1. Automatic nanodesign using evolutionary techniques Al Globus, MRJ Technology Solutions, Inc. at NASA Ames Research Center John Lawton, U.C. at Santa Cruz Todd Wipke, U.C. at Santa Cruz

2. http://www.foresight.org/Conferences/MNT6/Papers/Globus Problem Many molecules must be designed Often only requirements known Existing design techniques generally manpower intensive Genetic software can automatically design systems Molecular graph representation rarely supported by genetic software

3. http://www.foresight.org/Conferences/MNT6/Papers/Globus Hypothesis Crossover alone, operating on graphs, can evolve any possible molecule given an appropriate fitness function and a population containing both rings and chains. This hypothesis is supported but not proven.

4. http://www.foresight.org/Conferences/MNT6/Papers/Globus Genetic software Randomly generate a set of molecules Many times: Select parent molecules at random with bias towards better performance Randomly rip copies of each parent in two Mate opposite halves Replace random molecules with bias towards worse performance Repeat until satisfied

5. http://www.foresight.org/Conferences/MNT6/Papers/Globus Algorithm properties Stochastic Embarrassingly parallel Robust to failure No guaranteed outcome Fitness function is crucial and non-trivial Performs well as cycle-scavenger 300-400 NAS user workstations ~2.5 million idle workstation hours/year Condor, University of Wisconsin, http://www.cs.wisc.edu/condor

6. http://www.foresight.org/Conferences/MNT6/Papers/Globus Previous work Patent US5434796, David Weininger, Daylight Chemical Information Systems, Inc. 1995 two parameter crossover; fragments some commercial success Robert B. Nachbar, Merck Research Laboratories, 1998 tree representation no crossover within rings Astro Teller, CMU, 1998? Neural Programming

7. http://www.foresight.org/Conferences/MNT6/Papers/Globus

8. Crossover: rip in half Choose random bond Find the shortest path Remove and remember random path bond Repeat until cut set found

9. http://www.foresight.org/Conferences/MNT6/Papers/Globus Crossover: mate halves Select a random cut bond If cut bond in other half exist choose one at random merge cut bonds, respect valence else flip coin –heads -- attach cut bond to random atom in other half respecting valence –tails -- discard cut bond repeat until all cut bonds processed

10. http://www.foresight.org/Conferences/MNT6/Papers/Globus Fitness function Given two molecules, decides which is better Must operate on any molecule, including very bad ones Must provide routes for evolution to reach good molecules Must make fine distinctions

11. http://www.foresight.org/Conferences/MNT6/Papers/Globus Molecular target All-pairs-shortest-path (APSP) distance Assign extended types to each atom (element plus bond pattern) Find shortest path between each pair of atoms Create bag where each element is the extended types and length of each shortest path Tanimoto distance between bags |intersection| / |union|

12. http://www.foresight.org/Conferences/MNT6/Papers/Globus

14. Future work Drug discovery (preliminary results) Chemical stability fitness function Circuits Improvements in cycle-scavenging Data to Java server instead of file system Generic Java checkpointing problem: stack not consistent format

15. http://www.foresight.org/Conferences/MNT6/Papers/Globus Summary Genetic software techniques applied to molecular graphs Molecular design works but needs improvement Robust cycle-stealing execution Technique should generalize to other graph problems

16. http://www.foresight.org/Conferences/MNT6/Papers/Globus Acknowledgments John Lawton, UCSC Todd Wipke, UCSC Creon Levit, NASA Ames Jason Lohn, Caelum, Inc. at NASA Ames Rich McClellan, UCSC Subash Saini, NASA Ames Meyya Meyyapan, NASA Ames