Combinatorial chemistry functionalization

Precisely defined collections of different chemical compounds are denominated as chemical libraries that can be efficiently prepared by methods of combinatorial chemistry. Each chemical compound owes specific structural, steiic, and electronic properties that determine all possible interactions of the small molecule with a given protein or receptor. The molecule s properties are based on the steiic arrangement of functional groups, including the conformations that can be attained by a specific structure. 

The field of synthetic enzyme models encompasses attempts to prepare enzymelike functional macromolecules by chemical synthesis [30]. One particularly relevant approach to such enzyme mimics concerns dendrimers, which are treelike synthetic macromolecules with a globular shape similar to a folded protein, and useful in a range of applications including catalysis [31]. Peptide dendrimers, which, like proteins, are composed of amino acids, are particularly well suited as mimics for proteins and enzymes [32]. These dendrimers can be prepared using combinatorial chemistry methods on solid support [33], similar to those used in the context of catalyst and ligand discovery programs in chemistry [34]. Peptide dendrimers used multivalency effects at the dendrimer surface to trigger cooperativity between amino acids, as has been observed in various esterase enzyme models [35]. 

In this brief review we illustrated on selected examples how combinatorial computational chemistry based on first principles quantum theory has made tremendous impact on the development of a variety of new materials including catalysts, semiconductors, ceramics, polymers, functional materials, etc. Since the advent of modem computing resources, first principles calculations were employed to clarify the properties of homogeneous catalysts, bulk solids and surfaces, molecular, cluster or periodic models of active sites. Via dynamic mutual interplay between theory and advanced applications both areas profit and develop towards industrial innovations. Thus combinatorial chemistry and modem technology are inevitably intercoimected in the new era opened by entering 21 century and new millennium. 

The Jaccard similarity coefficient is then computed with eq. (30.13), where m is now the number of attributes for which one of the two objects has a value of 1. This similarity measure is sometimes called the Tanimoto similarity. The Tanimoto similarity has been used in combinatorial chemistry to describe the similarity of compounds, e.g. based on the functional groups they have in common [9]. Unfortunately, the names of similarity coefficients are not standard, so that it can happen that the same name is given to different similarity measures or more than one name is given to a certain similarity measure. This is the case for the Tanimoto coefficient (see further). 

The development of protein chip assays to determine protein function using purified components is a rapidly advancing area. Automated systems for the assay of protein function on chips in parallel for thousands of proteins simultaneously will likely be available in the next few years. These miniaturized arrays will be useful for basic research as well as for diagnostics and drug development. For instance, the combination of protein chips with combinatorial chemistry will allow the simultaneous screening of vast collections of small molecules against vast collections of potential target proteins. 

Recently, a solid-phase synthesis was used iteratively for the synthesis of organic substances like oligocarbamates [13] and oligoureas [14] by repeated coupling to amino-functionalized supports. In this way substance libraries [15] have been developed showing that iterative methods can also be employed in combinatorial chemistry [16]. 

One of the key technologies used in combinatorial chemistry is solid-phase organic synthesis (SPOS) [2], originally developed by Merrifield in 1963 for the synthesis of peptides [3]. In SPOS, a molecule (scaffold) is attached to a solid support, for example a polymer resin (Fig. 7.1). In general, resins are insoluble base polymers with a linker molecule attached. Often, spacers are included to reduce steric hindrance by the bulk of the resin. Linkers, on the other hand, are functional moieties, which allow the attachment and cleavage of scaffolds under controlled conditions. Subsequent chemistry is then carried out on the molecule attached to the support until, at the end of the often multistep synthesis, the desired molecule is released from the support. 

Certainly, other chemical structures (end groups) and suitable reactions can also be used in such a process. The main requirement of such combinatory chemistry systems is the conjunction of the initial solubility of the functionalized blocks in the solvent used and the existence of the driving force for the physical association of the more hydrophobic ff-blocks. 

Advances in chemical synthesis have enabled considerable sophistication in the construction of diverse compound libraries to probe protein function [61, 62). However, few general techniques exist that can directly assess binding mechanisms and evaluate ligand afEnities in a multiplexed format. To realize the full potential of combinatorial chemistry in the drug discovery process, generic and efficient tools must be applied that combine mixture-based techniques to characterize protein-ligand interactions with the strengths of diversity-oriented chemical synthesis. 

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