Elucidating the Role of Val-Asn 95 and Arg-Gly 52 Mutations on Structure and Stability of Fibroblast Growth Factor Homologous Factor 2

Author(s): Vidyalatha Kolli, Subhankar Paul, Praveen Kumar Guttula, Nandini Sarkar*

Journal Name: Protein & Peptide Letters

Volume 26 , Issue 11 , 2019


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Abstract:

Background: Fibroblast growth Factor Homologous Factors (FHFs) belong to a subclass of Fibroblast Growth Factor (FGF) family owing to their high sequence and structural similarities with FGFs. However, despite these similarities, there are properties which set them apart from FGFs. FHFs lack the secretion signal sequence unlike other FGF members, except FGF1 and 2. Unlike FGFs, FHFs are not able to bind to FGF Receptors (FGFRs) and instead have been implicated in binding to Voltage-Gated Sodium Channels (VGSCs), neuronal MAP kinase scaffold protein and islet-brain-2 (IB2). The two amino acids Arg-52 and Val95 are conserved in all FHFs and mutation of these residues lead to its inability to bind with VGSC/IB2. However, it is not clear whether the loss of binding is due to destabilization of the protein on mutation or due to involvement of Arg52 and Val95 in conferring functionality to FHFs.

Objective: In the present study, we have mutated these two conserved residues of FHF2 with its corresponding FGF counterpart amino acids and studied the effects of the mutations on the structure and stability of the protein.

Methods: Several biophysical methods like isothermal equilibrium denaturation study, ANS fluorescence, intrinsic fluorescence, acrylamide quenching, circular dichroism studies as well as using computational approaches were employed.

Results: The single mutations were found to affect the overall stability, conformation and functionality of the protein.

Conclusion: Thus, the studies throw light on the role of specific amino acids in deciding the stability, structure and functionality of proteins and will be useful for development of therapeutically engineered proteins.

Keywords: Fibroblast growth factors, intrinsic fluorescence, site directed mutagenesis, circular dichroism, stability, amino acids, molecular dynamic simulation.

[1]
Smallwood, P.M.; Munoz-Sanjuan, I.; Tong, P.; Macke, J.P.; Hendry, S.H.; Gilbert, D.J.; Copeland, N.G.; Jenkins, N.A.; Nathans, J. Fibroblast Growth Factor (FGF) homologous factors: new members of the FGF family implicated in nervous system development. Proc. Natl. Acad. Sci. USA, 1996, 93(18), 9850-9857.
[http://dx.doi.org/10.1073/pnas.93.18.9850] [PMID: 8790420]
[2]
Hartung, H.; Feldman, B.; Lovec, H.; Coulier, F.; Birnbaum, D.; Goldfarb, M. Murine FGF-12 and FGF-13: expression in embryonic nervous system, connective tissue and heart. Mech. Dev., 1997, 64(1-2), 31-39.
[http://dx.doi.org/10.1016/S0925-4773(97)00042-7] [PMID: 9232594]
[3]
Ornitz, D.M.; Itoh, N. Fibroblast growth factors. Genome Biol., 2001, 2, 1-12.
[PMID: 11276432]
[4]
Munoz-Sanjuan, I.; Smallwood, P.M.; Nathans, J. Isoform diversity among fibroblast growth factor homologous factors is generated by alternative promoter usage and differential splicing. J. Biol. Chem., 2000, 275(4), 2589-2597.
[http://dx.doi.org/10.1074/jbc.275.4.2589] [PMID: 10644718]
[5]
Pablo, J.L.; Pitt, G.S. Fibroblast growth Factor Homologous Factors (FHFs): new roles in neuronal health and disease. Neuroscientist, 2016, 22(1), 19-25.
[http://dx.doi.org/10.1177/1073858414562217] [PMID: 25492945]
[6]
Olsen, S.K.; Garbi, M.; Zampieri, N.; Eliseenkova, A.V.; Ornitz, D.M.; Goldfarb, M.; Mohammadi, M. Fibroblast Growth Factor (FGF) homologous factors share structural but not functional homology with FGFs. J. Biol. Chem., 2003, 278(36), 34226-34236.
[http://dx.doi.org/10.1074/jbc.M303183200] [PMID: 12815063]
[7]
Finch, P.W.; Rubin, J.S. Keratinocyte growth factor/fibroblast growth factor 7, a homeostatic factor with therapeutic potential for epithelial protection and repair. Adv. Cancer Res., 2004, 91, 69-136.
[http://dx.doi.org/10.1016/S0065-230X(04)91003-2] [PMID: 15327889]
[8]
Schoorlemmer, J.; Goldfarb, M. FGF Homologous factors and the islet Brain-2 scaffold protein regulate activation of a stress-activated protein kinase. J. Biochem., 2002, 277(51), 49111-49119.
[PMID: 12244047]
[9]
Plotnikov, A.N.; Hubbard, S.R.; Schlessinger, J.; Mohammadi, M. Crystal structures of two FGF-FGFR complexes reveal the determinants of ligand-receptor specificity. Cell, 2000, 101(4), 413-424.
[http://dx.doi.org/10.1016/S0092-8674(00)80851-X] [PMID: 10830168]
[10]
Goldfarb, M. Fibroblast growth factor homologous factors: evolution, structure, and function. Cytokine Growth Factor Rev., 2005, 16(2), 215-220.
[http://dx.doi.org/10.1016/j.cytogfr.2005.02.002] [PMID: 15863036]
[11]
Yu, F.H.; Catterall, W.A. Overview of the voltage-gated sodium channel family. Genome Biol., 2003, 4(3), 207-214.
[http://dx.doi.org/10.1186/gb-2003-4-3-207] [PMID: 12620097]
[12]
Goetz, R.; Dover, K.; Laezza, F.; Shtraizent, N.; Huang, X.; Tchetchik, D.; Eliseenkova, A.V.; Xu, C.F.; Neubert, T.A.; Ornitz, D.M.; Goldfarb, M.; Mohammadi, M. Crystal structure of a fibroblast growth Factor Homologous Factor (FHF) defines a conserved surface on FHFs for binding and modulation of voltage-gated sodium channels. J. Biol. Chem., 2009, 284(26), 17883-17896.
[http://dx.doi.org/10.1074/jbc.M109.001842] [PMID: 19406745]
[13]
Wang, Q.; McEwen, D.G.; Ornitz, D.M. Subcellular and developmental expression of alternatively spliced forms of fibroblast growth factor 14. Mech. Dev., 2000, 90(2), 283-287.
[http://dx.doi.org/10.1016/S0925-4773(99)00241-5] [PMID: 10640713]
[14]
Schoorlemmer, J.; Goldfarb, M. Fibroblast growth factor homologous factors are intracellular signaling proteins. Curr. Biol., 2001, 11(10), 793-797.
[http://dx.doi.org/10.1016/S0960-9822(01)00232-9] [PMID: 11378392]
[15]
Bugler, B.; Amalric, F.; Prats, H. Alternative initiation of translation determines cytoplasmic or nuclear localization of basic fibroblast growth factor. Mol. Cell. Biol., 1991, 11(1), 573-577.
[http://dx.doi.org/10.1128/MCB.11.1.573] [PMID: 1986249]
[16]
Cao, Y.; Ekström, M.; Pettersson, R.F. Characterization of the nuclear translocation of acidic fibroblast growth factor. J. Cell Sci., 1993, 104(Pt 1), 77-87.
[PMID: 7680660]
[17]
Sanz, J.M.; Giménez-Gallego, G. A partly folded state of acidic fibroblast growth factor at low pH. Eur. J. Biochem., 1997, 246(2), 328-335.
[http://dx.doi.org/10.1111/j.1432-1033.1997.00328.x] [PMID: 9208921]
[18]
Chi, Y.; Kumar, T.K.S.; Wang, H.M.; Ho, M.C.; Chiu, I.M.; Yu, C. Thermodynamic characterization of the human acidic fibroblast growth factor: evidence for cold denaturation. Biochemistry, 2001, 40(25), 7746-7753.
[http://dx.doi.org/10.1021/bi002364+] [PMID: 11412129]
[19]
Mach, H.; Middaugh, C.R. Interaction of partially structured states of acidic fibroblast growth factor with phospholipid membranes. Biochemistry, 1995, 34(31), 9913-9920.
[http://dx.doi.org/10.1021/bi00031a013] [PMID: 7543282]
[20]
Rajalingam, D.; Graziani, I.; Prudovsky, I.; Yu, C.; Kumar, T.K. Relevance of partially structured states in the non-classical secretion of acidic fibroblast growth factor. Biochemistry, 2007, 46(32), 9225-9238.
[http://dx.doi.org/10.1021/bi7002586] [PMID: 17636870]
[21]
Mohan, S.K.; Rani, S.G.; Yu, C. The heterohexameric complex structure, a component in the non-classical pathway for fibroblast growth factor 1 (FGF1) secretion. J. Biol. Chem., 2010, 285(20), 15464-15475.
[http://dx.doi.org/10.1074/jbc.M109.066357] [PMID: 20220137]
[22]
Ptitsyn, O.B. Molten globule and protein folding. Adv. Protein Chem., 1995, 47, 83-229.
[http://dx.doi.org/10.1016/S0065-3233(08)60546-X] [PMID: 8561052]
[23]
Dubey, V.K.; Singh, B.K.; Sarkar, N.; Pande, M.; Jagannadham, M.V. Biophysical characterization of fibroblast growth factor homologous factor-1b (FHF-1b): sodium dodecyl sulfate promotes two state folding. Protein Pept. Lett., 2008, 15(2), 215-218.
[http://dx.doi.org/10.2174/092986608783489535] [PMID: 18289114]
[24]
Moosavi-Movahedi, A.A.; Golchin, A.R.; Nazari, K.; Chamani, J.; Saboury, A.A.; Bathaie, S.Z.; Tangestani-Nejad, S. Microcalorimetry, energetics and binding studies of DNA–dimethyltin dichloride complexes. Thermochim. Acta, 2004, 414(2), 233-241.
[http://dx.doi.org/10.1016/j.tca.2004.01.007]
[25]
Tousi, S.H.; Saberi, M.R.; Chamani, J. Comparing the interaction of cyclophosphamide monohydrate to human serum albumin as opposed to holo-transferrin by spectroscopic and molecular modeling methods: evidence for allocating the binding site. Protein Pept. Lett., 2010, 17(12), 1524-1535.
[http://dx.doi.org/10.2174/0929866511009011524] [PMID: 20937032]
[26]
Chamani, J.; Heshmati, M. Mechanism for stabilization of the molten globule state of papain by sodium n-alkyl sulfates: spectroscopic and calorimetric approaches. J. Colloid Interface Sci., 2008, 322(1), 119-127.
[http://dx.doi.org/10.1016/j.jcis.2008.03.001] [PMID: 18405913]
[27]
Zolfagharzadeh, M.; Pirouzi, M.; Asoodeh, A.; Saberi, M.R.; Chamani, J. A comparison investigation of DNP-binding effects to HSA and HTF by spectroscopic and molecular modeling techniques. J. Biomol. Struct. Dyn., 2014, 32(12), 1936-1952.
[http://dx.doi.org/10.1080/07391102.2013.843062] [PMID: 24125112]
[28]
UCSD Signalling gateway., Available from: http://www.signaling-gateway.org/molecule/query?afcsid=A005756.
[29]
Worth, C.L.; Preissner, R.; Blundell, T.L. SDM--a server for predicting effects of mutations on protein stability and malfunction. Nucleic Acids Res, 2011, 39(Web Server issue). , W215-222.
[http://dx.doi.org/10.1093/nar/gkr363] [PMID: 21593128]
[30]
Zhang, Y. I-TASSER server for protein 3D structure prediction. BMC Bioinformatics, 2008, 9, 40.
[http://dx.doi.org/10.1186/1471-2105-9-40] [PMID: 18215316]
[31]
Tina, K.G.; Bhadra, R.; Srinivasan, N. PIC: Protein Interactions Calculator. Nucleic Acids Res, 2007, 35(Web Server issue). , W473-476.
[http://dx.doi.org/10.1093/nar/gkm423] [PMID: 17584791]
[32]
Waterhouse, A.; Bertoni, M.; Bienert, S.; Studer, G.; Tauriello, G.; Gumienny, R.; Heer, F.T.; de Beer, T.A.P.; Rempfer, C.; Bordoli, L.; Lepore, R.; Schwede, T. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res., 2018, 46(W1), W296-W303.
[http://dx.doi.org/10.1093/nar/gky427] [PMID: 29788355]
[33]
van Zundert, G.C.P.; Rodrigues, J.P.G.L.M.; Trellet, M.; Schmitz, C.; Kastritis, P.L.; Karaca, E.; Melquiond, A.S.J.; van Dijk, M.; de Vries, S.J.; Bonvin, A.M.J.J. The HADDOCK2.2 webserver: user-friendly integrative modeling of biomolecular complexes. J. Mol. Biol., 2016, 428(4), 720-725.
[http://dx.doi.org/10.1016/j.jmb.2015.09.014] [PMID: 26410586]
[34]
Vangone, A.; Bonvin, A.M.J.J. Contacts-based prediction of binding affinity in protein-protein complexes. eLife, 2015, 4e, 07454.
[http://dx.doi.org/10.7554/eLife.07454] [PMID: 26193119]
[35]
Xue, L.C.; Rodrigues, J.P.; Kastritis, P.L.; Bonvin, A.M.J.J.; Vangone, A. PRODIGY: a web server for predicting the binding affinity of protein-protein complexes. Bioinformatics, 2016, 32(23), 3676-3678.
[http://dx.doi.org/10.1093/bioinformatics/btw514] [PMID: 27503228]
[36]
Wallace, A.C.; Laskowski, R.A.; Thornton, J.M. LIGPLOT: a program to generate schematic diagrams of protein-ligand interactions. Protein Eng., 1995, 8(2), 127-134.
[http://dx.doi.org/10.1093/protein/8.2.127] [PMID: 7630882]
[37]
Lemkul, J.A. From proteins to perturbed Hamiltonians: a suite of tutorials for the Gromaccs-2018 molecular simulation package (Article1.0). Living J. Comp. Mol. Sci., 2019, 1(1), 5068-5121.
[http://dx.doi.org/10.33011/livecoms.1.1.5068]
[38]
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.
[http://dx.doi.org/10.1021/ja00214a001] [PMID: 27557051]
[39]
Kaminski, G.A.; Friesner, R.A.; Tirado-Rives, J.; Jorgensen, W.L. evaluation and Reparametrization of the OPLS-AA force field for protiens via comparison with accurate quantum chemical calculations on peptides. J. Phys. Chem., 2001, 105(28), 6474-6487.
[http://dx.doi.org/10.1021/jp003919d]
[40]
Mark, P.; Nilsson, L. Structure and dynamics of the TIP3P, SPC, and SPC/E water models at 298K. J. Phys. Chem., 2001, 105, 9954-9960.
[http://dx.doi.org/10.1021/jp003020w]
[41]
Ghisaidoobe, A.B.; Chung, S.J. Intrinsic tryptophan fluorescence in the detection and analysis of proteins: a focus on Förster resonance energy transfer techniques. Int. J. Mol. Sci., 2014, 15(12), 22518-22538.
[http://dx.doi.org/10.3390/ijms151222518] [PMID: 25490136]
[42]
Sanei, H.; Asoodeh, A.; Hamedakbari-Tusi, S.; Chamani, J. Multi-spectroscopic investigations of aspirin and colchicine interactions with human hemoglobin: binary and ternary systems. J. Solution Chem., 2011, 40(11), 1905-1931.
[http://dx.doi.org/10.1007/s10953-011-9766-3]
[43]
Sharif-Barfeh, Z.; Beigoli, S.; Marouzi, S.; Rad, A.S.; Asoodeh, A.; Chamani, J. SystemsMultispectroscopic and HPLC studies of the interaction between estradiol and cyclophosphamide with human serum albumin: binary and ternary systems. J. Solution Chem., 2017, 46(2), 488-504.
[44]
Málnási-Csizmadia, A.; Hegyi, G.; Tölgyesi, F.; Szent-Györgyi, A.G.; Nyitray, L. Fluorescence measurements detect changes in scallop myosin regulatory domain. Eur. J. Biochem., 1999, 261(2), 452-458.
[http://dx.doi.org/10.1046/j.1432-1327.1999.00290.x] [PMID: 10215856]
[45]
Chamani, J. Comparison of the conformational stability of the non-native α-helical intermediate of thiol-modified β-lactoglobulin upon interaction with sodium n-alkyl sulfates at two different pH. J. Colloid Interface Sci., 2006, 299(2), 636-646.
[http://dx.doi.org/10.1016/j.jcis.2006.02.049] [PMID: 16554059]
[46]
Pace, C.N.; Scholtz, J.M. Measuring the conformational stability of a protein. In: Protein Structure: A Practical Approach; Creighton, T.E., Ed.; Oxford University Press: Oxford, UK, 1997, pp. 299-321.
[47]
Calhoun, D.B.; Vanderkooi, J.M.; Holtom, G.R.; Englander, S.W. Protein fluorescence quenching by small molecules: protein penetration versus solvent exposure. Proteins, 1986, 1(2), 109-115.
[http://dx.doi.org/10.1002/prot.340010202] [PMID: 3130621]
[48]
Andrade, M.A.; Chacón, P.; Merelo, J.J.; Morán, F. Evaluation of secondary structure of proteins from UV circular dichroism spectra using an unsupervised learning neural network. Protein Eng., 1993, 6(4), 383-390.
[http://dx.doi.org/10.1093/protein/6.4.383] [PMID: 8332596]
[49]
Whitmore, L.; Wallace, B.A. Protein secondary structure analyses from circular dichroism spectroscopy: methods and reference databases. Biopolymers, 2008, 89(5), 392-400.
[http://dx.doi.org/10.1002/bip.20853] [PMID: 17896349]
[50]
Pandurangan, A.P.; Ochoa-Montaño, B.; Ascher, D.B.; Blundell, T.L. SDM: a server for predicting effects of mutations on protein stability. Nucleic Acids Res., 2017, 45(W1), W229-W235.
[http://dx.doi.org/10.1093/nar/gkx439] [PMID: 28525590]
[51]
Elmore, D.E.; Dougherty, D.A. Molecular dynamics simulations of wild-type and mutant forms of the Mycobacterium tuberculosis MscL channel. Biophys. J., 2001, 81(3), 1345-1359.
[http://dx.doi.org/10.1016/S0006-3495(01)75791-8] [PMID: 11509350]
[52]
el-Bastawissy, E.; Knaggs, M.H.; Gilbert, I.H. Molecular dynamics simulations of wild-type and point mutation human prion protein at normal and elevated temperature. J. Mol. Graph. Model., 2001, 20(2), 145-154.
[http://dx.doi.org/10.1016/S1093-3263(01)00113-9] [PMID: 11775001]
[53]
Dasgupta, J.; Sen, U.; Dattagupta, J.K. In silico mutations and molecular dynamics studies on a winged bean chymotrypsin inhibitor protein. Protein Eng., 2003, 16(7), 489-496.
[http://dx.doi.org/10.1093/protein/gzg070] [PMID: 12915726]
[54]
Bhardwaj, A.; Dhar, Y.V.; Asif, M.H.; Bag, S.K. In Silico identification of SNP diversity in cultivated and wild tomato species: insight from molecular simulations. Sci. Rep., 2016, 6, 38715.
[http://dx.doi.org/10.1038/srep38715] [PMID: 27929054]
[55]
Fukuyoshi, S.; Kometani, M.; Watanabe, Y.; Hiratsuka, M.; Yamaotsu, N.; Hirono, S.; Manabe, N.; Takahashi, O.; Oda, A. Molecular dynamic simulations to investigate the influences of amino acid mutations on protein three-dimensional structures of cytochrome P450 2D6.1, 2, 10, 14A, 51, and 62. PLoS One, 2016, 11(4)e0152946
[http://dx.doi.org/10.1371/journal.pone.0152946] [PMID: 27046024]
[56]
Schadzek, P.; Schlingmann, B.; Schaarschmidt, F.; Lindner, J.; Koval, M.; Heisterkamp, A.; Ngezahayo, A.; Preller, M. Data of the molecular dynamics simulations of mutations in the human connexin46 docking interface. Data Brief, 2016, 7, 93-99.
[http://dx.doi.org/10.1016/j.dib.2016.01.067] [PMID: 26958636]
[57]
Peng, X.N.; Wang, J.; Zhang, W. Molecular dynamics simulation analysis of the effect of T790M mutation on epidermal growth factor receptor protein architecture in non-small cell lung carcinoma. Oncol. Lett., 2017, 14(2), 2249-2253.
[http://dx.doi.org/10.3892/ol.2017.6387] [PMID: 28789446]
[58]
Pereira, G.R.C.; Da Silva, A.N.R.; Do Nascimento, S.S.; De Mesquita, J.F. In silico analysis and molecular dynamics simulation of human superoxide dismutase 3 (SOD3) genetic variants. J. Cell. Biochem., 2019, 120(3), 3583-3598.
[http://dx.doi.org/10.1002/jcb.27636] [PMID: 30206983]


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VOLUME: 26
ISSUE: 11
Year: 2019
Published on: 23 October, 2019
Page: [848 - 859]
Pages: 12
DOI: 10.2174/0929866526666190503092718
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