Combinatorial chemistry - molecular libraries

A complex system may adjust itself to an external stimulus by changing its molecular structure. A good example is liquid water, which may be regarded as a library of different clusters, aU of them being in an easy-to-shift equilibrium with others. This is why water is able to hydrate a nearly infinite variety of molecules, shifting the equilibrium towards the clusters that are needed to wrap the solute by a water coat . 

The immune system in our botfy is able to fight and win against practically any enemy, irrespective of its shape and molecular properties (charge distribution). How is it possible Would the organism be prepared for everything Well, yes and no. 

Let us imagine a system of molecules (building blocks) having some i nthons and able to create some van der Waals complexes. Fig. 15.2. Since the van der Waals forces are quite weak, the complexes are in dynamic equilibrium. All possible complexes are present in the solution, none of the complexes dominates. 

Non-linearity was an unwanted child of physics. It sharply interfered with making equations easy to solve. Without it, the solutions often represent beautiful, concise expressions, with great interpretative value, whereas with it everything gets difficult, clumsy and most often impossible to treat. We are eventually left with numerical solutions, which have to be treated case by case with no hope of a nice generalization. Sometimes the non-linearity could be treated by perturbation theories, 

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Combinatorial Chemistry => Large libraries of molecules High-Throughput Screening => Many biological data points Cheminformatics => Many molecular descriptors... 

In this book, we describe, extend and apply methods of computer chemistry and chemoinformatics, suitable for molecular structure generation, structure elucidation, combinatorial chemistry, QSPRs, the generation of chemical patent libraries and so on. The tools come from discrete mathematics (graph theory, constructive combinatorics), stochastics (explorative data analysis, supervised and unsupervised learning), computer science (data structures, algorithms) and chemistry (combinatorial chemistry, molecular structure elucidation). 

Research continues into new and. specialized chemical representations. At the level of indexes, the venerable concept of molecular ID numbers has re.surfaced as a critical component in a 3D chemical diversity partitioning scheme, in addition, hierarchical fragment indexes have been implemented with a tremendous enhancement in search performance. The primary driver for the introduction of new representations is the recent focus on the needs of combinatorial chemistry for library design, specification, storage and retrieval. Noteworthy examples are CHUCKLES and CHORTLES, both extensions of SMILES the former supports the representation of peptide and peptoid sequences on both the monomer and atomic levels, and the latter allows the representation of mixtures as simple strings of characters. 

A Polmski, RD Eemstem, S Shi, A Kuki. LiBrain Software for automated design of exploratory and targeted combinatorial libraries. In IM Chaiken, KD Janda, eds. Molecular Diversity and Combinatorial Chemistry Libraries and Drug Discovery. ACS Conf Proc Ser. Washington, DC Am Chem Soc, 1996, pp 219-232. 

Davies K. Using pharmacophore diversity to select molecules to test from commercial catalogues. In Chaiken IM and Janda KD, editors. Molecular diversity and combinatorial chemistry. Libraries and drug discovery. Washington DC American Chemical Society, 1996 309-16. 

Combinatorial chemistry, 7 380-434 8 400—401 13 283-284. See also High-throughput experimentation applications, 7 381-383 commercial environment, 7 387-389 methodology, 7 383-387 microwaves in, 16 548-552 nomenclature, 7 380 polymers, 7 405—413 Combinatorial libraries, 12 515-517 Combinatorial methods, 7 380 Combinatorial optimization approach, in computer-aided molecular design, 26 1037... 

On the other hand, there is considerable interest to quantify the similarities between different molecules, in particular, in pharmacology [7], For instance, the search for a new drug may include a comparative analysis of an active molecule with a large molecular library by using combinatorial chemistry. A computational comparison based on the similarity of empirical data (structural parameters, molecular surfaces, thermodynamical data, etc.) is often used as a prescreening. Because the DFT reactivity descriptors measure intrinsic properties of a molecular moiety, they are in fact chemical fingerprints of molecules. These descriptors establish a useful scale of similarity between the members of a large molecular family (see in particular Chapter 15) [18-21],... 

The SHAPES Linking Library was designed to facilitate the use of combinatorial chemistry to follow up screening hits [11]. This library consists primarily of commercially available compounds containing two drug-like scaffolds connected by a linkage that is synthetically accessible. To construct this library, a database of commercially available compounds was filtered to select for drug-likeness and the presence of the desired molecular... 

While this may in fact be the case for natural product mixtures, it is rarely the case when dealing with synthesized mixtures. Despite our attempts to create real molecular diversity in the test tube, our efforts have not even begun to anticipate the true diversity of atomic connectivity within "drug space" (estimated to be of the order of 1063 unique compounds, theory, famously in this case, greatly outpacing the amount of matter in the universe). Thus, combinatorial chemistry was never practically able to produce true chemical diversity and compounds produced in such library format ended up looking very much like one another, with the attendant similarities in biological activity profiles. 

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