Abstract
A combinatorial chemical library is a (usually large) set of compounds made to contain all possible structures of a certain type. The library is often made in order to find a lead compound for a specific drug action or for the optimisation of a lead. Because of the large number of synthesised compounds in the library, their biological activity is usually measured by rapid and simple tests, i.e. “high throughput screening” (HTS), giving crude answers, for instance “active” or “not”. Combinatorial chemistry (CombC) comprises a chain of parts linked by the objective of finding lead compounds for further development. Sometimes the objective is to optimise an existing lead compound, but this is not much discussed in this chapter. An analysis of this CombC chain indicates that the biological testing is the weakest part of the chain. This is due to the difficulty in performing an in-depth biological testing of any set of compounds exceeding a couple of hundred members. Hence there is a strong motivation to decrease the size of libraries to a size that allows in-depth biological testing.
We discuss how the size of a library can be drastically reduced without loss of information or decreases in the chances of finding a lead compound. The approach is based on the use of statistical molecular design (SMD) for the selection of library compounds to synthesise and test, followed by the use of quantitative structure activity relationships (QSARs) for the evaluation of the resulting test data.The use of SMD and QSAR is, in turn, critically dependent on an appropriate translation of the molecular structure to numerical descriptors, the recognition of inhomogeneities (clusters) in both the structural and biological data spaces, and the ability to analyse and interpret relationships between multidimensional data sets.
We present a strategy for constructing a library with optimal information while still taking synthetic feasibility into account. The objective is to provide optimal chemical diversity with a moderate number of compounds, plus adequate depth and width of the biological testing. The strategy is based on a multivariate characterisation of the synthesis starting materials (building blocks), Principal Component Analysis (PCA), multivariate design, and Multivariate Quantitative Structure-Activity Relationships (M-QSAR). The strategy applies both to solid phase synthesis as well as libraries in solution.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Broach, J.R., Thorner, J. High-throughput Screening for Drug Discovery, Nature, 1996, SUPPI., 384, 14–16.
Spilker, B. ‘Multinational Drug Companies’. Issues in Drug Discovery and Development. Raven Press, New York, 1989.
van de Waterbeemd H. (Ed.), QSAR: Chemometric Methods in Molecular Design. Methods and Principles in Medicinal Chemistry, 2, Verlag Chemie, Weinheim, 1995
Kubinyi, H. (Ed.), ‘3D QSAR in Drug Design; Theory, Methods and Applications’. ESCOM Science Publishers, Leiden, Holland, 1993.
Houghten, R.A., Pinilla, C., Bondelle, S.E., Appel, J.R., Dooley C.T. and Cuervo, J.H. Generation and Use of Synthetic Peptide Combinatorial Libraries for Basic Research and Drug Discovery. Nature, 1991, 354, 84–86.
Geysen, H.M., Meloen, R.H. and Barteling, S.J. Use of Peptide Synthesis to Probe Viral Antigens for Epitopes to a Resolution of a Single Amino Acid. Proc. Natl. Acad. Sci. U.S.A., 1984, 81, 3998–4002.
Houghten R.A. General Method for the Rapid Solid-Phase Synthesis of Large Numbers of Peptides: Specificity of Antigen-Antibody Interaction at the Level of Individual Amino Acids. Proc. Natl. Acad. Sci. U.S.A., 1985, 82, 5131–5135.
Carell, T., Wintner, E.A., Bashir-Hashemi, A. and Rebeck, J.Jr. A Novel Procedure for the Synthesis of Libraries Containing Small Organic Molecules. Angew. Chem. Int. Ed. Eng., 1994,33, 2059–2061.
Personal communication, T. Olsson, Astra Hassle AB, Sweden
Martin, E.J., Blaney, J.M., Siani M.A., Spellmyer, D.C., Wong, A.K. and Moos W.H. Measuring Diversity: Experimental Design of Combinatorial Libraries for Drug Design. J. Med.Chem., 1995, 38, 1431–1436.
Young, S.S. and Hawkins, D.M. Analysis of a 29 Full Factorial Chemical Library. J. Med. Chem., 1995, 38, 2784–2788.
van de Waterbeemd, H., Constantino, G., Clementi, S., Cruciani, G. and Valigi, R. Disjoint Principal Properties of Organic Substituents. In QSAR: Chemometric Methods in Molecular Design, Methods and Principles in Medicinal Chemistry, 2, Ed. H. van de Waterbeemd, Verlag Chemie, Weinheim, Germany, 1995
Lundstedt, T., Andersson, P.M., Clementi, S., Cruciani, G., Kettaneh, N., Linusson, A., Nordén, B., Pastor, M., Sjöström, M. and Wold, S. Intelligent Combinatorial Libraries. In Computer-Assisted Lead Finding and Optimization Ed. H. van de Waterbeemd, Verlag Helvetica Chimica Acta. Basel, Switzerland, 1997, 191–208.
Hansch, C. and Leo, A.J. Substituent Constants for Correlation Analysis in Chemistry and Biology. Wiley, New York, 1979.
Hansch, C., Leo, A.J. and Hoekman. D. Exploring QSAR, Hydrophobic, Electronic and Steric Constants, ACS, Washington DC, 1995.
Skagerberg, B., Bonelli, D., Clementi, S., Cruciani, G. and Ebert, C. Principal Properties for Aromatic Substituents. A Multivariate Approach for Design in QSAR. QSAR, 1989, 8, 32–38.
Hellberg, S., Sjöström, M., Skagerberg, B., Wikström. C. and Wold, S. On the design of multipositionally varied test series for quantitative structure-activity relationships. Acta Pharm Jugosl., 1987, 37, 53–65.
Hellberg, S., Sjöström. M. and Wold. S. The Prediction of Bradykinin Potentiating Potency of Pentapeptides. An Example of a Peptide Quantitative Structure-Activity Relationship. Acta Chem. Scand. 1986, B40, 135–140.
Jonsson, J., Eriksson, L., Hellberg, S., Sjöström, M. and Wold, S. Multivariate Parametrization of 55 Coded and Non-Coded Amino Acids, QSAR, 1989, 8, 204–209.
Sandberg, M., Eriksson, L., Jonsson, J., Sjöström, M. and Wold, S. New Chemical Descriptors Relevant for the Design of Biologically Active Peptides. A Multivariate Characterisation of 87 Amino Acids. J. Med. Chem., 1998, 41, 2481–2491.
Goodford, P.J. A computational procedure for determining energetically favourable binding sites on biologically important macromolecules. J.Med.Chem.,1985, 28, 849–857.
Clementi, S., Cruciani, G., Fisi, P., Riganelli, D., Valigi, R. and Musumarra G. A New Set of Principal Properties for Heteroaromatics Obtained by GRID. QSAR, 1996, 15, 108–120.
Jackson J.E. A Users Guide to Principal Components, Wiley, New York, 1991.
Wold, S., Sjöström, M., Carlson, R., Lundstedt, T., Hellberg, S., Skagerberg, B., Wikström, C. and Öhman, J. Multivariate Design. Anal. Chim. Acta, 1986, 191, 17–32.
Carlson, R. Design and Optimization in Organic Synthesis, Elsevier, Amsterdam, 1992.
Lundstedt, T. A QSAR Strategy for Screening of Drugs and Predicting Their Clinical Activity. Drug News Perspect., 1991, 4(8), 468–474.
Sjöström, M. and Eriksson, L. Application of Statistical Experimental Design and PLS Modelling in QSAR. In QSAR: Chemometric Methods in Molecular Design, Methods and Principles in Medicinal Chemistry, 2, Ed. H. van de Waterbeemd. Verlag Chemie, Weinheim, Germany, 1995
Box G.E.P. and Draper, N.R. Empirical Model-building and Response Surfaces, Wiley, Chichester, 1987.
Baroni, M., Clementi, S., Cruciani, G., Kettaneh-Wold, N. and Wold, S. D-Optimal Designs in QSAR. QSAR, 1993, 12, 225–231.
A. Linusson, F. Lindgren, J. Gottfries, S. Wold, in manuscript
Carlson. R., Prochazka. M.P. and Lundstedt. T. Principal Properties for Synthetic Screening: Ketones and Aldehydes. Acta Chem. Scand., 1988, B42, 145–156.
Lundstedt, T., Carlson, R. and Shabana, R.. Optimum Conditions for the Willgerodt-Kindler Reaction. 3. Amine Variation. Acta Chem. Scand., 1987, B41, 157–163.
Bezdek, J.C. Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York, 1981.
Wold, S. and Andersson, K. Major Components Influencing Retention Indices in Gas Chromatography. J. Chromatogr., 1973, 80, 43.
Dunn III, W.J. and Wold. S. SIMCA Pattern Recognition and Classification. In QSAR: Chemometric Methods in Molecular Design, Methods and Principles in Medicinal Chemistry, 2, Ed. van de Waterbeemd, H., Verlag Chemie, Weinheim, Germany, 1995.
Linusson A., Wold, S. and Nordén, B. Chemometrics and Intell. Lab. Syst., 1998, in press.
Carlson, R., Prochazka, M.P. and Lundstedt, T. Principal Properties for Synthetic Screening: Amines. Acta Chem. Scand., 1988, B42, 157–165.
Tsar 3.11, Oxford Molecular Group, http://www.oxmol.co.uk/"
Simca-P 3.01, Umetri AB, Umeå, http://www.umetri.se/
Carlson, R. and Lundstedt, T. Scope of Organic Synthetic Reactions. Multivariate Methods for Exploring the Reaction Space. An example by the Willgerodt-Kindler Reaction. Acta Chem. Scand., 1987, B41, 164–173.
Scitec Laboratory Automation SA, Av. de Provence 18, CH-1007 Lausanne, Switzerland.
Wold, S., Johansson, E. and Cocchi, M. PLS—Partial Least-Squares Projections to Latent Structures. In 3D QSAR in Drug Design; Theory, Methods and Applications, Ed. Kubinyi, H., ESCOM Science Publishers, Leiden, Holland. 1993, pp523–550.
Wold, S. PLS for Multivariate Linear Modeling. In QSAR: Chemometric Methods in Molecular Design, Methods and Principles in Medicinal Chemistry, 2, Ed. van de Waterbeemd, H., Verlag Chemie, Weinheim, Germany, 1995, pp195–218.
Eriksson, L., Berglind, R. and Sjöström, M. A Multivariate Quantitative Structure-Activity Relationship for Corrosive Carboxylic Acids. Chemometrics and Intell. Lab. Syst., 1994, 23, 235–245.
Box, G.E.P., Hunter, W.G. and Hunter, J.S. Statistics for Experimenters, Wiley, New York, 1978.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2002 Kluwer Academic Publishers
About this chapter
Cite this chapter
Andersson, P.M., Linusson, A., Wold, S., Sjöström, M., Lundstedt, T., Nordén, B. (2002). Design of Small Libraries for Lead Exploration. In: Dean, P.M., Lewis, R.A. (eds) Molecular Diversity in Drug Design. Springer, Dordrecht. https://doi.org/10.1007/0-306-46873-5_9
Download citation
DOI: https://doi.org/10.1007/0-306-46873-5_9
Publisher Name: Springer, Dordrecht
Print ISBN: 978-0-7923-5980-7
Online ISBN: 978-0-306-46873-5
eBook Packages: Springer Book Archive