Increasing affinity of interferon-γ receptor 1 to interferon-γ by computer-aided design
Language English Country United States Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
24199198
PubMed Central
PMC3807708
DOI
10.1155/2013/752514
Knihovny.cz E-resources
- MeSH
- Interferon-gamma chemistry genetics metabolism MeSH
- Humans MeSH
- Surface Plasmon Resonance MeSH
- Interferon gamma Receptor MeSH
- Receptors, Interferon chemistry genetics metabolism MeSH
- Protein Folding * MeSH
- Molecular Dynamics Simulation * MeSH
- Amino Acid Substitution MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- IFNG protein, human MeSH Browser
- Interferon-gamma MeSH
- Receptors, Interferon MeSH
We describe a computer-based protocol to design protein mutations increasing binding affinity between ligand and its receptor. The method was applied to mutate interferon-γ receptor 1 (IFN-γ-Rx) to increase its affinity to natural ligand IFN-γ, protein important for innate immunity. We analyzed all four available crystal structures of the IFN-γ-Rx/IFN-γ complex to identify 40 receptor residues forming the interface with IFN-γ. For these 40 residues, we performed computational mutation analysis by substituting each of the interface receptor residues by the remaining standard amino acids. The corresponding changes of the free energy were calculated by a protocol consisting of FoldX and molecular dynamics calculations. Based on the computed changes of the free energy and on sequence conservation criteria obtained by the analysis of 32 receptor sequences from 19 different species, we selected 14 receptor variants predicted to increase the receptor affinity to IFN-γ. These variants were expressed as recombinant proteins in Escherichia coli, and their affinities to IFN-γ were determined experimentally by surface plasmon resonance (SPR). The SPR measurements showed that the simple computational protocol succeeded in finding two receptor variants with affinity to IFN-γ increased about fivefold compared to the wild-type receptor.
See more in PubMed
Kraemer-Pecore CM, Wollacott AM, Desjarlais JR. Computational protein design. Current Opinion in Chemical Biology. 2001;5(6):690–695. PubMed
Kortemme T, Baker D. Computational design of protein-protein interactions. Current Opinion in Chemical Biology. 2004;8(1):91–97. PubMed
Reichmann D, Rahat O, Cohen M, Neuvirth H, Schreiber G. The molecular architecture of protein-protein binding sites. Current Opinion in Structural Biology. 2007;17(1):67–76. PubMed
Mandell DJ, Kortemme T. Computer-aided design of functional protein interactions. Nature Chemical Biology. 2009;5(11):797–807. PubMed
Karanicolas J, Kuhlman B. Computational design of affinity and specificity at protein-protein interfaces. Current Opinion in Structural Biology. 2009;19(4):458–463. PubMed PMC
Smith CA, Kortemme T. Predicting the tolerated sequences for proteins and protein interfaces using rosettabackrub flexible backbone design. PLoS ONE. 2011;6(7)e20451 PubMed PMC
Fleishman SJ, Whitehead TA, Strauch EM, Corn JE, Qin SB, et al. Community-wide assessment of protein-interface modeling suggests improvements to design methodology. Journal of Molecular Biology. 2011;414:289–302. PubMed PMC
Smith GP. Filamentous fusion phage: novel expression vectors that display cloned antigens on the virion surface. Science. 1985;228(4705):1315–1317. PubMed
Smith GP, Petrenko VA. Phage display. Chemical Reviews. 1997;97(2):391–410. PubMed
Kehoe JW, Kay BK. Filamentous phage display in the new millennium. Chemical Reviews. 2005;105(11):4056–4072. PubMed
Hanes J, Plückthun A. In vitro selection and evolution of functional proteins by using ribosome display. Proceedings of the National Academy of Sciences of the United States of America. 1997;94(10):4937–4942. PubMed PMC
Lipovsek D, Plückthun A. In-vitro protein evolution by ribosome display and mRNA display. Journal of Immunological Methods. 2004;290(1-2):51–67. PubMed
Fleishman SJ, Whitehead TA, Ekiert DC, et al. Computational design of proteins targeting the conserved stem region of influenza hemagglutinin. Science. 2011;332(6031):816–821. PubMed PMC
Karanicolas J, Corn JE, Chen I, et al. A De Novo protein binding pair by computational design and directed evolution. Molecular Cell. 2011;42(2):250–260. PubMed PMC
Whitehead TA, Chevalier A, Song Y, Dreyfus C, Fleishman SJ, et al. Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing. Nature Biotechnology. 2012;30:543–548. PubMed PMC
Chen TS, Keating AE. Designing specific protein-protein interactions using computation, experimental library screening, or integrated methods. Protein Science. 2012;21:949–963. PubMed PMC
Thiel DJ, Le Du M-H, Walter RL, et al. Observation of an unexpected third receptor-molecule in the crystal structure of human interferon-γ receptor complex. Structure. 2000;8(9):927–936. PubMed
Lassmann T, Frings O, Sonnhammer ELL. Kalign2: high-performance multiple alignment of protein and nucleotide sequences allowing external features. Nucleic Acids Research. 2009;37(3):858–865. PubMed PMC
Efremov IE, Fursov MY, Danilova YE. Ugene: High Performance Genome Analysis Suite. Moscow, Russia: 2009.
Müller U, Steinhoff U, Reis LFL, et al. Functional role of type I and type II interferons in antiviral defense. Science. 1994;264(5167):1918–1921. PubMed
Borden EC, Sen GC, Uze G, et al. Interferons at age 50: past, current and future impact on biomedicine. Nature Reviews Drug Discovery. 2007;6(12):975–990. PubMed PMC
Schroder K, Hertzog PJ, Ravasi T, Hume DA. Interferon-γ: an overview of signals, mechanisms and functions. Journal of Leukocyte Biology. 2004;75(2):163–189. PubMed
Gray PW, Goeddel DV. Structure of the human immune interferon gene. Nature. 1982;298(5877):859–863. PubMed
Ahmad JN, Li J, Biedermannova L, Kuchar M, Sipova H, et al. Novel high-affinity binders of human interferon gamma derived from albumin-binding domain of protein g. Proteins. 2012;80:774–789. PubMed
Sipova H, Sevcu V, Kuchar M, Ahmad JN, Mikulecky P, et al. Surface plasmon resonance biosensor based on engineered proteins for direct detection of interferon-gamma in diluted blood plasma. Sensors and Actuators B. 2012;174:306–311.
Johansson MU, Frick I-M, Nilsson H, et al. Structure, specificity, and mode of interaction for bacterial albumin-binding modules. Journal of Biological Chemistry. 2002;277(10):8114–8120. PubMed
Windsor WT, Walter LJ, Syto R, Fossetta J, Cook WJ, et al. Purification and crystallization of a complex between human interferon gamma receptor (extracellular domain) and human interferon gamma. Proteins. 1996;26:108–114. PubMed
Michiels L, Haelewyn J, Proost P, De Ley M. The soluble extracellular portion of the human interferon-γ receptor is a valid substitute for evaluating binding characteristics and for neutralizing the biological activity of this cytokine. International Journal of Biochemistry and Cell Biology. 1998;30(4):505–516. PubMed
Randal M, Kossiakoff AA. The structure and activity of a monomeric interferon-γ:α-chain receptor signaling complex. Structure. 2001;9(2):155–163. PubMed
Ealick SE, Cook WJ, Vijay-Kumar S, et al. Three-dimensional structure of recombinant human interferon-γ . Science. 1991;252(5006):698–702. PubMed
Landar A, Curry B, Parker MH, et al. Design, characterization, and structure of a biologically active single-chain mutant of human IFN-γ . Journal of Molecular Biology. 2000;299(1):169–179. PubMed
Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. Journal of Molecular Graphics. 1996;14(1):33–38. PubMed
Schymkowitz J, Borg J, Stricher F, Nys R, Rousseau F, Serrano L. The FoldX web server: an online force field. Nucleic Acids Research. 2005;33(2):W382–W388. PubMed PMC
Eastman P, Pande VS. Openmm: a hardware-independent framework for molecular simulations. Computing in Science and Engineering. 2010;12:34–39. PubMed PMC
Friedrichs MS, Eastman P, Vaidyanathan V, et al. Accelerating molecular dynamic simulation on graphics processing units. Journal of Computational Chemistry. 2009;30(6):864–872. PubMed PMC
Van Der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJC. GROMACS: fast, flexible, and free. Journal of Computational Chemistry. 2005;26(16):1701–1718. PubMed
Eswar N, John B, Mirkovic N, et al. Tools for comparative protein structure modeling and analysis. Nucleic Acids Research. 2003;31(13):3375–3380. PubMed PMC
Kollman PA. Advances and continuing challenges in achieving realistic and predictive simulations of the properties of organic and biological molecules. Accounts of Chemical Research. 1996;29(10):461–469.
DeGrado WF, Wasserman ZR, Chowdry V. Sequence and structural homologies among type I and type II interferons. Nature. 1982;300(5890):379–381. PubMed
Arakawa T, Hsu Y-R, Chang D. Structure and activity of glycosylated human interferon-γ . Journal of Interferon Research. 1986;6(6):687–695. PubMed
Pestka S, Langer JA, Zoon KC, Samuel CE. Interferons and their actions. Annual Review of Biochemistry. 1987;56:727–777. PubMed
Kelker HC, Yip YK, Anderson P, Vilcek J. Effects of glycosidase treatment on the physicochemical properties and biological activity of human interferon-γ . Journal of Biological Chemistry. 1983;258(13):8010–8013. PubMed
Sviridova E, Bumba L, Rezacova P, et al. Crystallization and preliminary crystallographic characterization of the iron-regulated outer membrane lipoprotein FrpD from Neisseria meningitidis. Acta Crystallographica Section F. 2010;66(9):1119–1123. PubMed PMC
Pierce BG, Haidar JN, Yu Y, Weng Z. Combinations of affinity-enhancing mutations in a T cell receptor reveal highly nonadditive effects within and between complementarity determining regions and chains. Biochemistry. 2010;49(33):7050–7059. PubMed PMC
Clark LA, Boriack-Sjodin PA, Eldredge J, et al. Affinity enhancement of an in vivo matured therapeutic antibody using structure-based computational design. Protein Science. 2006;15(5):949–960. PubMed PMC
Song G, Lazar GA, Kortemme T, et al. Rational design of intercellular adhesion molecule-1 (ICAM-1) variants for antagonizing integrin lymphocyte function-associated antigen-1-dependent adhesion. Journal of Biological Chemistry. 2006;281(8):5042–5049. PubMed PMC
Han J, Kim HJ, Lee S-C, et al. Structure-based rational design of a Toll-like receptor 4 (TLR4) decoy receptor with high binding affinity for a target protein. PLoS ONE. 2012;7(2)e30929 PubMed PMC
Sharabi O, Peleg Y, Mashiach E, et al. Design, expression and characterization of mutants of fasciculin optimized for interaction with its target, acetylcholinesterase. Protein Engineering, Design and Selection. 2009;22(10):641–648. PubMed PMC
Shifman JM, Mayo SL. Modulating calmodulin binding specificity through computational protein design. Journal of Molecular Biology. 2002;323(3):417–423. PubMed
Sammond DW, Eletr ZM, Purbeck C, Kuhlman B. Computational design of second-site suppressor mutations at protein-protein interfaces. Proteins. 2010;78(4):1055–1065. PubMed PMC
De Genst E, Areskoug D, Decanniere K, Muyldermans S, Andersson K. Kinetic and affinity predictions of a protein-protein interaction using multivariate experimental design. Journal of Biological Chemistry. 2002;277(33):29897–29907. PubMed
Marvin JS, Lowman HB. Redesigning an antibody fragment for faster association with its antigen. Biochemistry. 2003;42(23):7077–7083. PubMed
Selzer T, Albeck S, Schreiber G. Rational design of faster associating and tighter binding protein complexes. Nature Structural Biology. 2000;7(7):537–541. PubMed
Lengyel CSE, Willis LJ, Mann P, et al. Mutations designed to destabilize the receptor-bound conformation increase MICA-NKG2D association rate and affinity. Journal of Biological Chemistry. 2007;282(42):30658–30666. PubMed
Schreiber G, Shaul Y, Gottschalk KE. Electrostatic design of protein-protein association rates. Methods in Molecular Biology. 2006;340:235–249. PubMed
Gorham RD, Jr., Kieslich CA, Morikis D. Electrostatic clustering and free energy calculations provide a foundation for protein design and optimization. Annals of Biomedical Engineering. 2011;39(4):1252–1263. PubMed PMC
Krissinel E, Henrick K. Inference of macromolecular assemblies from crystalline state. Journal of Molecular Biology. 2007;372(3):774–797. PubMed
Nuara AA, Walter LJ, Logsdon NJ, et al. Structure and mechanism of IFN-γ antagonism by an orthopoxvirus IFN-γ-binding protein. Proceedings of the National Academy of Sciences of the United States of America. 2008;105(6):1861–1866. PubMed PMC
Levin AM, Bates DL, Ring AM, et al. Exploiting a natural conformational switch to engineer an interleukin-2 ’superkine’. Nature. 2012;484(7395):529–533. PubMed PMC
Bradshaw RT, Patel BH, Tate EW, Leatherbarrow RJ, Gould IR. Comparing experimental and computational alanine scanning techniques for probing a prototypical protein-protein interaction. Protein Engineering, Design and Selection. 2011;24(1-2):197–207. PubMed
Sharabi O, Dekel A, Shifman JM. Triathlon for energy functions: who is the winner for design of protein-protein interactions? Proteins. 2011;79(5):1487–1498. PubMed
Bradshaw RT, Aronica PGA, Tate EW, Leatherbarrow RJ, Gould IR. Mutational Locally Enhanced Sampling (MULES) for quantitative prediction of the effects of mutations at protein-protein interfaces. Chemical Science. 2012;3(5):1503–1511.