- Research article
- Open Access
Human S100A5 binds Ca2+ and Cu2+ independently
© The Author(s) 2017
- Received: 19 September 2017
- Accepted: 8 November 2017
- Published: 22 November 2017
S100A5 is a calcium binding protein found in a small subset of amniote tissues. Little is known about the biological roles of S100A5, but it may be involved in inflammation and olfactory signaling. Previous work indicated that S100A5 displays antagonism between binding of Ca2+ and Cu2+ ions—one of the most commonly cited features of the protein. We set out to characterize the interplay between Ca2+ and Cu2+ binding by S100A5 using isothermal titration calorimetry (ITC), circular dichroism spectroscopy (CD), and analytical ultracentrifugation (AUC).
We found that human S100A5 is capable of binding both Cu2+ and Ca2+ ions simultaneously. The wildtype protein was extremely aggregation-prone in the presence of Cu2+ and Ca2+. A Cys-free version of S100A5, however, was not prone to precipitation or oligomerization. Mutation of the cysteines does not disrupt the binding of either Ca2+ or Cu2+ to S100A5. In the Cys-free background, we measured Ca2+ and Cu2+ binding in the presence and absence of the other metal using ITC. Saturating concentrations of Ca2+ or Cu2+ do not disrupt the binding of one another. Ca2+ and Cu2+ binding induce structural changes in S100A5, which are measurable using CD spectroscopy. We show via sedimentation velocity AUC that the wildtype protein is prone to the formation of soluble oligomers, which are not present in Cys-free samples.
S100A5 can bind Ca2+ and Cu2+ ions simultaneously and independently. This observation is in direct contrast to previously-reported antagonism between binding of Cu2+ and Ca2+ ions. The previous result is likely due to metal-dependent aggregation. Little is known about the biology of S100A5, so an accurate understanding of the biochemistry is necessary to make informed biological hypotheses. Our observations suggest the possibility of independent biological functions for Cu2+ and Ca2+ binding by S100A5.
- S100 proteins
- Calcium binding proteins
- Copper binding
- Circular dichroism
S100A5 is a member of the calcium-binding S100 protein family. The protein is primarily homodimeric and is capable of binding one Ca2+ ion each at it’s EF-hand and pseudo-EF-hand sites [1, 2]. S100A5 undergoes a notable conformational change upon calcium-binding, resulting in the rotation and extension of a helix . This Ca2+-driven exposure of a hydrophobic surface is the primary mode of signal transduction in the S100 proteins . Through interactions with metals and protein targets, S100s play a variety of biological roles including control of cell proliferation, inflammatory signalling, and antimicrobial activity [4–7].
S100A5 is expressed primarily in the olfactory bulb and olfactory sensory neurons (OSNs). Its expression is dramatically upregulated by odor stimulation [8–10]. It has been proposed that S100A5 is actively involved in olfactory signalling due to its expression profile . Expression of the protein has also been observed in a small number of other tissues . It is used as a bio-marker for several types of brain cancers and inflammatory disorders and appears to be involved in inflammation via activation of RAGE [2, 11, 12]. Genetic work on S100A5 has been minimal, which has limited our understanding of its biological roles.
The first biochemical study of human S100A5 identified it as a novel Ca2+, Cu2+, and Zn2+ binding protein . The authors used flow-dialysis to measure binding of the metal ions to the protein and concluded that S100A5 is capable of binding four Ca2+ ions, four Cu2+ ions, and two Zn2+ ions per homodimer. One of the most striking observations of that study was the strong antagonism between the binding of Cu2+ and Ca2+ ions to the protein. This feature is one of the most highly cited aspects of S100A5. Because little is known about the protein, this fact is present in descriptions found across databases such as Uniprot, NCBI, Wikigenes, and Genecards [13–15]. While most S100s are capable of binding transition metal ions, antagonism with binding of Ca2+ is not known outside the S100A5 lineage. Thus, this unique feature of S100A5 provoked speculation about its possible biological implications [9, 16]. It was suggested that S100A5 might act as a Cu2+ and Ca2+ regulated signal during olfaction or as a Cu2+ sink to accommodate high Cu2+ concentrations in the olfactory bulb .
We sought to characterize this presumably important feature of S100A5 in more detail. Previously, we characterized the binding of Cu2+ and Zn2+ to a large number of S100 proteins including S100A5 . Via ITC competition experiments, we established that these two metals bind at different sites on the protein and do not compete for binding . We found that mutation of Cys43 and Cys79 lead to a loss of Zn2+ binding. In contrast neither of these residues was necessary for binding of Cu2+. Due to the original report of Ca2+ /Cu2+ antagonism we suspected that Ca2+ and Cu2+ may compete for the same sites on S100A5.
Here we report our study of the interplay between Ca2+ and Cu2+ binding by S100A5. Using a Cysteine-free variant (C43S/C79S) of the protein, we show that binding of Ca2+ and Cu2+ are not in fact antagonistic. The protein is capable of binding the two metals–which induce notable structural changes–simultaneously and independently. Furthermore, we establish that the Cysteine-containing (WT) protein is prone to the formation of high-ordered oligomers in solution, while the Cysteine-free variant is almost entirely dimeric. We suggest that this propensity for formation of large oligomeric species and precipitation under our experimental conditions may underlie the apparent antagonism observed in the original S100A5 report. Our results may suggest new biological roles for Cu2+ binding by this protein.
Ca2+ and Cu2+ binding to S100A5 are not antagonistic
We found previously that neither of the two native Cys residues in S100A5 were required for Cu2+ binding . We also noticed that–unlike the wildtype protein–the Cys-free mutant did not precipitate in the presence of saturating Ca2+ and Cu2+. We thus sought to use ITC to characterize the interaction between binding of the two metal ions using the Cys-Ser double mutant. Because some of the metal-binding curves were complex and difficult to fit, we used a Bayesian Markov Chain Monte Carlo sampler–as implemented in pytc–to estimate thermodynamic parameters for all binding models . We also included a floating “fraction competent” parameter to capture uncertainty in the relative protein and metal concentrations (following SEDPHAT ). This was necessary because a number of factors make it difficult to obtain accurate estimates of concentrations for components of this system. S100A5 has no tryptophan residues and, therefore, a low extinction coefficient that makes absorbance-based concentration estimates unreliable. Further, water absorption by dry metal salts, as well as interactions between metal ions and buffer, can also make estimates of metal concentration difficult. Because of these of uncertainties, ITC has been noted to provide poor estimates of stoichiometry for protein metal binding .
Fit parameters from pytc fits
Δ H 1
Δ H 2
We next performed the inverse set of experiments. We used ITC to measure the binding of Ca2+ to the protein in the apo and Cu2+ –saturated forms. For each condition, we used four different titrant/stationary ratios to better resolve the complex Ca2+ binding curve and then globally fit a binding model to all four datasets (Fig. 2 c). This binding curve had two distinct phases and could be fit with a two-site binding polynomial (Fig. 2 c). These Ca2+ binding curves presented a challenging model-fitting problem due to the complex shape of the curve. The individual enthalpies and binding constants may therefore be under-determined in our analysis. To resolve realistic parameter values from the binding polynomial model, we constrained the dilution heat and dilution intercept in the Bayesian fit to reasonable values.
We observed one high-affinity site (K d (μ M): 0.14≤0.46≤2.68) and one lower-affinity site (K d (μ M): 1.85≤6.33≤34.88). The values were roughly consistent with those reported in the literature . The presence of saturating Cu2+ did not inhibit the binding of Ca2+ ions (Fig. 2 d; Table 1). The K d value of the low affinity site (K d (μ M): 0.03≤0.18≤2.16) was not distinguishable within uncertainty from that of the apo protein. The K d of the high affinity site (K d (μ M): 1.86≤10.46≤100.3) is similarly indistinguishable from that for the apo protein (Table 1). Our results clearly demonstrate that Ca2+ and Cu2+ ions do not display strong antagonism when binding to S100A5.
S100A5 is prone to oligomerization and metal-driven aggregation
We hypothesized that the metal-driven aggregation process observed in our ITC experiments with the wildtype protein contributed to the apparent antagonism that was previously reported. To further examine this aggregation process we used sedimentation velocity AUC to test for the presence of oligomers in solution. We hypothesized that the oligomerization of the wildtype protein was driven by the presence of Cysteine residues. Due to the presence of Cu2+ in some samples we were unable to use a reducing agent in either the ITC or AUC experiments.
Binding of Ca2+ and Cu2+ induce reversible changes in S100A5 secondary structure
S100A5 is one of the lesser-known members of the S100 protein family. Its expression pattern is very narrow and its biological functions are mostly uncharacterized. However, it has been the target of multiple biochemical studies that have sought to characterize the properties of the protein itself. Binding of metals and proteins to S100A5 have been studied using various techniques [1, 2, 9, 11, 17]. X-ray crystallography and NMR have been used to solve structures of both apo and Ca2+ –bound forms of the protein [1, 26]. Despite the available biochemical data aspects of S100A5 have remained ambiguous. For example, the stoichiometry of transition metal binding and structural responses to metal binding have been variably reported [9, 17].
One of the most noted features of S100A5 is the strong antagonism between binding of Ca2+ and Cu2+ ions. This feature is reported in the gene descriptions found in many databases [13–15]. In this study we set out to characterize this unique feature of S100A5, hypothesizing that it was due to competition between the two metals for shared ligands. However, we found an absence of direct binding antagonism between Ca2+ and Cu2+. Neither metal ion affects the binding constant for the other. Instead, we observed a propensity of the protein for oligomerization and metal-induced aggregation. It is possible that the reduction of binding-competent protein caused by this aggregation process was interpreted in the original flow dialysis study of S100A5 as antagonism between Ca2+ and Cu2+. We also report notable changes in the secondary structure of S100A5 upon binding of both Ca2+ and Cu2+, which is contrary the original report that S100A5 structure is insensitive to the binding of metals.
One intriguing implication of our observations is that the Cu2+ binding site of S100A5 must be quite distinct from that of other S100 proteins. Ca2+ and Cu2+ clearly do not share ligands, or there would be evidence of competition in our ITC experiments. Cysteine residues are thought to be involved in metal-binding in some other S100s [16, 27] and we previously showed that the Cys-free mutant of S100A5 displays compromised Zn2+ binding . However, neither native Cys residue of S100A5 is required for Cu2+ binding. Furthermore, we showed that Zn2+ and Cu2+ do not share ligands, as they do not compete at all in ITC experiments . In addition, mutation of His17–which is present in the canonical transition metal site of many S100s–also had no effect on Cu2+ binding in S100A5 . The results presented here with the Cys-free mutant also clearly rule out the possibility of oligomer-dependent Cu2+ binding, such as could be achieved by the formation of a new site in a high-order oligomeric species. Thus, we still have no clues as to where Cu2+ ions bind on S100A5. Further characterization–such as via scanning mutagenesis–will be necessary to determine the identity of Cu2+ ligands.
Biological roles for the binding of transition metals have been established for some S100s and suggested for many others [16, 18, 27–29]. The binding constants that we measured for Ca2+ and Cu2+ suggest the possibility of physiologically relevant interactions in some tissues. Free Ca2+ concentrations in rat olfactory neurons reach ≈2 μ M during nerve stimulation . Likewise, pools of Cu2+ are released in and around olfactory neurons during signaling, reaching concentrations as high as 10 μ M in the synapse [31–34]. Further, despite high Cu2+ concentrations, the olfactory bulb in rats does not have elevated expression of the typical copper chaperone metallothionein . It has been suggested that S100A5 may play a role as a Cu2+ buffer or chaperone in OSNs during olfactory signaling . The fact that Cu2+ is able to induce structural changes in S100A5 suggests it could play a more active role: S100A5 could actually respond to Cu2+ and propagate a resulting signal by interacting with downstream targets.
Due to lack of antagonism, Cu2+ –dependent functions could be achieved even in the presence of saturating Ca2+ levels. Furthermore, there could be synergistic functional roles for binding of Ca2+ and Cu2+. For example, if S100A5 is acting as a Cu2+ chaperone, binding of Ca2+ could facilitate binding of protein targets–via exposure of the hydrophobic binding interface–to which Cu2+ is being delivered. Furthermore, S100A5 is capable of binding Zn2+ ions–which are also at high concentration in the olfactory bulb–with similar affinity to Cu2+ . Zn2+ and Cu2+ also bind noncompetitively and thus all three metals could potentially engage in synergistic activities .
One final possibility is that the oligomerization process we observed in this study may actually have a biological function. Wildtype S100A5 is prone to the formation of oligomers even in the apo form and is subject to extensive aggregation in solutions containing Ca2+ and Cu2+ even at relatively low protein concentrations. Roles for metal-driven oligomerization in S100s have been suggested previously [7, 36–38]. It is conceivable that Ca2+ and Cu2+ drive oligomerization of S100A5 in cells to facilitate a biological function, but further experiments would be required to determine if this process occurs in the reducing environment of the cell at physiologically-relevant concentrations of S100A5, Ca2+ and Cu2+.
Future experiments are needed to elucidate the biochemical features and biological functions of S100A5 that remain unknown. It will be important to identify the Cu2+ ligands in S100A5 to fully understand the biochemical interplay between the binding of various biologically relevent metals. To understand how Ca2+, Cu2+, and Zn2+ contribute to the biological activity of S100A5, experiments should be targeted at directly testing how these metals interact with the protein in vivo. The identification of more S100A5 biological targets and an increase in functional studies will be required to determine the chief roles of S100A5 in its cellular environment.
Antagonism between binding of Ca2+ and Cu2+ ions to S100A5 is one of the most oft-cited aspects of this protein. Several possible biological roles have been suggested. Using careful biophysical characterization, we discovered that binding of Ca2+ and Cu2+ ions is not antagonistic. A Cys-free mutant version of the protein makes measurements of metal binding using ITC possible and shows that the protein is capable of binding both metals simultaneously and independently. Rather than binding antagonism, it appears that the wildtype protein is prone to oligomerization and aggregation and that these behaviors may have contributed to the original interpretation. Furthermore, we also measured the effects of Ca2+ and Cu2+ binding on S100A5 secondary structure and found that both metals are capable of inducing increases in α-helical secondary character. These results also contrast the original report on S100A5 , but are consistent with previously published NMR data . The ability to bind Ca2+ and Cu2+ independently as well as the structural response to Cu2+ may suggest new Cu2+ –dependent biological roles for S100A5.
Protein expression and purification
We previously generated the 6-histidine-tagged cysteine double-mutant construct in a pet28/30 vector . In this study, the protein was expressed and purified using the same protocol detailed in the previous publication. Briefly, the protein was expressed in a 1.5L culture of Rosetta (DE3) pLysS cells (Millipore). Cells were lysed by sonication and treatment with DNase and lysozyme. Subsequently, the tagged protein was purified using HisTrap Ni2+ affinity columns (GE). The tag was then cleaved using TEV protease and the cleaved protein was further purified using Ca2+-dependent hydrophobic interaction chromatography. Finally, the sample was run over a second HisTrap Ni2+ affinity column to remove any uncleaved protein. The purified protein was dialyzed with 6000-8000 MWCO tubing (Fisher) against 2L 25 mM Tris, 100 mM NaCl, pH 7.4 with 2g chelex resin (BioRad). The dialyzed protein was filter-sterilized (0.22 μ m), flash-frozen dropwise in liquid nitrogen, and stored at − 80°C. We experimentally determined the extinction coefficient (5002M −1 cm −1) of the Cys-Ser double mutant. We measured the A 280 of the protein at the same concentration in both buffer and denaturing 6M GdHCl (Sigma). We used ProtParam  to predict an extinction coefficient for the protein based on sequence and then calculated the corrected coefficient using the equation ε native =ε 6MGdm ·A 280,native /A 280,6MGdm . Concentration measurements were also corrected for scattering in samples . Due to the low extinction coefficient of the protein, concentration is difficult to measure with high confidence, even with this careful protocol.
Isothermal titration calorimetry
Samples were prepared in 25 mM TES (Sigma), 100 mM NaCl (Thermo Scientific), buffer at pH 7.4. Protein was thawed from the frozen stock and exchanged into the experimental buffer using NAP-25 desalting columns (GE Healthcare). For competition experiments the experimental buffer also contained either 1 mM CaCl 2 (Sigma) or 0.25 mM CuCl 2 (Sigma). Titrant solutions were prepared in matching experimental buffer to ensure identical conditions to titrate. Anhydrous CaCl 2 or CuCl 2 was dissolved directly in the buffer and diluted to the appropriate concentration immediately prior to experiments. Fresh stocks were made for each set of experiments. Experiments were performed with 50-80 μ M protein at 25 °C. Two technical replicates of each Cu2+ binding experiment were performed. To resolve the complex Ca2+ binding curves, four Ca2+ binding experiments were performed using four different concentrations of titrant. Raw data were integrated using the NITPIC software package–which allows uncertainty in the baseline–and the integrated heats were exported in standard SedPhat format . We then used the Bayesian MCMC iterator included in pytc to estimate model parameters against all experiments simultaneously . We used the maximum likelihood estimate as a starting point and then explored the likelihood surface with 100 walkers, each taking 20,000 steps. We discarded the first 10% of steps as burn in. We restricted parameters against all experiments simultaneously. We verified convergence by performing the sampling procedure several times. A single site binding model was used for Cu2+ titration data and a two-site binding polynomial was used for Ca2+ titration data [42, 43]. For Ca2+ binding fits, we constrained the dilution heat and dilution intercept to between -3.0–0.0 kcal/mol and 0–10,000 kcal/mol/shot respectively. All other priors were uniform.
Sedimentation velocity analytical ultracentrifugation
Experiments were done in 25 mM TES (Sigma), 100 mM NaCl (Thermo Scientific), 100 μ M EDTA at pH 7.4 with the appropriate metal added directly to the buffer during preparation. Metals were added to a final concentration of 250 μ M. Samples were prepared at 40 μ M in the appropriate experimental buffer by overnight dialysis (6000-8000 MWCO) against 2L at 4 °C. Before ultracentrifugation samples were centrifuged at 18,000×g at 4 °C in a temperature-controlled centrifuge for 30 min. Ultracentrifugation was done with sapphire windows at 50,000×g in sector-shaped cells (Beckman) on a Beckman ProteomeLab XL-1. Sedimentation was monitored using interference mode rather than absorbance at 280 nm due to the low extinction coefficient of S100A5. The Lamm equation was fit to the sedimentation data–using SedFit–to calculate the continuous c(s) distribution [22, 23]. Estimated sedimentation coefficients of the species present in solution were calculated from the numerical fits.
Circular dichroism spectroscopy
Far-UV circular dichroism spectra (200–250 nm) were collected on a J-815 CD spectrometer (Jasco) with a 1 mm quartz cell (Starna Cells, Inc.). We prepared 50 μ M samples in a Chelex (Bio-Rad) treated, 25 mM TES (Sigma), 100 mM NaCl (Thermo Scientific), 100 μ M EDTA, buffer at pH 7.4. Samples were subsequently diluted to 25 μ M in buffers containing: no metal (apo), 1 mM Ca2+, 1 mM Cu2+, or both 1 mM Ca2+ and 1 mM Cu2+ –all prepared in the stock buffer above. Samples were centrifuged at 18,000×g at 25 °C in a temperature-controlled centrifuge (Eppendorf) before experiments. Spectra were collected at 25 °C in a Jasco peltier multi-cell sample unit. Reversibility of metal-induced structural changes was confirmed by adding a molar excess of EDTA to the metal-saturated samples and repeating spectra collection. In all cases, addition of EDTA returned the samples to the apo state. Five scans of each condition were collected. These scans were then averaged–using Jasco spectra analysis software–to minimize noise. Buffer blank spectra were generated for each condition. Applicable blanks were subtracted in the Jasco spectra analysis software. Blank-corrected data were exported as text files and raw signal was converted into mean molar ellipticity using the concentration and the number of residues (N res =95) in our S100A5 construct using the equation: MME=CD signal /c(M)·10·L(cm)·N res .
We would like to thank members of the Harms lab for useful conversations regarding interpretation of the results. We would also like to thank Stephen Weitzel in the von Hippel group for his assistance with the AUC experiments.
This work was funded by NIH R01GM117140 (MJH) and NIH training grant 7T32GM007759 (LCW). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Availability of data and materials
The data supporting the claims in this paper are available on the Harms lab GitHub page at https://github.com/harmslab/wheeler-harms-S100A5-Ca-Cu-data
LCW and MJH conceived the study and designed the experiments. LCW performed all experiments and data analysis. MJH secured funding for the work. LCW wrote the manuscript and generated the figures. Both authors have read and approved the manuscript.
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- Bertini I, Gupta SD, Hu X, Karavelas T, Luchinat C, Parigi G, et al. Solution structure and dynamics of S100A5 in the apo and Ca2+-bound states. JBIC J Biol Inorg Chem. 2009; 14(7):1097–107. Available from: http://link.springer.com/article/10.1007/s00775-009-0553-1.View ArticleGoogle Scholar
- Kim I, Lee KO, Yun YJ, Jeong JY, Kim EH, Cheong H, et al. Biophysical characterization of Ca2+-binding of S100A5 and Ca2+-induced interaction with RAGE. Biochem Biophys Res Commun. 2017; 483(1):332–8. Available from: http://www.sciencedirect.com/science/article/pii/S0006291X16322033.View ArticleGoogle Scholar
- Santamaria-Kisiel L, Rintala-Dempsey AC, Shaw GS. Calcium-dependent and -independent interactions of the S100 protein family. Biochem J. 2006; 396(2):201–14. Available from: http://www.biochemj.org/content/396/2/201.View ArticleGoogle Scholar
- Leclerc E, Fritz G, Vetter SW, Heizmann CW. Binding of S100 proteins to RAGE: An update. Biochimica et Biophysica Acta (BBA) - Mol Cell Res. 2009; 1793(6):993–1007. Available from: http://www.sciencedirect.com/science/article/pii/S0167488908004151.View ArticleGoogle Scholar
- Heizmann CW, Cox JA. New perspectives on S100 proteins: a multi-functional Ca 2+ -, Zn 2+ - and Cu 2+ -binding protein family. Biometals; 11(4):383–97. Available from: http://link.springer.com/article/10.1023/A:1009212521172.
- Zhu W, Xue Y, Liang C, Zhang R, Zhang Z, Li H, et al. S100A16 promotes cell proliferation and metastasis via AKT and ERK cell signaling pathways in human prostate cancer. Tumor Biol. 2016; 37(9):12241–50. Available from: http://link.springer.com/article/10.1007/s13277-016-5096-9.View ArticleGoogle Scholar
- Donato R, Cannon BR, Sorci G, Riuzzi F, Hsu K, Weber DJ, et al. Functions of S100 Proteins. Curr Mol Med. 2013; 13(1):24–57. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3707951/.View ArticleGoogle Scholar
- Fischl AM, Heron PM, Stromberg AJ, McClintock TS. Activity-Dependent Genes in Mouse Olfactory Sensory Neurons. Chem Senses. 2014; 39(5):439–49. Available from: https://academic.oup.com/chemse/article/39/5/439/2908167/Activity-Dependent-Genes-in-Mouse-Olfactory.View ArticleGoogle Scholar
- Schäfer BW, Fritschy JM, Murmann P, Troxler H, Durussel I, Heizmann CW, et al. Brain S100A5 Is a Novel Calcium-, Zinc-, and Copper Ion-binding Protein of the EF-hand Superfamily. J Biol Chem. 2000; 275(39):30623–30. Available from: http://www.jbc.org/content/275/39/30623.View ArticleGoogle Scholar
- Teratani T, Watanabe T, Yamahara K, Kumagai H, Ishikawa A, Arai K, et al. Restricted Expression of Calcium-Binding Protein S100A5 in Human Kidney. Biochem Biophys Res Commun. 2002; 291(3):623–7. Available from: http://www.sciencedirect.com/science/article/pii/S0006291X02964946.View ArticleGoogle Scholar
- Cho CC, Chou RH, Yu C. Pentamidine blocks the interaction between mutant S100A5 and RAGE V domain and inhibits the RAGE signaling pathway. Biochem Biophys Res Commun. 2016; 477(2):188–94. Available from: http://www.sciencedirect.com/science/article/pii/S0006291X16309597.View ArticleGoogle Scholar
- Hancq S, Salmon I, Brotchi J, De Witte O, Gabius HJ, Heizmann CW, et al. S100A5: a marker of recurrence in WHO grade I meningiomas. Neuropathol Appl Neurobiol. 2004; 30(2):178–87. Available from: http://onlinelibrary.wiley.com/doi/10.1046/j.0305-1846.2003.00525.x/abstract.View ArticleGoogle Scholar
- WikiGenes-Collaborative Publishing. Available from http://www.wikigenes.org/. Accessed 31 Aug 2017.
- S, 100A5 Gene-GeneCards | S10A5 Protein | S10A5 Antibody. Available from: http://www.genecards.org/cgi-bin/carddisp.pl?gene=S100A5. Accessed 31 Aug 2017.
- S, 100A5 - Protein S100-A5 - Homo sapiens (Human) - S100A5 gene & protein. Available from: http://www.uniprot.org/uniprot/P33763. Accessed 31 Aug 2017.
- Moroz OV, Wilson KS, Bronstein IB. The role of zinc in the S100 proteins: insights from the X-ray structures. Amino Acids. 2010; 41(4):761–72. Available from: http://link.springer.com/article/10.1007/s00726-010-0540-4.View ArticleGoogle Scholar
- Wheeler LC, Donor MT, Prell JS, Harms MJ. Multiple Evolutionary Origins of Ubiquitous Cu2+ and Zn2+ Binding in the S100 Protein Family. PLOS ONE. 2016; 11(10):164740. Available from: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0164740.View ArticleGoogle Scholar
- Gilston BA, Skaar EP, Chazin WJ. Binding of transition metals to S100 proteins. Sci China Life Sci. 2016;1–10 Available from: http://link.springer.com/article/10.1007/s11427-016-5088-4.
- pytc: python program for analyzing isothermal titration calorimetry data. Harms Lab @ University of Oregon; 2017. Original-date: 2016-06-23T00:52:45Z. Available from: https://github.com/harmslab/pytc. Accessed 2017.
- Zhao H, Piszczek G, Schuck P. SEDPHAT – A platform for global ITC analysis and global multi-method analysis of molecular interactions. Methods. 2015; 76(Supplement C):137–48. Available from: http://www.sciencedirect.com/science/article/pii/S1046202314003752.View ArticleGoogle Scholar
- Zhang Y, Akilesh S, Wilcox DE. Isothermal Titration Calorimetry Measurements of Ni(II) and Cu(II) Binding to His, GlyGlyHis, HisGlyHis, and Bovine Serum Albumin: A Critical Evaluation. Inorg Chem. 2000; 39(14):3057–64. Available from: http://dx.doi.org/10.1021/ic000036s.View ArticleGoogle Scholar
- Schuck P. Size-distribution analysis of macromolecules by sedimentation velocity ultracentrifugation and lamm equation modeling. Biophys J. 2000 Mar; 78(3):1606–19. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1300758/.View ArticleGoogle Scholar
- Brown PH, Schuck P. Macromolecular Size-and-Shape Distributions by Sedimentation Velocity Analytical Ultracentrifugation. Biophysical J. 2006; 90(12):4651–4661. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1471869/.View ArticleADSGoogle Scholar
- Bertini I, Borsi V, Cerofolini L, Gupta SD, Fragai M, Luchinat C. Solution structure and dynamics of human S100A14. J Biol Inorg Chem. 2012; 18(2):183–94. Available from: http://link.springer.com/article/10.1007/s00775-012-0963-3.View ArticleGoogle Scholar
- Sturchler E, Cox JA, Durussel I, Weibel M, Heizmann CW. S100A16, a Novel Calcium-binding Protein of the EF-hand Superfamily. J Biol Chem. 2006; 281(50):38905–17. Available from: http://www.jbc.org/content/281/50/38905.View ArticleGoogle Scholar
- Liriano M. Protein dynamics of calcium-S100A5 in the presence and absence of target peptide. Grantome. Available from: http://grantome.com/grant/NIH/F31-CA144560-01. Accessed 2012.
- Koch M, Bhattacharya S, Kehl T, Gimona M, Vašák M, Chazin W, et al. Implications on zinc binding to S100A2. Biochim Biophys Acta (BBA) - Mol Cell Res. 2007; 1773(3):457–70. Available from: http://www.sciencedirect.com/science/article/pii/S0167488906004551.View ArticleGoogle Scholar
- Damo SM, Kehl-Fie TE, Sugitani N, Holt ME, Rathi S, Murphy WJ, et al. Molecular basis for manganese sequestration by calprotectin and roles in the innate immune response to invading bacterial pathogens. Proc Natl Acad Sci. 2013; 110(10):3841–6. Available from: http://www.pnas.org/content/110/10/3841.View ArticleADSGoogle Scholar
- Sivaraja V, Kumar TKS, Rajalingam D, Graziani I, Prudovsky I, Yu C. Copper Binding Affinity of S100A13, a Key Component of the FGF-1 Nonclassical Copper-Dependent Release Complex. Biophys J. 2006 Sep; 91(5):1832–43. Available from: http://www.sciencedirect.com/science/article/pii/S0006349506718951.View ArticleGoogle Scholar
- Reisert J, Bauer PJ, Yau KW, Frings S. The Ca-activated Cl Channel and its Control in Rat Olfactory Receptor Neurons. J Gen Physiol. 2003; 122(3):349–64. Available from: http://jgp.rupress.org/content/122/3/349.View ArticleGoogle Scholar
- Gardner B, Dieriks BV, Cameron S, Mendis LHS, Turner C, Faull RLM, et al. Metal concentrations and distributions in the human olfactory bulb in Parkinson’s disease. Sci Rep. 2017 Sep; 7(1):10454. Available from: https://www.nature.com/articles/s41598-017-10659-6.View ArticleADSGoogle Scholar
- Herms J, Tings T, Gall S, Madlung A, Giese A, Siebert H, et al. Evidence of presynaptic location and function of the prion protein. J Neurosci: Official J Soc Neurosci. 1999; 19(20):8866–75.Google Scholar
- Hopt A, Korte S, Fink H, Panne U, Niessner R, Jahn R, et al. Methods for studying synaptosomal copper release. J Neurosci Methods. 2003; 128(1-2):159–72.View ArticleGoogle Scholar
- Horning MS, Trombley PQ. Zinc and copper influence excitability of rat olfactory bulb neurons by multiple mechanisms. J Neurophysiol. 2001; 86(4):1652–60.Google Scholar
- Ono SI, Cherian MG. Regional distribution of metallothionein, zinc, and copper in the brain of different strains of rats. Biol Trace Element Res. 1999; 69(2):151–9. Available from: https://link.springer.com/article/10.1007/BF02783866.View ArticleGoogle Scholar
- Streicher WW, Lopez MM, Makhatadze GI. Modulation of Quaternary Structure of S100 Proteins by Calcium Ions. Biophys Chem. 2010; 151(3):181–6. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2926197/.View ArticleGoogle Scholar
- Gribenko AV, Makhatadze GI. Oligomerization and divalent ion binding properties of the S100P protein: a Ca2+/Mg2+-switch model1. J Mo Biol. 1998; 283(3):679–94. Available from: http://www.sciencedirect.com/science/article/pii/S0022283698921167.View ArticleGoogle Scholar
- Moroz OV, Blagova EV, Wilkinson AJ, Wilson KS, Bronstein IB. The Crystal Structures of Human S100A12 in Apo Form and in Complex with Zinc: New Insights into S100A12 Oligomerisation. J Mol Biol. 2009; 391(3):536–51. Available from: http://www.sciencedirect.com/science/article/pii/S0022283609006937.View ArticleGoogle Scholar
- Gill SC, von Hippel PH. Calculation of protein extinction coefficients from amino acid sequence data. Anal Biochem. 1989; 182(2):319–26. Available from: http://www.sciencedirect.com/science/article/pii/0003269789906027.View ArticleGoogle Scholar
- Birdsall B, King RW, Wheeler MR, Lewis CA, Goode SR, Dunlap RB, et al. Correction for light absorption in fluorescence studies of protein-ligand interactions. Anal Biochem. 1983; 132(2):353–61.View ArticleGoogle Scholar
- Keller S, Vargas C, Zhao H, Piszczek G, Brautigam CA, Schuck P. High-Precision Isothermal Titration Calorimetry with Automated Peak Shape Analysis. Anal Chem. 2012 Jun; 84(11):5066–73. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3389189/.View ArticleGoogle Scholar
- Wiseman T, Williston S, Brandts JF, Lin LN. Rapid measurement of binding constants and heats of binding using a new titration calorimeter. Anal Biochem. 1989; 179(1):131–7.View ArticleGoogle Scholar
- Freire E, Schön A, Velazquez-Campoy A. Chapter 5 Isothermal Titration Calorimetry: General Formalism Using Binding Polynomials. In: Methods in Enzymology. vol. 455 of Biothermodynamics, Part A: Academic Press; 2009, pp. 127–155. doi:10.1016/S0076-6879(08)04205-5. Available from: http://www.sciencedirect.com/science/article/pii/S0076687908042055.