Bioisostere identification

Bioisosteres were then defined as the functional groups from the PDB entries selected by the sequence search occupying the same space as the input group. These groups could be identified either by eye or automatically by extracting all atoms within a user-defined threshold of those in the input functional group. 

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For both similarity-searching and privileged-structure strategies, it was correctly pointed out that intellectual property considerations can become a capital issue [8], This stresses again the above-mentioned need for scaffold hopping and bioisostere-identification methods and also the value of proprietary chemical and biological data [114-117]. 

Instead, many methods introduce a degree of fuzziness to their molecular description to abstract the functional characteristics from the elemental representation. It is this abstraction that permits the comparison of topologically quite distinct groups to identify their bioisosteric or functional similarity. We will see, by examples from the literature, the differentapproaches thathave been reported to introduce this controlled fuzziness for bioisosteric identification and replacement [1]. 

To correctly address the problem of identification of target-specific privileged motifs, one should take into account the phenomenon of bioisosterism [26]. Thus, several different bioisosteric structures can constitute only one distinct privileged structural motif. In order to include all possible bioisosteric analogs into one cluster, we use a special algorithm of ChemoSoft based on a collection of rules for bioisosteric conversions described in literature. AH bioisosteric analogs are considered similar with similarity coefficient 1 if they have identical substituents around the central bioisosterically transformed fragment. 

Ertl, P. Cheminformatics analysis of organic substituents identification of the most common substituents, calculation of substituent properties, and automatic identification of dmg-like bioisosteric groups. J. Chem. Inf. 

Chart 8 Chemical structures of the CA4 boronic acid bioisostere (9) and of MDL-27048. The former was proposed by a structure-based molecular modeling study, the latter was used to elaborate a virtual screening protocol for the identification of novel chalcone CSI... 

Liljebris, C., Larsen, S. D., Ogg, D., Palazuk, B. J., Bleasdale, J. E. Investigation of potential bioisosteric replacements for the carboxyl groups of peptidomimetic inhibitors of protein tyrosine phosphatase IB identification of a tetrazole-containing inhibitor with cellular activity. J. Med. Chem. 2002, 45(9), 1785-1798. 

Erd, P. (2007) In silico identification of bioisosteric functional groups. Current Opinion in Drug Discovery and Development, 10, 281-288. 

Cheeseright, T. (2009) The identification of bioisosteres as drug development candidates. Innovations in Pharmaceutical Technology, 28, 22-26. 

Devereux, M. and Popelier, P.LA. (2010) In silico techniques for the identification of bioisosteric replacements for drug design. Current Topics in Medicinal Chemistry, 10, 657-668. 

Figure 7.3 A web tool for identification of bioisosteric substituents based on similarity in their properties used at Novartis.

The work from Wagener and Lommerse [26] detailed a new ligand-based topological pharmacophore descriptor specifically for the identification of bioisosteres and can be seen as an approach to alleviate the issues of sensitivity to heteroatom replacement observed by Schuffenhauer et al. The descriptors applied in this work used an atom pair representation similar to that reported by Carhart et al. [28]. These descriptors are extracted from databases of known molecules by shredding the molecules at all deavable bonds with the attachment point being retained as a distinct atom type, X. 

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