JOELib is the Java successor of the OELib library from OpenEye and was registered 2001-11-09 at the SF sites.
There exists also OpenBabel which is the C++ successor of the OELib library from OpenEye and was registered 2001-11-25 at the SF sites.
JOELib has additional descriptor calculation classes. Furthermore there are some classes to process molecules and use external processing programs to modify molecular data. The processing functionality can be combined with filtering classes. A really usefull feature of this Java version is the possibility to define and use dynamicly defined IO, process and filter classes. On the other side, until now, there are some important features missing, like conformer generation and PDB-file import/export.
By the way, the JOELib logo uses the Tengwar scribe of J. R. R. Tolkien. So if you now think, that the main author of this software is a fantasy fan, you are right ! He like's fantasy novels, especially book's also suitable for childrens, because they are often much more funny and uses a more straight forward writting style.
"Some who have read the book, or at any rate have reviewed it, have found it boring, absurd, or contemptible; and I have no cause to complain, since I have similar opinions of their works, or of the kinds of writing that they evidently prefer." (J. R. R. Tolkien, foreword in lord of the rings)
"Yet the most interesting science is to be found in the unknown world. How do you go from the known to the unknown ?" (Sir D. H. R. Barton, foreword in 'Serendipity-Accidental discoveries in science, R. M. Roberts, 1989'). I think this holds also for the pharmaceutical industry, which searches for drugs (with no known patent). In contrast to this statement we hope to provide a software library presenting as much knowledge based and reproducible algorithms as possible, because we are interested to find serendipitious phenomens in chemistry not in the algorithms we apply.
By the way, experimental design algorithms (task for engineers or computer scientists) looks also in areas we have never discovered, but which similarity measure should we apply on dynamic chemical graphs ? So where are we now looking for new drugs ? "looking in known world" or "looking in the unknown world" ?