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11/01/2010 Segmentation of SES for Protein Structure Analysis Virginio Cantoni, Riccardo Gatti, Luca Lombardi University of Pavia, dept. of Computer Engineering.

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Presentation on theme: "11/01/2010 Segmentation of SES for Protein Structure Analysis Virginio Cantoni, Riccardo Gatti, Luca Lombardi University of Pavia, dept. of Computer Engineering."— Presentation transcript:

1 11/01/2010 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 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 2 Topic List Introduction to the project Generation of surfaces and volumes Segmentation Algorithms Presentation of results

3 Project background This paper is part of a wider research program that started last year at Computer Vision Lab (http://vision.unipv.it) in University of Pavia.http://vision.unipv.it The task is to use and adapt well known pattern recognition, image analysis, 3D graphic algorithms to generate new and fast bioinformatics tools for geometric and morfological analysis of complex 3D structure. In particolar we are now focusing on: Docking Comparison Visualization … 06/03/2016 PRIN06 - Ambienti intelligenti 3

4 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 4 Generation of the surfaces Convex hull Van der Waals surface Solvent accessibile surface Solvent-excluded surface These are the commons surface that are considered during geometrical and topological protein analysis:

5 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 5 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. Convex hull Van der Waals surface Solvent accessibile surface Solvent-excluded surface

6 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 6 Generation of the surfaces For a better visualization a triangle surface is generated with a modified version od the marching cubes algorithm + some relaxation step. Convex hull Van der Waals surface Solvent accessibile surface Solvent-excluded surface

7 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 7 Generation of the surfaces The SAS is generated by a Dilation operation from the Mathematical Morphology. The radius of the structure element is 1.4 Å. Convex hull Van der Waals surface Solvent accessibile surface Solvent-excluded surface

8 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 8 Generation of the surfaces The SES is generated by an Erosion operation from the Mathematical Morphology starting from the SAS. The radius of the structure element is 1.4 Å. Convex hull Van der Waals surface Solvent accessibile surface Solvent-excluded surface

9 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 9 Generation of the surfaces The Quickhull algorithm, is applied to the SES. Convex hull Van der Waals surface Solvent accessibile surface Solvent-excluded surface

10 11/01/2010 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

11 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 11 Propagation step (DT) A propagation algorithm (DT) inside the concavity volume is performed starting from the convex hull surface. Note that unreachable areas such as α β and γ are excluded. 2D Example A E D C B F g I h L   

12 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 12 Propagation step (DT) At the end a set of connected component is found. We can join together areas that have some voxels in common. 2D Example

13 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 13 Propagation step (DT) We can represent the previous result with a tree: 2D Example A B C D E F IL g h A E D C B F g I h L   

14 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 14 Practical case: By applying the previous steps to a test protein (1MK5) we can represent the result with a tree :

15 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 15 Practical case: An algorithm of back propagation is applied onto the tree to find inner regions of interest like tunnels and pockets. Simple constraint rules are applied to guide the back propagation: the minimum passage section  1 the maximum mouth aperture  2

16 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 16 Practical case: This is the result with  1 = 200 and  2 = 7500;

17 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 17 Practical case: This is the result with  1 = 200 and  2 = 2000;

18 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 18 Practical case: First pocket (starting from the deepest)

19 11/01/2010 Segmentation of SES for Protein Structure Analysis – Valencia 2010 19 Practical case: Second pocket

20 Thanks for your attention 06/03/2016 PRIN06 - Ambienti intelligenti 20


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