From the post:
In new research published in Journal of Systems Chemistry, Sijbren Otto and colleagues have provided the first experimental approach towards molecular networks that can predict bioactivity based on an assessment of molecular similarity.
Molecular similarity is an important concept in drug discovery. Molecules that share certain features such as shape, structure or hydrogen bond donor/acceptor groups may have similar properties that make them common to a particular target. Assessment of molecular similarity has so far relied almost exclusively on computational approaches, but Dr Otto reasoned that a measure of similarity might be obtained by interrogating the molecules in solution experimentally.
Important work for drug discovery but there are semantic lessons here as well:
Tests for similarity/sameness are domain specific.
Which means there are no universal tests for similarity/sameness.
Lacking universal tests for similarity/sameness, we should focus on developing documented and domain specific tests for similarity/sameness.
Domain specific tests provide quicker ROI than less useful and doomed universal solutions.
Documented domain specific tests may, no guarantees, enable us to find commonalities between domain measures of similarity/sameness.
But our conclusions will be based on domain experience and not projection from our domain onto others, less well known domains.