Matched Pair Analysis based tool to generate isosteric and bioisosteric molecular libraries

Seldom does it happen that an interesting molecule obtained as hits/lead has the right profile to be approved for human use. Multiple analogues need to be synthesized for SAR/QSAR/QSPR which is the focus for this proposal. Matched pair analysis considers molecules with similar scaffolds and automatically determines point r-group changes between pairs of molecules. Commercial (bio) isostere libraries are expensive, medicinal expertise to curate these not readily accessible. Thus such a tool is very valuable for indigenous efforts. This challenge involves utilizing known anti-viral data from ChEMBL including known antivirals and positive bioassay results to develop a software to help medicinal chemists generate bioisosteres. Success criteria is the software/program’s ability to automatically generate non-redundant bioisosteric molecule fragments using Matched molecular pair analysis & python libraries and store them in a SMILES text file. Validation of results will be done by medicinal chemists to generate well understood bioisosteres from known molecules.

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