In this webinar, Matt Segall and Peter Hunt present a flexible and intuitive framework in which similarity relationships can be interactively navigated to quickly interpret the results, identify important structure-activity relationships (SAR) and use that SAR in new compound design.
We illustrate this with applications of chemical and property spaces, clustering, activity cliff detection and matched molecular pairs (MMP) analysis in hit finding and lead optimisation.
Many fingerprinting methods may be used to compare compounds and identify those that are similar in terms of structure or properties. These are used in a wide range of analyses, such as clustering, activity landscapes and MMP, to find SAR that can guide the further optimisation of compounds and series. However, the interpretation of similarities and the resulting analyses can be challenging, presenting a barrier to the effective application of these methods.
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