Integrated computational approaches on pyrazoline derivatives as B-Raf kinase inhibitors for the development of novel anticancer agents

Abstract

Raf kinases (rapidly accelerated fibrosarcoma) is related to retroviral oncogenes found in three different isoforms, A, B and C-Raf and played a significant part in mediating cell survival and proliferation. Various derivatives of B-Raf inhibitors are developed under laboratory level and some are under clinical trial studies. Here, we completed different computational techniques to identify features required for B-Raf kinase inhibitory activity by using 49 pyrazoline analogues. The development of pharmacophore, 3D QSAR analysis, virtual screening and docking studies were used for the development of novel compounds. For 3-dimentional-QSAR study, all compounds were divided into training and test set and determined the importance of substituents on 49 pyrazoline derivatives for B-Raf kinase inhibitory activity. The final models showed significant statistical values (R2 = 0.8325, Q2 = 0.5854) for atom based QSAR and (R2 = 0.7945, Q2 = 0.5808) for field based QSAR by using 3 partial least squares (PLS) factor. The validation results of 3D QSAR models showed R2 CV = 0.625, 0.5803, for both models (atom based and field based), consecutively. The docking studies of potent pyrazoline analogues (C1, C12, C14, C16n) showed good XP docking scores (-7.962, -8.864, -6.893, -7.171) with the interaction of amino acid residue such as PHE 583, CYS 532, SER 536 and ASP 594. The compounds ZINC13989686 and ZINC23908357 generated through virtual screening study showed their best docking scores -11.97 and -10.73 with receptor B-Raf kinase (PDB ID:2FB8). These data may be used for the development of potent compounds against B-Raf kinase.