Abstract
Abstract
Background
Fibroblast growth factor receptor 3 is known as a favorable aim in vast range of cancers, particularly in bladder cancer treatment. Pharmacophore and QSAR modeling approaches are broadly utilized for developing novel compounds for the determination of inhibitory activity versus the biological target. In this study, these methods employed to identify FGFR3 potential inhibitors.
Methods
To find the potential compounds for bladder cancer targeting, ZINC and NCI databases were screened. Pharmacophore and QSAR modeling of FGFR3 inhibitors were utilized for dataset screening. Then, with regard to several factors such as Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) properties and Lipinski’s Rule of Five, the recognized compounds were filtered. In further step, utilizing the flexible docking technique, the obtained compounds interactions with FGFR3 were analyzed.
Results
The best five compounds, namely ZINC09045651, ZINC08433190, ZINC00702764, ZINC00710252 and ZINC00668789 were selected for Molecular Dynamics (MD) studies. Off-targeting of screened compounds was also investigated through CDD search and molecular docking. MD outcomes confirmed docking investigations and revealed that five selected compounds could make steady interactions with the FGFR3 and might have effective inhibitory potencies on FGFR3.
Conclusion
These compounds can be considered as candidates for bladder cancer therapy with improved therapeutic properties and less adverse effects.
Publisher
Springer Science and Business Media LLC
Subject
General Biochemistry, Genetics and Molecular Biology,General Medicine
Reference77 articles.
1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49.
2. Debela DT, Muzazu SGY, Heraro KD, Ndalama MT, Mesele BW, Haile DC, et al. New approaches and procedures for cancer treatment: current perspectives. SAGE Open Med. 2021;9:20503121211034370.
3. Zheng G, Sundquist K, Sundquist J, Försti A, Hemminki O, Hemminki K. Bladder and upper urinary tract cancers as first and second primary cancers. Cancer Rep. 2021;4(6): e1406.
4. Kamoun A, de Reyniès A, Allory Y, Sjödahl G, Robertson AG, Seiler R, et al. A consensus molecular classification of muscle-invasive bladder cancer. Eur Urol. 2020;77(4):420–33.
5. Isharwal S, Konety B. Non-muscle invasive bladder cancer risk stratification. Indian J Urol. 2015;31(4):289.