Author(s): Muhammad Arba, Jasriati Jasriati


DOI: 10.5958/0974-360X.2020.00553.3   

Address: Muhammad Arba*, Jasriati Jasriati
Faculty of Pharmacy, Universitas Halu Oleo, Kendari, Indonesia - 93231.
*Corresponding Author

Published In:   Volume - 13,      Issue - 7,     Year - 2020

The vascular endothelial growth factor (VEGF) plays a crucial role in a wide range of cellular functions particularly in the angiogenesis process. Overexpression of vascular endothelial growth factor receptor (VEGFR) leads to several disease including cancer. Inhibition of the VEGFR constitutes the major strategies for combating cancer growth. The current investigation was aimed at identifying potential inhibitor of VEGFR2 by using structure-based pharmacophore modelling using LigandScout 4.3. Advanced software. The pharmacophore hypothesis consisted of 4 hydrophobic, one hydrogen bond donor, and two hydrogen bond acceptors, which was built using the structure of cognate ligand of VEGFR2 (608). Further, the pharmacophore model was used to screen hit molecule against ZINC database using Pharmit. Further, 102 virtual hits were retrieved, which were submitted to molecular docking simulation by employing iDock software. Molecular dynamics simulation of 50 ns for each three best hits complexed with VEGFR2 indicated that each ligand underwent minor conformational changes as indicated by the values of Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF). Prediction of affinities employing Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) method identified one hit molecule (i.e. Lig5/ZINC33025328) with significant affinity lower than that of cognate ligand, which indicated its potential as a novel VEGFR2 inhibitor.

Cite this article:
Muhammad Arba, Jasriati Jasriati. Structure-based Pharmacophore Modelling for identifying VEGFR2 Inhibitor. Research J. Pharm. and Tech. 2020; 13(7): 3129-3134. doi: 10.5958/0974-360X.2020.00553.3

1. Roskoski R. VEGF receptor protein–tyrosine kinases: Structure and regulation. Biochemical and Biophysical Research Communications. 2008: 375; 287–291.
2. Roskoski R. Vascular endothelial growth factor (VEGF) signaling in tumor progression. Critical Reviews in Oncology/Hematology. 2007: 62; 179–213.
3. Terman BI, Carrion ME, Kovacs E, Rasmussen BA, Eddy RL and Shows TB. Identification of a new endothelial cell growth factor receptor tyrosine kinase. Oncogene. 1991: 6; 1677–1683.
4. Terman BI, Dougher-Vermazen M, Carrion ME, Dimitrov D, Armellino DC, Gospodarowicz D and Bohlen P. Identification of the KDR tyrosine kinase as a receptor for vascular endothelial cell growth factor. Biochemical and Biophysical Research Communications. 1992: 187; 1579–1586.
5. Roskoski R. Vascular endothelial growth factor (VEGF) and VEGF receptor inhibitors in the treatment of renal cell carcinomas. Pharmacological Research. 2017: 120; 116–132.
6. Simons M, Gordon E and Claesson-Welsh L. Mechanisms and regulation of endothelial VEGF receptor signalling. Nature Reviews Molecular Cell Biology. 2016: 17; 611-625.
7. Hoeben A, Landuyt B, Highley MS, Wildiers H, Oosterom ATV and De Bruijn EA. Vascular Endothelial Growth Factor and Angiogenesis. Pharmacological Reviews. 2004: 56; 549-580.
8. Locascio LE, Donoghue DJ. KIDs rule: regulatory phosphorylation of RTKs. Trends in Biochemical Sciences. 2013: 38; 75–84.
9. Taylor SS, Kornev AP. Protein kinases: evolution of dynamic regulatory proteins. Trends in Biochemical Sciences. 2011: 36; 65–77.
10. Matsumoto T, Bohman S, Dixelius J, Berge T, Dimberg A, Magnusson P, Wang L, Wikner C, Qi JH, Wernstedt C, Wu J, Bruheim S, Mugishima H, Mukhopadhyay D, Spurkland A and Claesson-Welsh L. VEGF receptor‐2 Y951 signaling and a role for the adapter molecule TSAd in tumor angiogenesis. The EMBO Journal. 2005: 24; 2342-2353.
11. Kendall RL, Rutledge RZ, Mao X, Tebben AJ, Hungate RW and Thomas KA. Vascular Endothelial Growth Factor Receptor KDR Tyrosine Kinase Activity Is Increased by Autophosphorylation of Two Activation Loop Tyrosine Residues. Journal of Biological Chemistry. 1999: 274; 6453–6460.
12. Waltenberger J, Claesson-Welsh L, Siegbahn A, Shibuya M and Heldin CH. Different signal transduction properties of KDR and Flt1, two receptors for vascular endothelial growth factor. Journal of Biological Chemistry. 1994: 269; 26988–26995.
13. Roskoski R. Structure and regulation of Kit protein-tyrosine kinase—The stem cell factor receptor. Biochemical and Biophysical Research Communications. 2005: 338; 1307–1315.
14. Chow LQM, Eckhardt SG. Sunitinib: From Rational Design to Clinical Efficacy. Journal of Clinical Oncology. 2007: 25; 884–896.

15. Udhaya LB, Sangeetha N, Manisha P, Ramkumar K, Kavitha M and Sabina EP. Virtual Screening of Peptidyl Arginine Deiminase Type 4 Inhibiting Potential of Chosen Flavonoids. Research Journal of Pharmacy and Technology. 2018: 11; 753–757.
16. Suganya J, Manoharan S, Radha M, Singh N and Francis A. Identification and Analysis of Natural Compounds as Fungal Inhibitors from Ocimum sanctum using in silico Virtual Screening and Molecular Docking. Research Journal of Pharmacy and Technology. 2017: 10; 3369–3374.
17. Suganya J, Radha M, Manoharan S, Vinoba V and Francis A. Virtual Screening and Analysis of Bioactive Compounds of Momordica charantia against Diabetes using Computational Approaches. Research Journal of Pharmacy and Technology. 2017:10; 3353–3360.
18. Madhumathi G, Anbarasu K and Jayanthi S. Computational Insights on Inhibition of MSH3 Induced DNA Repair with Reserpine Analogs. Research Journal of Pharmacy and Technology. 2018: 11; 3765-3768.
19. Barua A, Kesavan K and Jayanthi S. Molecular Docking Studies of Plant Compounds to Identify Efficient Inhibitors for Ovarian Cancer. Research Journal of Pharmacy and Technology. 2018: 11; 3811-3815.
20. Kumar KA, Jagannath P and Saleshier MF. Discovery of Novel Flavonoid Analogues as Angiotensin Converting Enzyme Inhibitors based on Pharmacophore Modelling and Virtual Screening Techniques. Research Journal of Pharmacy and Technology. 2018: 11; 4370-4378.
21. Anbarasu K, Senthilkumar D and Jayanthi S. Deciphering the impact of R324L Mutation in Polycystin-1PKD Domain associated with Autosomal Dominant Polycystic Kidney Disease ( ADPKD ): A Molecular Dynamics Perspective. Research Journal of Pharmacy and Technology. 2017: 10; 3089–3094.
22. Kesavan K, Jayanthi S. Structure Based Virtual Screening and Molecular Dynamics Studies to Identify Novel APE1 Inhibitor from Seaweeds as Anti-glioma Agent. Research Journal of Pharmacy and Technology. 2017: 10; 2474–2478.
23. Singh K, Rambabu M and Jayanthi S. Designing BRAF specific inhibitors against melanoma. Research Journal of Pharmacy and Technology. 2018: 11; 3494-3498.
24. Shankari B, Rambabu M and Jayanthi S. Identification and Designing Inhibitors for Hepatocellular Carcinoma by Targeting Claudin-10. Research Journal of Pharmacy and Technology. 2018: 11; 3529-3533.
25. Wolber G, Langer T. LigandScout:  3-D Pharmacophores Derived from Protein-Bound Ligands and Their Use as Virtual Screening Filters. Journal of Chemical Information and Modeling. 2005: 45; 160–169.
26. Hodous BL, Geuns-Meyer SD, Hughes PE, Albrecht BK, Bellon S, Bready J, Caenepeel S, Cee VJ, Chaffee SC, Coxon A, Emery M, Fretland J, Gallant P, Gu Y, Hoffman D, Johnson RE, Kendall R, Kim JL, Long AM, Morrison M, Olivieri PR, Patel VF, Polverino A, Rose P, Tempest P, Wang L, Whittington DA and Zhao H. Evolution of a Highly Selective and Potent 2-(Pyridin-2-yl)-1,3,5-triazine Tie-2 Kinase Inhibitor. Journal of Medicinal Chemistry. 2007:50; 611–626.
27. Mysinger MM, Carchia M, Irwin JJ and Shoichet BK. Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking. Journal of Medicinal Chemistry. 2012: 55; 6582–6594.
28. Irwin JJ, Sterling T, Mysinger MM, Bolstad ES and Coleman RG. ZINC: A Free Tool to Discover Chemistry for Biology. Journal of Chemical Information and Modeling. 2012: 52; 1757–1768.
29. Sunseri J, Koes DR. Pharmit: interactive exploration of chemical space. Nucleic Acids Research. 2016: 44; W442–W448.
30. Li H, Leung K and Wong M. idock: A multithreaded virtual screening tool for flexible ligand docking. in 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). 2012: 77–84.
31. Sensharma P, Anbarasu K and Jayanthi S. In silico Identification of Novel Inhibitors against Plasmodium falciparum Triosephosphate Isomerase from Anti-Folate Agents. Research Journal of Pharmacy and Technology. 2018: 11; 3367-3370.
32. Arba M, Nur-Hidayat A, Surantaadmaja SI and Tjahjono DH. Pharmacophore-based virtual screening for identifying β5 subunit inhibitor of 20S proteasome. Computational Biology and Chemistry. 2018: 77; 64–71.
33. Case DA, Cheatham III TE, Darden T, Gohlke H, Luo R, Merz Jr. KM, Onufriev A, Simmerling C, Wang B and Woods RJ. The Amber biomolecular simulation programs. Journal of Computational Chemistry. 2005: 26; 1668–1688.
34. Salomon-Ferrer R, Götz AW, Poole D, Le Grand S and Walker RC. Routine microsecond molecular dynamics simulations with AMBER on GPUs. 2. Explicit solvent particle mesh ewald. Journal of Chemical Theory and Computation. 2013: 9; 3878–3888.
35. Maier JA, Martinez C, Kasavajhala K, Wickstrom L, Hauser KE and Simmerling C. ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB. Journal of Chemical Theory and Computation. 2015: 11(8); 3696-3713.
36. Wang JM, Wolf RM, Caldwell JW, Kollman PA and Case DA. Development and testing of a general amber force field. Journal of Computational Chemistry. 2004: 25; 1157–1174.
37. Jakalian A, Jack DB and Bayly CI. Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. Journal of Computational Chemistry. 2002: 23; 1623–1641.
38. Arba M, Ihsan S and Tjahjono DH. Computational approach toward targeting the interaction of porphyrin derivatives with Bcl-2. Journal of Applied Pharmaceutical Science. 2018: 8; 60–66.
39. Arba M, Ruslin, Kalsum WU, Alroem A, Muzakkar MZ, Usman I and Tjahjono DH. QSAR, Molecular Docking and Dynamics Studies of Quinazoline Derivatives as Inhibitor of Phosphatidylinositol 3-Kinase. Journal of Applied Pharmaceutical Science. 2018: 8(5); 001–009.
40. Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK and Olson AJ. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. Journal of Computational Chemistry. 1998: 19; 1639–1662.

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