1. PRM based Protein Folding
CS365:Artificial Intelligence
Era Jain (Y9209)
Romil Gadia (Y9496)

2. Problem Statement
Motivation???

3. Protein Folding & Articulated Robot

4. Protein Folding & Articulated Robot

5. Importance of map reduction

6. Importance of map reduction

7. Map Reduction 2 step process: 1)Sampling of nodes
2)Connection of nodes

8. Node Sampling Sampled States Angles(phi,psi) perturbed Native State
(coordinates)
Native State
(angles)
Sampled States Angles(phi,psi) perturbed
(Coordinates)
Corresponding sampled states as nodes
Filtered Energies
Energies (Sampled States)

10. Node Sampling Sampled States Angles(phi,psi) perturbed Native State
(coordinates)
Native State
(angles)
Sampled States Angles(phi,psi) perturbed
(Coordinates)
Corresponding sampled states as nodes
Filtered Energies
Energies (Sampled States)

12. Node Sampling Sampled States Angles(phi,psi) perturbed Native State
(coordinates)
Native State
(angles)
Sampled States Angles(phi,psi) perturbed
(Coordinates)
Corresponding sampled states as nodes
Filtered Energies
Energies (Sampled States)

13. Node Sampling Formula

14. Node Sampling Sampled States Angles(phi,psi) perturbed Native State
(coordinates)
Native State
(angles)
Sampled States Angles(phi,psi) perturbed
(Coordinates)
Corresponding sampled states as nodes
Filtered Energies
Energies (Sampled States)

15. Energies
Filtered Energies

16. Node Sampling Sampled States Angles(phi,psi) perturbed Native State
(coordinates)
Native State
(angles)
Sampled States Angles(phi,psi) perturbed
(Coordinates)
Corresponding sampled states as nodes
Filtered Energies
Energies (Sampled States)

17. Node Connection Generating intermediate nodes between neighbors
Sampled Nodes(Nodes)
(Angles)
k-nearest neighbors for each node
Energies of intermediate nodes
Transition probabilities between intermediate nodes and original nodes
Graph with edges (weights as per energetic feasibilty)
Weights of edges

18. Node Connection Formula

19. Querying the Roadmap Protein Folding – Stochastic Process
Dijkstra’s Algorithm v/s Monte-Carlo Simulation

20. Our Progress so far...
Generated torsional angles from the native state pdb file
Generated about nodes (conformations) via Gaussian Sampling
Calculated energies for each of these conformations.
Filtered the nodes based on their energies
In short we are done with sampling. We have to work on node connection (edge weight calculation)
For parts 2, 3, 4 we wrote the code.
For part 1, we are using a python library[4]

21. References
[1 ] A Motion Planning Approach to Studying Molecular Motions, Lydia Tapia, Shawna
Thomas, Nancy M. Amato, Communications in Information and Systems, 10(1):53-68,
2010. Also, Technical Report, TR08-006, Parasol Laboratory, Department of Computer
Science, Texas A&M University, Nov 2008.
[2] Intelligent Motion Planning and Analysis with Probabilistic Roadmap Methods for the
Study of Complex and High-Dimensional Motions, Lydia Tapia, Ph.D. Thesis, Parasol
Laboratory, Department of Computer Science, Texas A&M University, College Station,
Texas, Dec 2009.
[3] Image Sources:
[4] Code Sources: