For many years the assumption that “Chemical compounds with similar
structures may have similar activities” has been a foundation for lead identification.
The similarity can be computed based upon topological, steric, electronic, and/or
physical properties. The chemical structure similarity search differs from the chemical
substructure search in that the former requires assessment of the properties of each
compound and thus no filter can be applied for skipping structures before they are assessed
to accelerate the computation. The latter can be accelerated by pre-screening
compounds and omitting those that miss one (or more) specified fragments from the
query. Moreover, three-dimensional similarity search requires superimposing many
conformation pairs for each compound in the library. This makes 3-D similarity
search algorithms time-consuming, and in general requires high performance computing (HPC) resources.
This review will summarize recent progress in the techniques for HPC-supported two and
three-dimensional chemical structure similarity search algorithms, and their applications in ligand-based
Keywords: Chemoinformatics, drug discovery, HPC, ligand-based virtual screening, structure similarity search.
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