Rational Design of Anti-Angiogenic Peptides to Inhibit VEGF/VEGFR2 Interactions
for Cancer Therapeutics

Samaneh      Ghasemali; Safar      Farajnia; Abolfazl      Barzegar; Mohammad      Rahmati; Babak      Negahdari; Leila      Rahbarnia; Hamidreza      Yousefi-Nodeh

doi:10.2174/1871520621666211118104051

Abstract

Background: Angiogenesis is a critical physiological process that plays a key role in tumor progression, metastatic dissemination, and invasion. In the last two decades, the vascular endothelial growth factor (VEGF) signaling pathway has been the area of extensive researches. VEGF executes its special effects by binding to vascular endothelial growth factor receptors (VEGFRs), particularly VEGFR-2.

Objective: The inhibition of VEGF/VEGFR2 interaction is known as an effective cancer therapy strategy. The current study pointed to design and model an anti-VEGF peptide based on VEGFR2 binding regions.

Methods: The large-scale peptide mutation screening was used to achieve a potent peptide with high binding affinity to VEGF for possible application in inhibition of VEGF/VEGFR2 interaction. The AntiCP and Peptide Ranker servers were used to generate the possible peptides library with anticancer activities and prediction of peptides bioactivity. Then, the interaction of VEGF and all library peptides were analyzed using Hex 8.0.0 and ClusPro tools. A number of six peptides with favorable docking scores were achieved. All of the best docking scores of peptides in complexes with VEGF were evaluated to confirm their stability, using molecular dynamics simulation (MD) with the help of the GROMACS software package.

Results: As a result, two antiangiogenic peptides with 13 residues of PepA (NGIDFNRDFFLGL) and PepC (NGIDFNRDKFLFL) were achieved and introduced to inhibit VEGF/VEGFR2 interactions.

Conclusion: In summary, this study provided new insights into peptide-based therapeutics development for targeting VEGF signaling pathway in tumor cells. PepA and PepC are recommended as potentially promising anticancer agents for further experimental evaluations.

Keywords: Angiogenesis, bioinformatics tools, peptide design, VEGF-A, VEGFR-2, molecular dynamics simulation.

« Previous Next »

Graphical Abstract

[1] 
Batlle, R.; Andrés, E.; Gonzalez, L.; Llonch, E.; Igea, A.; Gutierrez-Prat, N.; Berenguer-Llergo, A.; Nebreda, A.R. Regulation of tumor angiogenesis and mesenchymal-endothelial transition by p38α through TGF-β and JNK signaling. Nat. Commun.,  2019, 10(1), 3071.
[http://dx.doi.org/10.1038/s41467-019-10946-y] [PMID:  31296856] 
[2] 
Ikeuchi, T.; de Vega, S.; Forcinito, P.; Doyle, A.D.; Amaral, J.; Rodriguez, I.R.; Arikawa-Hirasawa, E.; Yamada, Y. Extracellular protein fibulin-7 and its C-terminal fragment have in vivo antiangiogenic activity. Sci. Rep.,  2018, 8(1), 17654.
[http://dx.doi.org/10.1038/s41598-018-36182-w] [PMID:  30518776] 
[3] 
Li, W.; Yalcin, M.; Bharali, D.J.; Lin, Q.; Godugu, K.; Fujioka, K.; Keating, K.A.; Mousa, S.A. Pharmacokinetics, biodistribution, and anti-angiogenesis efficacy of diamino propane tetraiodothyroacetic acid-conjugated biodegradable polymeric nanoparticle. Sci. Rep.,  2019, 9(1), 9006.
[http://dx.doi.org/10.1038/s41598-019-44979-6] [PMID:  31227723] 
[4] 
Ferrara, N.; Kerbel, R.S. Angiogenesis as a therapeutic target. Nature,  2005, 438(7070), 967-974.
[http://dx.doi.org/10.1038/nature04483] [PMID:  16355214] 
[5] 
Sagar, S.M.; Yance, D.; Wong, R.K. Natural health products that inhibit angiogenesis: A potential source for investigational new agents to treat cancer-Part 1. Curr. Oncol.,  2006, 13(1), 14-26.
[http://dx.doi.org/10.3747/co.v13i1.77] [PMID:  17576437] 
[6] 
Chung, A.S.; Ferrara, N. Developmental and pathological angiogenesis. Annu. Rev. Cell Dev. Biol.,  2011, 27, 563-584.
[http://dx.doi.org/10.1146/annurev-cellbio-092910-154002] [PMID:  21756109] 
[7] 
Carmeliet, P.; Jain, R.K. Principles and mechanisms of vessel normalization for cancer and other angiogenic diseases. Nat. Rev. Drug Discov.,  2011, 10(6), 417-427.
[http://dx.doi.org/10.1038/nrd3455] [PMID:  21629292] 
[8] 
Melincovici, C.S.; Boşca, A.B.; Şuşman, S.; Mărginean, M.; Mihu, C.; Istrate, M.; Moldovan, I.M.; Roman, A.L.; Mihu, C.M. Vascular endothelial growth factor (VEGF) - key factor in normal and pathological angiogenesis. Rom. J. Morphol. Embryol.,  2018, 59(2), 455-467.
[PMID:  30173249] 
[9] 
Seyedarabi, A.; Cheng, L.; Zachary, I.; Djordjevic, S. Production of soluble human vascular endothelial growth factor VEGF-A165-heparin binding domain in Escherichia coli. PLoS One,  2013, 8(2) ,e55690.
[http://dx.doi.org/10.1371/journal.pone.0055690] [PMID:  23409021] 
[10] 
Ferrara, N.; Adamis, A.P. Ten years of anti-vascular endothelial growth factor therapy. Nat. Rev. Drug Discov.,  2016, 15(6), 385-403.
[http://dx.doi.org/10.1038/nrd.2015.17] [PMID:  26775688] 
[11] 
Smith, D.A.; Di, L.; Kerns, E.H. The effect of plasma protein binding on in vivo efficacy: Misconceptions in drug discovery. Nat. Rev. Drug Discov.,  2010, 9(12), 929-939.
[http://dx.doi.org/10.1038/nrd3287] [PMID:  21119731] 
[12] 
Zahiri, J.; Khorsand-Ghaffari, B.; Zade, R.S.H.; Kargar, M.; Yousefi, A.A; Mahdevar, G. AntAngioCOOL: an R package for computational detection of anti-angiogenic peptides. J. Trans Med.,  2017, 17(1), 71.
[http://dx.doi.org/10.1186/s12967-019-1813-7] [PMID:  30832671] 
[13] 
Otvos, L., Jr; Wade, J.D. Current challenges in peptide-based drug discovery. Front Chem.,  2014, 2, 62.
[http://dx.doi.org/10.3389/fchem.2014.00062] [PMID:  25152873] 
[14] 
Craik, D.J.; Fairlie, D.P.; Liras, S.; Price, D. The future of peptide-based drugs. Chem. Biol. Drug Des.,  2013, 81(1), 136-147.
[http://dx.doi.org/10.1111/cbdd.12055] [PMID:  23253135] 
[15] 
Sulochana, K.N.; Ge, R. Developing antiangiogenic peptide drugs for angiogenesis-related diseases. Curr. Pharm. Des.,  2007, 13(20), 2074-2086.
[http://dx.doi.org/10.2174/138161207781039715] [PMID:  17627540] 
[16] 
Wijma, H.J.; Janssen, D.B. Computational design gains momentum in enzyme catalysis engineering. FEBS J.,  2013, 280(13), 2948-2960.
[http://dx.doi.org/10.1111/febs.12324] [PMID:  23647554] 
[17] 
Yeung, N.; Lin, Y-W.; Gao, Y-G.; Zhao, X.; Russell, B.S.; Lei, L.; Miner, K.D.; Robinson, H.; Lu, Y. Rational design of a structural and functional nitric oxide reductase. Nature,  2009, 462(7276), 1079-1082.
[http://dx.doi.org/10.1038/nature08620] [PMID:  19940850] 
[18] 
Kazlauskas, R.J.; Bornscheuer, U.T. Finding better protein engineering strategies. Nat. Chem. Biol.,  2009, 5(8), 526-529.
[http://dx.doi.org/10.1038/nchembio0809-526] [PMID:  19620988] 
[19] 
Höhne, M.; Schätzle, S.; Jochens, H.; Robins, K.; Bornscheuer, U.T. Rational assignment of key motifs for function guides in silico enzyme identification. Nat. Chem. Biol.,  2010, 6(11), 807-813.
[http://dx.doi.org/10.1038/nchembio.447] [PMID:  20871599] 
[20] 
Yin, H.; Slusky, J.S.; Berger, B.W.; Walters, R.S.; Vilaire, G.; Litvinov, R.I.; Lear, J.D.; Caputo, G.A.; Bennett, J.S.; DeGrado, W.F. Computational design of peptides that target transmembrane helices. Science,  2007, 315(5820), 1817-1822.
[http://dx.doi.org/10.1126/science.1136782] [PMID:  17395823] 
[21] 
Korendovych, I.V. Rational and semirational protein design. Protein Eng.,  2018, 1685, 15-23.
[http://dx.doi.org/10.1007/978-1-4939-7366-8_2] [PMID:  29086301] 
[22] 
Sun, Q.; Xu, X. A promising future for peptides in ophthalmology: Work effectively and smartly. Curr. Med. Chem.,  2015, 22(8), 1030-1040.
[http://dx.doi.org/10.2174/0929867322666150114163308] [PMID:  25620097] 
[23] 
Rosca, E.V.; Koskimaki, J.E.; Rivera, C.G.; Pandey, N.B.; Tamiz, A.P.; Popel, A.S. Anti-angiogenic peptides for cancer therapeutics. Curr. Pharm. Biotechnol.,  2011, 12(8), 1101-1116.
[http://dx.doi.org/10.2174/138920111796117300] [PMID:  21470139] 
[24] 
Rasafar, N.; Barzegar, A.; Mehdizadeh Aghdam, E. Design and development of high affinity dual anticancer peptide-inhibitors against p53-MDM2/X interaction. Life Sci.,  2020, 245 ,117358.
[http://dx.doi.org/10.1016/j.lfs.2020.117358] [PMID:  32001262] 
[25] 
Rasafar, N.; Barzegar, A.; Mehdizadeh Aghdam, E. Structure-based designing efficient peptides based on p53 binding site residues to disrupt p53-MDM2/X interaction. Sci. Rep.,  2020, 10(1), 11449.
[http://dx.doi.org/10.1038/s41598-020-67510-8] [PMID:  32651397] 
[26] 
Rismani, E.; Rahimi, H.; Arab, S.S.; Azadmanesh, K.; Karimipoor, M.; Teimoori-Toolabi, L. Computationally design of inhibitory peptides against Wnt signaling pathway: In silico insight on complex of DKK1 and LRP6. Int. J. Pept. Res. Ther.,  2018, 24(1), 49-60.
[http://dx.doi.org/10.1007/s10989-017-9589-1] 
[27] 
Laskowski, R.A.; Swindells, M.B. LigPlot+: Multiple ligand-protein interaction diagrams for drug discovery. J. Chem. Inf. Model.,  2011, 51(10), 2778-2786.
[http://dx.doi.org/10.1021/ci200227u] 
[28] 
Guex, N.; Peitsch, M.C. SWISS‐MODEL and the Swiss‐Pdb viewer: an environment for comparative protein modeling. Electrophoresis,  1997, 18(15), 2714-2723.
[http://dx.doi.org/10.1002/elps.1150181505] 
[29] 
E-Kobon, T.; Thongararm, P.; Roytrakul, S.; Meesuk, L.; Chumnanpuen, P. Prediction of anticancer peptides against MCF-7 breast cancer cells from the peptidomes of Achatina fulica mucus fractions. Comput. Struct. Biotechnol. J.,  2015, 14, 49-57.
[http://dx.doi.org/10.1016/j.csbj.2015.11.005] [PMID:  26862373] 
[30] 
Mooney, C.; Haslam, N.J.; Pollastri, G.; Shields, D.C. Towards the improved discovery and design of functional peptides: Common features of diverse classes permit generalized prediction of bioactivity. PLoS One,  2012, 7(10) ,e45012.
[http://dx.doi.org/10.1371/journal.pone.0045012] [PMID:  23056189] 
[31] 
Roy, A.; Kucukural, A.; Zhang, Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nat. Protoc.,  2010, 5(4), 725-738.
[http://dx.doi.org/10.1038/nprot.2010.5] [PMID:  20360767] 
[32] 
Yang, J.; Zhang, Y. I-TASSER server: New development for protein structure and function predictions. Nucleic Acids Res.,  2015, 43(W1), W174-W181.
[http://dx.doi.org/10.1093/nar/gkv342] [PMID:  25883148] 
[33] 
Yang, J.; Yan, R.; Roy, A.; Xu, D.; Poisson, J.; Zhang, Y. The I-TASSER suite: Protein structure and function prediction. Nat. Methods,  2015, 12(1), 7-8.
[http://dx.doi.org/10.1038/nmeth.3213] [PMID:  25549265] 
[34] 
Kelley, L.A.; Mezulis, S.; Yates, C.M.; Wass, M.N.; Sternberg, M.J. The phyre2 web portal for protein modeling, prediction and analysis. Nat. Protoc.,  2015, 10(6), 845-858.
[http://dx.doi.org/10.1038/nprot.2015.053] [PMID:  25950237] 
[35] 
Barzegar, A. Antioxidant activity of polyphenolic myricetin in vitro cell- free and cell-based systems. Mol. Biol. Res. Commun.,  2016, 5(2), 87-95.
[PMID:  28097162] 
[36] 
Lamiable, A.; Thévenet, P.; Rey, J.; Vavrusa, M.; Derreumaux, P.; Tufféry, P. PEP-FOLD3: faster de novo structure prediction for linear peptides in solution and in complex. Nucleic Acids Res.,  2016, 44(W1), W449-W454.
[http://dx.doi.org/10.1093/nar/gkw329] [PMID:  27131374] 
[37] 
Maupetit, J.; Derreumaux, P.; Tuffery, P. PEP-FOLD: An online
	resource for de novo peptide structure prediction. Nucleic Acids
	Res., 2009, 37(suppl_2), W498-W503. 
[38] 
Benkert, P.; Tosatto, S.C.; Schomburg, D. QMEAN: A comprehensive scoring function for model quality assessment. Proteins,  2008, 71(1), 261-277.
[http://dx.doi.org/10.1002/prot.21715] [PMID:  17932912] 
[39] 
Wiederstein, M.; Sippl, M.J. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res.,  2007, 35(Suppl. 2), W407-W410.
[http://dx.doi.org/10.1093/nar/gkm290] [PMID:  17517781] 
[40] 
Wang, Z.; Sun, H.; Shen, C.; Hu, X.; Gao, J.; Li, D.; Cao, D.; Hou, T. Combined strategies in structure-based virtual screening. Phys. Chem. Chem. Phys.,  2020, 22(6), 3149-3159.
[http://dx.doi.org/10.1039/C9CP06303J] [PMID:  31995074] 
[41] 
Sharifi, M.; Ezzati Nazhad Dolatabadi, J.; Fathi, F.; Zakariazadeh, M.; Barzegar, A.; Rashidi, M.; Tajalli, H.; Rashidi, M.R. Surface plasmon resonance and molecular docking studies of bovine serum albumin interaction with neomycin: Kinetic and thermodynamic analysis. Bioimpacts,  2017, 7(2), 91-97.
[http://dx.doi.org/10.15171/bi.2017.12] [PMID:  28752073] 
[42] 
Baghban, R.; Ghasemali, S.; Farajnia, S.; Hoseinpoor, R.; Andarzi, S.; Zakariazadeh, M. Design and in silico evaluation of a novel cyclic disulfide-rich anti-vegf peptide as a potential antiangiogenic drug. Int. J. Pept. Res. Ther.,  2021, 27, 2245-2256.
[http://dx.doi.org/10.1007/s10989-021-10250-8] 
[43] 
Gargari, S.A.; Barzegar, A. Simulations on the dual effects of flavonoids as suppressors of Aβ42 fibrillogenesis and destabilizers of mature fibrils. Sci. Rep.,  2020, 10(1), 16636.
[http://dx.doi.org/10.1038/s41598-020-72734-9] [PMID:  33024142] 
[44] 
Oostenbrink, C.; Villa, A.; Mark, A.E.; van Gunsteren, W.F. A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6. J. Comput. Chem.,  2004, 25(13), 1656-1676.
[http://dx.doi.org/10.1002/jcc.20090] [PMID:  15264259] 
[45] 
Berendsen, H.J.; Postma, J.P.; van Gunsteren, W.F.; Hermans, J. Interaction models for water in relation to protein hydration.In: Intermolecular Forces; Pullman, B., Ed.; Springer: Dordrecht, 1981, Vol. 14, pp. 331-342.
[http://dx.doi.org/10.1007/978-94-015-7658-1_21] 
[46] 
Pettersen, E.F.; Goddard, T.D.; Huang, C.C.; Couch, G.S.; Greenblatt, D.M.; Meng, E.C.; Ferrin, T.E. UCSF Chimera-A visualization system for exploratory research and analysis. J. Comput. Chem.,  2004, 25(13), 1605-1612.
[http://dx.doi.org/10.1002/jcc.20084] [PMID:  15264254] 
[47] 
Humphrey, W.; Dalke, A.; Schulten, K. VMD: Visual molecular
	dynamics. J. Mol. Graph., 1996, 14(1), 33-38, 27-28.. 
[http://dx.doi.org/10.1016/0263-7855(96)00018-5] [PMID:  8744570] 
[48] 
Kozakov, D.; Hall, D.R.; Xia, B.; Porter, K.A.; Padhorny, D.; Yueh, C.; Beglov, D.; Vajda, S. The ClusPro web server for protein-protein docking. Nat. Protoc.,  2017, 12(2), 255-278.
[http://dx.doi.org/10.1038/nprot.2016.169] [PMID:  28079879] 
[49] 
London, N.; Movshovitz-Attias, D.; Schueler-Furman, O. The structural basis of peptide-protein binding strategies. Structure,  2010, 18(2), 188-199.
[http://dx.doi.org/10.1016/j.str.2009.11.012] [PMID:  20159464] 
[50] 
Genheden, S.; Ryde, U. The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opin. Drug Discov.,  2015, 10(5), 449-461.
[http://dx.doi.org/10.1517/17460441.2015.1032936] [PMID:  25835573] 
[51] 
Andarzi Gargari, S.; Barzegar, A.; Tarinejad, A. The role of phenolic OH groups of flavonoid compounds with H-bond formation ability to suppress amyloid mature fibrils by destabilizing β-sheet conformation of monomeric Aβ17-42. PLoS One,  2018, 13(6) ,e0199541.
[http://dx.doi.org/10.1371/journal.pone.0199541] [PMID:  29953467] 
[52] 
Ghasemali, S.; Farajnia, S.; Barzegar, A.; Rahmati-Yamchi, M.; Baghban, R.; Rahbarnia, L.; Nodeh, H.R.Y. New developments in anti-angiogenic therapy of cancer, review and update. Anticancer. Agents Med. Chem.,  2021, 21(1), 3-19.
[http://dx.doi.org/10.2174/1871520620666200817103219] [PMID:  32807068] 
[53] 
Farzaneh Behelgardi, M.; Zahri, S.; Mashayekhi, F.; Mansouri, K.; Asghari, S.M. A peptide mimicking the binding sites of VEGF-A and VEGF-B inhibits VEGFR-1/-2 driven angiogenesis, tumor growth and metastasis. Sci. Rep.,  2018, 8(1), 17924.
[http://dx.doi.org/10.1038/s41598-018-36394-0] [PMID:  30560942] 
[54] 
Zhang, Y.; He, B.; Liu, K.; Ning, L.; Luo, D.; Xu, K.; Zhu, W.; Wu, Z.; Huang, J.; Xu, X. A novel peptide specifically binding to VEGF receptor suppresses angiogenesis in vitro and in vivo. Signal Transduct. Target. Ther.,  2017, 2, 17010.
[http://dx.doi.org/10.1038/sigtrans.2017.10] [PMID:  29263914] 
[55] 
Zhang, X.; Feng, S.; Liu, J.; Li, Q.; Zheng, L.; Xie, L.; Li, H.; Huang, D. Novel small peptides derived from VEGF 125-136: Potential drugs for radioactive diagnosis and therapy in A549 tumor-bearing nude mice. Sci. Rep.,  2017, 7(1), 4278.
[http://dx.doi.org/10.1038/s41598-017-04513-y] [PMID:  28655913] 
[56] 
Zanella, S.; Bocchinfuso, G.; De Zotti, M.; Arosio, D.; Marino, F.; Raniolo, S.; Pignataro, L.; Sacco, G.; Palleschi, A.; Siano, A.S.; Piarulli, U.; Belvisi, L.; Formaggio, F.; Gennari, C.; Stella, L. Rational design of antiangiogenic helical oligopeptides targeting the vascular endothelial growth factor receptors. Front Chem.,  2019, 7, 170.
[http://dx.doi.org/10.3389/fchem.2019.00170] [PMID:  30984741] 
[57] 
Soltanpour Gharibdousti, F.; Fazeli Delshad, B.; Falak, R.; Shayanfar, N.; Ganjalikhani Hakemi, M.; Andalib, A.; Kardar, G.A. Induction of humoral immune responses and inhibition of metastasis in mice by a VEGF peptide-based vaccine. Iran. J. Basic Med. Sci.,  2020, 23(4), 507-514.
[http://dx.doi.org/10.22038/ijbms.2020.38508.9141] [PMID:  32489566] 
[58] 
Kumar, A.; Purohit, R. Use of long term molecular dynamics simulation in predicting cancer associated SNPs. PLOS Comput. Biol.,  2014, 10(4) ,e1003318.
[http://dx.doi.org/10.1371/journal.pcbi.1003318] [PMID:  24722014] 
[59] 
Hess, B.; Kutzner, C.; van der Spoel, D.; Lindahl, E. GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. J. Chem. Theory Comput.,  2008, 4(3), 435-447.
[http://dx.doi.org/10.1021/ct700301q] [PMID:  26620784] 
[60] 
Kumar, A.; Purohit, R. Computational screening and molecular dynamics simulation of disease associated nsSNPs in CENP-E. Mutat. Res.,  2012, 738-739, 28-37.
[http://dx.doi.org/10.1016/j.mrfmmm.2012.08.005] [PMID:  22974711] 
[61] 
Kumar, A.; Rajendran, V.; Sethumadhavan, R.; Purohit, R. Evidence of colorectal cancer-associated mutation in MCAK: A computational report. Cell Biochem. Biophys.,  2013, 67(3), 837-851.
[http://dx.doi.org/10.1007/s12013-013-9572-1] [PMID:  23564489] 

Rights & Permissions Print Cite

Article Metrics

23

1

Journal Information

For Authors

For Editors

For Reviewers

Explore Articles

Open Access

Open Access Articles

For Visitors

DOI https://dx.doi.org/10.2174/1871520621666211118104051	Print ISSN 1871-5206
Publisher Name Bentham Science Publisher	Online ISSN 1875-5992

Anti-Cancer Agents in Medicinal Chemistry

Rational Design of Anti-Angiogenic Peptides to Inhibit VEGF/VEGFR2 Interactions for Cancer Therapeutics

Abstract Play Pause

Graphical Abstract

Related Journals

Related Books

Abstract