Bonvin AMJJ (2005). Data-driven docking for the study of biomolecular complexes. FEBS Journal • There is a wealth of (easily) available 272 293-312. experimental data on biomolecular interaction. • de Vries SJ and Bonvin AMJJ (2008). How proteins get in touch: • When classical structural studies fail, these are Interface prediction in the study of biomolecular complexes. Curr. Pept. and Prot. Research 9, 394-406. however often not used and the step to modelling (docking) is most of the time not taken. • de Vries SJ, de Vries M. and Bonvin AMJJ. The prediction of macromolecular complexes by docking. In: Prediction of Protein • These data can be very useful to filter docking Structures, Functions, and Interactions. Edited by J. Bujnicki Ed., solutions or even to drive the docking and thus John Wiley & Sons, Ltd, Chichester, UK (2009). limit the conformational search problem. • A.S.J. Melquiond and A.M.J.J. Bonvin. Data-driven docking: using external information to spark the biomolecular rendez-vous. In: Protein-protein complexes: analysis, modelling and drug design. Edited by M. Zacharrias, Imperial College Press, 2010. p 183-209. [ Faculty of Science [ Faculty of Science Chemistry] Chemistry]
Experimental sources: Overview mutagenesis ! Introduction ! Information sources ! General aspects of docking ! Information-driven docking with HADDOCK ! Incorporating biophysical data into docking ! Multiple choice topics... ! Challenges Advantages/disadvantages Detection ! Conclusions & perspectives + Residue level information - Binding assays - Loss of native structure - Surface plasmon resonance - Mass spectrometry should be checked - Yeast two hybrid - Phage display libraries, … [ Faculty of Science Chemistry] Experimental sources: Experimental sources: H/D exchange cross-linking and other chemical modifications Advantages/disadvantages Detection Advantages/disadvantages Detection + Distance information between - Mass spectrometry + Residue information - Mass spectrometry linker residues - Direct vs indirect effects - NMR 15 N HSQC - Cross-linking reaction problematic - Labeling needed for NMR - Detection difficult [ Faculty of Science [ Faculty of Science Chemistry] Chemistry]
Experimental sources: Experimental sources: NMR chemical shift perturbations NMR orientational data (RDCs, relaxation) Advantages/disadvantages Detection + Residue/atomic level - NMR 15 N or 13 C HSQC + No need for assignment if Advantages/disadvantages Detection combined with a.a. selective labeling + Atomic level - NMR - Labeling needed - Direct vs indirect effects - Labeling needed [ Faculty of Science [ Faculty of Science Chemistry] Chemistry] Experimental sources: Other potential experimental sources NMR saturation transfer • Paramagnetic probes in combination with NMR Amide protons at interface are saturated • Cryo-electron microscopy or tomography and ==> intensity decrease small angle X-ray scattering (SAXS) ==> shape information • Fluorescence quenching Advantages/disadvantages • Fluorescence resonance energy transfer (FRET) + Residue/atomic level + No need for assignment if • Infrared spectroscopy combined with specific combined with a.a. selective labeling labeling - Labeling (including deuteration) needed • … [ Faculty of Science [ Faculty of Science Chemistry] Chemistry]
Predicting interaction surfaces What is conservation? • In the absence of any experimental information • Conservation occurs when residues are expected to (other than the unbound 3D structures) we can mutate, but do not mutate, or much more slowly try to predict interfaces from sequence • How to calculate conservation? information? – Generate a sequence alignment • WHISCY: – Calculate the expected mutation behavior WHat Information does Surface – Calculate deviations from this behavior Conservation Yield? – Is there less change than expected? Alignment • The residue conservation score is the sum of all Propensities Surface smoothing EFRGSFSHL deviations from expected behavior EFKGAFQHV + + EFKVSWNHM LFRLTWHHV IYANKWAHV predicted true EFEPSYPHI http://www.nmr.chem.uu.nl/whiscy De Vries, van Dijk Bonvin . Proteins 2006 [ Faculty of Science [ Faculty of Science Chemistry] Chemistry] How to calculate expected Residue mutation matrix example conservation? • “ Four residue world ” : Ala, Asp, Glu, Trp AFRGTFSHL AFRGTFSHL • Sequence distance: 1 % mutation EFRGSFSHL EFEPSYPHI Ala Asp Glu Trp Near identical sequences Different sequences Ala 99 0.33 0.33 0.33 No conservation Conservation Asp 0.33 99 0.33 0.33 glu 0.33 0.33 99 0.33 Sequence distance must be taken into account Trp 0.33 0.33 0.33 99 [ Faculty of Science [ Faculty of Science Chemistry] Chemistry]
Residue mutation matrix example Residue mutation matrix example • Some residues mutate however faster than • Some mutations are more likely than others others Ala Asp Glu Trp Ala Asp Glu Trp Ala 98 0.67 0.67 0.67 Ala 98 0.67 0.67 0.67 Asp 0.33 99 0.33 0.33 Asp 0.17 99 0.67 0.17 glu 0.33 0.33 99 0.33 glu 0.17 0.67 99 0.17 Trp 0.17 0.17 0.17 99.5 Trp 0.17 0.17 0.17 99.5 [ Faculty of Science [ Faculty of Science Chemistry] Chemistry] Residue mutation matrix example Residue mutation matrix • Several such matrices exist • You can multiply the matrix by itself to generate distance specific matrices • The best known is the Dayhoff (PAM) – E.g. result of 20 multiplications: 20 % mutation matrix (Dayhoff et al. 1978) Ala Asp Glu Trp • This matrix is used in Whiscy Ala 65.96 11.35 11.35 11.35 Asp 2.84 82 11.74 3.42 glu 2.84 11.74 82 3.42 Trp 2.84 3.42 3.42 90.32 [ Faculty of Science [ Faculty of Science Chemistry] Chemistry]
WHISCY calculation WHISCY calculation • Take as input a 3D structure and a sequence alignment • protdist (Felsenstein et al. ) used to calculate the sequence • Each residue is scored independently distances • WHISCY compares the master sequence to every other sequence distance distance EFRGSFSHL 5 EFRGSFSHL 5 EFKGAFQHV EFKGAFQHV 18 18 EFKVSWNHM 75 EFKVSWNHM 75 AFRGTFSHL AFRGTFSHL master master 85 85 LFRLTWHHV LFRLTWHHV IYANKWAHV IYANKWAHV 102 102 EFEPSYPHI 121 EFEPSYPHI 121 [ Faculty of Science [ Faculty of Science Chemistry] Chemistry] WHISCY calculation Partial score • The partial score is equal to the probability Compare with in the distance-dependent mutation matrix Partial scores observed residue distance Master R ... 5 Mutation matrix • A correction factor corresponding to the sum sequence ... K residue of squares of all probabilities is subtracted 18 Mutation matrix ... K 75 Mutation matrix R • This makes sure that the average score is R ... 85 Mutation matrix zero ... A 102 Mutation matrix ... • WHISCY score > 0 indicates conservation E 121 Mutation matrix + Total score The sequences are weighted so that the distance range is represented equally [ Faculty of Science [ Faculty of Science Chemistry] Chemistry]
Recommend
More recommend
