This article about the idea of collaborative map/reduce in the browser and this one on Depth-First gave me the idea to try something other than distributed word counting: distributed substructure matching.
The server was quickly written in Python, the backend in this case is Postgresql with a table holding the structures as V2000 molfiles in plain text format. No magic so far.
Here's the code of the server.
The server schedules a job of maxsize random molecules from the database and constructs a page containing those molecules as molfiles. After the page has completely loaded in the browser, the matching is done and the page is posted back to the server which parses the result. Once manually started by opening http://:8080/get, the pages keep reloading automatically by means of a meta http-equiv="refresh" in the result page.
Of course, the server is very basic. It notably lacks keeping track of the results and housekeeping to restart broken jobs and uses a hardcoded substructure as search argument.
But it can be done.