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In drug discovery one uses chemical space as a concept to organize molecules according to their
structures and properties. One often would like to generate new possible molecules at a specific
location in chemical space marked by a molecule of interest. Herein we report the peptide design
genetic algorithm (PDGA, code available at https://github.com/reymondgroup/PeptideDesignGA), a computational tool capable of producing peptide sequences of
various chain topologies (linear, cyclic/polycyclic or dendritic) in proximity of any molecule of
interest in a chemical space defined by MXFP, an atom-pair fingerprint describing molecular
shape and pharmacophores. We show that PDGA generates high similarity analogs of bioactive
peptides, including in selected cases known active analogs, as well as of non-peptide targets. We
illustrate the chemical space accessible by PDGA with an interactive 3D-map of the MXFP
property space available at http://faerun.gdb.tools/. PDGA should be generally useful to generate
peptides at any location in chemical space.