Russian version English version
About the Journal
Editorial Board
Instructions for Authors
Information for Readers and Authors
Current Issue
Archive
Contact Us
Search

Send manuscript
 


Volume 18   Issue 1   Year 2023
Navaneetha Nambigari

Cancer Therapeutics: Structure-Based Drug Design of Inhibitors for a Novel Angiogenic Growth Factor

Mathematical Biology & Bioinformatics. 2023;18(1):72-88.

doi: 10.17537/2023.18.72.

References

  1. Harris A.L. Angiogenesis as a New Target for Cancer Control. Eur. J. Cancer, Suppl. 2003;1(2):1–12. doi: 10.1016/S1359-6349(03)00007-7
  2. Gavalas N., Liontos M., Trachana S.P., Bagratuni T., Arapinis C., Liacos C., Dimopoulos M., Bamias A., Angiogenesis-Related Pathways in the Pathogenesis of Ovarian Cancer. Int. J. Mol. Sci. 2013;14(8):15885–15909. doi: 10.3390/ijms140815885
  3. Bergers G., Hanahan D. Modes of Resistance to Anti-Angiogenic Therapy. Nat. Rev. Cancer. 2008;8(8):592–603. doi: 10.1038/nrc2442
  4. Plate K.H., BreierG., Farrell C.L., Risau W. Platelet-Derived Growth Factor Receptor-Beta Is Induced Duringtumor Development and Upregulated during Tumor Progressionin Endothelial Cells in Human Gliomas. Lab. Invest. 1992;67:529–534.
  5. Yu J.H., Ustach C., ChoiKim H.R. Platelet-Derived Growth Factor Signaling and Human Cancer. BMB Rep. 2003;36(1):49–59. doi: 10.5483/BMBRep.2003.36.1.049
  6. Anderberg C., Li H., Fredriksson L., Andrae J., Betsholtz C., Li X., Eriksson U., Pietras K. Paracrine Signaling by Platelet-Derived Growth Factor-CC Promotes Tumor Growth by Recruitment of Cancer-Associated Fibroblasts. Cancer Res. 2009;69(1):369–378. doi: 10.1158/0008-5472.CAN-08-2724
  7. Crawford Y., Kasman I., Yu L., Zhong C., Wu X., Modrusan Z., Kaminker J., Ferrara N. PDGF-C Mediates the Angiogenic and Tumorigenic Properties of Fibroblasts Associated with Tumors Refractory to Anti-VEGF Treatment. Cancer Cell. 2009;15(1):21–34. doi: 10.1016/j.ccr.2008.12.004
  8. Reigstad L. J., Varhaug J. E.; Lillehaug, J. R. Structural and Functional Specificities of PDGF-C and PDGF-D, the Novel Members of the Platelet-Derived Growth Factors Family. FEBS J. 2005;272(22):5723–5741. doi: 10.1111/j.1742-4658.2005.04989.x
  9. Wågsäter D., Zhu C., Björck H. M., Eriksson P. Effects of PDGF-C and PDGF-D on Monocyte Migration and MMP-2 and MMP-9 Expression. Atherosclerosis. 2009;202(2):415–423. doi: 10.1016/j.atherosclerosis.2008.04.050
  10. Li X., Kumar A., ZhangF., Lee C., Li Y. Tang Z., Arjunan P. VEGF-Independent Angiogenic Pathways Induced by PDGF-C. Oncotarget. 2010;1(4):309–314. doi: 10.18632/oncotarget.141
  11. Risau W., Drexler H., Mironov V., Smits A., Siegbahn A., Funa K., Heldin C.-H. Platelet-Derived Growth Factor Is Angiogenic In Vivo. Growth Factors. 1992;7(4):261–266. doi: 10.3109/08977199209046408
  12. Zwerner J.P., May W.A. Dominant Negative PDGF-C Inhibits Growth of Ewing Family Tumor Cell Lines. Oncogene. 2002;21(24):3847–3854. doi: 10.1038/sj.onc.1205486
  13. Zwerner J.P,. May W.A. PDGF-C Is an EWS/FLI Induced Transforming Growth Factor in Ewing Family Tumors. Oncogene. 2001;20(5):626–633. doi: 10.1038/sj.onc.1204133
  14. Gilbertson D.G., Duff M.E., West J.W., Kelly J.D., Sheppard P.O., Hofstrand P.D., Gao Z., Shoemaker K., Bukowski T.R., Moore M., Feldhaus A.L., Humes J.M. Palmer T.E., Hart C.E. Platelet-Derived Growth Factor C (PDGF-C), a Novel Growth Factor That Binds to PDGF α and β Receptor. J. Biol. Chem. 2001;276(29):27406–27414. doi: 10.1074/jbc.M101056200
  15. Li X., Pontén A., Aase K., Karlsson L. Abramsson A., Uutela M., Bäckström G., Hellström M., Boström H., Li H., Soriano P., Betsholtz C., Heldin C.-H., Alitalo K., Östman A. Eriksson U. PDGF-C Is a New Protease-Activated Ligand for the PDGF α-Receptor. Nat. Cell Biol. 2000;2(5):302–309. doi: 10.1038/35010579
  16. Raica M., Cimpean A.M. Platelet-Derived Growth Factor (PDGF)/PDGF Receptors (PDGFR) Axis as Target for Antitumor and Antiangiogenic Therapy. Pharmaceuticals. 2010;3(3):572–599. doi: 10.3390/ph3030572
  17. Chothia C., Lesk A.M. The Relation between the Divergence of Sequence and Structure in Proteins. EMBO J. 1986;5(4):823–826. doi: 10.1002/j.1460-2075.1986.tb04288.x
  18. Martí-Renom M.A., Stuart A.C., Fiser A., Sánchez R., Melo F., Šali A. Comparative Protein Structure Modeling of Genes and Genomes. Annu. Rev. Biophys. Biomol. Struct. 2000;29(1):291–325. doi: 10.1146/annurev.biophys.29.1.291
  19. Altschul S. Gapped BLAST and PSI-BLAST: A New Generation of Protein Database Search Programs. Nucleic Acids Res. 1997;25(17):3389–3402. doi: 10.1093/nar/25.17.3389
  20. Cole C,. Barber J.D., Barton G.J. The Jpred 3 Secondary Structure Prediction Server. Nucleic Acids Res. 2008;36:W197–W201. doi: 10.1093/nar/gkn238
  21. Contreras-Moreira B., Bates P.A. Domain Fishing: A First Step in Protein Comparative Modelling. Bioinformatics. 2002;18(8):1141–1142. doi: 10.1093/bioinformatics/18.8.1141
  22. Berman H.M. The Protein Data Bank. Nucleic Acids Res. 2000;28(1):235–242. doi: 10.1093/nar/28.1.235
  23. Gonnet G.H., Cohen M.A., Benner S.A. Exhaustive Matching of the Entire Protein Sequence Database. Science. 1992;256(5062):1443–1445. doi: 10.1126/science.1604319
  24. Thompson J.D., Higgins D.G., Gibson T.J. CLUSTAL W: Improving the Sensitivity of Progressive Multiple Sequence Alignment through Sequence Weighting, Position-Specific Gap Penalties and Weight Matrix Choice. Nucleic Acids Res. 1994;22(22):4673–4680. doi: 10.1093/nar/22.22.4673
  25. Larkin M.A., Blackshields G., Brown N.P., Chenna R., McGettigan P.A., McWilliam H., Valentin F., Wallace I.M., Wilm A., Lopez R., Thompson J.D., Gibson T.J., Higgins D.G. Clustal W and Clustal X Version 2.0. Bioinformatics. 2007;23(21):2947–2948. doi: 10.1093/bioinformatics/btm404
  26. Brooks B.R., Bruccoleri R.E., Olafson B.D., States D.J., Swaminathan S.K.M. CHARMM: A Program for Macromolecular Energy, Minimization, and Dynamics Calculations. J. Comput. Chem. 1983;4:187–217. doi: 10.1002/jcc.540040211
  27. Šali A., Potterton L., Yuan F., van Vlijmen H., Karplus M. Evaluation of Comparative Protein Modeling by MODELLER. Proteins Struct. Funct. Genet. 1995;23(3):318–326. doi: 10.1002/prot.340230306
  28. Šali A., Blundell T.L. Comparative Protein Modelling by Satisfaction of Spatial Restraints. J. Mol. Biol. 1993;234(3):779–815. doi: 10.1006/jmbi.1993.1626
  29. Guex N., Peitsch M.C. SWISS-MODEL and the Swiss-Pdb Viewer: An Environment for Comparative Protein Modeling. Electrophoresis. 1997;18(15):2714–2723. doi: 10.1002/elps.1150181505
  30. Fiser A., Do R.K.G., Šali A. Modeling of Loops in Protein Structures. Protein Sci. 2000;9(9):1753–1773. doi: 10.1110/ps.9.9.1753
  31. Jorgensen W.L., Tirado-Rives J. The OPLS [Optimized Potentials for Liquid Simulations] Potential Functions for Proteins, Energy Minimizations for Crystals of Cyclic Peptides and Crambin. J. Am. Chem. Soc. 1988;110(6):1657–1666. doi: 10.1021/ja00214a001
  32. Jorgensen W.L. Maxwell D.S., Tirado-Rives J. Development and Testing of the OPLS All-Atom Force Field on Conformational Energetics and Properties of Organic Liquids. J. Am. Chem. Soc. 1996;118(45):11225–11236. doi: 10.1021/ja9621760
  33. Laskowski R.A., MacArthur M.W., Moss D.S. Thornton J.M. PROCHECK: A Program to Check the Stereochemical Quality of Protein Structures. J. Appl. Crystallogr. 1993;26(2):283–291. doi: 10.1107/S0021889892009944
  34. Ramachandran G.N., Ramakrishnan C. Sasisekharan V. Stereochemistry of Polypeptide Chain Configurations. J. Mol. Biol. 1963;7(1):95–99. doi: 10.1016/S0022-2836(63)80023-6
  35. 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:W407–W410. doi: 10.1093/nar/gkm290
  36. Laurie A.T. Methods for the Prediction of Protein-Ligand Binding Sites for Structure-Based Drug Design and Virtual Ligand Screening. Curr. Protein Pept. Sci. 2006;7:395–406. doi: 10.2174/138920306778559386
  37. Dundas J., Ouyang Z., Tseng J., Binkowski A., Turpaz Y., Liang J. CASTp: Computed Atlas of Surface Topography of Proteins with Structural and Topographical Mapping of Functionally Annotated Residues. Nucleic Acids Res. 2006;34:W116–W118. doi: 10.1093/nar/gkl282
  38. Laurie A.T.R., Jackson R.M. Q-SiteFinder: An Energy-Based Method for the Prediction of Protein-Ligand Binding Sites. Bioinformatics. 2005;21(9):1908–1916. doi: 10.1093/bioinformatics/bti315
  39. Halgren T.A. Identifying and Characterizing Binding Sites and Assessing Druggability. J. Chem. Inf. Model. 2009;49(2):377–389. doi: 10.1021/ci800324m
  40. Goverdhan L., Revanth B., Mahendar D., Manan B., Sarita Rajender P. Identification and optimisation of novel selective inhibitors against human regulator of G protein signalling 2 (RGS2) protein for type 2 diabetes mellitus: an in silico approach. Int. J. Comput. Biol. Drug Des. 2021;14(3):166–189. doi: 10.1504/IJCBDD.2021.10040273
  41. Navaneetha N., Kiran Kumar M., Vasavi M., Bhargavi K., Sarita Rajender P., Ramasree D., Uma V. Angiogenesis: An Insilico Approach to Angiogenic Phenotype. J. Pharm. Res. 2012;5(1):583–588.
  42. Schneidman-Duhovny D., Inbar Y., Nussinov R., Wolfson H.J. PatchDock and SymmDock: Servers for Rigid and Symmetric Docking. Nucleic Acids Res. 2005;33:W363–W367. doi: 10.1093/nar/gki481
  43. Accelrys Discovery Studio Visualiser v 3.5.0.12158. San Diego: Accelrys Software Inc., 2012.
  44. Ghosh S., Nie A., An J., Huang Z. Structure-Based Virtual Screening of Chemical Libraries for Drug Discovery. Curr. Opin. Chem. Biol. 2006;10(3):194–202. doi: 10.1016/j.cbpa.2006.04.002
  45. Klebe G. Virtual Ligand Screening: Strategies, Perspectives and Limitations. Drug Discov. Today. 2006;11(13–14):580–594. doi: 10.1016/j.drudis.2006.05.012
  46. Lengauer T., Rarey M. Computational Methods for Biomolecular Docking. Curr. Opin. Struct. Biol. 1996;6(3):402–406. doi: 10.1016/S0959-440X(96)80061-3
  47. Lanka G., Bathula R., Bhargavi M., Potlapall S.R. Homology modeling and molecular docking studies for the identification of novel potential therapeutics against human PHD3 as a drug target for type 2 diabetes mellitus. Journal of Drug Delivery and Therapeutics. 2019;9(4):265–273.
  48. Friesner R.A. Banks J.L. Murphy R.B., Halgren T.A., Klicic J.J., Mainz D.T., Repasky M.P., Knoll E.H., Shelley M., Perry J.K. et al. Glide:  A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy. J. Med. Chem. 2004;47(7):1739–1749. doi: 10.1021/jm0306430
  49. Kawatkar S., Wang H., Czerminski R., Joseph-McCarthy D. Virtual Fragment Screening: An Exploration of Various Docking and Scoring Protocols for Fragments Using Glide. J. Comput. Aided. Mol. Des. 2009;23(8):527–539. doi: 10.1007/s10822-009-9281-4
  50. Podvinec M., Lim S.P., Schmidt T., Scarsi M., Wen D., Sonntag L.-S., Sanschagrin P., Shenkin P.S., Schwede T. Novel Inhibitors of Dengue Virus Methyltransferase: Discovery by in Vitro-Driven Virtual Screening on a Desktop Computer Grid. J. Med. Chem. 2010;53(4):1483–1495. doi: 10.1021/jm900776m
  51. LigPrep, Version 3.3. New York, NY: Schrödinger, LLC, 2010.
  52. GLIDE, Version 5.6. New York, NY: Schrödinger, LLC, 2010.
  53. Friesner R.A., Murphy R.B., Repasky M.P., Frye L.L., Greenwood J.R., Halgren T.A., Sanschagrin P.C., Mainz D.T. Extra Precision Glide:  Docking and Scoring Incorporating a Model of Hydrophobic Enclosure for Protein−Ligand Complexes. J. Med. Chem. 2006;49(21):6177–6196. doi: 10.1021/jm051256o
  54. Rodrigues A.D. Preclinical Drug Metabolism in the Age of High-Throughput Screening: An Industrial Perspec. Pharm. Res. 1997;14(11):1504–1510. doi: 10.1023/A:1012105713585
  55. Daina A., Zoete V. A BOILED-Egg To Predict Gastrointestinal Absorption and Brain Penetration of Small Molecules. Chem. Med. Chem. 2016;11(11):1117–1121. doi: 10.1002/cmdc.201600182
  56. Johnson M., Zaretskaya I., Raytselis Y., Merezhuk Y., McGinnis S., Madden T.L. NCBI BLAST: A Better Web Interface. Nucleic Acids Res. 2008;36:W5–W9. doi: 10.1093/nar/gkn201
  57. Karlin S., Altschul S.F. Methods for Assessing the Statistical Significance of Molecular Sequence Features by Using General Scoring Schemes. Proc. Natl. Acad. Sci. 1990;87(6):2264–2268. doi: 10.1073/pnas.87.6.2264
  58. Drozdetskiy A., Cole C., Procter J., Barton G.J. JPred4: A Protein Secondary Structure Prediction Server. Nucleic Acids Res. 2015;43(W1):W389–W394. doi: 10.1093/nar/gkv332
  59. Kerfeld C.A., Scott K.M. Using BLAST to Teach “E-Value-Tionary” Concepts. PLoS Biol. 2011;9(2):e1001014. doi: 10.1371/journal.pbio.1001014
  60. 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:W407–W410. doi: 10.1093/nar/gkm290
  61. Bergers G., Song S., Meyer-Morse N., Bergsland E., Hanahan D. Benefits of Targeting Both Pericytes and Endothelial Cells in the Tumor Vasculature with Kinase Inhibitors. J. Clin. Invest. 2003;111(9):1287–1295. doi: 10.1172/JCI17929
  62. Östman A. PDGF Receptors-Mediators of Autocrine Tumor Growth and Regulators of Tumor Vasculature and Stroma. Cytokine Growth Factor Rev. 2004;15(4):275–286. doi: 10.1016/j.cytogfr.2004.03.002
  63. Erber R., Thurnher A., Katsen A.D., Groth G., Kerger H., Hammes H., Menger M.D., Ullrich A., Vajkoczy P. Combined Inhibition of VEGF- and PDGF-signaling Enforces Tumor Vessel Regression by Interfering with Pericyte-mediated Endothelial Cell Survival Mechanisms. FASEB J. 2004;18(2):338–340. doi: 10.1096/fj.03-0271fje
  64. Andrae J., Gallini R., Betsholtz C. Role of Platelet-Derived Growth Factors in Physiology and Medicine. Genes Dev. 2008;22(10):1276–1312. doi: 10.1101/gad.1653708
  65. Fredriksson L., Li H., Fieber C., Li X., Eriksson U. Tissue Plasminogen Activator Is a Potent Activator of PDGF-CC. EMBO J. 2004;23(19):3793–3802. doi: 10.1038/sj.emboj.7600397
  66. Ritchie T.J., Ertl P., Lewis R. The Graphical Representation of ADME-Related Molecule Properties for Medicinal Chemists. Drug Discov. Today. 2011;16(1–2):65–72. doi: 10.1016/j.drudis.2010.11.002
  67. Breier A., Gibalova L., Seres M., Barancik M., Sulova Z. New Insight into P-Glycoprotein as a Drug Target. Anti-Cancer Agents in Medicinal Chemistry (Formerly Current Medicinal Chemistry - Anti-Cancer Agents). 2013;13(1):159–170. doi: 10.2174/187152013804487380
  68. Park S.J., Baars H., Mersmann S., Buschmann H., Baron J.M., Amann P.M., Czaja K., Hollert H., Bluhm K., Redelstein R., Bolm C. N -Cyano Sulfoximines: COX Inhibition, Anticancer Activity, Cellular Toxicity, and Mutagenicity. Chem. Med. Chem. 2013;8(2):217–220. doi: 10.1002/cmdc.201200403
Table of Contents
Original Article
Math. Biol. Bioinf.
2023;18(1):72-88
doi: 10.17537/2023.18.72
published in English

Abstract (eng.)
Abstract (rus.)
Full text (eng., pdf)
References
Supplementary data

 
  Copyright IMPB RAS © 2005-2024