{"id":1520,"date":"2015-08-24T16:12:02","date_gmt":"2015-08-24T15:12:02","guid":{"rendered":"https:\/\/nextmovesoftware.com\/blog\/?p=1520"},"modified":"2015-08-24T16:12:02","modified_gmt":"2015-08-24T15:12:02","slug":"biopolymer-canonicalisation-scaling-between-toolkits","status":"publish","type":"post","link":"https:\/\/nextmovesoftware.com\/blog\/2015\/08\/24\/biopolymer-canonicalisation-scaling-between-toolkits\/","title":{"rendered":"Biopolymer Canonicalisation Scaling Between Toolkits"},"content":{"rendered":"

We’ve previously shown using all-atom structure representations is a tractable approach to handling biologics (see https:\/\/nextmovesoftware.com\/blog\/2014\/11\/<\/a>). Handling biologics in this way allows you to reuse existing registration infrastructure (e.g. Canonical SMILES\/InChI\/CACTVS keys).<\/p>\n

At the Fall ACS ’15, Roger presented an update to this on-going work showing that many popular open-source cheminformatics toolkits can already handle peptides < 500 AA (the size of immunoglobulin heavy chains) in less than a second. We timed the generation of a canonical SMILES string (from the internal representation) over SwissProt. With the exception of Indigo\/CDK (that hit hard error limits) the lines stop due to time constraints.\n\n


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One thing the timings highlighted was recent improvements in RDKit that show faster canonicalisation and and reduced scatter (similar size structures ~ same amount of time). CDK was originally limited by the number of primes listed (it uses product of primes for refinement); patching<\/a> the CDK to use more primes allows it to encode biopolymers of over 1000 AA.<\/p>\n


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Roger’s full talk is available here:<\/p>\n


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