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Segmentation of SES for Protein Structure Analysis

Explore advanced segmentation algorithms for analyzing protein structures through the generation and visualization of key surfaces. This project focuses on geometric and topological protein analysis methods. Using innovative techniques, discover complex 3D structure insights for enhanced scientific understanding.

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Segmentation of SES for Protein Structure Analysis

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  1. Segmentation of SES for Protein Structure Analysis Virginio Cantoni, Riccardo Gatti, Luca Lombardi University of Pavia, dept. of Computer Engineering and Systems Science,Via Ferrata 1, Pavia, Italy {virginio.cantoni, riccardo.gatti, luca.lombardi}@unipv.it

  2. Topic List • Introduction to the project • Generation of surfaces and volumes • Segmentation Algorithms • Presentation of results Segmentation of SES for Protein Structure Analysis – Valencia 2010

  3. Project background Thispaperis part of a widerresearchprogramthatstarted last year at Computer Vision Lab (http://vision.unipv.it) in Universityof Pavia. The task istouse and adaptwellknown pattern recognition, imageanalysis, 3D graphicalgorithmsto generate new and fast bioinformaticstoolsforgeometric and morfologicalanalysisofcomplex 3D structure. In particolar we are nowfocusing on: Docking Comparison Visualization … PRIN06 - Ambienti intelligenti

  4. Van der Waals surface Convex hull Solvent-excluded surface Solvent accessibile surface Generation of the surfaces • These are the commonssurfacethat are consideredduringgeometrical and topologicalproteinanalysis: Segmentation of SES for Protein Structure Analysis – Valencia 2010

  5. Van der Waals surface Convex hull Solvent-excluded surface Solvent accessibile surface Generation of the surfaces • In the discrete space the protein and the CH are defined in a cubic grid V of dimension L x M x N.The voxel resolution adopted is 0.25 Å. Segmentation of SES for Protein Structure Analysis – Valencia 2010

  6. Van der Waals surface Convex hull Solvent-excluded surface Solvent accessibile surface Generation of the surfaces • For a bettervisualization a trianglesurfaceisgeneratedwith a modifiedversion od the marchingcubesalgorithm + some relaxationstep. Segmentation of SES for Protein Structure Analysis – Valencia 2010

  7. Van der Waals surface Convex hull Solvent-excluded surface Solvent accessibile surface Generation of the surfaces • The SASisgeneratedby a Dilationoperationfrom the MathematicalMorphology. The radiusof the structureelementis 1.4 Å. Segmentation of SES for Protein Structure Analysis – Valencia 2010

  8. Van der Waals surface Convex hull Solvent-excluded surface Solvent accessibile surface Generation of the surfaces • The SESisgeneratedbyanErosionoperationfrom the MathematicalMorphologystartingfrom the SAS. The radiusof the structureelementis 1.4 Å. Segmentation of SES for Protein Structure Analysis – Valencia 2010

  9. Van der Waals surface Convex hull Solvent-excluded surface Solvent accessibile surface Generation of the surfaces • The Quickhull algorithm, is applied to the SES. Segmentation of SES for Protein Structure Analysis – Valencia 2010

  10. Propagation step (DT) Let us call R the region between the CH and the SES (the concavity volume) that is: 2D Example Segmentation of SES for Protein Structure Analysis – Valencia 2010

  11. Propagation step (DT) A propagationalgorithm (DT) inside the concavity volume isperformedstartingfrom the convexhullsurface. Note thatunreachableareassuchasαβ and γ are excluded. 2D Example A a C E D b g L I F h B g Segmentation of SES for Protein Structure Analysis – Valencia 2010

  12. Propagation step (DT) At the end a set ofconnectedcomponentisfound. We can join togetherareasthathave some voxels in common. 2D Example Segmentation of SES for Protein Structure Analysis – Valencia 2010

  13. Propagation step (DT) We can represent the previousresultwith a tree: 2D Example A a C E D b L I g h g L I F h B F E D C B g A Segmentation of SES for Protein Structure Analysis – Valencia 2010

  14. Practical case: Byapplying the previousstepsto a test protein (1MK5) we can represent the resultwith a tree : Segmentation of SES for Protein Structure Analysis – Valencia 2010

  15. Practical case: An algorithmof back propagationisappliedonto the treetofindinnerregionsof interest liketunnels and pockets. Simpleconstraintrules are appliedto guide the back propagation: the minimum passage section 1 the maximum mouth aperture 2 Segmentation of SES for Protein Structure Analysis – Valencia 2010

  16. Practical case: Thisis the resultwith1 = 200 and 2 = 7500; Segmentation of SES for Protein Structure Analysis – Valencia 2010

  17. Practical case: Thisis the resultwith1 = 200 and 2 = 2000; Segmentation of SES for Protein Structure Analysis – Valencia 2010

  18. Practical case: First pocket (startingfrom the deepest) Segmentation of SES for Protein Structure Analysis – Valencia 2010

  19. Practical case: Second pocket Segmentation of SES for Protein Structure Analysis – Valencia 2010

  20. Thanks for your attention PRIN06 - Ambienti intelligenti

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