Design of Small Libraries for Lead Exploration

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.

[1]  J. Broach,et al.  High-throughput screening for drug discovery. , 1996, Nature.

[2]  R. Houghten.  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. , 1985, Proceedings of the National Academy of Sciences of the United States of America.

[3]  Gabriele Cruciani,et al.  Disjoint Principal Properties of Organic Substituents , 1995 .

[4]  B. Spilker,et al.  Multinational Drug Companies: Issues in Drug Discovery and Development , 1989 .

[5]  Svante Wold,et al.  Major components influencing retention indices in gas chromatography , 1973 .

[6]  T. Carell,et al.  A Novel Procedure for the Synthesis of Libraries Containing Small Organic Molecules , 1994 .

[7]  Han van de Waterbeemd,et al.  Chemometric methods in molecular design , 1995 .

[8]  George E. P. Box,et al.  Empirical Model‐Building and Response Surfaces , 1988 .

[9]  Michael Sjöström,et al.  On the design of multipositionally varied test series for quantitative structure activity relationships , 1987 .

[10]  Lennart Eriksson,et al.  A multivariate quantitative structure-activity relationship for corrosive carboxylic acids , 1994 .

[11]  Torbjörn Lundstedt,et al.  Optimum Conditions for the Willgerodt‐Kindler Reaction. Part 3. Amine Variation. , 1987 .

[12]  S. Wold,et al.  The prediction of bradykinin potentiating potency of pentapeptides. An example of a peptide quantitative structure-activity relationship. , 1986, Acta chemica Scandinavica. Series B: Organic chemistry and biochemistry.

[13]  H. M. Geysen,et al.  Use of peptide synthesis to probe viral antigens for epitopes to a resolution of a single amino acid. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[14]  Torbjörn Lundstedt,et al.  Principal properties for synthetic screening: ketones and aldehydes , 1988 .

[15]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[16]  A. Leo,et al.  Substituent constants for correlation analysis in chemistry and biology , 1979 .

[17]  Hugo Kubinyi,et al.  3D QSAR in drug design : theory, methods and applications , 2000 .

[18]  Torbjörn Lundstedt,et al.  Scope of Organic Synthetic Reactions. Multivariate Methods for Exploring the Reaction Space. An Example with the Willgerodt-Kindler Reaction. , 1987 .

[19]  Gabriele Cruciani,et al.  A New Set of Principal Properties for Heteroaromatics Obtained by GRID , 1996 .

[20]  Gabriele Cruciani,et al.  Principal Properties for Aromatic Substituents. A Multivariate Approach for Design in QSAR , 1989 .

[21]  Svante Wold,et al.  Multivariate Parametrization of 55 Coded and Non‐Coded Amino Acids , 1989 .

[22]  S. Wold,et al.  PLS: Partial Least Squares Projections to Latent Structures , 1993 .

[23]  Han van de Waterbeemd,et al.  Computer-Assisted Lead Finding and Optimization , 1997 .

[24]  R. Carlson,et al.  Design and optimization in organic synthesis , 1991 .

[25]  Sidney Addelman,et al.  trans-Dimethanolbis(1,1,1-trifluoro-5,5-dimethylhexane-2,4-dionato)zinc(II) , 2008, Acta crystallographica. Section E, Structure reports online.

[26]  P. Goodford.  A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. , 1985, Journal of medicinal chemistry.

[27]  Torbjörn Lundstedt,et al.  Principal properties for synthetic screening: amines , 1988 .

[28]  S. Wold,et al.  The Prediction of Bradykinin Potentiating Potency of Pentapeptides. , 1986 .

[29]  D C Spellmeyer,et al.  Measuring diversity: experimental design of combinatorial libraries for drug discovery. , 1995, Journal of medicinal chemistry.

[30]  D. Hawkins,et al.  Analysis of a 2(9) full factorial chemical library. , 1995, Journal of medicinal chemistry.

[31]  Torbjörn Lundstedt,et al.  Optimum conditions for the Willgerodt-Kindler reaction. III: Amine variation , 1987 .

[32]  R. Houghten,et al.  Generation and use of synthetic peptide combinatorial libraries for basic research and drug discovery , 1991, Nature.

[33]  S. Wold,et al.  New chemical descriptors relevant for the design of biologically active peptides. A multivariate characterization of 87 amino acids. , 1998, Journal of medicinal chemistry.

[34]  Svante Wold,et al.  D-Optimal Designs in QSAR , 1993 .