Abstract
Computer-assisted molecular design supports drug discovery by suggesting novel chemotypes and compound modifications for lead structure optimization. While the aspect of synthetic feasibility of the automatically designed compounds has been neglected for a long time, we are currently witnessing an increased interest in this topic. Here, we review state-of-the-art software for de novo drug design with a special emphasis on fragment-based techniques that generate druglike, synthetically accessible compounds. The importance of scoring functions that can be used to predict compound reactivity and potency is highlighted, and several promising solutions are discussed. Recent practical validation studies are presented that have already demonstrated that rule-based fragment assembly can result in novel synthesizable compounds with druglike properties and a desired biological activity.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Danziger, D. J. and Dean, P. M. (1989) Automated site-directed drug design: a general algorithm for knowledge acquisition about hydrogen-bonding regions at protein surfaces. Proc R Soc Lond B Biol Sci 236, 101–13.
Schneider, G. and Fechner, U. (2005) Computer-based de novo design of drug-like molecules. Nat Rev Drug Discov 4, 649–63.
Mauser, H. and Guba, W. (2008) Recent developments in de novo design and scaffold hopping. Curr Opin Drug Discov Devel 11, 365–74.
Nikitin, S., Zaitseva, N., Demina, O., Solovieva, V., Mazin, E., Mikhalev, S., Smolov, M., Rubinov, A., Vlasov, P., Lepikhin, D., Khachko, D., Fokin, V., Queen, C., and Zosimov, V. (2005) A very large diversity space of synthetically accessible compounds for use with drug design programs. J Comput Aided Mol Des 19, 47–63.
Douguet, D., Munier-Lehmann H., Labesse G., and Pochet S. (2005) LEA3D: a computer-aided ligand design for structure-based drug design. J Med Chem 48, 2457–68.
Fechner, U. and Schneider, G. (2006) Flux (1): a virtual synthesis scheme for fragment-based de novo design. J Chem Inf Model 46, 699–707.
Fechner, U., and Schneider, G. (2007) Flux (2): comparison of molecular mutation and crossover operators for ligand-based de novo design. J Chem Inf Model 47, 656–67.
Degen, J. and Rarey, M. (2006) FlexNovo: structure-based searching in large fragment spaces. ChemMedChem 1, 854–68.
Feher, M., Gao, Y., Baber, C., Shirley, W. A., and Saunders, J. (2008) The use of ligand-based de novo design for scaffold hopping and sidechain optimization: two case studies. Bioorg Med Chem 16, 422–7.
Dey, F., and Caflisch, A. (2008) Fragment-based de novo ligand design by multiobjective evolutionary optimization. J Chem Inf Model 48, 679–90.
Proschak, E., Zettl, H., Tanrikulu, Y., Weisel, M., Kriegl, J. M., Rau, O., Schubert-Zsilavecz, M., and Schneider, G. (2009) From molecular shape to potent bioactive agents I: bioisosteric replacement of molecular fragments. ChemMedChem 4, 41–4.
Proschak, E., Sander, K., Zettl, H., Tanrikulu, Y., Rau, O., Schneider, P., Schubert-Zsilavecz, M., Stark, H., and Schneider, G. (2009) From molecular shape to potent bioactive agents II: fragment-based de novo design. ChemMedChem 4, 45–8.
Hecht, D. and Fogel, G. B. (2009) A novel in silico approach to drug discovery via computational intelligence. J Chem Inf Model 49, 1105–21.
Kutchukian, P. S., Lou, D., and Shakhnovich, E. I. (2009) FOG: fragment optimized growth algorithm for the de novo generation of molecules occupying druglike chemical space. J Chem Inf Model 49, 1630–42.
Moriaud, F., Doppelt-Azeroual, O., Martin, L., Oguievetskaia, K., Koch, K., Vorotyntsev, A., Adcock, S. A., and Delfaud, F. (2009) Computational fragment-based approach at PDB scale by protein local similarity. J Chem Inf Model 49, 280–94.
Nicolaou, C. A., Apostolakis, J., and Pattichis, C. S. (2009) De novo drug design using multiobjective evolutionary graphs. J Chem Inf Model 49, 295–307.
Nisius, B., and Rester, U. (2009) Fragment shuffling: an automated workflow for three-dimensional fragment-based ligand design. J Chem Inf Model 49, 1211–22.
Durrant, J. D., Amaro, R. E., and McCammon, J. A. (2009) AutoGrow: a novel algorithm for protein inhibitor design. Chem Biol Drug Des 73, 168–78.
Schneider, G. and Baringhaus, K.-H. (2008) Molecular Design, Wiley-VCH, Weinheim.
Schneider, G., Hartenfeller, M., Reutlinger, M., Tanrikulu, Y., Proschak, E., and Schneider, P. (2009) Voyages to the (un)known: adaptive design of bioactive compounds. Trends Biotechnol 27, 18–26.
Green, D. V. (2003) Virtual screening of virtual libraries. Prog Med Chem 41, 61–97.
Richardson, J. S. and Richardson, D. C. (1989) The de novo design of protein structures. Trends Biochem Sci 14, 304–9.
Richardson, J. S., Richardson, D. C., Tweedy, N. B., Gernert, K. M., Quinn, T. P., Hecht, M. H., Erickson, B. W., Yan, Y., McClain, R. D., and Donlan, M. E. (1992) Looking at proteins: representations, folding, packing, and design. Biophys J 63, 1185–209.
Lameijer, E. W., Tromp, R. A., Spanjersberg, R. F., Brussee, J., and Ijzerman, A. P. (2007) Designing active template molecules by combining computational de novo design and human chemist's expertise. J Med Chem 50, 1925–32.
Gillet, V. J., Khatib, W., Willett, P., Fleming, P. J. and Green, D. V. (2002) Combinatorial library design using a multiobjective genetic algorithm. J Chem Inf Comput Sci 42, 375–85.
Gillet V. J. (2008) New directions in library design and analysis. Curr Opin Chem Biol 12, 372–8.
Hopkins A. L., Groom C. R., and Alex A. (2004) Ligand efficiency: a useful metric for lead selection. Drug Discov Today 15, 430–1.
Bembenek S. D., Tounge B. A., and Reynolds C. H. (2009) Ligand efficiency and fragment-based drug discovery. Drug Discov Today 14, 278–83.
Schneider, G., Lee, M., Stahl, M., and Schneider, P. (2000) De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks. J Comput Aided Mol Des 14, 487–94.
Pierce, A. C., Rao, G., and Bemis, G. W. (2004) BREED: generating novel inhibitors through hybridization of known ligands. Application to CDK2, P38, and HIV protease. J Med Chem 47, 2768–75.
Miranker, A. and Karplus, M. (1991) Functionality maps of binding sites: a multiple copy simultaneous search method. Proteins 11, 29–34.
RCSB Protein Data Bank, http://www.rcsb.org/pdb/ (accessed September 28, 2009).
The PubChem Project, http://pubchem.ncbi.nlm.nih.gov/ (accessed September 28, 2009).
Pearlman, D. A. and Murcko, M. A. (1996) CONCERTS: dynamic connection of fragments as an approach to de novo ligand design. J Med Chem 39, 1651–63.
Luo, Z., Wang, R., and Lai, L. (1996) RASSE: a new method for structure-based drug design. J Chem Inf Comput Sci 36, 1187–94.
Bohacek, R. S. and McMartin, C. (1994) Multiple highly diverse structures complementary to enzyme binding sites: results of extensive application of a de novo design method incorporating combinatorial growth. J Am Chem Soc 116, 5560–71.
Gillett, V. A., Johnson, A. P., Mata, P., and Sike, S. (1990) Automated structure design in 3D. Tetrahedron Comput Method 3, 681–96.
Rotstein, S. H. and Murcko, M. A. (1993) GenStar: a method for de novo drug design. J Comput Aided Mol Des 7, 23–43.
DeWitte, R. S. and Shakhnovich, E. I. (1996) SMoG: de novo design method based on simple, fast, and accurate free energy estimates. 1. Methodology and supporting evidence. J Am Chem Soc 118, 11733–44.
Ishchenko, A. V. and Shakhnovich, E. I. (2002) SMall molecule growth 2001 (SMoG2001): an improved knowledge-based scoring function for protein – ligand interactions. J Med Chem 45, 2770–80.
Gillet, V. J., Johnson, A. P., Mata P., Sike, S., and Williams P. (1993) SPROUT: a program for structure generation. J Comput Aided Mol Des 7 , 127–53.
Gillet, V. J., Newell, W., Mata, P., Myatt, G., Sike, S., Zsoldos, Z. and Johnson, A. P. (1994) SPROUT: recent developments in the de novo design of molecules. J Comput Aided Mol Des 34 , 207–17.
Gillett, V. J., Myatt, G., Zsoldos, Z., and Johnson, A. P. (1995) SPROUT, HIPPO and CAESA: tools for de novo structure generation and estimation of synthetic accessibility. Perspect Drug Discov Des 3, 34–50.
Böhm, H.-J. (1992) The computer program LUDI: a new simple method for the de-novo design of enzyme inhibitors. J Comput Aided Mol Des 6 , 61–78.
Böhm, H.-J. (1992) LUDI: rule-based automatic design of new substituents for enzyme inhibitor leads. J Comput Aided Mol Des 6 , 593–606.
Böhm, H.-J. (1993) A novel computational tool for automated structure-based drug design. Journal of Molecular Recognition, 6, 131–7.
Böhm, H.-J. (1994). The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure. J Comput Aided Mol Des 8 , 243–56.
Böhm, H.-J. (1998). Prediction of binding constants of protein ligands: a fast method for the prioritization of hits obtained from de novo design or 3D database search programs. J Comput Aided Mol Des 12 , 309–23.
Tschinke, V. and Cohen, N. C. (1993) The NEWLEAD program: a new method for the design of candidate structures from pharmacophoric hypothesis. J Med Chem 36, 3863–70.
Thompson, D. C., Denny, R. A., Nilakantan, R., Humblet, C., Joseph-McCarthy, D., and Feyfant, E. (2008) CONFIRM: connecting fragments found in receptor molecules. J Comput Aided Mol Des 22, 761–72.
Markov, A.A., (1971) Extension of the limit theorems of probability theory to a sum of variables connected in a chain. In: Howard, R. (Ed.), Dynamic Probabilistic Systems, vol. 1, Markov Chains (reprinted in Appendix B), John Wiley and Sons, Hoboken.
Lewell, X. Q., Judd, D., Watson, S., and Hann, M. (1998) RECAP – retrosynthetic combinatorial analysis procedure: a powerful new technique for identifying privileged molecular fragments with useful applications in combinatorial chemistry. J Chem Inf Comput Sci 38, 511–22.
Boda, K., Seidel, T., and Gasteiger, J. (2007) Structure and reaction based evaluation of synthetic accessibility. J Comput Aided Mol Des 21, 311–25.
Law, J., Zsoldos, Z., Simon, A., Reid, D., Liu, Y., Khew, S. Y., Johnson, A. P., Major, S., Wade, R. A., and Ando, H. Y. (2009) Route designer: a retrosynthetic analysis tool utilizing automated retrosynthetic rule generation. J Chem Inf Model 49, 593–602.
Vinkers, H. M., de Jonge, M. R., Daeyaert, F. F., Heeres, J., Koymans, L. M., Lenthe, J. H., Lewi, P. J., Timmerman, H., Van Aken, K., and Janssen, P. A. (2003) SYNOPSIS: SYNthesize and OPtimize system in silico. J Med Chem 46, 2765–73.
Symyx Technology Inc., 2440 Camino Ramon, Suite 300, San Ramon, CA 94583, USA.
Daylight Chemical Information Systems, Inc., 120 Vantis-Suite 550, Aliso Viejo, CA 92656, USA.
Patel, H., Bodkin, M. J., Chen, B., and Gillet, V. J. (2009) Knowledge-based approach to de novo design using reaction vectors. J Chem Inf Model 49, 1163–84.
Reisen, F. H., Schneider, G., and Proschak, E. (2009) Reaction-MQL: line notation for functional transformation. J Chem Inf Model 49, 6–12.
Rupp, M., Proschak, E., and Schneider, G. (2007) Kernel approach to molecular similarity based on iterative graph similarity. J Chem Inf Model 47, 2280–6.
Bohacek R. S., McMartin C., and Guida W. C. (1996) The art and practice of structure-based drug design: a molecular modeling perspective. Med Res Rev 16, 3–50.
Mauser, H. and Stahl, M. (2007) Chemical fragment spaces for de novo design. J Chem Inf Model 47, 318–24.
Klebe G. and Böhm H. J. (1997) Energetic and entropic factors determining binding affinity in protein-ligand complexes. J Recept Signal Transduct Res 17, 459–73.
Jorissen, R. N., Reddy, G. S., Ali, A., Altman, M. D., Chellappan, S., Anjum, S. G., Tidor, B., Schiffer, C. A., Rana, T. M., and Gilson, M. K. (2009) Additivity in the analysis and design of HIV protease inhibitors. J Med Chem 52,737–54.
Rarey, M., Kramer, B., Lengauer, T., and Klebe, G. (1996) A fast flexible docking method using an incremental construction algorithm. J Mol Biol 261, 470–89.
Cramer, R. D., Poss, M. A., Hermsmeier, M. A., Caulfield, T. J., Kowala, M. C., and Valentine, M. T. (1999) Prospective identification of biologically active structures by topomer shape similarity searching. J Med Chem 42, 3919–33.
Rarey, M. and Stahl, M. (2001) Similarity searching in large combinatorial chemistry spaces. J Comput Aided Mol Des 15, 497–520.
Rarey, M. and Dixon, S. (1998) Feature trees: a new molecular similarity measure based on tree matching. J Comput Aided Mol Des 12, 471–90.
Boehm, M., Wu, T. Y., Claussen, H., and Lemmen, C. (2008) Similarity searching and scaffold hopping in synthetically accessible combinatorial chemistry spaces. J Med Chem 51, 2468–80.
Lessel, U., Wellenzohn, B., Lilienthal, M., and Claussen, H. (2009) Searching fragment spaces with feature trees. J Chem Inf Model 49, 270–9.
Agarwal, A. K., Johnson, A. P., and Fishwick, C. W. (2008) Synthesis of de novo designed small-molecule inhibitors of bacterial RNA polymerase. Tetrahedron 64, 10049–54.
Sova, M., Cadez, G., Turk, S., Majce, V., Polanc, S., Batson, S., Lloyd, A. J., Roper, D. I., Fishwick, C. W., and Gobec, S. (2009) Design and synthesis of new hydroxyethylamines as inhibitors of D-alanyl-D-lactate ligase (VanA) and D-alanyl-D-alanine ligase (DdlB). Bioorg Med Chem Lett 19, 1376–9.
Park, H., Bahn, Y. J., and Ryu, S. E. (2009) Structure-based de novo design and biochemical evaluation of novel Cdc25 phosphatase inhibitors. Bioorg Med Chem Lett 19, 4330–4.
Wang, R., Gao, Y., and Lai, L. (2000) LigBuilder: a multi-purpose program for structure-based drug design. J Mol Model 6, 498–516.
Schüller, A., Suhartono, M., Fechner, U., Tanrikulu, Y., Breitung, S., Scheffer, U., Göbel, M. W., and Schneider, G. (2008) The concept of template-based de novo design from drug-derived molecular fragments and its application to TAR RNA. J Comput Aided Mol Des 22, 59–68.
Schneider, G., Neidhart, W., Giller, T., and Schmid, G. (1999) “Scaffold-Hopping” by topological pharmacophore search: a contribution to virtual screening. Angew Chem Int Ed 38 , 2894–6.
Mauser, H. and Guba, W. (2008) Recent developments in de novo design and scaffold hopping. Curr Opin Drug Discovery Dev 11, 365–74.
Todorov, N. P., Buenemann, C. L., and Alberts, I. L. (2006) De novo ligand design to an ensemble of protein structures. Proteins: Struct, Funct, Bioinf 64, 43–59.
Alberts, I. L., Todorov, N. P., and Dean, P. M. (2005) Receptor flexibility in de novo ligand design and docking. J Med Chem 48, 6585–96.
Maass, P., Schulz-Gasch, T., Stahl, M., and Rarey, M. (2007) Recore: a fast and versatile method for scaffold hopping based on small molecule crystal structure conformations. J Chem Inf Model 47, 390–9.
Grabowski, K., Proschak, E., Baringhaus, K., Rau, O., Schubert-Zsilaveczc, M., and Schneider, G. (2008) Bioisosteric replacement of molecular scaffolds: fromnatural products to synthetic compounds. Nat Prod Commun 3, 1355–60.
Hartenfeller, M., Proschak, E., Schüller, A., and Schneider, G. (2008) Concept of combinatorial de novo design of drug-like molecules by particle swarm optimization. Chem Biol Drug Des 72, 16–26.
Acknowledgments
The authors thank Herbert Köppen and Karl-Heinz Baringhaus for stimulating discussion. M.H. is grateful to Merz Pharmaceuticals for a scholarship. This research was supported by the Beilstein Institut zur Förderung der Chemischen Wissenschaften and the DFG (SFB579, project A11.2).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Hartenfeller, M., Schneider, G. (2010). De Novo Drug Design. In: Bajorath, J. (eds) Chemoinformatics and Computational Chemical Biology. Methods in Molecular Biology, vol 672. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-839-3_12
Download citation
DOI: https://doi.org/10.1007/978-1-60761-839-3_12
Published:
Publisher Name: Humana Press, Totowa, NJ
Print ISBN: 978-1-60761-838-6
Online ISBN: 978-1-60761-839-3
eBook Packages: Springer Protocols