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      Ligand-based combinatorial design of selective purinergic receptor (A2A) antagonists using self-organizing maps.

      Journal of Combinatorial Chemistry

      metabolism, Receptor, Adenosine A2A, Protein Binding, chemistry, Pharmaceutical Preparations, Molecular Structure, Ligands, Humans, methods, Drug Evaluation, Preclinical, Drug Design, Combinatorial Chemistry Techniques, Adenosine A2 Receptor Antagonists

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          Abstract

          A virtual screening procedure based on a topological pharmacophore similarity metric and self-organizing maps (SOM) was developed and applied to optimizing combinatorial products functioning as P(1) purinergic receptor antagonists. The target was the human A(2A) receptor. A SOM was developed using a set of biologically tested molecules to establish a preliminary structure-activity relationship. A combinatorial library design was performed by projecting virtually assembled new molecules onto the SOM. A small focused library of 17 selected combinatorial products was synthesized and tested. On average, the designed structures yielded a 3-fold smaller binding constant ( approximately 33 vs approximately 100 nM) and 3.5-fold higher selectivity (50 vs 14) than the initial library. The most selective compound obtained revealed a 121-fold relative selectivity for A(2A) with K(i) (A(2A)) = 2.4 nM, and K(i) (A(1)) = 292 nM. This result demonstrates that it was possible to design a small, activity-enriched focused library with an improved property profile using the SOM virtual screening approach. The strategy might be particularly useful in projects in which structure-based design cannot be applied because of a lack of receptor structure information, for example, in the many projects aiming at finding new GPCR modulators.

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          Author and article information

          Journal
          10.1021/cc020092j
          12739938

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