Research ArticleComputational investigation of TGF-β receptor inhibitors for treatment of idiopathic pulmonary fibrosis: Field-based QSAR model and molecular dynamics simulation
Graphical abstract
Introduction
Idiopathic pulmonary fibrosis (IPF) is consider to vary dramatically in an extent of disease that is chronic, progressive and irreversible, which causes severe impairment in patients that need long-term treatment (Duck et al., 2015; Ohkouchi et al., 2015). IPF is the most common, lethal among the idiopathic and interstitial pulmonary (IIP) and estimated to affect patients vary from 14 to 43 of per 100,000 persons (Collum et al., 2017; Xu et al., 2016). IPF is characterized by accumulation of mesenchymal cells in connective tissue within alveolar walls and invade into alveolar air space, which decrease vital capacity (Homma et al., 2015; Xu et al., 2017). As for IPF in human, it is characterized microscopically usual interstitial pneumonia (UIP), which is a member of IIP (Lilja-Maula et al., 2014). Moreover, pathology features of IPF contain fibroproliferative foci and over-deposition of extracellular matrix (ECM), and the histopatholigical alterations of ECM are predominantly discovered in sub-pleural regions (Zhang et al., 2017). A previousage and age-sex-matched showed that IPF was an isolated venture factor for these comorbidities. Although the aetiology of IPF is still indistinct, the lung factors show that it might do harm to the pulmonary parenchyma generating an inflammatory response and subsequent fibrosis which has been implicated to be crucial for the development of the disease (Smoktunowicz et al., 2015).
The polypeptides in TGF-β family were first obtained by de Larco and Todaro in the 1970s making up a group of compounds called the sarcoma growth factor (SGF). These compounds are also able to cause malignant transformation in rat’s kidney fibroblasts (Poniatowski et al., 2015). Cytokines of the TGF-β superfamily are composed of a diverse range of proteins and contain the dimeric proteins with conserved structures, which could regulate numerous aspects of physiological processes, including embryonic development, homeostasis, wound healing, chemotaxis, and cell cycle control (Leask and Abraham, 2004). As an inactive ‘latent’ complex, the TGF-β protein is a TGF-β dimer in a non-covalent complex with two prosegments which are often linked with one of several ‘latent TGF-β binding proteins’. The latent complex which may stabilize and target latent TGF-β to the sequestered extracellular matrix represents a significant safeguard against ‘inadvertent’ activation. Thus, the matrix acts as a reservoir in which TGF-β can be recruited readily without the need of new synthesis (Derynck et al., 2001). Over the last decade, some important papers in TGF-β signaling have been reported from molecular level to cellular level (Shi and Massagué, 2003). In human, over-expression and excitation of transforming growth factor β (TGF-β) as an outcome for reduplicating alveolar epithelial damage and disrupted epithelial repair are regarded as an essential part in the progress of fibrosis (Agassandian et al., 2015; Margadant and Sonnenberg, 2010). Moreover, TGF-β may be best known as its regulatory infection on fibrogenesis in humans which is a family member of dimeric polypeptide growth factors (Shi and Massagué, 2003). The human gene code of TGF-β is located on chromosome 19q13.TGF-β plays a crucial role in growth of tissue fibrosis and inhibition of TGF-β that biological activity has shown potent proinflammatory outcomes (Lahn et al., 2005).
However, the developments of TGF-β receptor inhibitors have been affected through its toxicity (Adamali and Maher, 2012; Porte and Jenkins, 2014). All those substantial evidences show there are not distinct inhibitors of the TGF-β that have revealed as therapies for IPF. This is the first time quantitative structure-activity relationship (QSAR) model is used in statistics and computational chemistry that makes up for our experimental approach which is linked to chemical structures of biological activities (Martinez et al., 2015). Such matrix can be utilized to conduct a prediction on the bioactivities of compounds designed and determination can be made whether these compounds could really be synthesized and tested. Molecular dynamics (MD) simulation explained the interactions of the receptor complexes with its ligand very clearly, and the result is consistent with QSAR model (Ishikawa et al., 2010).
In this context, the application of field-based QSAR model based on molecular alignment studies was carried out to predict the activity of 7-substituted-pyrazolo [4, 3-b] pyridine series and interactive fields might raise their activity (Sabat et al., 2017). Moreover, the predictive capacity of the generated model was verified by test set compounds. In field-based QSAR model, the results that would be came out through this could provide prominent ideology for the binding process and prescribe available information for developing new potent TGF-β receptor inhibitors.
Section snippets
Data set and biological activity
TGF-β receptor inhibitors were obtained from some distinct paper containing inhibitory data in vitro enzyme. The 7-substituted-pyrazolo [4.3-b] pyridine series investigated in this literature were synthesized and their bio-activities were tested by Douglas R. Dougan and co-workers (Sabat et al., 2017). The 7-substituted-pyrazolo [4, 3-b] pyridine derivatives are representative inhibitors with highly potent inhibitory activity towards TGF-β receptor. This series of compounds exhibited a broad
Data set and biological activity
Molecular field-based QSAR study was performed based on biological activity (pIC50) data and field similarity score (alignment) for the molecules. The score of field similarity to the molecules was calculated on the surface and electrostatic properties which include positive, negative electrostatic fields, van der Waals and hydrophobic effects on the molecules. The IPF activity of 7-substituted-pyrazolo [4.3-b] pyridine series was defined with pIC50 value in evaluating the structure–activity
Conclusions
In the present study, we first proposed a field-based model, which was constructed based on the molecular filed of the 38 TGF-β receptor inhibitors a constructed field-based QSAR model has shown good predictability in internal and external validations. Moreover, it could identify the key structural features affecting the activity. The best ligand-based model shows good predictive ability according to their Q2, R2training, and R2test values, and all those outcomes showed insight into the key
Conflict of interest statement
The authors declare that they have no conflicts of interest.
Acknowledgements
The work was financially supported by the Fund for long-term training of young teachers in Shenyang Pharmaceutical University (ZQN2015002), the National Natural Science Foundation of Liaoning province (Grant No. 20170540854) and Training Program Foundation for the Distinguished Young Scholars of University in Liaoning Province (LJQ2015109). Liaoning Provincial Department of Education Research Project (LFD2017004) Liaoning Province Natural Science Foundation (201602588) Shenyang Science and
References (33)
- et al.
VCAM-1 is a TGF-beta1 inducible gene upregulated in idiopathic pulmonary fibrosis
Cell. Signal.
(2015) - et al.
Usefulness of a disease severity staging classification system for IPF in Japan: 20 years of experience from empirical evidence to randomized control trial enrollment
Respir. Investig.
(2015) - et al.
Emerging new technologies in pharmacogenomics: rapid SNP detection, molecular dynamic simulation, and QSAR analysis methods to validate clinically important genetic variants of human ABC transporter ABCB1 (P-gp/MDR1)
Pharmacol. Ther.
(2010) - et al.
Comparative study of transforming growth factor-beta signalling and regulatory molecules in human and canine idiopathic pulmonary fibrosis
J. Comp. Pathol.
(2014) - et al.
Design, synthesis and optimization of 7-substituted-pyrazolo[4,3-b]pyridine ALK5 (activin receptor-like kinase 5) inhibitors
Bioorg. Med. Chem. Lett.
(2017) - et al.
Mechanisms of TGF-β signaling from cell membrane to the nucleus
Cell
(2003) - et al.
Genetic polymorphism in matrix metalloproteinase-9 and transforming growth factor-beta1 and susceptibility to combined pulmonary fibrosis and emphysema in a Chinese population
Kaohsiung J. Med. Sci.
(2017) - et al.
miR-18a-5p inhibits sub-pleural pulmonary fibrosis by targeting TGF-beta receptor II
Mol. Ther.
(2017) - et al.
Current and novel drug therapies for idiopathic pulmonary fibrosis
Drug Des. Dev. Ther.
(2012) - et al.
Combined 2D and 3D-QSAR, molecular modelling and docking studies of pyrazolodiazepinones as novel phosphodiesterase 2 inhibitors
SAR QSAR Environ. Res.
(2014)
High content pharmacophores from molecular fields: a biologically relevant method for comparing and understanding ligands
Curr. Comput. Aided Drug Des.
Pulmonary hypertension associated with idiopathic pulmonary fibrosis: current and future perspectives
Can. Respir. J.
TGF-beta signaling in tumor suppression and cancer progression
Nat. Genet.
Applying ligands profiling using multiple extended electron distribution based field templates and feature trees similarity searching in the discovery of new generation of urea-based antineoplastic kinase inhibitors
Plos One
IPF care: a support program for patients with idiopathic pulmonary fibrosis treated with pirfenidone in Europe
Adv. Ther.
Comparative molecular field analysis and molecular dynamics studies of alpha/beta hydrolase domain containing 6 (ABHD6) inhibitors
J. Mol. Model.
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