Design, 3D QSAR modeling and docking of TGF-β type I inhibitors to target cancer. (October 2018)

• Record Type: Journal Article
• Authors: Ajay Kumar, TV; Athavan, Alias Anand S; Loganathan, C; Saravanan, K; Kabilan, S; Parthasarathy, V
• Is Part Of: Computational biology and chemistry. Volume 76(2018)
• Page Start: 232
• Page End: 244
• Publication Date: 2018-10
• Subjects: TGF-β superfamily -- Serine/threonine-kinase receptors -- Binding database -- 3D-QSAR -- TGF-β-type I -- TGF-β inhibitors -- Pharmacophore -- SB431542 -- Galunisertib; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2018.07.011
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: Among 63 molecules from the binding database, the pharmacophore AAAHR.27 was identified using "PHASE" module, Schrödinger. The pharmacophore AAAHR was used to screen the molecules from the NCI, ZINC and Maybridge database. All the screened molecules were docked with TGF–β type I protein (PDB ID:1VJY) using GLIDE module of Schrödinger. Hit molecules were screened using docking score and ADME properties. 7 leads were identified as potent TGF-β type I inhibitor when compared to the standard inhibitors SB431542 and Galunisertib. Abstract: Transforming growth factor-β (TGF-β) family members plays a vital role in regulating hormonal function, bone formation, tissue remodeling, and erythropoiesis, cell growth and apoptosis. TGF-β super-family members mediate signal transduction via serine/threonine kinase receptors located on the cell membrane. Variation in expression of the TGF-β type I and II receptors in the cancer cells compromise its tumor suppressor activities which direct to oncogenic functions. The present study was aimed to screen the potent TGF-β type I inhibitors through atom based 3D-QSAR and pharmacophore modelling. For this purpose, we have chosen known TGF-β type I inhibitors from the binding database. The PHASE module of Schrodinger identified the best Pharmacophore model which includes three hydrogen bond acceptors (A), one hydrophobic region (H), and one ring (R) as the structural features. The top pharmacophore model AAAHR.27 was chosen with the R 2 value of 0.94 and validated externally using molecules of the test set. Moreover the AAAHR.27 model underwent virtual screening using the molecules from the NCI, ZINC and Maybridge database. The screened molecules were further filtered using molecular docking and ADME properties prediction. Additionally, the 7 lead molecules were compared with a newly identified compound "SB431542" (well known TGF-β type I receptor inhibitor) and Galunisertib, a small molecule inhibitor of TGF-β type I, under clinical development (phase II trials) using the docking score and other binding properties. Also a top scored screened molecule from our study has been compared and confirmed using molecular dynamic simulation studies. By this way, we have obtained 7 distinct drug-like TGF-β type I inhibitors which can be beneficial in suppressing cancers reported with up-regulation of TGF-β type I. This result highlights the guidelines for designing molecules with TGF-β Type I inhibitory properties.