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Matched molecular pair (MMP) analysis has become a standard tool for the extraction of medicinal chemistry knowledge from large databases [18].
The result, medicinal chemistry knowledge sharing (MeCKS), was designed to capture and communicate emerging issues and their solutions to the medicinal chemistry community.
By considering drug design as a process, the core of medicinal chemistry knowledge can be abstracted as the possession of facts and the possession of skills.
Substructures predicted to influence in the same way the compound bioactivity on both COX-1 and COX-2 are small, which makes difficult to extract medicinal chemistry knowledge therefrom (Additional file 8: Figure S7).
We describe how the WizePairZ system can be used to archive and apply medicinal chemistry knowledge from one drug discovery project to another as well as identify common bioisosteres.
It is clear that the effective capture and dissemination of medicinal chemistry knowledge and experience will be a key differentiator among pharmaceutical organizations and crucial for the future success in delivering effective and safe drug candidates.
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Hence, in addition to the study of activity cliffs on a case-by-case basis in medicinal chemistry, a large knowledge base of activity cliff information is emerging.
At the preclinical level, 5-HT6 receptor medicinal chemistry is benefiting from knowledge that has been acquired since the discovery of the receptor using tools such as pharmacophore modeling, three-dimensional molecular docking or structure similarity algorithms.
No previous knowledge of medicinal chemistry is assumed.
Steadily growing numbers of active compounds provide a critically important knowledge base for medicinal chemistry but also challenge Structure-Activity Relationship (SAR) analysis.
In addition to the data sets designed for the development and evaluation of computational methods, we also make available data sets that were generated as a resource and knowledge base for medicinal chemistry applications.
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