In chemical optimization, it is difficult to estimate when an analog series might be saturated and synthesis of additional compounds would be unlikely to yield further progress. Only few approaches are currently available to monitor series progression and aid in decision making. A new computational method is introduced to assess progression saturation of analog series by comparing existing compounds to virtual candidates. Neighborhoods of analogs in chemical space and distance relationships between existing and candidate compounds are analyzed. A dual scoring scheme is applied to quantify progression saturation. An essential component of the approach is the design of virtual candidate compounds for which different concepts have been developed.

Progression saturation analysis of analog series using virtual candidate compounds

256th National Meeting (2018)

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