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

We present a new open-source software, called Open Growth, 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/.