Overview ! Introduction ! Information sources Integrative modeling of ! General aspects of docking ! Information-driven docking with HADDOCK biomolecular complexes ! Incorporating biophysical data into docking ! 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 protein-protein interaction Cosmos Adding the 3 rd dimension Experimental Structures Computational Models Homology Peptide-mediated Modeling Interactions Biomolecular Docking Domain-domain Interactions Hybrid Macromolecular Modeling Complex Stein et al. Curr Op Struct Biol. 2011 3 [ Faculty of Science Chemistry]
Molecular Docking Structural coverage of interactomes Unique interactions in interactomes • ~7,500 binary interactions in E.coli • ~44,900 binary interactions in H.sapiens E.coli H.sapiens with complete structures with partial (domain-domain) or complete models with structures for the interactors (suitable for docking) without structural data [ Faculty of Science [ Faculty of Science Chemistry] Chemistry] Methodology Data Integration during Sampling Data incorporation Global Search Information-driven Search Sampling Interaction Energy Interaction Energy Interaction Energy Conformational Landscape Conformational Landscape Scoring Conformational Landscape [ Faculty of Science [ Faculty of Science Chemistry] Chemistry]
What is Integrative Modeling? Related reviews • Halperin et al. (2002) Principles of docking: an overview of search algorithms and a guide to scoring functions. PROTEINS: Struc. Funct. & Genetics 47, 409-443. • Special issues of PROTEINS: (2003) (2005) (2007) (2010) and (2013), which are dedicated to CAPRI. • de Vries SJ and Bonvin AMJJ (2008). How proteins get in touch: Interface prediction in the study of biomolecular complexes . Curr. Pept. and Prot. Research 9 , 394-406. • Melquiond ASJ, Karaca E, Kastritis PL and Bonvin AMJJ (2012). Next challenges in protein-protein docking: From proteome to interactome and beyond . WIREs Computational Molecular Science 2 , 642-651 (2012). • Karaca E and Bonvin AMJJ (2013). Advances in integrated modelling of biomolecular complexes . Methods , 59 , 372-381 (2013). • Rodrigues JPGLM and Bonvin AMJJ (2014). Integrative computational modelling of protein interactions . FEBS J ., 281 , 1988-2003 (2014). [ 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 ! Conclusions & perspectives Advantages/disadvantages Detection + 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 + Atomic level - NMR combined with a.a. selective labeling - Labeling needed - Direct vs indirect effects - Labeling needed [ Faculty of Science [ Faculty of Science Chemistry] Chemistry]
Other potential experimental sources Predicting interaction surfaces • In the absence of any experimental information • Paramagnetic probes in combination with NMR (other than the unbound 3D structures) we can try to predict interfaces from sequence • Cryo-electron microscopy or tomography and information? small angle X-ray scattering (SAXS) ==> shape • WHISCY: information WHat Information does Surface Conservation Yield? • Fluorescence quenching Alignment • Fluorescence resonance energy transfer (FRET) Propensities Surface smoothing EFRGSFSHL EFKGAFQHV + + • Infrared spectroscopy combined with specific EFKVSWNHM LFRLTWHHV labeling 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] CPORT webserver Interface prediction servers • PPISP (Zhou & Shan,2001; Chen & Zhou, 2005) http://pipe.scs.fsu.edu/ppisp.html • ProMate (Neuvirth et al., 2004) � http://bioportal.weizmann.ac.il/promate • WHISCY (De Vries et al., 2005) � http://www.nmr.chem.uu.nl/whiscy • PINUP (Liang et al., 2006) � http://sparks.informatics.iupui.edu/PINUP • PIER (Kufareva et al., 2006) � http://abagyan.scripps.edu/PIER • SPPIDER (Porollo & Meller, 2007) http://sppider.cchmc.org Consensus interface prediction (CPORT) haddock.science.uu.nl/services/CPORT [ Faculty of Science [ Faculty of Science haddock.science.uu.nl/services/CPORT/ Chemistry] Chemistry]
Combining experimental or predicted Overview data with docking • a posteriori : data-filtered docking ! Introduction – Use standard docking approach ! Information sources – Filter/rescore solutions ! General aspects of docking • a priori : data-directed docking ! Information-driven docking with HADDOCK – Include data directly in the docking ! Incorporating biophysical data into docking by adding an additional energy term ! Conclusions & perspectives or limiting the search space [ Faculty of Science Chemistry] Docking Explicit representation of the system • x,y,z, coordinates of each atom for both molecules • Choices to be made in docking: • Search method will be in real space – Representation of the system – Sampling method: • 3 rotations and 3 translations • Internal degrees of freedom? – Scoring x,y,z – Flexibility, conformational changes? – Use experimental information? [ Faculty of Science [ Faculty of Science Chemistry] Chemistry]
Grid-based representation of the Mixed representations of the system system • Ligand and/or part of the interacting region is • Discretise of the 3D structure of a protein onto a grid explicitly represented • Remaining of structure is mapped onto a grid • Interaction explicit atoms <-> grid • E.g. AutoDock, ICM – � Shape representation � of the protein (source: / Krippahl) – Resolution defined by grid spacing – Docking will require to match the shapes ( � geometric matching � ) – Search in real or Fourier space [ Faculty of Science [ Faculty of Science Chemistry] Chemistry] Surface representation of the system: Surface representation of the system: spherical harmonics surface patches • Surface of protein described by an expansion of • Molecular shape representation: identify relevant � puzzle � spherical harmonics, e.g. pieces from the surface (e.g. convex or concave patches) • Try to find mathing patches (geometric hashing) E.g.: PatchDock (Nussinov & Wolfson) 15 1 • ∑ ∑ r( θ , φ ) = a lm ψ lm ( θ , φ ) l = 0 m = − 1 (source: PatchDock / Nussinov & Wolfson) (source: HEX / Richie) [ Faculty of Science [ Faculty of Science Chemistry] Chemistry]
Systematic search Overview • Sample rotations (3) and translations (3) ! Introduction • For each orientation calculate a score ! Information sources • Can be very time consuming depending on scoring ! General aspects of docking function ! Representation of the system • Translational search often carried out in (2D or ! Search methods 3D) Fourier space by convolution of the grids ! Information-driven docking with HADDOCK ! Incorporating biophysical data into docking • Examples: ! Conclusions & perspectives – FFT methods: Z-DOCK, GRAMM, FTDOCK… – Direct search: Bigger (uses fast boolean operations) [ Faculty of Science Chemistry] Systematic search � Energy-driven � search methods • Conformational search techniques aiming at • Search can be carried out stepwise: minimizing some kind of energy function (e.g. – from low to high resolution VdW, electrostatic…): – from crude to more sophisticated scoring – Energy minimization • A decreasing number of solutions is kept at each – Molecular dynamics stages – Brownian dynamics – Monte-Carlo methods • Final solutions often further refined (EM, MD…) – Genetic algorithms – … • Often combined with some simulated annealing scheme [ Faculty of Science [ Faculty of Science Chemistry] Chemistry]
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