Discovery of Ligand-Protein Interactome
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Combined experimental and structural-bioinformatics approach is presented for proteome-scale protein-metabolite/drug interactions. Experimental methods combine pulse-proteolysis and mass spec. Bioinformatics part uses Patch-Surfer software.
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Discovery of Ligand-Protein Interactome
- 1. Genome-Wide Discovery of Protein-Ligand Interactions by a Combined Computational & Energetic-Based Approach Daisuke Kihara Department of Biological Sciences Department of Computer Science Purdue University, IN, USA 1 http://kiharalab.org
- 2. Comprehensive Detection of Protein- Ligand Interactions in a Cell From single molecules to interactions and networks Protein-protein interaction networks can be identified by several experimental methods, yeast 2 hybrid, tagged-protein + mass spec Protein-ligand interaction network (pathways) e.g. KEGG: compilation of individual interactions in literature 2
- 3. Combined Computational & Experimental Approach 3 (Zeng et al., J Proteome Res, 2016)
- 4. Patch-Surfer 2.0: Local Patch-Based Pocket Comparison Method 4 (Sael & Kihara, Proteins, 2012) (Zhu, Xiong, & Kihara, Bioinformatics, 2015)
- 5. 3D Zernike invariants An extension of spherical harmonics based descriptors A 3D object can be represented by a series of orthogonal functions, thus practically represented by a series of coefficients as a feature vector Compact Rotation invariant 5 A surface representation of 1ew0A (A) is reconstructed from its 3D Zernike invariants of the order 5, 10, 15, 20, and 25 (B-F). (Sael & Kihara, 2009) ),()(),,( ϕϑϕϑ m lnl m nl YrRrZ = ),( ϕϑm lY )(rRnl ),,( ϕϑrZ m nl : Spherical harmonics, : radial functions polynomials in Cartesian coordinates ∫ ≤ =Ω 14 3 .)()( x xxx dZf m nl m nl πZernike moments: Zernike invariants: 2 )( m nl lm lm nlF Ω= ∑ = −=
- 6. Pocket Features to Compare 6 • Shape • Electrostatic Potential • Hydrophobicity • Visibility 3DZD for Approximate Patch Position: Histogram of Geodesic Distance to other Seed Points
- 7. The Number of Patches for Several Ligand Binding Pockets 7
- 8. Non-Redundant Database of Ligand Binding Pockets Selected from ligand-bound protein structures from PDB 2444 different ligand types 6547 pockets 117 ligands have more than 5 pockets 8
- 9. Predicting Binding Ligand from Screening Results 9 Query pocket Query pocket Pocket database Pocket database Matched pockets Ligand of the pocket 1lj8_A NAD 1ebw_AB BEI 3b4y_A F42_FLC 3oa2_ACD NAD 1bxk_A NAD 3c1o_A NAP 1nuq_A DND 2jhf_A NAD 1nyt_B NAP …… …… ligand Pocket Score NAP 22.87 NAD 18.75 NDP 16.55 DND 14.81 ATP 12.75 ….. ….. Pocket _ score(P,F) = wl(i),F log n i ÷ ÷. wl(i),Fi=1 k ∑ wl(i),Fi=1 n ∑i=1 k ∑
- 10. Binding Ligand Prediction Results Top 5 Top 10 Top 15 Top 20 Top 25 117 Ligands 0.254 0.438 0.547 0.611 0.659 50 Groups* 0.459 0.628 0.726 0.791 0.835 (without flexible ligands)** 107 Ligands 0.272 0.472 0.587 0.653 0.699 50 Groups 0.487 0.663 0.754 0.810 0.845 10 * Ligands are grouped with SIMCOMP ligand structure similarity. At this level, ligands with up to a few atom differences are clustered. E. g. glucose and mannose are grouped but not with sucrose. NAD and NADP are clustered but not with ATP. ** After removing 10 ligands with largest flexibility (the average number of rotatable bonds per atom)
- 11. Ligand Types with High and Low Accuracies 11 darunavir NADPH Iron-sulfur cluster Tris- aminomethane polyethylene glycol N-acetyl-D- glucosamine 3-Pyridinium-1- Ylpropane-1-Sulfonate
- 12. Patch-Surfer Retrieval Results for Flexible Ligands: FAD and NAD 12 flavin adenine dinucleotide (FAD) FAD Nicotinamide adenine dinucleotide(NAD) 1cqx 1jr8 1e8g 1k87 1mi3 1s7g Patch-based: 3rd Global pocket: 31st Patch-based: 1st Global pocket: 18th Patch-based: 2nd Global pocket: 16th
- 13. PL-PatchSurfer2: Local Surface- Based Virtual Screening Shin, Christoffer, Wang, & Kihara, J Chem Inf. Model. (2016)
- 14. Benchmark 25 targets from DUD set (Huang et al., 2006) Nuclear receptors: 8 Kinase: 7 Serine protease: 2 Other proteins: 8 ~40~360 actives for each target. Active: Decoy ratio is kept to 1:29. If the library is larger than 3000, 60 actives and 1740 decoy compounds are selected.
- 15. Program EF1% EF5% EF10% BEDROC PL- PatchSurfer 15.47 5.25 3.11 0.310 AutoDock Vina 7.92 5.05 3.37 0.276 AutoDock4 7.36 3.83 2.74 0.226 DOCK6 11.47 4.02 2.47 0.239 ROCS 11.76 5.54 3.52 0.317 Screening Results on the DUD set
- 16. Programs EF1% EF5% EF10% BEDROC PL-P.Surfer 14.69/12.48 5.12/4.55 3.03/2.91 0.30/0.28 DOCK6 12.49/7.69 4.60/3.58 2.86/2.48 0.27/0.21 Vina 7.35/3.86 4.95/2.55 3.39/2.00 0.27/0.16 Difference of Enrichment Factor for 19 Holo/Apo Target Structures
- 17. Screening Results Using Structure Models Methods Structu re EF1% EF5% EF10% BEDROC PL-PSurfer X-ray 12.86 5.28 3.29 0.31 TBM 11.76 5.28 3.35 0.31 Autodock Vina X-ray 8.63 6.14 4.09 0.33 TBM 1.68 1.30 1.30 0.09 DOCK6 X-ray 11.70 4.40 2.98 0.26 TBM 2.58 1.88 1.58 0.12 17 TBM: template-based models
- 18. Combined Computational & Experimental Approach 18 (Zeng et al., J Proteome Res, 2016)
- 19. Identifying NAD Binding Proteins with Pulse-Proteolysis in E.coli Proteome 19 • Stabilization from ligand binding leads to a change in protein abundance after pulse proteolysis. • Digested peptides by pulse proteolysis is filtered out by FASP. • The change in abundance was measured by tandem mass tags (TMT) labeling coupled quantitative mass spectrometry.
- 20. Detected NAD Binding Proteins 20 Three urea concentrations,3.5M, 4.0M, and 4.5M were used. Considered as NAD binding if the stability changed by 1.25 fold or larger with/without NAD in 2 or more replicates.
- 21. 21 (Zeng et al., J Proteome Res, 2016)
- 22. Predicted NAD binding pose of the eight predicted novel NAD binding proteins 22 NAD is colored in cyan and crystal structure of the cognate ligand is shown in magenta.
- 23. 23 (2016)
- 24. Summary Patch-Surfer2.0 compares a query pocket against a database of known ligand binding pockets and predicts binding ligands for the pocket. PL-PatchSurfer2 compares a pocket directly against ligand molecules. Tolerant to small difference of conformations of molecules Combined with Pulse-proteolysis to identify novel NAD binding proteins in the E. coli proteome. 24
- 25. Acknowledgements W. Andy Tao (Purdue) Lingfei Zeng 25 @kiharalab Woong-Hee Shin Chiwook Park (Purdue) Nathan Gardner Lyman Monroe
Editor's Notes
- eed to explain the data . move after 22. spell out FAD and NAD. why how important is FAD and NAD. Electron transfer In metabolism, NAD+ is involved in oxidation-reduction (redox) reactions, carrying electrons from one reaction to another. In biochemistry, flavin adenine dinucleotide (FAD) is a redox cofactorinvolved in several important reactions inmetabolism. Among the improved cases, we take further look at the FAD and NAD groups. The ligand FAD and NAD have the highest flexibility among the nine ligands studied and we wanted to know if segmenting the binding site to smaller patches actually improved in retrieving binding sites of flexible ligands. Figure shows three example of cases where local patch method was better in retrieving the binding pocket with different conformation but same ligand type. In all three cases the retrieval ranks higher than global pocket metho for the protein in the right for the query protein in the left. ------------------------------- Figure FLEX Example pocket match of flexible ligands FAD and NAD. A is FAD binding protein pair 1cqx (left) and 1jr8 (right). B is FAD binding protein pair 1e8g (left) and 1k87 (right). C is NAD binding protein pair 1mi3 (left) and 1s7g (right). Three matching pairs of local patches for each of the pairs of proteins are shown. Color codes shows corresponding local match for pairs of proteins.