13. Construction of Drug-Like Compounds by Markov Chains

  1. Gisbert Schneider
  1. Peter S. Kutchukian1,
  2. Salla I. Virtanen2,
  3. Eugen Lounkine1,
  4. Meir Glick1 and
  5. Eugene I. Shakhnovich2

Published Online: 11 OCT 2013

DOI: 10.1002/9783527677016.ch13

De novo Molecular Design

De novo Molecular Design

How to Cite

Kutchukian, P. S., Virtanen, S. I., Lounkine, E., Glick, M. and Shakhnovich, E. I. (2013) Construction of Drug-Like Compounds by Markov Chains, in De novo Molecular Design (ed G. Schneider), Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany. doi: 10.1002/9783527677016.ch13

Editor Information

  1. ETH Zürich, Institute of Pharmaceutical Sciences, Wolfgang-Pauli-Strasse 10, 8093 Zürich, Switzerland

Author Information

  1. 1

    Novartis Institutes for BioMedical Research, Center for Proteomic Chemistry, 250 Massachusetts Avenue, Cambridge, MA 02139, USA

  2. 2

    Harvard University, Chemistry and Chemical Biology, 12 Oxford Street, Cambridge, MA 02138, USA

Publication History

  1. Published Online: 11 OCT 2013
  2. Published Print: 13 NOV 2013

ISBN Information

Print ISBN: 9783527334612

Online ISBN: 9783527677016



  • drug-like compound;
  • FOG algorithm;
  • SMoG algorithm;
  • molecular fingerprint;
  • BACE-1;
  • ligand–target affinity;
  • de novo drug design;
  • Naïve Bayesian Classifier


De novo design programs continue to be a source of inspiration for structure-based ligand design. As there advent, they have progressed from addressing a few objectives such as ligand–target affinity to multiple objectives such as polypharmacological activity. The steady increase in experimentally validated designs continues to secure the position of the de novo approach in structure-based ligand design. In this chapter, we provide some historical context for the fragment optimized growth (FOG) algorithm and describe two applications of its use.