Influence of Heparin Mimetics on Assembly of the FGF·FGFR4 Signaling Complex

Saxena, Krishna; Schieborr, Ulrich; Anderka, Oliver; Duchardt‐Ferner, Elke; Elshorst, Bettina; Gande, S.L.; Janzon, Julia; Kudlinzki, D.; Sreeramulu, Sridhar; Dreyer, Matthias; Wendt, K. Ulrich; Herbert, Corentin; Duchaussoy, Philippe; Bianciotto, Marc; Driguez, Pierre‐Alexandre; Lassalle, Gilbert; Savi, Pierre; Mohammadi, Moosa; Bono, Françoise; Schwalbe, Harald

doi:10.1074/jbc.m109.095109

Cited by 31 publications

(36 citation statements)

References 76 publications

(172 reference statements)

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“…According to the calculated H-bonding frequencies (Fig. 5a), Asn 18, Lys 112, Lys 113, Arg 122 and Arg 128 form the most frequently observed H-bonds with IdoA2S units of HE dp6, highlighting the particular importance of IdoA2S sulfate groups in binding, which is in good agreement with previous SPR measurements [50]. Similarly, from the MD simulations of these three FGF1-HE crystal structures, only the central GlcNS was comparable to IdoA2S units in terms of H-bonding frequencies.…”

Section: Resultssupporting

confidence: 89%

Computational drill down on FGF1-heparin interactions through methodological evaluation

2016

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Glycosaminoglycans (GAGs) exhibit a key role in cellular communication processes through interactions with target proteins of the extracellular matrix (ECM). The sandwich-like interaction established between Fibroblast growth factor (FGF) and heparin (HE) represents quite a peculiar protein-GAG-protein system, which has been both structurally and functionally intensively studied. The molecular recognition characteristics of this system have been exploited in various computational studies in order to deepen understanding of GAG-protein interactions. Here, we drill down on the interactions established in this peculiar macromolecular complex by analyzing the applicability of docking techniques and molecular dynamics (MD)-based approaches, and we dissect the molecular recognition properties exhibited by FGF towards a series of HE derivatives. We examine the sensitivity of MM-GBSA free energy calculations in terms of receptor conformational space sampling and changes in the ligand structures. Furthermore, we investigate its predictive power in combination with other computational methods, namely the well-established Autodock3 (AD3) and dynamic molecular docking (DMD), a targeted MD-based docking method specifically developed to account for flexibility and solvent in computer simulations of protein-GAG systems. Our results show that a site-mapping approach can be effectively combined with AD3 and DMD calculations to accurately reproduce available experimental data and, furthermore, to determine specific GAG recognition patterns. This study deepens our understanding of the applicability of available theoretical approaches to the investigation of molecular recognition in protein-GAG systems.Electronic supplementary materialThe online version of this article (doi:10.1007/s10719-016-9745-4) contains supplementary material, which is available to authorized users.

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Section: Resultssupporting

confidence: 89%

Computational drill down on FGF1-heparin interactions through methodological evaluation

2016

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“…B, DP required for complex formation between FGF2 and polySia. Left panel, FGF2 (100 ng) was incubated without (none) or with oligo/polySia (DP ϭ 1-10 (mixture of 1-10), DP ϭ 11-20 (mixture of [11][12][13][14][15][16][17][18][19][20], DP ϭ 21-30 (mixture of [21][22][23][24][25][26][27][28][29][30], and DP ϭ 31-40 (mixture of [21][22][23][24][25][26][27][28][29][30]) in TBS at 37°C for 2 h. Right upper panel, FGF2 (100 ng) was incubated with polySia with defined DP (DP ϭ 11-16) in TBS at 37°C for 2 h. Right lower panel, FGF2 (100 ng) was incubated with polySia with defined DP (DP ϭ 15-24) in TBS at 37°C for 2 h. Samples were analyzed by horizontal native-PAGE. Arrowhead, origin; Ϫ, cathode; ϩ, anode.…”

Section: Resultsmentioning

confidence: 99%

“…FGF2 exhibits high affinity to IIIc-type FGFR-1 and -2 and low affinity to IIIctype FGFR-3 (27,28). FGF2 is also known to have affinity to heparan sulfate (HS) proteoglycan (19), with the HS of HS proteoglycan functioning as the key molecule for the formation of the ternary complex with FGF2 and FGFR (29,30). The K d values of FGF2 binding to HS and FGFR-1 are 39 and 62 nM, respectively, as determined by the surface plasmon resonance (SPR) (31) method.…”

mentioning

confidence: 99%

Novel Regulation of Fibroblast Growth Factor 2 (FGF2)-mediated Cell Growth by Polysialic Acid

Ono

Hane

Kitajima

et al. 2012

Journal of Biological Chemistry

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Background: Polysialic acid (polySia) binds neurological factors, BDNF and dopamine. Results: PolySia specifically binds FGF2 and inhibits the cell growth facilitated by signaling through a ternary complex of FGF2, FGFR, and heparan sulfate (HS). Conclusion: PolySia regulates the FGF2-mediated cell growth differently from HS. Significance: A new function of polySia to regulate the action of neurological factors is established.

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“…Lipid/membrane interactions Polysaccharide interactions Protein/peptide interactions with polymers and nanoparticles …”

Section: Introductionmentioning

confidence: 99%

Applications of isothermal titration calorimetry in pure and applied research—survey of the literature from 2010

Ghai

Falconer

Collins

2011

J of Molecular Recognition

163

108

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Isothermal titration calorimetry (ITC) is a biophysical technique for measuring the formation and dissociation of molecular complexes and has become an invaluable tool in many branches of science from cell biology to food chemistry. By measuring the heat absorbed or released during bond formation, ITC provides accurate, rapid, and label-free measurement of the thermodynamics of molecular interactions. In this review, we survey the recent literature reporting the use of ITC and have highlighted a number of interesting studies that provide a flavour of the diverse systems to which ITC can be applied. These include measurements of protein-protein and protein-membrane interactions required for macromolecular assembly, analysis of enzyme kinetics, experimental validation of molecular dynamics simulations, and even in manufacturing applications such as food science. Some highlights include studies of the biological complex formed by Staphylococcus aureus enterotoxin C3 and the murine T-cell receptor, the mechanism of membrane association of the Parkinson's disease-associated protein α-synuclein, and the role of non-specific tannin-protein interactions in the quality of different beverages. Recent developments in automation are overcoming limitations on throughput imposed by previous manual procedures and promise to greatly extend usefulness of ITC in the future. We also attempt to impart some practical advice for getting the most out of ITC data for those researchers less familiar with the method.

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Influence of Heparin Mimetics on Assembly of the FGF·FGFR4 Signaling Complex

Cited by 31 publications

References 76 publications

Computational drill down on FGF1-heparin interactions through methodological evaluation

Computational drill down on FGF1-heparin interactions through methodological evaluation

Novel Regulation of Fibroblast Growth Factor 2 (FGF2)-mediated Cell Growth by Polysialic Acid

Applications of isothermal titration calorimetry in pure and applied research—survey of the literature from 2010

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