Abstract
IRS1 is a cytoplasmic adaptor protein that helps in cellular growth, glucose metabolism, proliferation, and differentiation. Highly disordered (insulin receptor substrate 1) IRS1 protein sequence (mol.wt- 131,590.97 da) has been used to develop model using ab initio modeling technique by I-Tassar tool and Discovery Studio/ DogSite Server to decipher a novel active site. The constructed protein model has been submitted with PMDB Id- PM0082210. GRAVY index of IRS1 model ( − 0.675) indicated surface protein–water interaction. Protparam tool instability index (75.22) demonstrated disorderedness combined with loops owing to prolines/glycines. After refinement, the Ramachandran plot showed that 88 percent of AAs were present in the allowed region and only 0.5% in the disallowed region. Novel IRS1 model protein has 10 α-helices, 22 β-sheets, 20 β-hairpins, 5 β-bulges, 47 strands, 105 β-turns, and 8 γ-turns. Docking of IRS1 with drug MH demonstrated interaction of Ser-70, Thr-18, and Pro-69 with C–H bonds; Gln-71, and Glu-113 with hydrogen bonds; while both Glu-114 and Glu-113 with salt-bridge connection. Permissible 1.0–1.5 Å range of RMSD fluctuation between 20 and 45 ns was obtained in simulation of IRS1 and IRS1-met complex confirmed that both complexes were stable during whole simulation process. RMSF result showed that except positions 57AA and 114AA, the binding of drug had no severe effects on the flexibility of the IRS1 and IRS1-met complex. The RoG value of compactness and rigidity showed little change in IRS1 protein. SASA value of IRS1 indicated non-significant fluctuation between IRS1 and drug MH means ligand (drug) and IRS1 receptor form stable structure. Hydrogen bond strength of IRS1 and IRS1-met was 81.2 and 76.4, respectively, which suggested stable interaction.
Similar content being viewed by others
Data Availability
Not available.
References
Abdelwahab SI, Farasani A, Jerah A, Elhassan Taha MM, Bidwai A (2022) Molecular docking of amphetamine, cathine and cathinone with dihydrofolate reductase: a computational analysis of inhibition of dihydrofolate reductase by khat alkaloids. Toxicol Commun 4(2):8. https://doi.org/10.53388/2022020208
Adeniji SE, Arthur DE, Oluwaseye A (2020) Computational modeling of 4-phenoxynicotinamide and 4-phenoxypyrimidine-5-carboxamide derivatives as potent anti-diabetic agent against TGR5 receptor. J King Saud Univ-Sci 32(1):102–115. https://doi.org/10.1016/j.jksus.2018.03.007
Ahuja P, Cantrelle FX, Huvent I, Hanoulle X, Lopez J, Smet C, Wieruszeski JM, Landrieu I, Lippens G (2016) Proline conformation in a functional tau fragment. J Mol Biol 428(1):79–91. https://doi.org/10.1016/j.jmb.2015.11.023
Aljarba NH, Hasnain MS, Bin-Meferij MM, Alkahtani S (2022) An In-silico investigation of potential natural polyphenols for the targeting of COVID main protease inhibitor. J King Saud Univ-Sci. https://doi.org/10.1016/j.jksus.2022.102214
Beema Shafreen RM, Seema S, Alagu Lakshmi S, Srivathsan A, Tamilmuhilan K, Shrestha A, Balasubramanian B, Dhandapani R, Paramasivam R, Al Obaid S, Salmen SH (2022) In vitro and in vivo antibiofilm potential of eicosane against Candida albicans. Appl Biochem Biotechnol. https://doi.org/10.1007/s12010-022-03984-8
Björnholm M, He A, Attersand A, Lake S, Liu S, Lienhard G, Taylor S, Arner P, Zierath J (2002) Absence of functional insulin receptor substrate-3 (IRS-3) gene in humans. Diabetologia 45:1697–1702. https://doi.org/10.1007/s00125-002-0945-z
Blom N, Gammeltoft S, Brunak S (1999) Sequence and structure-based prediction of eukaryotic protein phosphorylation sites. J Mol Biol 294(5):1351–1362. https://doi.org/10.1006/jmbi.1999.3310
Blom N, Sicheritz-Pontén T, Gupta R, Gammeltoft S, Brunak S (2004) Prediction of post-translational glycosylation and phosphorylation of proteins from the amino acid sequence. Proteomics 4(6):1633–1649. https://doi.org/10.1002/pmic.200300771
Cai D, Dhe-Paganon S, Melendez PA, Lee J, Shoelson SE (2003) Two new substrates in insulin signaling, IRS5/DOK4 and IRS6/DOK5. J Biol Chem 278(28):25323–25330. https://doi.org/10.1074/jbc.M212430200
Castrignano T, De Meo PDO, Cozzetto D, Talamo IG, Tramontano A (2006) The PMDB protei n model database. Nucl Acids Res 34(1):D306–D309. https://doi.org/10.1093/nar/gkj105
Ciborowski P, Silberring J (eds) (2016) Proteomic profiling and analytical chemistry: the crossroads. Elsevier
Copps KD, White MF (2012) Regulation of insulin sensitivity by serine/threonine phosphorylation of insulin receptor substrate proteins IRS1 and IRS2. Diabetologia 55:2565–2582. https://doi.org/10.1007/s00125-012-2644-8
Corbo T, Kalajdzic A, Delic D, Suleiman S, Pojskic N (2022) In silico prediction suggests inhibitory effect of halogenated boroxine on human catalase and carbonic anhydrase. J Genet Eng Biotechnol 20(1):1–11. https://doi.org/10.1186/s43141-022-00437-x
Das C, Das D, Mattaparthi VSK (2022) Computational Investigation on the efficiency of small molecule inhibitors identified from indian spices against SARS-CoV-2 Mpro. Biointerface Resin Appl Chem. https://doi.org/10.33263/BRIAC133.235
DassaultSystèmes BIOVIA, Discovery studio modeling environment, release 2017, San Diego: DassaultSystèmes, 2016
Dearth RK, Cui X, Kim HJ, Hadsell DL, Lee AV (2007) Oncogenic transformation by the signaling adaptor proteins insulin receptor substrate (IRS)-1 and IRS-2. Cell Cycle 6(6):705–713. https://doi.org/10.4161/cc.6.6.4035
Du Z, Uversky VN (2017) A comprehensive survey of the roles of highly disordered proteins in type 2 diabetes. Int J Mol Sci 18(10):2010. https://doi.org/10.3390/ijms18102010
Dupont J, Tesseraud S, Simon J (2009) Insulin signaling in chicken liver and muscle. Gen Comp Endocrinol 163(1–2):52–57. https://doi.org/10.1016/j.ygcen.2008.10.016
Eck MJ, Dhe-Paganon S, Trüb T, Nolte RT, Shoelson SE (1996) Structure of the IRS-1 PTB domain bound to the juxtamembrane region of the insulin receptor. Cell 85(5):695–705. https://doi.org/10.1016/S0092-8674(00)81236-2
Finn RD, Bateman A, Clements J, Coggill P, Eberhardt RY, Eddy SR, Heger A, Hetherington K, Holm L, Mistry J, Sonnhammer EL (2013) Pfam: the protein families database. Nucl Acids Res 42(D1):D222–D230. https://doi.org/10.1093/nar/gkt1223
Fiser A, Sali A (2003) ModLoop: automated modeling of loops in protein structures. Bioinformatics 19(18):2500–2501. https://doi.org/10.1093/bioinformatics/btg362
Fu H, Grimsley GR, Razvi A, Scholtz JM, Pace CN (2009) Increasing protein stability by improving β turns. Proteins Struct Funct Bioinform 77(3):491–498. https://doi.org/10.1002/prot.22509
Gasteiger E, Hoogland C, Gattiker A, Wilkins MR, Appel RD, Bairoch A (2005) Protein identification and analysis tools on the ExPASy server. In: Walker JM (ed) The proteomics protocols handbook. Humana Press, pp 571–607. https://doi.org/10.1385/1-59259-890-0:571
Gibbs N, Clarke AR, Sessions RB (2001) Ab initio protein structure prediction using physicochemical potentials and a simplified off-lattice model. Proteins Struct Funct Genet 43(2):186–202
Gorai S, Junghare V, Kundu K, Gharui S, Kumar M, Patro BS, Nayak SK, Hazra S, Mula S (2022) Synthesis of Dihydrobenzofuro [3, 2-b] chromenes as potential 3CLpro Inhibitors of SARS-CoV-2: a molecular docking and molecular dynamics study. ChemMedChem 17(8):e202100782. https://doi.org/10.1002/cmdc.202100782
Guex N, Peitsch MC (1997) SWISS-MODEL and the Swiss-Pdb Viewer: an environment for comparative protein modeling. Electrophoresis 18(15):2714–2723. https://doi.org/10.1002/elps.1150181505
Hakuno F, Fukushima T, Yoneyama Y, Kamei H, Ozoe A, Yoshihara H, Yamanaka D, Shibano T, Sone-Yonezawa M, Yu BC et al (2015) The novel functions of high-molecular-mass complexes containing insulin receptor substrates in mediation and modulation of insulin-like activities: emerging concept of diverse functions by IRS-associated proteins. Front Endocrinol (lausanne) 6:73. https://doi.org/10.3389/fendo.2015.00073
IRS1-Insulin receptor substrate 1 - Homo Sapiens (Human) - IRS1 gene & protein. www.uniprot.org. Retrieved 2016–04–21
Johansson MU, Zoete V, Michielin O, Guex N (2012) Defining and searching for structural motifs using DeepView/Swiss-PdbViewer. BMC Bioinform 13(1):173. https://doi.org/10.1186/1471-2105-13-173
Kalimuthu AK, Panneerselvam T, Pavadai P, Pandian SRK, Sundar K, Murugesan S, Ammunje DN, Kumar S, Arunachalam S, Kunjiappan S (2021) Pharmacoinformatics-based investigation of bioactive compounds of Rasam(South Indian recipe) against human cancer. Sci Rep 11(1):1–19. https://doi.org/10.1038/s41598-021-01008-9
Khoba K, Kumar S, Chatterjee S, Purty RS (2023) Isolation, characterization, and in silico interaction studies of bioactive compounds from Caesalpinia bonducella with target proteins involved in Alzheimer’s disease. Appl Biochem Biotechnol. https://doi.org/10.1007/s12010-022-03937-1
Kim SK, Novak RF (2007) The role of intracellular signaling in insulin-mediated regulation of drugmetabolizing enzyme gene and protein expression. Pharmacol Ther 113(1):88–120. https://doi.org/10.1016/j.pharmthera.2006.07.004
Krogh A, Brown M, Mian IS, Sjölander K, Haussler D (1994) Hidden Markov models in computational biology: applications to protein modeling. J Mol Biol 235(5):1501–1531. https://doi.org/10.1006/jmbi.1994.1104
Kumari R, Kumar R, Lynn A (2014) Open-source drug discovery. Lynn J Chem Inf Model 54(1951):10–1021. https://doi.org/10.1021/ci500020m
Kyte J, Doolittle RF (1982) A simple method for displaying the hydropathic character of a protein. J Mol Biol 157(1):105–132. https://doi.org/10.1016/0022-2836(82)90515-0
Laskowski RA, MacArthur MW, Moss DS, Thornton JM (1993) PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Crystallogr 26(2):283–291. https://doi.org/10.1107/S0021889892009944
Laskowski RA, Hutchinson EG, Michie AD, Wallace AC, Jones ML, Thornton JM (1997) PDBsum: a web-based database of summaries and analyses of all PDB structures. Trends Biochem Sci 22(12):488–490. https://doi.org/10.1016/S0968-0004(97)01140-7
Lavan BE, Fantin VR, Chang ET, Lane WS, Keller SR, Lienhard GE (1997) A novel 160-kDa phosphotyrosine protein in insulin-treated embryonic kidney cells is a new member of the insulin receptor substrate family. J Biol Chem 272(34):21403–21407. https://doi.org/10.1074/jbc.272.34.21403
Lindorff-Larsen K, Piana S, Palmo K, Maragakis P, Klepeis JL, Dror RO, Shaw DE (2010) Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins Struct Funct Bioinform 78(8):1950–1958. https://doi.org/10.1002/prot.22711
Liu YF, Herschkovitz A, Boura-Halfon S, Ronen D, Paz K, LeRoith D, Zick Y (2004) Serine phosphorylation proximal to its phosphotyrosine binding domain inhibits insulin receptor substrate 1 function and promotes insulin resistance. Mol Cell Biol 24(21):9668–9681. https://doi.org/10.1128/MCB.24.21.9668-9681.2004
Marchler-Bauer A, Bo Y, Han L, He J, Lanczycki CJ, Lu S, Chitsaz F, Derbyshire MK, Geer RC, Gonzales NR, Gwadz M (2016) CDD/SPARCLE: functional classification of proteins via subfamily domain architectures. Nucl Acids Res 45(D1):D200–D203. https://doi.org/10.1093/nar/gkw1129
Martín-Peláez S, Fito M, Castaner O (2020) Mediterranean diet effects on type 2 diabetes prevention, disease progression, and related mechanisms. A review. Nutrients 12(8):2236
Osigbemhe IG, Louis H, Khan EM, Etim EE, Oyo-Ita EE, Oviawe AP, Edet HO, Obuye F (2022) Antibacterial potential of 2-(-(2-Hydroxyphenyl)-methylidene)-amino) nicotinic acid: experimental, DFT studies, and molecular docking approach. Appl Biochem Biotechnol 194(12):5680–5701. https://doi.org/10.1007/s12010-022-04054-9
Ossai EC, Madueke AC, Amadi BE, Ogugofor MO, Momoh AM, Okpala COR, Anosike CA, Njoku OU (2021) Potential enhancement of metformin hydrochloride in lipid vesicles targeting therapeutic efficacy in diabetic treatment. Int J Molecular Sci 22(6):2852. https://doi.org/10.3390/ijms22062852
Perálvarez-Marín A, Lórenz-Fonfría VA, Simón-Vázquez R, Gomariz M, Meseguer I, Querol E, Padrós E (2008) Influence of proline on the thermostability of the active site and membrane arrangement of transmembrane proteins. Biophys J 95(9):4384–4395. https://doi.org/10.1529/biophysj.108.136747
Polavarapu NK, Kale R, Sethi B, Sahay RK, Phadke U, Ramakrishnan S, Mane A, Mehta S, Shah S (2020) Effect of gliclazide or gliclazide plus metformin combination on glycemic control in patients with T2DM in India: a real-world, retrospective, longitudinal, observational study from electronic medical records. Drugs-Real World Outcomes 7(4):271–279. https://doi.org/10.1007/s40801-020-00206-7
Roy A, Kucukural A, Zhang Y (2010) I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protoc 5(4):725. https://doi.org/10.1038/nprot.2010.5
Sahu A, Patra PK, Yadav MK, Varma M (2017) Identification and characterization of ErbB4 kinase inhibitors for effective breast cancer therapy. J Receptors Signal Transd 37(5):470–480. https://doi.org/10.1080/10799893.2017.1342129
Singh A, Chaube R (2014) Bioinformatic analysis, structure modeling, and active site prediction of aquaporin protein from Catfish Heteropneustes fossilis. Int J Recent Innov Trends Comput Commun 2(10):3208–3215
Takeuchi H, Matsuda M, Yamamoto TA, Kanematsu T, Kikkawa U, Yagisawa H, Watanabe Y, Hirata M (1998) PTB domain of insulin receptor substrate-1 binds inositol compounds. Biochem J 334(1):211–218. https://doi.org/10.1042/bj3340211
Taniguchi CM, Emanuelli B, Kahn CR (2006) Critical nodes in signaling pathways: Insights into insulin action. Nat Rev Mol Cell Biol 7(2):85–96. https://doi.org/10.1038/nrm1837
Tripathi A, Shrinet K, Singh VK, Kumar A (2019) Molecular modelling and docking of Mus musculus HMGB1 inflammatory protein with CGA. Bioinformation 15(7):467–473. https://doi.org/10.6026/97320630015467
Van Aalten DM, Bywater R, Findlay JB, Hendlich M, Hooft RW, Vriend G (1996) PRODRG, a program for generating molecular topologies and unique molecular descriptors from coordinates of small molecules. J Comput Aided Mol Des 10(3):255–262. https://doi.org/10.1007/BF00355047
Venkitakrishnan RP, Zaborowski E, McElheny D, Benkovic SJ, Dyson HJ, Wright PE (2004) Conformational changes in the active site loops of dihydrofolate reductase during the catalytic cycle. Biochemistry 43(51):16046–16055. https://doi.org/10.1021/bi048119y
Vijayan S, Loganathan C, Sakayanathan P, Thayumanavan P (2022) Synthesis and characterization of plumbagin S-allyl cysteine ester: determination of anticancer activity in-silico and in vitro. Appl Biochem Biotechnol 194(12):5827–5847. https://doi.org/10.1007/s12010-022-04079-0
Vishvakarma VK, Singh MB, Jain P, Kumari K, Singh P (2022) Hunting the main protease of SARS-CoV-2 by plitidepsin: molecular docking and temperature-dependent molecular dynamics simulations. Amino Acids 54(2):205–213. https://doi.org/10.1007/s00726-021-03098-1
Volkamer A, Kuhn D, Rippmann F, Rarey M (2012) DoGSiteScorer: a web server for automatic binding site prediction, analysis, and druggability assessment. Bioinformatics 28(15):2074–2075. https://doi.org/10.1093/bioinformatics/bts310
White MF (2002) IRS proteins and the common path to diabetes. Am J Phys Endocrinol Metab 283(3):E413–E422. https://doi.org/10.1152/ajpendo.00514.2001
Xu D, Zhang Y (2011) Improving protein models’ physical realism and structural accuracy by a two-step atomic-level energy minimization. Biophys J 101(10):2525–2534. https://doi.org/10.1016/j.bpj.2011.10.024
Yang J, Zhang Y (2015) I-TASSER server: new development for protein structure and function predictions. Nucl Acids Res 43(W1):W174–W181. https://doi.org/10.1093/nar/gkv342
Yang J, Roy A, Zhang Y (2012) BioLiP: a semi-manually curated database for biologically relevant ligand–protein interactions. Nucl Acids Res 41(D1):D1096–D1103. https://doi.org/10.1093/nar/gks966
Yang J, Roy A, Zhang Y (2013) Protein-ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment. Bioinformatics 29(20):2588–2595. https://doi.org/10.1093/bioinformatics/btt447
Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y (2015) The I-TASSER Suite: protein structure and function prediction. Nat Methods 12(1):7. https://doi.org/10.1038/nmeth.3213
Yun RH, Anderson A, Hermans J (1991) Proline in α helix: Stability and conformation studied by dynamics simulation. Proteins Struct Funct Bioinform 10(3):219–228. https://doi.org/10.1002/prot.340100306
Du Z, Uversky VN (2017) A comprehensive survey of the roles of highly disordered proteins in type 2 diabetes. Int J Mol Sci 18(10):2010. https://doi.org/10.3390/ijms18102010
Acknowledgements
The financial support to the School of Biotechnology, Institute of Science from DBT, DBT-SAP, UGC-UPE, and DST-PURSE program of Govt. of India, New Delhi, is duly acknowledged.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
There is no financial and/or non-financial conflict of interests including authorship sequence among the authors.
Ethical approval
Experiments were performed in silico conditions and no animals/humans were required.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Singh, R.K., Chaurasiya, A.K. & Kumar, A. Ab initio modeling of human IRS1 protein to find novel target to dock with drug MH to mitigate T2DM diabetes by insulin signaling. 3 Biotech 14, 108 (2024). https://doi.org/10.1007/s13205-024-03955-2
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s13205-024-03955-2