extfieldsofstudy: Biology Medicine

s2fieldsofstudy: Chemistry Biology

text:
Complex structure of cytochrome c–cytochrome c oxidase reveals a novel protein–protein interaction mode

Abstract Mitochondrial cytochrome c oxidase (CcO) transfers electrons from cytochrome c (Cyt.c) to O2 to generate H2O, a process coupled to proton pumping. To elucidate the mechanism of electron transfer, we determined the structure of the mammalian Cyt.c–CcO complex at 2.0‐Å resolution and identified an electron transfer pathway from Cyt.c to CcO. The specific interaction between Cyt.c and CcO is stabilized by a few electrostatic interactions between side chains within a small contact surface area. Between the two proteins are three water layers with a long inter‐molecular span, one of which lies between the other two layers without significant direct interaction with either protein. Cyt.c undergoes large structural fluctuations, using the interacting regions with CcO as a fulcrum. These features of the protein–protein interaction at the docking interface represent the first known example of a new class of protein–protein interaction, which we term “soft and specific”. This interaction is likely to contribute to the rapid association/dissociation of the Cyt.c–CcO complex, which facilitates the sequential supply of four electrons for the O2 reduction reaction.

Introduction
Cytochrome c oxidase (CcO) is a typical aa 3 -type CcO, in which electrons are transferred to an active site consisting of heme a 3 and Cu B from Cu A via heme a. CcO initially accepts electrons from cytochrome c (Cyt.c) to reduce a dioxygen molecule (Ferguson-Miller & Babcock, 1996;Yoshikawa & Shimada, 2015). Electron transfer (ET) from Cu A to the O 2 reduction center is coupled to proton pumping across the membrane.
Extensive steady-state kinetic analyses of oxidation of ferro-Cyt.c by CcO have revealed two Cyt.c-binding sites, both of which are actively involved in catalytic turnover (Ferguson-Miller et al, 1976). Speck et al (1984) proposed a single-catalytic site model in which one binding site is the catalytic site through which electrons are transferred, whereas the other controls ET in the catalytic site. The amino-acid residues on the Cyt.c surface that interact with CcO were examined by chemically modifying basic residues of Cyt.c and observing the effect on CcO activity; these experiments revealed the critical involvement of basic residues on the Cyt.c surface (Ferguson-Miller et al, 1978;Osheroff et al, 1980). The residues that interact with CcO have been investigated more extensively by NMR studies (Sakamoto et al, 2011), which revealed that hydrophobic residues on the surface of Cyt.c make major contributions to complex formation, whereas the charged residues near the hydrophobic core refine the orientation of Cyt.c to precisely control ET. However, as noted above, analyses of the mechanism of ET between Cyt.c and CcO have been largely restricted to the Cyt.c side. With the exception of docking simulation analyses (Roberts & Pique, 1999;Sato et al, 2016), essentially no experimental information is available regarding the Cyt.c-binding surface of CcO.
Although a significant amounts of data have accumulated regarding ET from Cyt.c to CcO (Speck et al, 1984;Sakamoto et al, 2011), and the X-ray structures of mammalian CcO (PDB 5B1A) and Cyt.c (Bushnell et al, 1990;De March et al, 2014) have been determined at high resolution, the underlying mechanism of ET remains incompletely understood. A crystal structure of the complex of CcO and Cyt.c would be invaluable for mechanistic studies, but to date no structure of a Cyt.c-CcO complex has been determined other than that of caa 3 -type CcO from Thermus thermophilus (Lyons et al, 2012), which has a covalently tethered cytochrome c domain. Thus, it remains unclear whether this fused Cyt.c has functions analogous to those of the Cyt.c molecules that participate in catalytic turnover in the eukaryotic CcO system. Two-dimensional (2D) crystals of the mammalian Cyt.c-CcO complex were prepared at higher pH (7.4-9.0) with both proteins in the oxidized state (Osuda et al, 2016), but these 2D crystals could not provide a structure of sufficient resolution to allow a detailed analysis of the interactions between these proteins. Therefore, in this study, we optimized the three-dimensional (3D) crystallization conditions for ferri-Cyt.c and oxidized CcO at high pH and solved the X-ray structure of the complex at 2.0-Å resolution. The results revealed a novel mode of protein-protein interaction mediated by three water layers.

Results and Discussion
Crystallization of the Cyt.c-CcO complex Previously, bovine CcO stabilized with n-decyl-b-D-maltoside (DM) was crystallized at a pH ≤ 6.8 and analyzed at the atomic level (Tsukihara et al, 1995(Tsukihara et al, , 1996. However, no 3D crystallization trial of the Cyt.c-CcO complex has been successful under crystallization conditions similar to those used for CcO at low pH. Therefore, we performed co-crystallization of Cyt.c and CcO at pH 8.0 under the same conditions used for 2D crystallization of the Cyt.c-CcO complex (Osuda et al, 2016). CcO purified from bovine heart was solubilized with DM and fluorinated octyl-maltoside (FOM), followed by addition of horse Cyt.c at a Cyt.c/CcO molar ratio of 1.2. The Cyt.c-CcO complex was then co-crystallized by the batchwise method at 277 K (Appendix Fig S1A). Absorption spectral analysis indicated that the resultant crystals contained both Cyt.c and CcO (Appendix Fig S1B). The crystals were soaked in a crystallization solution both containing 50 lM Cyt.c and gradually increasing concentrations of the cryo-protectant ethylene glycol (EG; 40% at the final step), and then frozen in a cryo-nitrogen stream at 100 K. The addition of 50 lM Cyt.c prevented the crystal from deterioration due to release of Cyt.c molecules from the complex during soaking. These crystals diffracted X-rays to a resolution of 1.8 Å (Appendix Fig S1C and D). Statistics of the intensity data and structure refinement at 2.0-Å resolution are provided in Table 1.
Structure determination and overall structure of the Cyt.c-CcO complex Initial phases were determined by the molecular replacement (MR) method (Rossmann & Blow, 1962) using CcO, and Cyt.c molecules were located using the F o -F c difference map and anomalous difference map (Appendix Fig S2A and B). Structure refinement at 2.0-Å resolution converged well: R/R free = 0.167/0.207; r.m.s.d of bond lengths = 0.023 Å ; r.m.s.d. of bond angles = 2.0° (Table 1). The (2F o -F c ) electron-density map for the interface of Cyt.c and CcO clearly shows electron densities of side chains interacting with their counterpart proteins (Appendix Fig S2C).
The asymmetric unit of the monoclinic lattice contains a dimer consisting of two complexes of CcO and Cyt.c. The dimeric structure of CcO of the Cyt.c-CcO complex is almost identical to that of CcO crystallized in an orthorhombic lattice (Tsukihara et al, 1996). As in the CcO orthorhombic crystal (Tomizaki et al, 1999), one of the two CcO molecules in the asymmetric unit had a lower B-factor than the other, by about 7 Å 2 , and no significant structural difference was detected between the two complexes. Furthermore, structure refinement was performed under non-crystallographic symmetry restraint between two CcO molecules; therefore, we focused our structural descriptions on this complex.
Cyt.c is localized on the positive side of a concave surface of CcO (Figs 1 and EV1). Although B-factors of Cyt.c were significantly higher than those of CcO, all the side chains except for Lys 25 were located in the positive density of (2F o -F c ) map. Consistent with the results of studies in which Cyt.c was chemically modified at lysyl residues, CcO interacts with the front surface of Cyt.c in a region that includes the exposed heme edge of Cyt.c (Ferguson-Miller et al, 1978;Osheroff et al, 1980). By contrast, in caa 3 -type CcO, the  (Lyons et al, 2012). CcO interacts with Cyt.c mainly via subunit II, with 94% of the contact surface of CcO with Cyt.c belonging to subunit II, and 5 and 1% of it belonging to subunits VIb and I, respectively. The closest inter-atomic distance between Cyt.c and any Cyt.c-CcO complex related by crystallographic symmetry is 6.9 Å . Because Cyt.c does not interact directly with any symmetry-related Cyt.c-CcO complexes (Appendix Fig S3), molecular packing in the crystal does not perturb the structure of Cyt.c in the Cyt.c-CcO complex. The CcO and Cyt.c structures in the complex superpose well with the previously determined structures of the individual proteins, as shown in Appendix Fig S4. At the current resolution, docking of CcO and Cyt.c results in no significant structural changes in the main chains. In Appendix Fig S5, phospholipids are depicted (sticks) along with the C a traces of the complex (ribbons). All phospholipids detected in the crystal structure of CcO (PDB 5B1A), but no additional lipids, are present in the Cyt.c-CcO complex. None of these phospholipids are localized near the Cyt.c-binding site; therefore, Cyt.c does not interact with phospholipids in the crystal of the complex.
A possible electron transfer pathway from heme c to Cu A The concave surface consists of subunit II, which contains Cu A , the first loading site for electrons transferred from Cyt.c. The distance between the iron atom of heme c and the copper atom of Cu A is 23.0 Å . The dominant ET pathway from the heme c iron to Cu A of CcO was explored using the Pathways plugin for VMD (Humphrey et al, 1996;Balabin et al, 2012). The calculations suggest that the most probable ET pathway, as shown in Figs 2 and EV2, proceeds through the iron atom of heme c (Cyt.c)-Cys 14 (Cyt.c)-Lys 13 (Cyt.c)-Tyr 105 (subunit II of CcO)-Met 207 (subunit II of CcO)-Cu A. This ET pathway contains two short through-space jumps: one from the N f atom of Lys 13 (Cyt.c) to the C f atom of Tyr 105 (subunit II of CcO) (a distance of 3.6 Å ), and the other from the N atom of the main chain of Tyr 105 (subunit II of CcO) to the S d atom of Met 207 (subunit II of CcO) (a distance of 4.0 Å ). The running distance along the pathway is 41.9 Å . Chemical modification of Lys 13 of Cyt.c induces drastic inhibition on ET activity (Ferguson-Miller et al, 1978;Osheroff et al, 1980). All vertebrate Cyt.c proteins contain Lys at the 13 th residue and Cys at the 14 th residue (Appendix Fig S6A); in addition, Tyr 105 and Met 207 of CcO subunit II are conserved among vertebrates (Appendix Fig S6B). These observations strongly suggest that the Cyt.c-binding site in the Cyt.c-CcO complex structure is the catalytic binding site of Cyt.c through which electrons are transferred. Compared with the pathway in caa 3 -type CcO, only the ET from Met 207 (subunit II of CcO) to Cu A is conserved ( Fig EV2) (Lyons et al, 2012).
It has been proposed that Trp 121 in Paracoccus denitrificans CcO (Trp 104 in subunit II of bovine CcO) is the electron entry site from Cyt.c, based on W121Q mutation (Witt et al, 1998). The proposal was supported by some docking simulations (Roberts & Pique, 1999;Drosou et al, 2002). However, this mutation is likely to greatly influence the redox potential of Cu A , because the side chain of Gln 121 in the W121Q mutant is predicted to make hydrogen bonds with both the S d atom of Met 227 and the S c atom of Cys 220 , which coordinate to copper ions of Cu A (Appendix Fig S7B). Furthermore, the present X-ray structure of the complex shows that Trp 104 does  Satoru Shimada et al A novel mode of protein-protein interaction The EMBO Journal not interact tightly with Cyt.c. There is a large gap between the protein surface around Trp 104 and Cyt.c, in which Trp 104 is separated from the closest atom of heme c by 9.0 Å (Appendix Fig S7A). Thus, the possible electron transfer pathway identified in the present X-ray structural analyses suggests a significantly more facile electron transfer than the one through the structure including Trp 104 (Appendix Fig S7A).

Catalytic binding sites
Speck et al (Speck et al, 1984) proposed a single-catalytic site model including a catalytic site and a non-catalytic regulatory site on CcO for Cyt.c to interpret the steady-state kinetic results indicating two different Michelis-Menten kinetics, without giving any experimental confirmation. In other words, no experimental result has disproven the two-catalytic site model (Ferguson-Miller et al, 1976). Following the Speck's definition, the above structure strongly suggests the catalytic binding site, since the Cyt.c-CcO complex shows a facile electron transfer pathway from heme c to Cu A . However, following the two-catalytic site model, this retains both possibilities of the first and the second catalytic sites. The positive side of the concave surface of CcO is negatively charged, whereas the surface area around the exposed heme edge of Cyt.c is positively charged (Fig 3A and B). Prominent intermolecular interactions in this region include six hydrogen bonds or salt bridges between CcO and Cyt.c ( Fig 3C and Table 2). Lys 8 (Cyt.c) interacts with Asp 139 of subunit II (CcO) via a salt bridge, Gln 12 (Cyt.c) forms hydrogen bonds with Asp 139 (CcO subunit II), Lys 13 (Cyt.c) forms hydrogen bonds with Tyr 105 and Tyr 121 (CcO subunit II) and a salt bridge with Asp 119 (CcO subunit II), and Lys 87 (Cyt.c) forms hydrogen bonds with Ser 117 (CcO subunit II). These four interacting residues of Cyt.c are restricted to the molecular surface near the exposed heme edge (Fig 3B). On the basis of chemical modification and kinetic studies (Ferguson-Miller et al, 1978), three lysine residues, Lys 8 , Lys 13 , and Lys 87 , were predicted to interact with CcO. Recent site-directed mutagenesis and kinetics studies of Cyt.c indicated that the ET activities of K13L, K86L/K87L, and K7L/K8L mutants are significantly lower than that of the wild-type protein (Sato et al, 2016). The side chains of Lys 8 , Gln 12 , Lys 13 , and Lys 87 of Cyt.c, as well as the side chains of Tyr 105 , Asp 119 , Ser 117 , Tyr 121 , and Asp 139 of CcO subunit II, provide the physiological electron transfer complex, not an encounter complex under nonphysiological conditions.
A previous NMR study (Sakamoto et al, 2011) detected structural changes in several hydrophobic amino-acid residues of Cyt.c upon the docking of two proteins, and the authors of that study concluded that Cyt.c interacted with CcO via its non-polar surface surrounding the heme cleft, as in the cytochrome bc 1 complex (Cyt.bc 1 )-Cyt.c (Lange & Hunte, 2002) and Cyt.c-cytochrome c peroxidase (CcP) complexes (Jasion et al, 2012). By contrast, our crystal structure of the Cyt.c-CcO complex has no inter-molecular interactions between hydrophobic amino acids with an inter-atomic distance < 5 Å . This is likely because NMR spectroscopy sensitively detected a small structural change undetectable by X-ray, mediated by an interaction between the residues of Cyt.c and CcO via water molecules present between the two proteins.
The ionic interaction between Lys 13 (Cyt.c) and Asp 119 (CcO) was predicted by a docking simulation (Roberts & Pique, 1999), and A, B Open-book view of electrostatic potentials of the interaction surfaces of subunit II (residues 91-227) of CcO (A) and Cyt.c (B) in the Cyt.c-CcO complex. Electrostatic potentials were calculated separately using the program APBS (Baker et al, 2001). The displayed potentials range from À5 (red) to 5 (blue) kTe À1 . Heme c (yellow sticks), slightly exposed to the surface, is indicated by an arrow. Dotted circles indicate sites of aminoacid residues, indicated by single-letter notation with residue number. C Close-up view of the interaction site, shown as a stereoscopic pair. Amino-acid residues involved in the interaction between Cyt.c and CcO are represented by pink (Cyt.c) and cyan sticks (subunit II of CcO). Oxygen and nitrogen atoms are shown in red and blue, respectively. Hydrogen bonds and salt bridges are shown as dashed lines. Amino-acid residues are indicated by single-letter notation with residue number. D, E Comparison of variation in B-factors in the Cyt.c molecule. Stick representation of Cyt.c molecule in the Cyt.c-CcO complex (D) and free Cyt.c (PDB 1HRC) (E); colors represent B-factor ranging from 37.7 Å 2 (blue) to 136.0 Å 2 (red) in (D) and 5.8 Å 2 (blue) to 77.4 Å 2 (red) in (E).
The EMBO Journal Vol 36 | No 3 | 2017 ª 2016 The Authors The EMBO Journal A novel mode of protein-protein interaction Satoru Shimada et al another docking simulation assigned Lys 8 , Lys 13 , and Lys 87 of Cyt.c as residues interacting with CcO (Sato et al, 2016), as observed in this study. However, inconsistencies remain between the X-ray structure and the simulated structures of Cyt.c-CcO complex. The former simulation predicted that Lys 72 (Cyt.c), which is distant from CcO in the complex structure (Appendix Fig S8), interacts with Gln 103 and Asp 158 of CcO subunit II. The most probable structure from the latter simulation indicated that the subunit I of CcO had a larger contact surface area with Cyt.c than subunit II of CcO, whereas in our structure most of the contact surface of CcO with Cyt.c belongs to subunit II. These inconsistencies likely arose because water molecules are present between Cyt.c and CcO, but bulk waters were removed from the surfaces of both proteins in the docking simulations. Amino-acid residues included in the catalytic binding were assigned based on the Cyt.c-CcO complex structure equilibrated in a solution in which the enzyme exerts its normal catalytic activity (Yonetani & Ray, 1965). The interactions between Cyt.c and CcO elucidated by this crystallographic study are consistent with those revealed for the enzyme-substrate complex under turnover conditions by previous experimental studies involving chemical modifications and kinetics (Ferguson-Miller et al, 1978) or solution NMR and kinetics for complexes containing wild-type and mutant Cyt.c proteins (Sakamoto et al, 2011;Sato et al, 2016).

Novel protein-protein interaction scheme
Cyt.c donates electrons to CcO and (CcP) and accepts electrons from (Cyt.bc 1 ). We compared the interaction scheme of the Cyt.c-CcO complex with those of the Cyt.c-CcP (Pelletier & Kraut, 1992;Jasion et al, 2012) and the Cyt.bc 1 -Cyt.c complex (Lange & Hunte, 2002;Solmaz & Hunte, 2008). The shortest distance between two C a atoms of Cyt.c and CcO is 8.2 Å . By contrast, the shortest distances in the Cyt.c-CcP (PDB 4GED) and Cyt.bc 1 -Cyt.c (PDB 3CX5) complexes are much shorter, 5.3 and 5.6 Å , respectively. Thus, Cyt.c in the Cyt.c-CcO complex is farther from CcO than it is from CcP and Cyt.bc 1 in the corresponding complexes. Ahmed et al (2011) compiled 179 X-ray structures of protein-protein complexes from the RSCB Protein Data Bank (Berman et al, 2000). The intermolecular C a distances of these 179 structures were calculated, and the distribution of the shortest distance in each complex is illustrated in Appendix Fig S9. Notably, the shortest distance in the Cyt.c-CcO complex, 8.2 Å , falls well outside the distribution. Furthermore, the contact surface areas for three ET complexes were calculated by removing surface water molecules. The area of the Cyt.c-CcO complex (222.8 Å 2 ) is approximately one-third that of the Cyt.c-CcP complex (615.2 Å 2 ), and less than one-fourth that of Cyt.bc 1 -Cyt.c (1008.7 Å 2 ). Thus, fewer direct protein-protein interactions are involved in formation of the Cyt.c-CcO complex than either of the other two complexes. No direct interaction (< 5.0 Å ) between hydrophobic residues was detected in the Cyt.c-CcO complex, whereas the other two complexes have several non-polar groups involved in their inter-molecular interactions.
The water molecules within 7 Å of both proteins of Cyt.c and CcO fall into three categories, as noted by Ahmed et al (2011): bridging waters that interact with both proteins; non-bridging waters that interact with one but not both proteins; and noninteracting waters that are more than 3.5 Å from both proteins. In this study, interactions between waters and proteins atoms were assigned based on a distance of < 3.5 Å between the water oxygen atom and the nearest atom of the protein. As shown in Fig 4 and Appendix Table S1, more water molecules are present between Cyt.c and CcO than between Cyt.c and CcP or Cyt.bc 1 and Cyt.c, and there are a total of 14 non-interacting water molecules in the Cyt.c-CcO complex. By contrast, the Cyt.c-CcP and Cyt.bc 1 -Cyt.c complexes each have only four and two non-interacting water molecules, respectively. Almost the same numbers of bridging waters are in three ET complexes. Extremely fewer non-bridging waters are at Cyt.c in the both complexes of Cyt.bc 1 -Cyt.c and Cyt.c-CcP than Cyt.c-CcO complex (Fig 4; Appendix Table S1). Hydrophobic A B C Figure 4. Comparison of the distribution of water molecules between Cyt.c and each redox partner.

A-C Stereo views of water molecules between proteins in Cyt.c-CcO (A),
Cyt.bc 1 -Cyt.c (PDB 3CX5) (B), and Cyt.c-CcP complexes (PDB ID 4GED) (C). Bridging and non-interacting waters are shown in yellow and blue, respectively. Non-bridging waters interacting with Cyt.c are red spheres, and that interacting with redox partners are shown in green. Cyt.c and the redox partners are shown by wire models in red and green, respectively.

Satoru Shimada et al A novel mode of protein-protein interaction
The EMBO Journal residues of Cyt.c in the Cyt.bc 1 -Cyt.c complex and the Cyt.c-CcP complex likely contact directly with their counterpart and remove waters in part from the surface of their Cyt.c. Any water in the Cyt.c-CcO complex has at least one hydrogen bond with a protein atom or a water molecule. Each of the bridging and non-bridging waters in the Cyt.c-CcO complex interacts, on average, with three polar atoms or waters and one non-polar atom (Appendix Table S2). The waters at CcO interact prominently with Asp, whereas those at Cyt.c interact mainly with Lys and Gln (Appendix Table S3). At least two water molecules closely contact a non-interacting water molecule. These water molecules construct a hydrogen bond network between Cyt.c and CcO (Fig EV3). The averaged B-factor of 64 waters is 62.7 Å 2 , which is between that of CcO (37.9 Å 2 ) and that of Cyt.c (88.2 Å 2 ).
Out of 19 non-bridging waters at CcO in the complex, 14 are located at almost the same sites in the CcO crystal (PDB 5B1A), four are in slightly shifted positions, and one water is not assigned in the CcO crystal. Out of 23 non-bridging waters at Cyt.c in the complex, only five waters are present in the Cyt.c crystal structure (PDB 1HRC). This is probably because the interacting sites of Cyt.c in the Cyt.c-CcO complex are involved in the tight contacts of crystal packing in the Cyt.c crystal, which removes waters from the molecular surface upon crystallization. Because the protein volumes of Cyt.c-CcO and CcO crystals are~30% of their unit cell volume, significantly lower than that of Cyt.c crystal, more than 40%, non-bridging water sites are common to the Cyt.c-CcO and CcO crystals.
When Cyt.c docks with CcO, both proteins preserve their main chain folds, and retain water molecules on their surfaces, and they interact with each other via the long arms of side chains (Fig 5A). On the other hand, the docking of Cyt.c and CcP or Cyt.bc 1 leads to the exclusion of water molecules from the surface of each protein (Fig 5B). The chemical shift-perturbed residues of ferri-Cyt.c associated with the binding of CcO (Sakamoto et al, 2011) are not affected by direct protein-protein interactions, but are influenced by indirect interactions via the water layers in the crystal structure.
The main chain folds of CcO and Cyt.c in Cyt.c-CcO complex are almost identical to those of the corresponding crystals, with C a r.m.s.d. values of 0.47 and 0.41 Å , respectively. All the CcO side chain structures in the region interacting with Cyt.c are similar to those of the CcO crystal except for Asn 203 (subunit II of CcO), where the two structures are different from each other by a À90°rotation angle around the C b -C c bond. By contrast, several side chains of Cyt.c in the interacting region have different orientations between the crystals of Cyt.c-CcO and Cyt.c, probably because of packing effects in the Cyt.c crystal, as noted above for non-bridging waters at Cyt.c.
The B-factors of the side chain atoms of N f (Lys 8 ), N e (Gln 12 ), N f (Lys 13 ), and N f (Lys 87 ) of Cyt.c, which interact with residues of CcO, are 37.7, 39.3, 41.7, and 48.7 Å 2 , respectively, significantly lower than the average B-factor of Cyt.c (88.2 Å 2 ) and as low as that of the extracellular domain (residues 91-227) of CcO subunit II (35.2 Å 2 ). By contrast, the B-factors of Cyt.c atoms increase with distance from these CcO-interacting residues (Fig 3D). Cyt.c in the Cyt.c-CcO complex undergoes a large fluctuation, using the regions interacting with CcO as a fulcrum. The variation in the B-factors in Cyt.c molecule of the Cyt.c-CcO complex is another unique feature of the ET complex. However, horse ferri-and ferro-Cyt.c and the Cyt.c molecules in the Cyt.c-CcP and Cyt.bc 1 -Cyt.c complexes exhibit low B-factors at the heme c group (Figs 3E and EV4). The high flexibility of Cyt.c in the Cyt.c-CcO complex is likely to compensate for the entropy loss caused by introduction of more waters upon docking.
The inter-molecular interaction between Cyt.c and CcO is characterized by mutual recognition mediated by a few long arms of hydrophilic amino acids, small contact surface, a long span between the two proteins, the presence of three water layers between the two proteins, and a large fluctuation of Cyt.c that uses the regions A B Figure 5. Schematic representation of the distribution of water molecules at the protein-protein interaction site.
A In the Cyt.c-CcO complex system, water molecules on the surfaces of each protein are preserved to form three layers upon docking, but each protein specifically interacts via the long arms of side chains. Red and green circles represent water molecules on the surfaces of proteins of the corresponding color; blue circles represent water molecules belonging to the noninteracting water. Black circles and semicircles represent side chains of residues involved in protein-protein interactions. B In other ET complex systems, electron donor and acceptor proteins form an ET complex by excluding water molecules from the surface of each protein.
Orange and gray circles represent water molecules on the surfaces of proteins of the corresponding color. Magenta circles and semicircles represent the main chains of residues involved in protein-protein interactions. Black circles and semicircles represent side chains of residues involved in protein-protein interactions. Figure 6. Locations of four interacting residues in relation to Cyt.c and water molecules that engage in no direct interactions with either protein in the Cyt.c molecule.
Cyt.c (red) and CcO (green) are shown as surface representations. The heme c group shown as black sticks is slightly exposed to the surface. Blue spheres represent water molecules belonging to the non-interacting water. Amino-acid residues involved in interactions between Cyt.c and CcO are shown in white, and figures indicate their residue numbers.
The EMBO Journal Vol 36 | No 3 | 2017 ª 2016 The Authors The EMBO Journal A novel mode of protein-protein interaction Satoru Shimada et al that interact with CcO as a fulcrum. The non-interacting water molecules in the Cyt.c-CcO complex exist in vacant spaces around the interacting amino-acid residues of both proteins (Fig 6) and closely contact with water molecules, thus providing hydrogen bond network between Cyt.c and CcO (Fig EV3). This novel mode of protein-protein interaction, which we term "soft and specific contact", is not observed in other ET complexes (Table 3) (Shen et al, 1994;Morales et al, 2000;Mü ller et al, 2001;Axelrod et al, 2002;Darnault et al, 2003;Ashikawa et al, 2006;Sukummar et al, 2006;Dai et al, 2007;Hagelueken et al, 2007;Senda et al, 2007;Nojiri et al, 2009;Fritz-Wolf et al, 2011;Hiruma et al, 2013;Yukl et al, 2013;Acheson et al, 2014;McGrath et al, 2015). The same region of Cyt.c interacts with Cyt.bc 1 in the Cyt.bc 1 -Cyt.c complex crystal (Lange & Hunte, 2002;Solmaz & Hunte, 2008) and with CcO in the Cyt.c-CcO complex crystal, as proposed based on the results of a chemical modification study (Rieder & Bosshard, 1980). Cyt.c receives and donates electrons through the same site via a repeated association/dissociation process. The novel mode of protein-protein interaction discovered in this study is likely to decrease the potential barrier caused by structural changes upon association/dissociation of the Cyt.c-CcO complex because conformational change of both proteins and rearrangement of surface waters are not required upon docking. Therefore, soft and specific contact between the two proteins is important for efficient donation of four electrons from Cyt.c to CcO for the O 2 reduction reaction. It is remarkable that the X-ray structure of the interface of Cyt.c-CcO complex facilitating the electron transfer from heme c to Cu A is greatly different from that from heme c 1 to heme c, indicating the electron tranfering structures in these two complexes are speciallized for the different electron transfer processes [e.g., two electron transfer from heme c 1 to heme c versus four electron transfer from heme c to Cu A ; and different molar contents of 3:7:9 for Cyt.bc 1 , CcO, and Cyt.c (Hatefi & Galante, 1978)]. Further structural and functional comparisons of these complexes would develop insights in the mechanism of the energy trunsduction by the mitochondrial electron transfer system.
We hypothesize that there are many cases of soft and specific protein-protein interactions involved in various cellular processes. One reason why these interactions were not discovered previously may be related to the need to perform extensive searches for optimal crystallization conditions for these intrinsically unstable protein complexes, as described above. Because single-particle analysis by cryo-electron microscopy does not require a crystal, a highresolution single-particle analysis would increase the chance of detecting soft and specific protein-protein interaction.

Preparation of horse heart Cyt.c sample
For each crystallization trial, horse heart Cyt.c (Nacalai Tesque) was freshly dissolved in 15 mM sodium phosphate buffer at pH 8.0, and then dialyzed for 1 h against the same buffer to remove remaining salts. The concentration of Cyt.c was calculated from the absorption spectrum of the fully dithionite-reduced form, using De 550-535 nm = 19.2 mM À1 cm À1 .

Crystallization of the Cyt.c-CcO complex
CcO in the fully oxidized state was purified from bovine heart mitochondria (Tsukihara et al, 1995) and dissolved in 40 mM sodium phosphate buffer (pH 6.8) containing 0.2% (w/v) n-decyl-b-Dmaltoside (DM) (Dojin). CcO was diluted 10-fold in 15 mM sodium phosphate buffer (pH 8.0) containing 0.7% (w/v) fluorinated octylmaltoside (FOM) (Anatrace). CcO at pH 8.0 preserved Cyt.c  (Yonetani & Ray, 1965). FOM-treated CcO was concentrated using a membrane filter (Amicon Ultra Centrifugal Filters (100 kDa), Millipore). The concentration of CcO was calculated from the absorption spectrum of the fully dithionite-reduced form, using De 604-630 nm = 46.6 mM À1 cm À1 . CcO solubilized with DM and FOM was mixed with Cyt.c at a Cyt.c/CcO molar ratio of 1.2. Co-crystallization of Cyt.c and CcO was performed by the batch-wise method at 277 K; Cyt.c-CcO (100 mg/ml CcO,~0.5 mM CcO) was mixed with~5% polyethylene glycol (PEG) 4000, a precipitant. Rectangular plates of Cyt.c-CcO complex crystals were obtained within 1 day. The crystals were gradually soaked in a crystallization solution containing both 50 lM Cyt.c and ethylene glycol (EG) as cryo-protectant, reaching final concentrations of 40% EG and 6% PEG 4000. After cryo-protection, crystals were quickly frozen in a cryo-nitrogen stream at 100 K.

Structure determination
Crystal screening and X-ray experiments were carried out at beamline BL26B2 and BL44XU of SPring-8. The dataset for the structural analysis was obtained at BL44XU, equipped with an MX300HE CCD detector. The X-ray beam cross-section for X-ray diffraction experiments was 50 × 50 lm at the crystal, and the wavelength was 0.9 Å . Photon number at the sample position was 3.0 × 10 11 photons/s. For data acquisition at 100 K, the crystals were frozen in a cryo-nitrogen stream. The dataset was collected with an exposure time of 1 s and a 0.5°oscillation angle over 180°. Diffraction images were processed and scaled with DENZO and SCALEPACK (Otwinowski & Minor, 1997), respectively, and the datasets from the two crystals were merged. A total of 720 images were successfully processed and scaled. The structure factor amplitude (|Fo|) was calculated using the CCP4 program TRUNCATE (French & Wilson, 1978;Weiss, 2001;Winn et al, 2011). The crystal belongs to space group P2 1 , with unit cell dimensions of a = 113.3 Å , b = 183.9 Å , c = 148.9 Å , and b = 102.1°. The asymmetric unit of the crystal lattice contains two complexes of CcO and Cyt.c. The solvent content and V M were 65.6% and 3.58 Å 3 Da À1 , respectively (Matthews, 1968). CcO was initially located in the unit cell at 3.0-Å resolution by the molecular replacement (MR) method (Rossmann & Blow, 1962) using the program MOLREP in CCP4 (Collaborative Computational Project 4, 1994) with the fully oxidized CcO structure, previously determined at 1.8-Å resolution (PDB 2DYR) (Shinzawa-Itoh et al, 2007), as a model. Cyt.c was located following the MR search at 3.0-Å resolution using horse Cyt.c (PDB 1HRC) (Bushnell et al, 1990) as a model, as in the previous case. Initial phases up to 5.0-Å resolution were calculated with atomic parameters determined by MR and extended to 2.0-Å resolution by density modification (Wang, 1985) coupled with non-crystallographic symmetry averaging (Bricogne, 1974(Bricogne, , 1976 using the CCP4 program DM (Cowtan, 1994). The resultant phase angles (a MR/DM ) were used to calculate the electron-density map (MR/DM map) with Fourier coefficients c. The structural model of Cyt.c-CcO was built in the MR/DM map. The structure was refined using the program REFMAC (Winn et al, 2001;Murshudov et al, 2011) at 2.0-Å resolution. Bulk solvent correction and anisotropic scaling of the observed and calculated structure amplitudes and TLS parameters were incorporated into the refinement calculation. The anisotropic temperature factors for iron, copper, and zinc atoms were imposed on the calculated structure factors. Because the two crystallographically independent monomers packed differently in the crystal, each monomer of CcO was assigned to a single TLS group in the REFMAC refinement. The quality of the structural refinement was characterized by the R and R free values. F o -F c maps were calculated with Fourier coefficients (|F o | -|F c |) exp(ia c ), where |F c | and a c are the calculated structure amplitude and phase, respectively, obtained in the structural refinement. Out of 3822 amino-acid residues, 56 residues of CcO could not be located in the electron-density maps of the Cyt.c-CcO complex. A total of 33 residues of CcO have multiple conformations. The structure refinement was well converged: R = 0.167 and R free = 0.207. The root-mean-square deviations (r.m.s.d.) of bond lengths and angles from their ideal values were 0.023 Å and 2.0°, respectively. Electrostatic potential was calculated separately for Cyt.c and subunit II of CcO using APBS (Baker et al, 2001). Accessible surface area was calculated with the program AREAIMOL (Lee & Richards, 1971) in CCP4, using a probe with radius 1.4 Å .

Electron transfer pathway calculation
The possible ET pathways from the heme c iron to Cu A of CcO were explored by an empirical method, the Pathways plugin for VMD (Humphrey et al, 1996;Balabin et al, 2012), which evaluates the donor-to-acceptor tunneling coupling (T DA ) value for each pathway. We attached hydrogen atoms based on the charmm22 force field (MacKerell et al, 1998), and performed energy minimization with respect to the hydrogen atoms, which enabled us to positively identify the hydrogen bonds. To evaluate the diversity of the possible ET pathways, we generated 200 candidates, and found that most of the identified ET pathways and their T DA values were similar. In fact, the top 100 solutions contained the route between Lys 13 (Cyt.c) and Tyr 105 (CcO). Accordingly, we took the ET pathway with the most efficient T DA value as the final solution.

Accession numbers
Atomic coordinates and structure factors have been deposited in the Protein Data Bank with accession code 5IY5.
Expanded View for this article is available online.


extfieldsofstudy:
Materials Science
Medicine

text:
Rice Husk Ash-Derived Silica Nanofluids: Synthesis and Stability Study

Nanofluids, colloidal suspensions consisting of base fluids and nanoparticles, are a new generation of engineering working fluids. Nanofluids have shown great potential in heat/mass transfer applications. However, their practical applications are limited by the high production cost and low stability. In this study, a low-cost agricultural waste, rice husk ash (RHA), was used as a silicon source to the synthesis of silica nanofluids. First, silica nanoparticles with an average size of 47 nm were synthesized. Next, by dispersing the silica nanoparticles in water with ultrasonic vibration, silica nanofluids were formed. The results indicated that the dispersibility and stability of nanofluids were highly dependent on sonication time and power, dispersant types and concentrations, as well as pH; an optimal experiment condition could result in the highest stability of silica nanofluid. After 7 days storage, the nanofluid showed no sedimentation, unchanged particle size, and zeta potential. The results of this study demonstrated that there is a great potential for the use of RHA as a low-cost renewable resource for the production of stable silica nanofluids. Graphical Abstract Rice husk ash was used as a low-cost renewable resource for production of silica nanofluids with high stability.

The application of nanofluids has significant prospects, but it still faces several challenges for future development [11]. Specifically, the low stability and high production cost of nanofluids are the major limiting factors [4,11,12]. Because of high surface energy, nanoparticles always have a tendency to coagulate automatically [13,14]. Preventing the coagulation of nanoparticles is the primary issue for the application of nanofluids [15]. On the other hand, the currently available methods used for preparing nanofluids usually require expensive raw materials and sophisticated equipments, and thus leading to higher production cost [11,12]. Low-cost production of stable nanofluids is one of the most promising directions for future research [11].
With the speedy development of green nanotechnology, there is a growing tendency to produce nanoparticles with renewable resources [16]. Rice husk, a low-cost agricultural residue, is abundantly available in riceproducing countries. Rice husk has a high calorific value (13-16 MJ/kg), and most of which is burned as fuel to generate energy, thus generating a significant volume of rice husk ash (RHA) [17]. If the RHA is improperly handled, it will become a tremendous waste and can potentially pollute the environment. Nowadays, there is an increasing demand for eco-friendly disposal and utilization of RHA. Many studies indicated that it was a promising low-cost candidate for preparation of silica nanoparticles [18][19][20]. Nano-sized silica can be used to form nanofluids with special interest because of its high specific surface area, excellent stability, high mechanical resistance, and possibility of reuse [21,22]. However, to the best of our knowledge, most of the silica used for preparing nanofluids are commercially available nanoparticles. The commercially available silica nanoparticles are typically prepared by using a silica precursor as silicon source, such as silicon alkoxide (typically silicon tetraethoxysilane). However, the synthesis of silica precursors is usually energy intensive and associated with high cost, eco-hazardous, and unsustainability issues [18].
Generally, there are two primary methods for producing nanofluids [23]: (i) the one-step method, which represents the direct formation of nanoparticles inside the base fluids, and (ii) the two-step method, which means the preparation of nanoparticles and subsequent dispersion of nanoparticles in the base fluids. As compared to the single-step method, the two-step method is the most popular and economic process for the production of nanofluids [2], particularly, it is very suitable to prepare nanofluids containing oxide nanoparticles [14], such as SiO 2 , SnO 2 , CuO, and so on.
Kim et al. reported a sol-gel process for the synthesis of silica nanofluids [24]. TEOS (Tetra Ethyl Ortho Silicate) was used as precursor. The stability of silica nanofluids were determined by zeta potential analysis. However, the long-term stability information was not available. Fazeli et al. synthesized silica nanofluids with commercially available silica nanoparticles by the twostep method [25]. The nanofluids were stable for a period of 72 h without any visible settlements. Many other researchers also prepared silica nanofluids with commercial nanoparticles, but the stability results were not fully reported [26,27].
In this work, RHA was employed as a low-cost silicon source for the synthesis of silica nanofluids by the twostep method. A flow diagram of the process was shown in Fig. 1. First, silica nanoparticles were synthesized using RHA as raw material. Then, silica nanofluids were formed by dispersing the silica nanoparticles in water with ultrasonic vibration. Silica nanoparticles were characterized by SEM, TEM, XRD, and FT-IR. The dispersibility and stability of silica nanofluids were also investigated in detail.

Reagents and Materials
Rice husk ash was from Ji'an of Jiangxi Province in China. Hydrochloric acid and anhydrous sodium carbonate were supplied by Sinopharm Chemical Reagent Co., Ltd (China). Sodium dodecyl benzene sulfonate (SDBS), sodium dodecyl sulfate (SDS), and polyethylene glycol (PEG-1000) were purchased from Aladdin in Shanghai (China). Sodium hexametaphosphate (SH) was obtained from Wenzhou Chemistry Material Factory (China). All chemicals were analytical grade.

Preparation of Silica Nanoparticles
In a typical experiment, 100 g of RHA was added into 1000 ml of 1.0 M HCl solution and boiled for 2 h under stirring. The suspension was then filtered, and the solid residue was washed by distilled water to remove metallic ions. After that, the solid residue was dried in a ventilated oven at 120°C for 12 h.
After acid treatment, RHA (50 g) was put into a threenecked flask, and 250 ml of Na 2 CO 3 solution (20 wt%) was added. The suspension was boiled with reflux condenser. After 4 h of vigorous stirring, the suspension was filtered and washed with 250 ml of hot water. Finally, the filtrate was transferred to another flask. CO 2 was then introduced the filtrate. Stirring for 1 h, the resulting slurry (containing silica nanoparticles) was kept aging for 3 h and then filtered. The precipitate was washed by distilled water and was dried in a vacuum oven at 120°C for 24 h. The yield of silica was 71 ± 2%.

Preparation of Silica Nanofluids
Silica nanofluids were prepared by the two-step method, and deionized water was used as base fluid. First, silica nanoparticles were synthesized using RHA as silicon source, as described above. Second, the silica nanoparticles were dispersed in water with the help of ultrasonic vibration, and thus forming silica nanofluids. Typically, 1 g of silica nanoparticles was dispersed in 100 g water by stirring. Next, 1 g of dispersant was dissolved in the suspension. Subsequently, the suspension was placed into an ultrasonic generator (JY92-IIN, Ningbo Scientz Biotechnology Co., Ltd, China) and sonicated for 2 h. The temperature was kept below 25°C.

Characterization
The morphology of silica nanoparticles were observed by scanning electron microscopy (SEM, Hitachi S-4700) and transmission electron microscopy (TEM, Tecnai G2 F30). The column chart of the particle size distribution (PSD) was obtained using the Image-Pro 5.1 (Media Cybernetics, Inc.) software according to the SEM and TEM images. Zeta potential was measured using a dynamic light scattering instrument (Zetasizer-nano ZS90, Malvern). X-ray diffractometer (XRD) measurements were carried out using an X-ray diffractometer (X'Pert PRO, PANalytical). The results were recorded using diffraction from 15°to 60°, 2θ, at a scanning rate of 5°/min. Fourier transform infrared (FT-IR) spectra were recorded with a

Preparation of Silica Nanofluids
In this study, the two-step method was applied to prepare silica nanofluids. First, silica nanoparticles were synthesized using RHA as a silicon source. Figure 2a shows the SEM image of the prepared silica nanoparticles. It could be seen that near-spherical silica nanoparticles with an average diameter about 50 nm were formed. The SEM result was further confirmed by TEM analysis (Fig. 2b). Figure 2c exhibits the particle size distribution of the silica nanoparticles. It is observed that the silica particles had relatively better dispersion. The average particle size was 47 nm. XRD pattern of the silica nanoparticles was shown in Fig. 3a, which shows a broad peak at 2θ angle of 22°, indicating the amorphous state of silica. FT-IR spectra of the silica nanoparticles were recorded by FT-IR spectrometer. As presented in Fig. 3b, the major chemical groups of silica are identified. The bands located at 467, 800, and 1095 cm −1 are ascribed to the consequence of stretching and bending vibrations of silica. The peaks at 3434 and 956 cm −1 are attributed to the Si-OH stretching vibration and bending vibration, respectively. The band at 1630 cm −1 belonged to H-O-H bending vibration of the adsorbed water. There were no other absorption peaks, which confirmed that the nanoparticles consisted of pure silica.
To form nanofluids, nanoparticles were usually dispersed in water with the help of intensive mechanical force agitation. Ultrasonication, a generally accepted mechanical technique, is widely used to improve dispersion behavior of nanofluids. Ultrasonication is very Fig. 2 a SEM and b TEM images of silica nanoparticles prepared using RHA as a silicon source. c Particle size distribution of silica nanoparticles suitable for dispersing the highly entangled or aggregated nanoparticle samples [13,28], especially nanofluids containing oxide nanoparticles [29].
To investigate the effect of ultrasonic vibration on the dispersibility of silica nanofluids, 1 g of silica nanoparticles and 1 g of SDBS were added in 100 g of water and dispersed by an ultrasonic generator with an output power of 100 W (20 Hz). The relationship of the average silica cluster particle size and the sonication time was recorded using a dynamic light scattering instrument. As displayed in Fig. 4, the average cluster particle size was clearly decreased with the increasing of sonication time. This could be ascribed to the fact that silica clusters were gradually broken into small particles under intensive ultrasonic energy. After 120 min, however, the cluster particle size was 115 nm and basically unchanged, which indicated that the silica clusters cannot be effectively dispersed at the power of 100 W.
Enhancing the energy intensity of ultrasonic vibration is an effective way to improve the dispersibility of nanofluids. In order to obtain silica nanofluids with good dispersibility and stability, intensified ultrasonication power of 200, 300, 400, and 500 W (20 Hz) were further tested. The sonication time was set at 120 min for all cases. As exhibited in Fig. 5, with the enhancement of sonication power, the average cluster particle size was gradually decreased. At the sonication power of 500 W, the average particle size of the silica nanofluid was about 63 nm, which demonstrated

Influence of Dispersants on the Stability of Silica Nanofluids
The stability of nanofluids is very important for their practical applications, and it is closely related to nanofluids' electrokinetic properties [13]. High-stable nanofluids can be formed with high surface charge density to provide sufficiently repulsive forces. The investigation of the electrophoretic behavior through measurement of the zeta potential is important for understanding the dispersion behavior of nanofluids [13,28,30]. Generally, nanofluids with high absolute zeta potential are electrically stabilized and have good stability, whereas those with low absolute zeta potentials are easy to coagulate or flocculate. It is widely accepted that nanofluids with the absolute zeta potential above 30 mV are physically stable.
Adding dispersants is an easy and economic way to improve the stability of nanofluids. Dispersants can adsorb on particle surface, and thus notably changing the electrokinetic characteristics of nanoparticles. In this study, four surfactants including sodium dodecyl benzene sulfonate (SDBS), sodium dodecyl sulfate (SDS), sodium hexametaphosphate (SH), and polyethylene glycol (PEG-1000) were tested as dispersants for stabilizing silica nanofluids. The concentration of the dispersants was set at 1.0 wt%. The solid concentration and pH of silica nanofluids were 0.5 wt% and 7.0, respectively. As shown in Fig. 6, the silica nanofluids were negatively charged with the tested dispersants. For SDBS, zeta potential was −36.5 mV, which demonstrates a stable system. While for the other three dispersants, the absolute zeta potential was smaller than 30 mV, stabilization fail. The plausible stabilization mechanism of SDBS is as follows: SDBS can partially ionize in water and thus generate negatively charged dodecylbenzene sulfonate. The anionic species could be adsorbed on the surface of silica nanoparticles, which leads to an electrostatic stabilization effect [13].

Influence of SDBS Concentration on the Stability of Silica Nanofluids
The influence of SDBS concentration on the stability of silica nanofluids are shown in Fig. 7. It can be seen that as the SDBS concentration increases from 0.2 to 1.0 wt%, the absolute zeta potential increases to a maximal value of 42.3 mV. However, further increasing SDBS concentration to 1.2 or 1.5 wt%, the absolute zeta potential was not increased. This may be attributed to the reasons that with the increase of SDBS, the anion Fig. 6 Influence of dispersants on zeta potential of silica nanofluids Fig. 7 Influence of SDBS concentration on zeta potential of silica nanofluids groups pushed into the adsorbed layer causes the thickness of electrical double layer increases, thereby increasing the electrostatic repulsion among the particles [13]. When SDBS concentration reached to 1.0 wt%, an equilibrium state is reached between the repulsive force and van der Waals attractive force.
Influence of pH on the Stability of Silica Nanofluids Figure 8 shows the change of zeta potential as a function of pH. When the pH was below 3.5, the absolute zeta potential value was at the minimum. Due to the repulsive force is not sufficient to overcome the van der Waals attraction force, the dispersion stability is poor [31,32]. As the pH is increasing, the absolute zeta potential value increases, the repulsive force becomes sufficient to prevent attraction and collision among particles caused by Brownian motion. At pH ≈ 9.5, the zeta potential value reached the maximum level of −40.5 mV, which demonstrated that the repulsive force is the strongest, and the dispersion stability of nanofluid is the best. Further increase of the pH to 11.5 and 13.0, however, the absolute zeta potential value decreased to 37.1 and 34.8, respectively. This fact could be explained by the following reasons: as the pH increases, the concentration of the pH adjustment reagent (i.e., NaOH) increases, which makes the compression of electrical double layer, thus resulting in a lower absolute zeta potential value [13].

Long-term Stability of Silica Nanofluid
Long-term stability is a crucial characteristic of nanofluids. The particle size analysis, zeta potential measurement, and visual observation were used for analyzing the nanofluid's stability. Silica nanofluid (pH = 9.5, 1 wt% silica nanoparticles, 1 wt% SDBS) was prepared by ultrasonic vibration (sonication power 500 W, sonication time 2 h). As shown in Fig. 9, the particle size and zeta potential were basically unchanged during 7 days storage at room temperature. Moreover, no sedimentation was observed, which indicates a good stability of the silica nanofluid.

Conclusions
Rice husk ash-derived stable silica nanofluids were prepared by the two-step method. Ultrasonic vibration was employed to disperse silica nanoparticles in water. Well-dispersed silica nanofluids could be obtained with the sonication power of 500 W. SDBS was a suitable dispersant for silica nanofluids. With 1.0 wt% SDBS, the absolute zeta potential could reach to a maximal value of 42.3 mV. The stability of silica nanofluids was also highly dependent on pH. At a pH of 9.5, the stability of nanofluid is the best. Long-term stability study indicated that nanofluid prepared at the optimal experiment conditions showed unchanged particle size and zeta potential during 7 days storage. Therefore, RHA is a promising low-cost renewable resource for the preparation of stable silica nanofluids.


extfieldsofstudy: Chemistry Medicine

text:
Cobalt Oxide and Cobalt‐Graphitic Carbon Core–Shell Based Catalysts with Remarkably High Oxygen Reduction Reaction Activity

The vital role of ethylenediaminetetraacetic acid on the structure and the oxygen reduction reaction activity of the non‐precious‐metal‐based pyrolyzed catalyst is reported and elaborated. The resultant catalyst can overtake the performance of commercial Pt/C catalyst in an alkaline medium.

Characterizations
Powder X-ray diffraction (XRD, Rigaku Smartlab 3kW) was performed to identify the constituent phases of the synthesized catalysts using filtered Cu-Kα radiation (λ =1.5418Å) operating at a tube voltage of 40kV and a current of 200 mA. The diffraction patterns were obtained using a step scan at 2θ = 10-75° with a step size of 0.02°.The morphology of the CoOx/Co@GC-NC sample was obtained using a field emission scanning electron microscope (FE-SEM, HITACHI-S4800). The transmission electron microscopy (TEM) was conducted at 200 kV with FEI Tecnai G2T20 electron microscope and the corresponding EDX mappings were obtained using an FEI Tecnai G2F30 S-TWIN field emission transmission electron microscope equipped with EDAX operated at 300 kV. The chemical compositions and surface element states were probed by X-ray photoelectron spectroscopy (XPS, PHI5000 VersaProbe spectrometer equipped with an Al-Kα X-ray source). The Raman spectra were collected using an HR800 UV Raman microspectrometer (JOBIN YVON, France) with the green line of an argon laser as the excitation source. The specific surface area and pore size distribution were measured using N2-adsorption on a BELSOR-MAX instrument.The elemental analysis results were acquired using a Vario EL elemental analyzer.

Electrodes preparation and electrochemical characterizations
For accurate comparison, analogous mass loading of catalyst was used in all electrochemical measurements performed on a CHI 760E Bipotentiostat. Electrochemical characterizations were conducted in a standard thee-electrode electrochemical cell with glassy carbon as the working electrode substrate, Pt wire as the counter electrode and Ag|AgCl (3.5 M KCl) as the reference electrode. Working electrode ink was prepared by dispersing 20 mg of each catalyst sample into a mixture of 100 μL of 5 wt % Nafion solution and 1 mL of ethanol followed by sonication for at least 1 hour. A 5 μL of ink aliquot was drop-casted onto glassy carbon substrate (5 mm diameter, 0.196 cm 2 area) and dried at room temperature inside an upside-down glass jar, leading to an approximate catalyst loading of 0.464 mg cm -2 .The commercial 20wt. % Pt/C catalyst (Johnson Matthey Corp.) was used as a comparison. Except for Pt/C case which used a quarter loading only of 5 mg, the working electrodes were prepared following the identical process which led to an approximate catalyst loading of 0.116 mgtotal cm -2 .
For approximately 30 min prior to the start of each test till the end of test, O2 or N2 was continuously bubbled through 0.1 M KOH aqueous electrolyte solution. Cyclic voltammetry (CV) and linear sweep voltammetry (LSV) were carried out using a rotating disk electrode (RDE). LSVs were performed at different rotation speeds (400, 800, 1200, 1600, 2000 and 2500 rpm) at a scan rate of 5 mV s -1 from 0.2 V to -0.6 V versus Ag|AgCl (3.5 M KCl) in O2-saturated 0.1M KOH.Notably, the LSVs of the commercial 20 wt % Pt/C catalyst were recorded in the positive scan (−0.6 to 0.2 V) to avoid performance loss caused by anion adsorption. For CV, the scan rate was kept at 10 mV s -1 with potential from 0.1 V to -0.9 V versus Ag|AgCl (3.5 M KCl) in a N2 or O2 atmosphere.
Ag|AgCl (3.5 M KCl) was used as the reference electrode in all electrochemical measurements, which was calibrated to reversible hydrogenelectrode (RHE). The calibration was performed in the high purity hydrogen saturated0.1 M KOH solution with a platinum rotating disk electrode (0.126cm 2 , Pine Research Instrumentation) as the working electrode. CV was cycled at a scan rate of 1mVs -1 from -0.8V to -1.15 V and the cross-over point at which the hydrogen evolution current changes into the hydrogen oxidation currents was taken as the thermodynamic (zero) potential for the hydrogen electrode reactions. The kinetic parameters such as the electron transfer number were determined using Koutecky-Levich (K-L) equation: Where J is the measured current density, JL is the diffusion-limited current density, Jk is the mass-transport-corrected kinetic ORR current density, n is the electron transfer number, F is the Faraday constant, C 0 is the saturated concentration of oxygen in 0.1 M KOH, ω is the rotating rate (rad s −1 ), DO2 is the diffusion coefficient of oxygen, ν is the kinetic viscosity of the solution and k is the rate constant of ORR.
Rotating ring-disk electrode (RRDE) measurements were performed using Pt ring electrode to obtain the electron transfer number (n) and peroxide yield (X, percentage of HO2 − relative to total products). For each measurement, the working (disk) electrode was scanned cathodically at 1600 rpm using a scan rate of 5 mV s -1 from 0.2 V to -0.6 V whereas the ring potential was set at 0.5 V versus Ag|AgCl (3.5 M KCl) to induce complete peroxide (OH2 -) decomposition. The electron transfer number (n) and peroxide yield (X, % HO2 -) were calculated as follows: Where Id is the disk current, Ir is the ring current and N is the current collection efficiency of the Pt ring (0.422 according to earlier measurements).            [3] Co3O4/N-rmGO 0.  [14] Co3O4 OC/RGO 0.4 ----0.14V vs Hg/HgO Sci. Rep. 2013, 3, 2300. [15]