Abstract

QSAR is an analytical application that can be used to interpret the quantitative relationship between the biological activities of a particular molecule and its structure. The product of QSAR will then produce useful equations, images or models in either 2D or 3D form that would relate their biological responses or physical properties to their molecular structure. Hologram QSAR (HQSAR) uses molecular holograms and PLS to generate fragment-based structure-activity relationships. Unlike other 3D-QSAR methods, HQSAR does not require alignment of molecules, allowing automated analysis of very large data sets. CoMFA can be applied, as it often is, when the 3D structure of the receptor is unknown. To apply CoMFA, all that is needed are the activities and the 3D structures of the molecules. Comparative Molecular Similarity Indices Analysis (CoMSIA) is known as one of the newer 3D QSAR methodology. This technique is most commonly used in drug discovery to find the common features that are important in binding to the relevant biological receptor. The partial least squares (PLS) method was used to explore a linear correlation between the CoMFA and CoMSIA fields and the biological activity values.

Keywords

  • QSAR
  • HQSAR
  • CoMFA
  • CoMSIA and Partial least squares

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