QSAR – Modelování kvantitativních vztahů mezi strukturou a aktivitou chemických látek

  • C. Škuta CZ-OPENSCREEN: Národní infrastruktura pro chemickou biologii, Ústav molekulární genetiky AV ČR v.v.i., Praha
  • D. Svozil CZ-OPENSCREEN: Národní infrastruktura pro chemickou biologii, Ústav molekulární genetiky AV ČR v.v.i., Praha | CZ-OPENSCREEN: Národní infrastruktura pro chemickou biologii, Laboratoř informatiky a chemie, Fakulta chemické technologie, Vysoká škola chemicko-technologická v Praze, Praha
Klíčová slova: QSAR, modelování biologické aktivity, vytěžování znalostí z dat, virtuální screening, oblast použitelnosti, konformní predikce

Abstrakt

Quantitative structure–activity relationship (QSAR) modelling is one of the most popular techniques of virtual screening used to predict the activity of a compound toward a biological target. While QSAR classification models are able to predict whether a compound is active or inactive (class) toward a target, regression models try to predict its exact activity value. To find the relationship between the structure and activity of a compound, common machine learning methods are employed (e.g., Support Vector Machines, Random Forest, Neural Networks etc.) together with diverse types of compound descriptors (e.g., physico-chemical properties, structural keys, binary fingerprints etc.). QSAR models are generally very fast and, when a correct approach to their validation and applicability domain setting is used, also reliable. They became a common part of computational drug design workflows employed to detect new drug candidates, elucidate their side/adverse effects or assess their potential toxicity risks.

Publikované
2017-11-15
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