International Journal of Education and Management Engineering(IJEME)
ISSN: 2305-3623 (Print), ISSN: 2305-8463 (Online)
Published By: MECS Press
IJEME Vol.11, No.4, Aug. 2021
Application of the Docking Protocol Optimization for Inhibitors of IGF-1R and IR and Understanding them through Artificial Intelligence and Bibliography
Full Text (PDF, 1139KB), PP.1-11
The cancer cell prolonged and continues proliferation is a major cause of tumorigenesis. In general, Insulin like growth factor receptor (IGF-1R) and Insulin receptor (IR-A) protein are responsible for such cell proliferations. However, with respect to cancers, the specific over-expression of these receptors along with the elevated levels of their agonist, i.e. insulin-like growth factor 1 (IGF-1) and insulin-like growth factor 2 (IGF-2) have shown to be the integral part of cancer cell’s proliferation. The understanding of the dual targeting of (IR) and (IGF-1R) through Artificial Intelligence in tumorigenesis is now considered to be a possible aspect to achieve the desired results. In this research we signify that according to data based on artificial intelligence, the tyrosine kinase domain of these two receptors can accommodates number of small molecules inhibitors to block the ongoing signaling cascade for cell proliferation. It is indeed found to be of paramount importance to develop such candidates as clinical solutions to block the activity of tyrosine kinase domain of IR and IGF-1R. Therefore, this study aims to use artificial intelligence for understanding the key molecular interactions responsible for activation and inhibition of the proliferation signal via tyrosine kinase domain. Further, we optimized docking protocol on crystal structures of such system from protein databank. Our study revealed that H-bond donor and hydrophobic pocket play a key role in the initiation of the signal cascade for cell proliferation. The simulations ran produced an acceptable solution based on the statistical measures of Mathew’s correlation factor and delineated two H- bonds distances between 12-22. Our study also concluded that how a docking protocol can be optimized to accommodate the non-congeneric series small molecules. We successfully ran the simulation to conclude that LYS 1030, GLU 1077, MET 1079 and ASP 1083 amino acids positions play an important role in binding of small molecules to inhibit cancer cell proliferation. This research bridges the gap between in-silico and in-vitro experimentations and paves a way to reproduce the results experimentally.
Cite This Paper
Mustafa Kamal Pasha, Khurram Munawar, Asma Talib Qureshi, " Application of the Docking Protocol Optimization for Inhibitors of IGF-1R and IR and Understanding them through Artificial Intelligence and Bibliography", International Journal of Education and Management Engineering (IJEME), Vol.11, No.4, pp. 1-11, 2021. DOI: 10.5815/ijeme.2021.04.01
Stauffer, F., et al., Identification of a 5-[3-phenyl-(2-cyclic-ether)-methylether]-4-aminopyrrolo [2, 3-d] pyrimidine series of IGF-1R inhibitors. Bioorganic & medicinal chemistry letters, 2016. 26(8): p. 2065-2067.
Anastassiadis, T., et al., A highly selective dual insulin receptor (IR)/insulin-like growth factor 1 receptor (IGF-1R) inhibitor derived from an extracellular signal-regulated kinase (ERK) inhibitor. Journal of Biological Chemistry, 2013. 288(39): p. 28068-28077.
Huang, F., et al., IRS2 copy number gain, KRAS and BRAF mutation status as predictive biomarkers for response to the IGF-1R/IR inhibitor BMS-754807 in colorectal cancer cell lines. Molecular cancer therapeutics, 2015. 14(2): p. 620-630.
Jin, M., et al., Small-molecule ATP-competitive dual IGF-1R and insulin receptor inhibitors: structural insights, chemical diversity and molecular evolution. Future medicinal chemistry, 2012. 4(3): p. 315-328.
 Vincent, E.E., et al., Targeting non-small cell lung cancer cells by dual inhibition of the insulin receptor and the insulin-like growth factor-1 receptor. PLoS One, 2013. 8(6): p. e66963.
Yamaguchi, Y., et al., Ligand-binding properties of the two isoforms of the human insulin receptor. Endocrinology, 1993. 132(3): p. 1132-1138.
Munshi, S., et al., Structure of apo, unactivated insulin-like growth factor-1 receptor kinase at 1.5 Å resolution. Acta Crystallographica Section D: Biological Crystallography, 2003. 59(10): p. 1725-1730.
Buck, E., et al., Compensatory insulin receptor (IR) activation on inhibition of insulin-like growth factor-1 receptor (IGF-1R): rationale for cotargeting IGF-1R and IR in cancer. Molecular cancer therapeutics, 2010. 9(10): p. 2652-2664.
Denley, A., et al., The insulin receptor isoform exon 11-(IR-A) in cancer and other diseases: a review. Hormone and Metabolic Research, 2003. 35(11/12): p. 778-785.
De Meyts, P. and J. Whittaker, Structural biology of insulin and IGF1 receptors: implications for drug design. Nature Reviews Drug Discovery, 2002. 1(10): p. 769-783.
Torres, A.M., et al., Solution structure of human insulin-like growthfactor II. Relationship to receptor and binding protein interactions. Journal of molecular biology, 1995. 248(2): p. 385-401.
Haluska, P., et al., In vitro and in vivo antitumor effects of the dual insulin-like growth factor-I/insulin receptor inhibitor, BMS-554417. Cancer Research, 2006. 66(1): p. 362-371.
 Munawar HS, Awan AA, Khalid U, Munawar S, Maqsood A. Revolutionizing Telemedicine by Instilling H. 265. International Journal of Image, Graphics & Signal Processing(IJIGSP). 2017 May 1;9(5).
 Munawar, H. S., Qayyum, S., Ullah, F., & Sepasgozar, SBig Data and Its Applications in Smart Real Estate and the Disaster Management Life Cycle: A Systematic Analysis. Big Data and Cognitive Computing; 2020, 4(2).
 Munawar, H. S., Zhang, J., Li, H., Mo, D., & Chang, L. Mining multispectral aerial images for automatic detection of strategic bridge locations for disaster relief missions. In Pacific-Asia Conference on Knowledge Discovery and Data Mining (pp. 189-200). Springer, Cham. . (2019, April)
 Munawar HS, Hammad A, Ullah F, Ali TH. After the flood: A novel application of image processing and machine learning for post-flood disaster management. InProceedings of the 2nd International Conference on Sustainable Development in Civil Engineering (ICSDC 2019), Jamshoro Pakistan 2019 Dec (pp. 5-7).
Munawar, H. S. "International Journal of Wireless and Microwave Technologies (IJWMT)."
Munawar, H. S. "An Overview of Reconfigurable Antennas for Wireless Body Area Networks and Possible Future Prospects."
Munawar, H. S., Khalid, U., Jilani, R., & Maqsood, A. (2017). Version Management by Time Based Approach in Modern Era. International Journal of Education and Management Engineering(IJEME), 4, 13-20.
 Munawar, H. S. "Reconfigurable Origami Antennas: A Review of the Existing Technology and its Future Prospects."
 Munawar, H. S., & Maqsood, A. Isotropic Surround Suppression based Linear Target Detection using Hough Transform.
Gaulton, A., et al., ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic acids research, 2011. 40(D1): p. D1100-D1107.
Jin, M., et al., Discovery of an orally efficacious imidazo [5, 1-f][1, 2, 4] triazine dual inhibitor of IGF-1R and IR. ACS medicinal chemistry letters, 2010. 1(9): p. 510-515.
Henikoff, S. and J.G. Henikoff, Amino acid substitution matrices from protein blocks. Proceedings of the National Academy of Sciences, 1992. 89(22): p. 10915-10919.
Wu, J., et al., Small‐molecule inhibition and activation‐loop trans‐phosphorylation of the IGF1 receptor. The EMBO journal, 2008. 27(14): p. 1985-1994.
Wittman, M.D., et al., Discovery of a 2, 4-disubstituted pyrrolo [1, 2-f][1, 2, 4] triazine inhibitor (BMS-754807) of insulin-like growth factor receptor (IGF-1R) kinase in clinical development. Journal of medicinal chemistry, 2009. 52(23): p. 7360-7363.
Heinrich, T., et al., Allosteric IGF-1R inhibitors. ACS medicinal chemistry letters, 2010. 1(5): p. 199-203.
Kettle, J.G., et al., Discovery and Optimization of a Novel Series of Dyrk1B Kinase Inhibitors To Explore a MEK Resistance Hypothesis. Journal of medicinal chemistry, 2015. 58(6): p. 2834-2844.
Sanderson, M.P., et al., BI 885578, a Novel IGF1R/INSR Tyrosine Kinase Inhibitor with Pharmacokinetic Properties That Dissociate Antitumor Efficacy and Perturbation of Glucose Homeostasis. Molecular cancer therapeutics, 2015. 14(12): p. 2762-2772.
Hendlich, M., F. Rippmann, and G. Barnickel, LIGSITE: automatic and efficient detection of potential small molecule-binding sites in proteins. Journal of Molecular Graphics and Modelling, 1997. 15(6): p. 359-363.
Labute, P. and M. Santavy, Locating binding sites in protein structures. Journal of Chemical Computing Group, 2007.
Knegtel, R.M., I.D. Kuntz, and C. Oshiro, Molecular docking to ensembles of protein structures. Journal of molecular biology, 1997. 266(2): p. 424-440.
Österberg, F., et al., Automated docking to multiple target structures: incorporation of protein mobility and structural water heterogeneity in AutoDock. Proteins: Structure, Function, and Bioinformatics, 2002. 46(1): p. 34-40.
Edelsbrunner, H., Weighted Alpha Shapes, 1992. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, 1992. 61810.
Corbeil, C.R., C.I. Williams, and P. Labute, Variability in docking success rates due to dataset preparation. Journal of computer-aided molecular design, 2012. 26(6): p. 775-786.
Charifson, P.S., et al., Consensus scoring: A method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins. Journal of medicinal chemistry, 1999. 42(25): p. 5100-5109.
 Gill, P.E., W. Murray, and M.H. Wright, Practical optimization. 1981.
 Munawar, H. S., Khalid, U., & Maqsood, A. Fire detection through Image Processing; A brief overview.
 Munawar, H. S., Khalid, U., & Maqsood, A. Modern day detection of Mines; Using the Vehicle Based Detection Robot.
Munawar HS, Awan AA, Maqsood A, Khalid U. REINVENTING RADIOLOGY IN MODERN ERA.
 Munawar, H. S. (2020). Flood Disaster Management: Risks, Technologies, and Future Directions. Machine Vision Inspection Systems: Image Processing, Concepts, Methodologies and Applications, 1, 115-146.
 Munawar, H. S. (2020). Image and Video Processing for Defect Detection in Key Infrastructure. Machine Vision Inspection Systems: Image Processing, Concepts, Methodologies and Applications, 1, 159-177.