Conformation‐Independent QSAR Study on Human Epidermal Growth Factor Receptor‐2 (HER2) Inhibitors

• Published in: ChemistrySelect (Weinheim) 2017-05, Vol.2 (13), p.3725-3731
• Main Authors: Duchowicz, Pablo R., Fioressi, Silvina E., Castro, Eduardo, Wróbel, Karolina, Ibezim, Nnenna E., Bacelo, Daniel E.
• Format: Article
• Language: English
• Subjects: Cancer; HER2; QSAR; Tyrosine kinase protein
• ISSN: 2365-6549; 2365-6549
• DOI: 10.1002/slct.201700436

Inhibition of HER2 (human epidermal growth factor receptor 2) expression and function is required in several cancer treatments. Numerous compounds with very different molecular structures have been suggested as HER2 inhibitors. Here we perform quantitative structure‐activity relationship (QSAR) analysis on 444 of such compounds to investigate the molecular properties that may influence its efficiency. Models based on 1D and 2D flexible molecular descriptors are proposed to develop simple models based solely on constitutional and topological molecular features. A large number of non‐conformational descriptors (17974) was used to thoroughly explore the structural characteristics that influence the HER2 inhibitory activity. Three different approaches were explored using: 1) Molecular Descriptors, 2) Flexible Molecular Descriptors, and 3) Hybrid Descriptors. A QSAR model for HER2 inhibitors was successfully developed. Some properties such as electronegativity, aromatic character, and the presence of amino groups appear as molecular characteristics that may have influence in the HER2 inhibitory activity. QSAR analysis was performed on 444 compounds with experimentally proven inhibition activity towards HER2 to investigate the molecular properties that may influence inhibition efficiency. Three different approaches based on 1D and 2D flexible molecular descriptors were explored. We succeed in developing simple models that do not require the knowledge of molecular conformation as part of structural representation. Electronegativity, aromaticity, and the presence of amino groups appear in the best predictive models as molecular characteristics that may influence HER2 inhibitory activity.