OpenGrowth: An Automated and Rational Algorithm for Finding New Protein Ligands

We present a new open-source software,
called OpenGrowth, which
aims to create de novo ligands by connecting small organic fragments
in the active site of proteins. Molecule growth is biased to produce
structures that statistically resemble drugs in an input training
database. Consequently, the produced molecules have superior synthetic
accessibility and pharmacokinetic properties compared with randomly
grown molecules. The growth process can take into account the flexibility
of the target protein and can be started from a seed to mimic R-group
strategy or fragment-based drug discovery. Primary applications of
the software on the HIV-1 protease allowed us to quickly identify
new inhibitors with a predicted Kd as
low as 18 nM. We also present a graphical user interface that allows
a user to select easily the fragments to include in the growth process.
OpenGrowth is released under the GNU GPL license and is available
free of charge on the authors’ website and at http://opengrowth.sourceforge.net/.