The albumin molecule, in contrast to many other plasma proteins, is not covered with a carbohydrate moiety and can bind and transport various molecules of endogenous and exogenous origin. The enzymatic activity of albumin, the existence of which many scientists perceive skeptically, is much less studied. In toxicology, understanding the mechanistic interactions of organophosphates with albumin is a special problem, and its solution could help in the development of new types of antidotes. In the present work, the history of the issue is briefly examined, then our in silico data on the interaction of human serum albumin with soman, as well as comparative in silico data of human and bovine serum albumin activities in relation to paraoxon, are presented. Information is given on the substrate specificity of albumin and we consider the possibility of its affiliation to certain classes in the nomenclature of enzymes. The first publications devoted to the study of serum albumin date back to the end of the 19th century . By the 2+, Zn2+, Cu2+, Ni2+, Cd2+, Co2+, Pt2+, Au+ [The albumin molecule is not covered with a carbohydrate moiety and can bind a wide variety of molecules and atoms: water and metal cations , free ft2+, Au+ . By bindt2+, Au+ .p-nitrophenylacetate (NPA) [Albumin is not only a passive but also an active participant in numerous pharmaco- or toxicokinetic processes. Firstly, we are interested in the interaction of albumin with esters. In numerous experiments, esterase or pseudo-esterase activity of albumin was demonstrated with respect to: α- and β-naphthyl acetate and te (NPA) ,14,15, fte (NPA) , aspirinte (NPA) , ketoprote (NPA) , cyclophte (NPA) , esters te (NPA) , octanoyte (NPA) , nitroacte (NPA) , nitrotrte (NPA) , and orgte (NPA) .Acetylation is a characteristic example of the pseudo-esterase activity of albumin (pseudo-first order reaction), when the decrease in the ester substrate is due not to its hydrolysis, but to the formation of covalent bonds along many amino acid residues (sites) of the albumin molecule. It was found that acetylation of albumin by NPA can proceed along 82 a.a. (sites), of which 59 are lysines, 10serines, eight threonines, four tyrosines, and one asparagine . NPA exhIn toxicology, the problem of (pseudo) esterase activity of albumin with respect to organophosphates (OPs)—esters of phosphoric or phosphonic acids—is of great importance. The sites for the formation of covalent adducts of OPs with albumin—Tyr411 and Tyr150 ,27,28—haThe aim of the work reported here was to analyze selected data obtained over decades, which, along with our own data, would allow us to substantiate not only the “pseudo” but also the true enzymatic activity of albumin, and to clarify the role of albumin in the toxicology of OPs. Information was collected not only on the esterase, but also on other enzymatic activities of albumin, in order to consider its possible place in the nomenclature of enzymes.−.Three-dimensional structures of four isomers of soman and other ligands were constructed and then minimized by the method of steepest descent  using thFor molecular docking of paraoxon into the binding sites of HSA and BSA, three models of HSA (models 1–3) and three models of BSA (models 4–6) from the Protein Data Bank were used . The datKd) calculated using this value and the formula Kd = exp(deltaG/(R*T)) [Kd values. Thus, the result of molecular docking procedure was a set of the 3–6 most likely conformations of an albumin-ligand complex. Launches, 4–18, of conformational search converged into each of these conformations. The productivity of the obtained conformations  was estimated from the distance between the hydroxyl oxygen atom of a catalytic acid (or Nζ-atom in the case of lysines) and the phosphorus (or carboxyl carbon in the case of NPA) atom of a ligand molecule (dist(P(C)-O(N))). The conformations inside a cluster have the same value of dist(P(C)-O(N)) due to their small RMSD. To further estimate Kd and MD calculations, conformations corresponding to the productivity criterion were selected. If the productive complexes were not found by molecular docking, the cluster with the lowest energy value was chosen. The final value of Kd was calculated as the mean of all values of the constants obtained in this cluster, while the error was estimated as half the difference between the maximum and minimum values inside the cluster.Molecular docking of ligands to albumin binding sites was performed using the Autodock4.0 software package . The appG/(R*T)) . The LamG/(R*T)) . The seaConformational changes of ligand-enzyme complexes were calculated by the MD method using the GROMACS software package . The comk2 constant  becomes a constant for the formation of a covalent adduct , an additional kinetic constant k3  is introduced, which usually characterizes the limiting stage of the enzymatic reaction. In the case of acylation k3 describes the rate of hydrolysis itself, i.e., transition of an acyl group from a protein molecule to a water molecule  redmolecule  [26,44,4Taking this into account, p-nitrophenol, are released in a ratio close to equimolar, and after complete hydrolysis of a single portion of NPA, the enzymatic activity of albumin does not disappear, nor even decrease with the addition of the next batch of substrate. They also showed that the kinetics of the hydrolysis reaction of esters by albumin follows Michaelis-Menten kinetics with the formation of an intermediate complex [p-nitrophenyl-N-methylcarbamate, is 1.4 × 10–4 M, and this value corresponds to the sK value of many other esterases [The fact that hydrolysis of esters by albumin, in particular NPA, does not differ significantly from “classical” hydrolysis, was first stated by Casida and Augustinsson in 1959 . Studyin complex . In addisterases .The first publication on the existence of at least two different centers (sites) responsible for the two types of activity in the albumin molecule—“true” esterase and pseudo-esterase—appeared in 1972 . In thatcatk) of 0.9 and 54 s–1, respectively, but this is certainly too slow compared with carboxyl esterase of the liver hydrolyzing NPA at a rate of 41,000 s–1 [catk << k−1 and/or catk ≤ +k1, i.e., when the values of mK and sK are nearly equal (rapid equilibrium approximation). The situation when catk >> k−1 and/or k+1, or when we do not know a priori how many free substrate exist in a stationary state  means a serious deviation from classical kinetics and requires the use of other models, for example, the van Slyke-Cullen or Morrison models [catk >> k–1, i.e., the rapid equilibrium approximation is not met; the latter one is a situation where the total enzyme concentration is above the Km of the system, i.e., the free ligand approximation is not met . Thereby the kinetics of albumin interaction with certain substrates over a certain range of concentrations completely corresponds to classical enzymatic kinetics, perhaps even more than the kinetics of the most “true” enzymes.The problems of identification and classification of esterases have been repeatedly discussed by biochemists, especially in the 1970s and 1980s ,50. Perh,000 s–1 . Moreove,000 s–1 ,51 assumn models ,53,54,55Some 60 years ago it was proposed to separate esterases into two groups, A and B ,57. AccoJunge and Krisch in 1973 noted that, from the theoretical point of view, it is very difficult to draw a clear line between esterases that are sensitive to OPs and esterases hydrolyzing OPs because some B-esterases can indeed hydrolyse some OPs  . The maik+3 of the Tyr411 site is much lower than the acylation constant +k2 . It is important to notice that no other sites have been studied. A comparative analysis of albumin activity towards para- and ortho-nitrophenyl esters with various side chains as substrates showed that the most “suitable” substrate showing the presence of esterase activity in albumin is p-nitrophenylpropionate  × 10–4 M [k+2 = (4.2 ± 0.4) × 10–1 s–1; k+2/Ks = (8.9 ± 0.9) × 102 М–1s–1 . Borrowing the missing constant k+3 = 3.2 × 10–6 c–1 (at pH 8.0) from reference [Km = (Ks × k+3)/(k+2 + k+3) ~ 3 × 10–9 M [Km can be obtained if parameters of the generalized equilibrium state of all sites of the albumin molecule interacting with NPA (or another substrate) are attributed to one site, Tyr411. Theoretically, the total number of these sites can reach 82, if we take into account all those amino acid residues that are acetylated by prolonged incubation of albumin with supersaturated concentrations of NPA [k2 instead of k1 should better be taken for estimation of specific Ks. Continuing the calculations: k+3/Km = 1 × 103 М–1s–1. To compare, similar parameters calculated in the study of the interaction of acetylcholine with AChE  catk is equal to 0.15 c−1, mK is equal to sK with a maximum value of 9 × 10–6 M at pH 5, hence kcat/Km = 1.7 × 104 М–1s–1 [k−1 >> k+2), As for the problems of esterase activity and the possibility of attributing albumin to esterases, we believe that they should be discussed not from the point of the characteristics of A- and B-esterases, but from the point of the existence of several binding/activity sites in albumin with different values of kinetic constants. Thus, some authors  consideropionate : kcat = 9 M–1s–1 . Again, obtained : k+1 ≥ 6× 10–4 M . Let us eference , the aut× 10–9 M . Such a s of NPA . In thisith AChE : k1 = 6.44.6 s–1 . If Km i8 М–1s–1 ) are obv4 М–1s–1 . Thus, t4 М–1s–1 . The amoInteraction of albumin with OPs is a very interesting area of research both from the basic and applied points of view. Nevertheless, research in this field has not been fulfilled to the extent that all the questions are answered concerning binding and enzymatic activities of albumin. In this section, we consider two main problems that were raised in several previous research studies: interaction of albumin with soman, and comparative study of human and bovine serum albumins.31P-NMR spectroscopy, spectrophotometric determination of fluoride ion, along with molecular modeling and biochemical studies, the authors solved a system of differential equations and determined the following kinetic characteristics of interaction of albumin with soman  khо = (3.42 ± 0.07) × 10–3 min–1; and the constant of the so-called “spontaneous hydrolysis of soman in the presence of albumin”  kh = (7.6 ± 5) × 10–3 min–1. Thus, if one compares the constants, “spontaneous hydrolysis of soman in the presence of albumin” is not much more than 2-fold faster than spontaneous hydrolysis of soman in water solution, but it is 100-fold faster than the reactivation of the site Tyr411. Despite the rather large standard deviation, two orders of magnitude of a difference between the mean values do not give a reason to doubt the reliability of the difference. Some misunderstanding arises from the fact that the scheme is depicted in such a way that albumin does not seem to participate, and the expression "spontaneous hydrolysis of soman in the presence of albumin" is rather strange. Furthermore, in the text of the article, the authors have attempted several times to explain the phenomenon they discovered. In albumin itself provides a physicochemical environment that enhances the spontaneous hydrolysis of soman”, then they suppose that “catalysis takes place at a differentsite” of albumin, below they suggest that “albumin-mediated hydrolysis of soman occurs via a mechanism that does not involve a covalent intermediate”, and then again assume “a nonenzymatic, physicochemical interfacial reaction”, and finally, to their credit, they come to conclusion at the end of the section: “we cannot rule out the existence of a second active center”. The authors [h = 0.0076 min–1) with a rate 100 times higher than the turnover at Tyr411hydrolysis of soman at a second site P(+) and C(−)P(−); C(+)P(−) and C(−)P(+))are present in the synthetic C(±)P(±)-soman in a ratio of 45:55, with an equivalent number of two enantiomers within each pair . The mos authors  could noof paper  gives sikp, is equal to 15 ± 3 M–1min–1. Furthermore, if the albumin concentration in plasma is 600 μM, then the apparent first order rate constant of the reaction of soman with albumin  is equal to 9 × 10–3 min–1. At the same time, the total pseudo first order rate constant for the reaction of soman with AChE and BChE is 4.5 min–1, i.e., 500 times higher. This value is obtained if the concentration of AChE in human blood is considered to be equal to 2.5 nM, the BChE concentration to be 50 nM, and the ratio k2/Kd for both enzymes to be 9 × 107 M–1min–1. The 500-fold difference is a very serious challenge, but we recall that the authors rely on the stoichiometric properties of the site Tyr411 only, which is very difficult to amplify 500-fold. However, if we consider the properties of the hypothetical second site, which is 100 times faster and catalytically  interacting with the soman, then the task of enhancing these properties by only 5-fold seems to be more feasible.As indicated above, the bimolecular rate constant for albumin phosphonylation at Tyr411, At the same time, the real possibilities of albumin for detoxifying OPs were proved by the elegant experiments of a Spanish laboratory under the leadership of Vilanova ,64,65. TKd greatly, but C(+) and C(−) stereoisomers interact with the site Tyr411 with different efficiencies. Molecular docking of soman into the site Tyr411 in the non-activated (protonated) state was first made in 2008 [Kd values can be explained by the fact that in our research the albumin molecule was minimized before the docking procedure, which led to a change in the conformation of the binding sites. In the complexes of soman with deprotonated Tyr411, all the stereoisomers bind at the same position; dist(P-O) is equal to 0.36 nm for the P(+)C(+)-isomer and 0.37 nm for the other three isomers C(−)-isomer, 524 ± 31 μM for P(+)C(−)-isomer, 425 ± 22 μM for P(−)C(+)-isomer, and 738 ± 44 μM for P(+)C(+)-isomer.Using in silico methods, we have identified all possible sites of interaction between albumin and soman, and the sites of our special interest were those other than Tyr411. The main candidate for the site of esterase activity of albumin was Tyr150. Analysis of the complexes of soman with protonated Tyr411 has shown that dist(P-O) is equal to 0.68 nm for C(+)-isomers, 0.72 and 0.73 nm for P(−)C(−)and P(+)C(−)-isomers, respectively A. It is  in 2008 . Accordi in 2008 . The dif isomers B. In thiKd values are equal to 280 ± 16 μM for P(−)C(−)-isomer, 496 ± 25 μM for P(+)C(−)-isomer, 192 ± 9 μM for P(−)C(+)-isomer, and 487 ± 26 μM for P(+)C(+)-isomer. Kd for P(+)-stereoisomers is higher than for P(−)-isomers. These results seem to be very important, given that the P(−)-isomers of soman are more toxic [Kd values are equal to 295 ± 18 μM for P(−)C(−)-isomer, 470 ± 31 μM for P(+)C(−)-isomer, 205 ± 10 μM for P(−)C(+)-isomer, and 457 ± 26 μM for P(+)C(+)-isomer. Again, in such complexes, the P(+)-isomers interact with the site Tyr150 worse than the P(−)-isomers, and the C(−)- and C(+)-enantiomers bind to this site with equal efficiency. Therefore, the protonation state of Tyr150 does not affect the dist(P-O) and Kd values.The analysis of the complexes of soman with the protonated Tyr150 has revealed that all stereoisomers bind in the same position; the distance between the hydroxyl oxygen of the tyrosine and the phosphorus atom of soman varies from 0.33 to 0.36 nm C. Kd valre toxic . C(−)- aThus, it has been shown that the formation of the chemical bond between soman and Tyr411 occurs only under the condition of deprotonation of tyrosine. The most important point, however, is that Tyr150 binds soman more efficiently than Tyr411 does. The deprotonation of Tyr150 does not determine the effectiveness of binding, but may affect the stability of the formed complex.3P(F)(O)O-group, fluorine and phosphorus atoms of a ligand and hydroxyl oxygen of the catalytic serine are positioned in one line [Furthermore, it is known that in productive complexes of cholinesterases with OPs containing CHone line . In the We then calculated by molecular dynamics further conformational changes of the ligand-protein complexes. The dependence of dist(P-O) on time were calculated using the trajectories obtained. The analysis of the obtained dependences has shown that the complexes of the stereoisomers of soman with protonated Tyr150 and with Tyr411, in both protonation states, are unstable. During the simulation, the value of dist(P-O) does not descent below 0.38 nm. The results of MD simulation of the complexes of soman with deprotonated Tyr150 differ for different isomers of the ligand A,B.Kd and the distances between the phosphorus atoms of soman and the carboxyl oxygen atom (nitrogen in the case of lysine) of a studied amino acid (dist(P-O(N)) were calculated. Kd of most complexes have been found to be very high . Only a few values of Kd are close to those obtained for the sites Tyr150 and Tyr411 -isomers of soman are unstable, the dist(P-O) value does not descent below 0.38 nm during the simulation, whereas the complexes with P(−)-stereoisomers of soman are stable during the first 20 ps of simulation. It is known that 10 ps is sufficient for the formation of a new covalent bond , consequd Tyr411 .Kd = 581 ± 10 μM. However, the distance between the phosphorus atom of the ligand and the oxygen of the hydroxyl group of the serine is equal to 1.1 nm. At the same time, the graphical analysis has revealed that soman binds near Ser193; the distance between the phosphorus atom of the ligand and the hydroxyl oxygen of Ser193 is only 0.38 nm. The result of the molecular docking of soman into the site Ser193 is a complex with Kd = 518 ± 14 μM. The resulting conformation coincides with the result of docking into the site Ser192.The result of the molecular docking of soman into the site Ser192 is a complex with Kd = 290 ± 6 μM. However, the distance between the oxygen atom of the hydroxyl group of the threonine and the phosphorus atom of soman is equal to 1.28 nm. Graphical analysis has revealed that in this complex, soman binds in the site Tyr150; the distance between the phosphorus atom of soman and the hydroxyl oxygen of the tyrosine is equal to 0.35 nm. The resulting conformation is consistent with the result of the docking of soman into the site Tyr150. The result of the molecular docking of soman into the site Ser287 is a complex with Kd = 295 ± 15 μM, while the distance between the hydroxyl oxygen of the serine and the phosphorus atom of soman is 0.77 nm. The analysis has shown that soman is again sorbed in the site Tyr150, with the distance between the phosphorus atom of soman and the hydroxyl of the tyrosine being 0.35 nm. The resulting conformation is also consistent with the result of the docking into the sites Tyr150 and Thr243. The graphical analysis of the complex of soman with the site Lys402 has shown that the ligand binds near the lysine residue. Kd of the complex is 737 ± 27 μM, and the distance between the phosphorus atom of the ligand and the Nζ atom of the lysine is 0.37 nm. Kd of the complex of soman and the site Ser454 is equal to 572 ± 17 μM. However, the distance between the hydroxyl oxygen of the amino acid and the phosphorus atom of soman is 1.14 nm. The graphical analysis has revealed that, in this case, soman binds in the site Tyr411; the distance between the phosphorus atom of soman and hydroxyl oxygen of the tyrosine is 0.71 nm. The conformation obtained coincides with the result of the docking of soman into the protonated site Tyr411. The result of the molecular docking of soman into the site Thr540 is a complex Kd = 759 ± 21 μM. The graphical analysis has shown that soman binds near Lys402; the distance between the phosphorus atom of soman and the atom Nζ of the lysine is 0.37 nm whereas the distance between the hydroxyl oxygen of Thr540 and the phosphorus atom of soman is 0.87 nm. The conformation that we obtained coincides with the result of the docking of soman near Lys402. According to the authors of [Kd = 518 ± 14 μM) indicates that Ser193 can provide true esterase activity of albumin and hydrolysis of soman molecule. It is important that near Ser193 there is a histidine residue, and the distance between the hydroxyl oxygen of the serine and the atom Nδ of the histidine, which can accept the proton from the serine, is only 0.22 nm.Thr243 was also not indicated as an acetylation site in the report by Lockridge et al. . The anathors of , the serthors of . The absKd and dist(P-O(N)) are presented in Thus, according to the docking data, in addition to the sites Tyr150 and Tyr411, the sites Ser193 and Lys402 can interact with soman productively. To investigate the properties of these sites, the remaining P(+)C(−)-, P(−)C(+)- and P(+)C(+)-stereoisomers of soman were docked into these binding sites and the results  and two products of hydrolysis of the substrate  and it is impossible to detect the intermediate adduct by MALDI mass spectrometry. To confirm these assumptions, it is necessary to investigate the kinetics of the formation of PMPA, and to conduct additional in silico calculations, which will help to study the interaction of albumin with OPs and other ethers in more detail. This research has not just theoretical, but also great practical significance. Understanding of the mechanisms of binding and esterase activity of albumin will allow the targeted regulation (modulation) of the toxic or pharmacological properties of many biologically active substances.In addition, we have hypothesized the involvement of not only Arg410 but also Lys414 in the site Tyr411 and His242 in the site Tyr150 as proton acceptors from the tyrosine residues. Thus, it is possible that the hydrolysis of some substrates by albumin requires a catalytic dyad His-Tyr or Arg(Lys)-Tyr, in which histidine or lysine residues act as an acid residue; such cases are described in the literature but with the difference that two different histidine residues serve as acid and basic residues . It can 2 group, interacts more effectively binds to HSA. The polyphenols curcumin and diacetylcurcumin interact much more efficiently with BSA than with HSA [a priori whether the OPs will better interact with HSA or BSA. We suggested that such patterns could be identified using molecular modeling methods, which enables one to determine and compare the structural characteristics of the binding sites of these enzymes responsible for the effectiveness of their interaction with ligands. This at least would help to carry out a comparative analysis of these proteins from an evolutionary point of view.In in vitro experiments devoted to studying the (pseudo-)esterase activity of albumin, both human ,73 (HSA)with HSA . It was with HSA , and metwith HSA . Thus, aKd) and the distances between the phosphorus atom of paraoxon and the hydroxyl oxygen of the tyrosines (dist(P-O)) were estimated. The complexes with the minimal value of dist(P-O) were selected for further analysis. Thus, the model-1 was selected for the complex of paraoxon with the site Tyr150 of HSA; model-2—for the complex of paraoxon with the site Tyr411 of HSA; model-5—for the complexes of paraoxon with the sites Tyr149 and Ty410 of BSA. Energetic and geometric characteristics of these complexes are given in As a first stage, molecular docking of paraoxon into the sites Tyr150 (149) and Tyr411 (410) was performed. Then the conformational changes of the obtained complexes were calculated using 10 ns MD simulation. The approach and the parameters of the docking and MD procedures are described in the Methods section. Based on the results of the docking procedure, the dissociation constants of the ligand-protein complexes  than one hydrogen bond. Therefore, in the most energetically favorable conformations of the complexes of paraoxon with albumin obtained by docking, the NO2-group of the ligand interacts with the nearest arginine residue. The different position of the nearest arginine in HSA and BSA also explains the different position of paraoxon in the sites Tyr150 of HSA and Tyr149 of BSA, though the values of Kd are similar. Kd, the position of paraoxon is similar for HSA and BSA. The comparative analysis of the energy components showed that the contribution of the electrostatic interactions between the protein and the ligand is rather similar for both proteins, while the difference is due to the energies of the hydrogen bonding and van der Waals interactions. Such difference in these characteristics can be explained by the difference in the orientation of the side chains of the amino acids of the site, mainly the position of the side chain of Lys414 (413). The paraoxon molecule is closer to the lysine in BSA than in HSA, and an additional hydrogen bond between the phosphoryl oxygen atom of paraoxon and NH3-group of the lysine is formed.Analysis of the paraoxon environment has revealed that in the case of HSA, the NOd report , which sThe stability and conformational changes of four selected albumin-paraoxon complexes were studied by 10 ns MD simulation. The dependence of the RMSD values of the amino acid residues of albumin on time was calculated. For all complexes, the RMSD value of amino acid residues increased during the first 3 ns of the simulation, then stayed on the level of 0.4–0.5 nm, which indicates the stabilization of the polypeptide chain of the albumin molecule. The exception was the complex of paraoxon with the site Tyr410 of BSA. For this complex, the RMSD value reached the plateau after 8 ns of simulation. The dependence of the values of dist(P-O) on time was also calculated. The results are shown in The analysis of the data obtained has shown that the complex of paraoxon with the site Tyr150 of HSA is unstable. During the first 2 ns of the simulation, the value of dist(P-O) oscillates in the interval of 0.4–1.0 nm. During the last 8 ns of the simulation it remains unchanged and fluctuates insignificantly at the level of 0.6 nm. The analysis of the position of paraoxon in this part of the trajectory has shown that paraoxon is fixed by the Coulomb interaction between the phosphoryl oxygen of the ligand and the side chain of Arg257. It should be noted that in BSA, there is an arginine in this position too.2-group of paraoxon and the side chain of Gln195. In HSA, these positions have a histidine and a glutamine too. The analysis of the environment of paraoxon in this complex has revealed that within 0.4 nm of the phosphorus atom of the ligand, there are no amino acids capable of forming a covalent bond with a paraoxon molecule.According to the data of Lockridge et al. , there aThus, the stable position of paraoxon in the sites Tyr150 of HSA and Tyr149 of BSA is different for these proteins, despite the conservativeness of the environment of the catalytic tyrosine. The graphical analysis has revealed that in the case of BSA, the amino acids of the site Tyr149 are positioned more compactly, which makes the steric size of this binding site smaller in BSA than in HSA. However, for both HSA and BSA, the formation of a covalent bond between paraoxon and Tyr150 (149) is impossible in an unmodified protein. According to our earlier data, the trigger that improves the affinity of the site Tyr150 (149) for OPs can be either the transfer of a proton from a catalytic tyrosine to the imidazole ring of His242(241) , or the The time dependence of the value of dist(P-O) for the complex of paraoxon and the site Tyr411(410) is shown in Thus, according to the data obtained, the site Tyr411 (410) is more conservative than the site Tyr150 (149): amino acids taking part in the binding of paraoxon in this site (Tyr411 (410), Arg410 (409), Lys414 (413), Arg257 256)) are the same for both albumins. For both HSA and BSA, the site Tyr411(410) is the primary site of phosphorylation: additional conditions (binding of modulators at other sites) are not required for the productive binding of an OPs molecules and, according to the data of MD simulation, the mechanism of the phosphorylation reaction is the same for both proteins. These data agree with the data of our previous studies ,85,86,87) are theN-terminal residue of human albumin, Asp-Ala-His-Lys, complexed with Cu2+ ions possesses significant superoxide dismutase activity [2+ ions enhance the buildup of ascorbate radical, while molecular oxygen and protons oxidize Cu+ ions back to Cu2+ [Several years ago, Dr. Kragh-Hansen made a fruitful attempt to summarize available data on enzymatic activities of albumin . As a reactivity . Albuminactivity . Cyanide to Cu2+ .Cysteine peroxidase activity of albumin towards phospholipid hydroperoxides is not high enough , but it was objectively noted  that suc2 is dehydrated by Arg257 site yielding 15-keto PGA2. Albumin also exhibits exotic activities, such as glucuronidase activity -carprofen glucuronide—an NSAID—hydrolysis mediated by tyrosine and lysine residues) [Prostaglandin-D synthase and other types of albumin activities, related to prostanoid metabolism, should also be mentioned: for instance, 15-keto PGEesidues) ,104,105,esidues) ,107; theo-nitroacetanilide and o-nitrotrifluoroacetanilide, and it was shown that hydrolysis yielding o-nitroaniline and acetate/trifluoroacetate is mediated by Tyr411. Moreover, both reaction products do not form covalent adducts with albumin, being released simultaneously to the medium. Contrary to the above, acetylsalicylate deacetylase activity (EC 3.1.1.55) [Most studies over several decades are related to two groups of albumin activities. One group is comprised of carboxylesterase (EC 3.1.1.1), arylesterase (EC 3.1.1.2), and arylacylamidase activities (EC 3.5.1.13) ,23. It i.1.1.55)  may be j.1.1.55) .2+) are required for the reaction [2+ ions suggest that diisopropylfluorophosphatase and aryldialkylphosphatase are different names for the same enzyme, which is commonly known as paraoxonase 1 (PON1) [The other group comprises various phosphatase related activities: phosphomonoesterase (EC 3.1.3.2) , RNA-hydreaction . Carbaryreaction . Diisoprreaction ,118,119.1 (PON1) ,121. How1 (PON1) . The phy1 (PON1) ,124. Fur1 (PON1) ,126. Thu1 (PON1) . Phospho1 (PON1) ,129,130.«The characterization and classification of the two groups of esterase discussed here is hindered by a common problem - the shortage of pure preparations of the enzymes» [2+ ions; this fact is recognized in differential analysis of these enzymatic activities [It is worthwhile to quote from 25 years ago, the relevance of which has not diminished during this time: enzymes» . Thus, otivities ,65,132.2+ ions do not allow us to assign albumin to any established number in enzyme nomenclature. Thus, its place is yet to be defined, and now we suggest at least two numbers as a draft assignment: EC 3.1.1.103 and EC 3.1.8.3 [In 1986, concerns were raised over the adequacy of esterase nomenclature and albumin was referred to as a protein that acted as an esterase, but was not assigned an EC number . Recent  3.1.8.3 . These nUnderstanding of the binding and catalytic possibilities of albumin allowed us to identify two problems related to albumin within toxicological studies and translational medicine. The problem of poisoning by OPs  remains relevant, and it is possible that albumin due to its large amount in blood plasma can act as the main modulator of OPs activity in toxicologically relevant concentrations and doses. Therefore, the study of the interaction of OPs with albumin is important from both fundamental and practical perspectives. Albumin has at least two sites of interaction with OPs. In one (Sudlow II), a covalent adduct is formed. In the other (Sudlow I) the covalent adduct is not formed, but it catalytically interacts with the OPs. The problem is that both the formation of the covalent adduct with OPs and catalytic cleavage of the OPs occur slowly, therefore albumin primarily serves as a “vehicle” for the delivery of OPs to the sites with much higher affinity (cholinesterases). For therapeutic purposes, several strategies are proposed to be applied either individually or concurrently: (1) to promote the formation of the covalent adduct in the site Sudlow II (which would lead to detoxification of the OPs); (2) to strengthen the binding of albumin to the OPs and to accelerate the hydrolysis in the site Sudlow I; (3) to prevent “the passenger” from “landing the vehicle”, and then an OP molecule  would rapidly find and irreversibly bind to blood cholinesterases, which would be better than the same binding outside the bloodstream especially AChE of neuromuscular and neuronal synapses. This could be done with the help of endogenous or exogenous ligands that modulate the binding and esterase properties of albumin.Another range of the problems is the possibility of molecular modeling when studying the interaction of albumin with OPs and the translation of the obtained data to the human organism. Experiments in vivo, which are most closely approximated to actual poisoning situations, are conducted mainly in rodents; the use of other mammals for research is rare and difficult nowadays. Some studies showed that human (HSA) and rat (RSA) serum albumins have similar binding characteristics for biologically active substances ,136. HowThus, comparative and modeling studies, together with a new therapeutic strategy—interference to the traffic of OPs with albumin—are the perspectives which we rely upon in our studies, bearing in mind that many types of its natural “passengers”  can help the organism to trip safely through life.


HDM) allergens. The objective of this study was to characterize the immunodominant IgE epitopes of Der p 5 and Der p 21 responsible for their high allergenic activity.Due to high IgE recognition frequency and high allergenic activity, Der p 5 and Der p 21 are clinically important house dust mite (A panel of 12 overlapping peptides spanning the Der p 5 and Der p 21 sequence were synthesized to search for sequential IgE epitopes by direct testing for allergic patients' IgE reactivity. Peptide‐specific antibodies raised in rabbits were used in inhibition studies for localizing conformational IgE epitopes which were visualized on the surfaces of the allergen structures by molecular modelling. IgE cross‐reactivity between the allergens was investigated by IgE inhibition studies.Immunodominant IgE epitopes defined by allergic patients' IgE on Der p 5 and Der p 21 were primarily of the conformational, discontinuous type including N‐ and C‐terminal portions of the protein. They could be located on each allergen on one area with similar localization, but despite similar structure of the allergens, no relevant IgE cross‐reactivity could be detected.HDM allergy.Our study shows that Der p 5 and Der p 21 contain a major conformational IgE epitope‐containing area located on similar portions of their structure, but they lack relevant IgE cross‐reactivity. These data are important for the development of modern allergy vaccines based on defined molecules for allergen‐specific immunotherapy of  Table E. coli and purified as described elsewhere.http://www.rcsb.org/pdb/home/home.do; PDB: 2JMH) because it represented a monomeric solution structure.2. The surface exposure of the peptides was calculated as follows: surface exposure [%] = SAS of all amino acids of the peptide/SAS of all amino acids of the protein*100. Graphic depictions of the model were rendered with PyMOL .Peptides were synthesized using Applied Biosystems peptide synthesizer Model 433A  and purified by HPLC as described previously.2.23, antisera derived from two rabbits were combined in ratio 1:1 to a total sera dilution of 1:50 for both, CFA‐immunized rabbits and Al(OH)3‐immunized rabbits. After overnight incubation with sera from HDM‐allergic patients (diluted 1:5), bound IgE antibodies were detected with the horseradish peroxidase‐labelled goat anti‐human IgE antibodies . The percentage reduction in IgE binding achieved by means of pre‐incubation with rabbit antisera was calculated as follows: 100‐(ODI/ODP) × 100), where ODI and ODP represent optical density values after pre‐incubation with the rabbit immune serum or pre‐immune serum, respectively. Cross‐inhibition experiments were performed as described above, rDer p 5 and rDer p 21 were coated on ELISA plates, and after blocking, plates were pre‐incubated with anti‐Der p 5 antiserum, anti‐Der p 21 antiserum, anti‐Der p 5‐peptide antisera or anti‐Der p 21‐peptide antisera. ELISA plates were then incubated with patients’ sera (diluted 1:5) which were double positive to Der p 5 and Der p 21 to test for cross‐reactive epitopes.ELISA plates were coated overnight with 1 μg/mL rDer p 5 or rDer p 21, blocked for 2.5 hours and were then pre‐incubated for 24 hours with anti‐Der p 5 peptide antisera, mix of anti‐Der p 5 peptide antisera, anti‐Der p 5 antiserum, anti‐Der p 21 peptide antisera, mix of anti‐Der p 21 peptide antisera, anti‐Der p 21 antiserum, or, for control purposes, with the corresponding pre‐immune sera. As each peptide was used for immunization of 2 rabbits with CFA and 2 rabbits with Al(OH)33.1In a first approach, we covered the Der p 5 sequence with 4 peptides P1‐P4) having a length from 32 to 37 amino acids  with a length from 29 to 36 amino acids Figure . When th3.2The IgE‐binding capacity of the four Der p 5‐derived peptides was compared with complete rDer p 5 allergen in a nondenaturing RAST‐based IgE‐binding dot‐blot assay using sera from 27 Der p 5‐positive HDM‐allergic patients  or N‐termini P1‐2, P4‐2) Figure . Shorten, P4‐2 FiIgE reactivity of the four Der p 21‐derived peptides was compared with that of complete Der p 21 in 25 Der p 21‐sensitized patients by dot‐blot assay  induced IgG antibodies that recognized Der p 5 at dilutions of the antisera between 1:1.000‐1:5.000 with P4 being the most immunogenic peptide Figure A‐D. A prIn a second set of experiments, we immunized rabbits with shortened versions of P1 and P4  to compare the immunogenicity of the shortened peptides with the longer versions. In these immunizations, we included also a rabbit which was immunized with alum‐adsorbed complete rDer p 5. Figure Likewise, we compared the allergen‐specific antibody titres of rabbits which had been immunized with KLH‐coupled Der p 21‐derived peptides with those of rabbits immunized with the complete rDer p 21 Figure . We foun3.4The lack of relevant IgE reactivity against the Der p 5‐derived peptides in patients that reacted with intact, folded Der p 5 suggested that the major IgE epitopes of Der p 5 are likely discontinuous and/or conformational epitopes. It is possible to map the localization of such epitopes with the use of peptide‐specific antibodies that can recognize the folded complete antigen by competitive binding ELISA experiment.When alum was used as an adjuvant for immunization of the rabbits, the highest mean inhibition was obtained by anti‐P4 serum  followed by anti‐P1 with a mean inhibition of 35% . Table We then mapped Der p 21 IgE epitopes using anti‐Der p 21 peptide antibodies (Table Figure 3.5Der p 5 and Der p 21 both have similar alpha helical structure and IgE epitopes are located in similar regions, but earlier IgE inhibition studies showed that there is no relevant cross‐reactivity of IgE antibodies between the two molecules.4Blomia tropicalis, have a three‐dimensional structure which is similar to that of Der p 5 and Der p 21. IgE cross‐reactivity between Blo t 5 and Der p 5 has been reported,House dust mites are one of the most potent and frequent respiratory allergen sources worldwide. Der p 5 and Der p 21 are important allergens in HDM which, depending on the population of patients, are recognized by 30%‐60% of HDM‐allergic patients.Rudolf Valenta has received research grants from Biomay AG, Vienna, Austria, and Viravaxx, Vienna, Austria. He is a consultant for Biomay AG and Viravaxx, Austria. Other authors declare that they have no conflict of interest.RV designed and coordinated the study, participated in the interpretation of the findings, wrote and critically revised the manuscript, read and revised the final version. MC contributed to design of the study, performed experiments, participated in the interpretation of the findings, wrote the manuscript and revised the final version. WH kindly provided sera of HDM‐allergic subjects, read and revised the manuscript. MFT, SV and WK contributed to design and planning of the study, interpretation of findings, read and revised the manuscript. TG, YRM, KWC, GH and KF performed experiments, read and revised the manuscript. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


There is a paucity of mechanistic information that is central to the understanding of the adverse health effects of source emission exposures. To identify source emission-related effects, blood and saliva samples from healthy volunteers who spent five days near a steel plant  and at a well-removed College site were tested for oxidative stress, inflammation and endothelial dysfunction markers.Biomarker analyses were done using multiplexed protein-array, HPLC-Fluorescence, EIA and ELISA methods. Mixed effects models were used to test for associations between exposure, biological markers and physiological outcomes. Heat map with hierarchical clustering and Ingenuity Pathway Analysis (IPA) were used for mechanistic analyses.2 and ultrafine particles (UFP) levels on the day of biological sampling were higher at the Bayview site compared to College site. Bayview site exposures “without” mask were associated with increased (p < 0.05) pro-inflammatory cytokines  and endothelins (ETs) compared to College site. Plasma IL-1β, IL-2 were increased (p < 0.05) after Bayview site “without” compared to “with” mask exposures. Interquartile range (IQR) increases in CO, UFP and SO2 were associated with increased (p < 0.05) plasma pro-inflammatory cytokines  and ET-1(1–21) levels. Plasma/saliva BET-1 levels were positively associated (p < 0.05) with increased systolic BP. C-reactive protein (CRP) was positively associated (p < 0.05) with increased heart rate. Protein network analyses exhibited activation of distinct inflammatory mechanisms after “with” and “without” mask exposures at the Bayview site relative to College site exposures.Mean CO, SOThese findings suggest that air pollutants in the proximity of steel mill site can influence inflammatory and vascular mechanisms. Use of mask and multiple biomarker data can be valuable in gaining insight into source emission-related health impacts.The online version of this article (10.1186/s12989-018-0270-4) contains supplementary material, which is available to authorized users. These samples were then de-proteinized, clarified with ethyl acetate and affinity purified by using a polyclonal 8-iso-PGF-2α antibody following the procedure described by Bielecki et al., 2012 [50 μL sam3 – Q1. The mean and 95% CI are reported for the mean values. We computed the 95% confidence interval for the mean with the following formula: Lower 95% limit = Mean - T.95σM; Upper 95% limit = Mean + T.95σM. Where, T.95 is the number of standard deviations extending from the mean of a T- distribution required to contain 0.95 of the area and σM is the standard error of the mean.Descriptive statistics was done for air pollution levels on Fridays at College and Bayview site and the pollution levels averaged over 5 days at these sites. Also, IQR values were determined based on data collected on Fridays, and it is equal to the difference between 75th and 25th percentiles, in other words, between upper and lower quartiles, IQR = Q2, NOx, O3, PM2.5, SO2, UFP) levels on plasma and saliva endpoints and physiological endpoints (blood pressure BP and heart rate HR), adjusting for various confounders. The types of associations tested using statistical models are as follows. Test 1. Biomarker levels for Bayview site  vs College site exposures (site only); Test 2. Biomarker levels for Bayview site (“with” mask) vs College site exposures (site only); Test 3. Biomarker levels for Bayview site  vs Bayview site (“with” mask) exposures; Test 4. Association between individual air pollutant levels (daily average for Fridays) and biomarkers; Test 5. Exposure type-related differences in physiological (Friday data) measures  associated due to simply wearing the mask, was removed prior to carrying out these comparisons. For this purpose, profiles of each physiological measure (y axis) for with and without mask exposure conditions were plotted against air pollutant levels (x axis) on all five days/exposure week, for each air pollutant. The curves for “with” and “without” mask exposures at the Bayview site were extended to x = 0, and the difference (∆) between the two curves were determined to assess the pure “mask” effect on these physiological measures. The pure “mask” effect “∆” value calculated for each physiological measure was in the same order of magnitude irrespective of the air pollutant, suggesting that it is almost a constant measure and a reasonable estimate of the pure “mask” effect. For each physiological measure, the “∆” value for all air pollutants were thus averaged, and the “∆avg” value was subtracted from the physiological measures for the “with” mask exposures (daily average for Fridays), prior to carrying out comparisons of physiological measures by exposure type); Test 6. Individual air pollutant levels (daily average for Fridays) vs physiological measures; Test 7. Biomarker levels vs physiological measures.Associations among the various saliva and plasma markers were tested by Spearman Rank Order Correlation analyses for all data. Further statistical analyses using mixed effect model testing were conducted to assess the influence of exposure conditions  and criteria air pollutant  were calculated as averages of air pollution levels from time the subject arrived at the study site until time of blood or saliva sample collection. For each saliva and blood endpoint, we conducted descriptive statistics, for the complete dataset and for each exposure level separately. All plasma and saliva markers showed skewness in the data points and were log-transformed prior to modelling to attain normality, with the exception of physiological endpoints (BP and HR). Mixed effects models with Restricted Maximum Likelihood (REML) estimation were employed in these analyses. The exposures and the air pollution levels were treated as fixed effects, and the study participants were treated as random effects. The subjects with masks were not included in the statistical analyses conducted to identify air pollution-related effects, since air pollutant levels under the mask were not measured. The subjects with masks at the Bayview site were only included when exposure site-related effects were tested. An additional random effect of date was examined to reflect the fact that there were four study cohorts present at the study sites on different sets of days.The models were adjusted for various sets of candidate covariates: date of exposure, carry-over effect (since the same subjects were exposed to the different conditions after one week wash out period), age, sex, body mass index (BMI), ambient air pressure, humidity and temperature.p < 0.05.Baseline observations for plasma and saliva endpoints prior to the exposure regimen were considered as covariates in the model since air pollution measurements were not available. Blood pressure and heart rate measurements considered in these analyses are medians of five readings taken on Friday afternoons around the time when the plasma samples were obtained as well. Note: Biomarker changes (on Fridays of the exposure week) due to exposure at the Bayview site “without” mask (ambient) or at the Bayview site “with” mask, were tested separately against College site exposures. The Akaike Information Criterion was used to choose the best-fitting models. All data management and modelling were conducted in SAS EG 4.2  and R version 2.15.1 . Statistical significance was considered at http://genepattern.broadinstitute.org/gp/pages/login.jsf), and formatted in Java treeview (http://jtreeview.sourceforge.net/). Furthermore, Ingenuity Pathway Analysis (IPA)  was used to analyse for protein interaction networks, biofunctions and disease pathways using the normalized data. Fold change values (average marker response at Bayview site (with or without mask)/average marker response at the College site) were used for this purpose, and only the protein markers that were significant based on the above mentioned statistical analyses results were included for this analysis.We also normalized the biomarker level for each subject at different exposure conditions by the average values for this subject during the study period to adjust for individual variability. This information was used to conduct following bioinformatics analyses. Heat map with hierarchical clustering was employed to visualize differential pattern of plasma marker responses as a result of the different exposure scenario. The analysis was done using the hierarchical clustering option in GenePattern (2).The results described here are from 52 subjects  who participated in the entire exposure study, and consented to blood draws. Characteristics of the study subjects are shown in Table 2, NO2, NOx, CO and UFP levels were different compared to that at the College site as stated in our previous reports . Plasma BET-1 was seen to be positively associated with circulating lipid oxidation marker 8-ISOP  and plasma ET-11-21 was negatively correlated  with 8-ISOP. Plasma ET-11-21 was also found to be negatively correlated  with the acute phase proteins AGP, fibrinogen, SAP and haptoglobin. Plasma BET-1 was positively associated with PF4 . Acute phase proteins AGP, fibrinogen, SAP, PF4, adipsin, vWF and haptoglobin were positively correlated  with each other except for adiponectin. The acute phase proteins AGP, fibrinogen, SAP and haptoglobin were positively associated  with IL-7, IL-8, IL-12, TNF-α and IFN-γ. These correlation coefficients were weak to modest.The Spearman Rank Order correlation analysis on plasma and saliva end points to assess the relationships between the different biological endpoints in these subjects revealed associations between salivary and plasma endothelins. Salivary BET-1 was correlated with plasma BET-1 (Test 1) are shown in Table p < 0.05) cytokines , saliva/plasma endothelins , ET-3) and adiponectin compared to the College site (Table p < 0.05) with exposures at the Bayview site (ambient) compared to the College site. In addition, plasma ET-1(1–21), IL-1β, CRP and saliva ET-3 levels exhibited an increasing trend (p < 0.1), while plasma A2M and PF-4 showed a decreasing trend (p < 0.1) with exposures at the Bayview site (ambient) compared to the College site.Relative changes in the biomarker responses at the two sites (Test 2) showed increased (p < 0.05) TNF-α, saliva BET-1, ET-11-21 levels and decreased (p < 0.05) levels of AGP, haptoglobin, vWF and IL-2 levels after exposure at the Bayview site (with mask) compared to the College site.(Table p < 0.1) in IFNγ, IL-4, IL-8, plasma ET-11-21, ET-3 and saliva ET-11-31 levels and a decreasing trend (p < 0.1) in PF-4 and SAP levels are seen with exposures at the Bayview site (with mask) compared to the College site  are provided in Table p < 0.05) levels of IL-1β and IL-2, as well as an increasing trend in the levels of plasma BET-1 are seen with exposures at the Bayview site “without” (ambient) mask relative to “with” mask exposures.Results from biomarker response comparisons for the Bayview site “without” (ambient) vs “with” mask exposures ((Test 4) are provided in Table p < 0.05) in IL-6, IL-7, IL-8, IL-12 and IL-13 cytokines, respectively; IQR increase in O3 was associated with 47.6 and 14.3% increase in IL-2 and TNF-α (p < 0.05) and with increasing trends (5.3%) of IL-8; IQR increases in NO and NOx were associated with decreased (p < 0.05) IL-8 levels. In terms of endothelin isoforms, increased (p < 0.05) plasma Big ET-levels were associated with IQR increases in O3, but IQR increases in SO2, and UFP were associated with increased (p < 0.05) plasma ET-11-21 levels, and similar association (p < 0.05) was seen with PM2.5 and saliva ET-11-21 levels. In addition, saliva ET-11-21 levels decreased IQR increases in CO as well as O3 (p < 0.05). Acute phase protein profile results showed that adipsin, AGP, A2M, fibrinogen, haptoglobin, L-selectin and PF4 decreased (p < 0.05) with IQR increases in all pollutants, except for an increasing trend (p < 0.1) for SO2. Also, IQR increases in SO2 and PM2.5 were associated with an increasing trend in vWF levels (p < 0.1).The best fit model results for the tests of association between individual criteria air pollutant levels and plasma/saliva endpoints Test 5) from the best fit models are shown in Table p < 0.05) relative to the Bayview site “without” mask exposures, as well as the College site exposures. Heart rate after College site exposures exhibit a decreasing trend relative to Bayview site “without” mask exposures.Results on associations between physiological measures systolic/diastolic BPs, HR and exposure conditions (Test 6) are illustrated in Table p < 0.05) systolic BP is seen with IQR increase in O3. IQR increase in UFP is associated with increased (p < 0.05) systolic BP. A decrease in diastolic BP is seen with IQR increases CO, O3 and PM2.5, with similar trends (p < 0.1) seen for NO2, NOx and UFP. IQR increases in NO, O3, PM2.5 and UFP levels were associated with increased (p < 0.05) HR values. IQR increase in NOx exhibited a similar trend (p < 0.1) in HR as well.The relationships between individual air pollutants and the physiological endpoints (BP and HR) from the mixed models (Test 7) for associations between plasma/saliva markers and physiological parameters  showed that saliva BET-1 levels were positively associated (p < 0.05), while adipsin and PF4 were negatively associated (p < 0.05) to systolic BP levels (Table p < 0.05) with saliva BET-1 and negatively associated (p < 0.05) to plasma BET-1 and vWF. In addition, CRP levels were positively associated (p < 0.05) with heart rates, while IL-6 and IL-12 were negatively associated (p < 0.05) with HR.Mixed model results  specific to the Bayview (“with” and “without” mask) and College site exposures Fig. . Pro-infThe significant protein interaction network with the highest score was different for Bayview site “with” mask exposures compared to that of Bayview site “without” mask Fig.  exposureIn this study, biomarkers of oxidative stress, inflammation and vascular effects were assessed in healthy humans Table  exposed 2, UFP, CO, NO and NOx at the Bayview site compared to the College site  varied between exposure sites, especially with increases in SOte Table , these fnditions . Sioutasnditions  reportedp < 0.05) between saliva and plasma BET-1 levels consistent with our previous work [p = 0.05), but was negatively associated (p < 0.05) with ET-11-21, suggesting that oxidative stress may play a role in mediating BET-1, ET-1 responses [Our general analysis of target biomarker data showed a positive correlation  mixed effects model results, since we are aware that false associations due to multiple comparisons may occur during statistical analyses on a relatively large dataset. Yet, due to the exploratory nature of this work, we also show trends in some consistent, mechanistically meaningful target biomarkers  that are known to respond with air pollutant exposures, and the directionality of these markers can be useful in collective biomarker pattern-based mechanistic verification. Association of study site exposures to biomarker levels exhibited increased (p < 0.05) pro-inflammatory cytokines, vasoactive endothelins, and an increasing trend in a known marker of inflammation CRP [We focussed on significant  altered some inflammatory and vascular function-related biomarker levels as with “without mask” exposures at this site, compared to College site exposures (Table p < 0.05) plasma IL-1β and IL-2 levels and an increasing trend (p < 0.1) in plasma BET-1 levels after Bayview site “without” mask exposures compared to “with” mask exposures  in vWF levels were observed with IQR increases in SO2 and PM2.5 levels.(Table 1-21), and the remainder of the site-related responses appeared to be influenced by inter-pollutant interactions based on the nature of the air pollutant mixture [1-21, adiponectin and decreased haptoglobin responses associated “with” mask exposures at this site appeared to be typical responses for IQR increases in CO and UFP  systolic blood pressure (SysBP) with UFP, but not with PM2.5 (Table https://medlineplus.gov/ency/article/002804.htm). Also, IQR increases in PM2.5 and UFP were associated with increased heart rate values, and similar relationships were seen with O3, NO and NOx. Increased systolic and diastolic BP values were associated (p < 0.05) with increased saliva BET-1 levels in this study (Table p < 0.05) with plasma CRP , both systolic and diastolic BP values (Fridays) were relatively decreased (not significant) after Bayview site “with” mask exposures compared to the other two exposures Table . Neverth.5 Table . Similardy Table . This isRP Table , consistOverall, the mixed model results suggest that relatively high levels of air pollutants at the Bayview site may have contributed to elevated levels of some pro-inflammatory markers and endothelins as well as some acute phase protein changes. Even though the use of mask removed many criteria pollutants, CO and UFP fractions filtered through this mask along with any escaped VOCs may have contributed to the relatively decreasing trends in BP and increasing heart rate compared to other exposures. Although, CO X UFP interaction can explain the observed results, since CO exposure is associated with lowering of BP through cGMP pathway , it coulAlternatively, heat map and hierarchical clustering results on normalized biomarker data (to remove the inter-subject variability) also revealed that Bayview and College site exposures elicited distinct inflammatory and endothelinergic responses Fig.  as with 2 are shown to mediate NFkB-signalling pathway-related inflammatory conditions [Protein interaction networks obtained by conducting Ingenuity Pathway Analyses (IPA) on normalized multiple protein biomarker information (included significant changes) provided mechanistic information . The hignditions , 58, whinditions . We havenditions , and thenditions . The canDespite the strengths of this work, there were some limitations in this study. For instance, masks were used only at the source emission site, the site central to this study and not at the college site, due to budget, timeline and resource constraints-driven 3-type of exposure design. Also, the subjects in this study had to raise the hood of the mask during eating and drinking for very short periods of time, for snacks and lunch. However, the hood was up for a brief period during food intake only, and there still was a flow of cool, clean air over them. Also, the hood was up during the lung function tests , yet thiIn essence, the multiple biomarker analysis along with the use of mask in this work is a novel approach for the assessment of air pollution-related health effects. Exposure to relatively higher air pollutant levels in the Bayview neighborhood may mediate molecular mechanisms relevant to inflammatory and vascular function-related pathways. Activation of some compensatory mechanisms noticed in these healthy subjects may have played a protective role thus resulting in only subtle physiological changes. Single air pollutant-specific biomarker responses in combination with exposure type-related differences assisted in gaining insight into inter-pollutant interactions. Furthermore, the unique approach of use of mask along with multiple biomarker response information in different biological compartments permitted insight into source emission-associated mechanistic changes related to observed physiological outcomes. Thus, these findings contribute to the advancement of source emission-related risk assessment efforts.Our findings from multiple biomarker analyses reveal that elevated air pollutant levels at the steel mill site can contribute to perturbations in inflammatory and vascular mechanisms, and perhaps may explain the subtle physiological changes seen in this study and in previous reports. The use of mask can permit experimental deconstruction of complex air pollution mixtures thus simplifying the exposure matrix to gain insight on target pollutant-specific effects as well as inter-pollutant interactions. This work warrants the use of high content biomarker analyses  in combination with the use of mask in future air pollution exposure studies, to advance the understanding on source emission-related adverse outcome pathways.Additional file 1:Figure S1. Canonical pathways identified by IPA analysis using Fisher’s exact test on protein marker changes. BM (Bayview “with” mask exposures) vs C (College site exposures) – Dark Blue; BA  vs C (College site exposures) – Pale Blue. (DOCX 100 kb)


Scattered and indirect evidence suggests that sea ice occurred as far south as the Iceland Sea during the Early Pliocene, when the global climate was warmer than present. However, conclusive evidence as well as potential mechanisms governing sea ice occurrence outside the Arctic Ocean during a time with elevated greenhouse gas concentrations are still elusive. Here we present a suite of organic biomarkers and palynological records from the Iceland Sea and Yermak Plateau. We show that sea ice appeared as early as ~4.5 Ma in the Iceland Sea. The sea ice either occurred seasonally or was transported southward with the East Greenland Current. The Yermak Plateau mostly remained free of sea ice and was influenced dominantly by Atlantic water. From ~4.0 Ma, occurrence of extended sea ice conditions at both the Yermak Plateau and Iceland Sea document a substantial expansion of sea ice in the Arctic. The expansion occurred contemporaneous with increased northward heat and moisture transport in the North Atlantic region, which likely led to a fresher Arctic Ocean that favors sea ice formation. This extensive sea ice cover along the pathway of the East Greenland Current gradually isolated Greenland from warmer Atlantic water in the Late Pliocene, providing a positive feedback for ice sheet expansion in Greenland. As a result of increasing anthropogenic greenhouse gas emissions, Arctic sea ice extent has been declining drastically over the past decades3 and the Arctic may become sea ice-free during summer within a few decades5. Nevertheless, some studies suggest that Arctic sea ice has occurred repeatedly during times with elevated atmospheric CO2 concentrations6 such as the Middle Eocene9, the Late Miocene10 and the Pliocene11. There remains a debate on the existence of perennial or seasonal sea ice in the Late Miocene Arctic Ocean12, but seasonal sea ice did occur in the marginal Arctic Ocean during the Early Pliocene from ~4.0 Ma11. While circumstantial evidence from Early Pliocene palynological and biogenic opal records suggest that sea ice might have occurred in the Iceland Sea14 and Labrador Sea15, a recent biomarker study demonstrates that seasonal sea ice appeared north of Iceland during the Late Pliocene (<3.6 Ma)16.Today, Arctic sea ice plays an important role in both regional and global climate due to its effect on Earth’s albedo, ocean-atmosphere exchange and primary productivity2 was in the range of 380–400 ppm18 and the Fram Strait was the only Arctic–Atlantic ocean gateway , various mechanisms may have caused sea ice occurrence in the Iceland Sea. One important candidate causing sea ice to occur in the Iceland Sea is the East Greenland Current (EGC), which is today the main exporter of sea ice laden, lower salinity Arctic waters from the Arctic Ocean into the Nordic Seas  to intensified glaciations in the Northern Hemisphere. While the current consensus is that the CAS closure/shoaling was not a direct trigger for the glaciation in the Northern Hemisphere around 2.7 Ma (e.g. ref.22), the proposed mechanism predicts the formation of sea ice in the Pliocene Arctic Ocean following enhanced northward heat and moisture supply in the North Atlantic region. This atmospheric moisture is transported via the westerlies to Eurasia, ensuring precipitation that feeds the northward draining Siberian rivers. These rivers then deliver more fresh water to the Arctic Ocean and thereby facilitate sea ice formation. Crucial evidence supporting freshening of the surface waters in the Russian Arctic is still lacking, but paleoclimatic records from the North Atlantic23 and Norwegian Sea24 indicate increased heat transport and the first seasonal sea ice in the marginal Arctic Ocean (Yermak Plateau) around 4.0 Ma11.In the Early Pliocene, when global atmospheric CO25, the Early Pliocene does provide the opportunity to study the mechanisms governing sea ice presence in the Iceland Sea in a world characterized by high CO2 levels17 and global temperatures26. Here, we present the first Early Pliocene (~4.9–3.5 Ma) sea ice reconstructions based on the sea ice proxy IP25, sterols and palynology from the Iceland Sea Ocean Drilling Program (ODP) Site 907 and Yermak Plateau ODP Hole 911A  in ODP Hole 911A reflects that conditions were sporadically suitable for sea ice to be present  alternated with ice edge conditions (high IP25 and high brassicasterol) in the Iceland Sea between 4.0 and 3.7 Ma  transport in the North Atlantic and the enhanced formation of sea ice in the Arctic. Essential for enhanced sea ice formation is a freshening of the Arctic Ocean. It was proposed that the moisture source for this freshening originates from increased northward heat and moisture transport in the North Atlantic21. This is evident in the reconstructed high SSTs in the eastern North Atlantic23 and Norwegian Sea24 around 4.0 Ma 38, albeit in volumes considerably lower than in the Late Pliocene and Quaternary. Tectonic uplift made elevated plateaus available in Greenland during the Early Pliocene39 where glaciers and ice caps could nucleate and eventually expand into a large, IRD producing ice sheet. Such large ice sheet started to deliver considerable IRD into the North Atlantic during the Late Pliocene40, when the zonal gradient in the Nordic Seas was already established. In fact, the cooler water and more substantial sea ice presence in the Iceland Sea after 4.0 Ma and in the Late Pliocene16, may have contributed to the gradual expansion of continental ice in Greenland. A more substantial and long-term sea ice presence along the East Greenland coast acts to thermally isolate Greenland from relatively warmer Atlantic waters41 and reduces heat advection42, as well as providing a sea ice-albedo feedback and inhibiting ocean–atmosphere heat exchange. These combined effects, together with the tectonic uplift of the circum-Arctic land masses43 all provide positive feedbacks for expansion of the Greenland Ice Seet (GIS).Despite the relatively high Early Pliocene atmospheric CO2 concentration (380–400 ppm18) correspond to a strongly reduced GIS. The occasional presence of sea ice in the Early Pliocene Iceland Sea and Yermak Plateau was insufficient to provide an insolating buffer between the warm surface waters in the Nordic Seas and the GIS before ~4.0 Ma. Together with the high atmospheric Pliocene greenhouse gas concentrations, this setting likely inhibited major glaciation in Greenland. It is only when a more stable ice edge developed along the coast of East Greenland in the Late Pliocene16 and CO2 concentrations gradually decreased18 that the GIS could expand to reach the coast line44. As such, sea ice along the east Greenland coast acts as a positive feedback for sustaining and expanding the GIS. Our data do not allow disentangling the relative effects of Arctic sea ice extent and greenhouse gas concentrations on the GIS, which should be addressed in future modeling studies.In the modern context of increasing atmospheric greenhouse gas concentrations and rapidly declining Arctic sea ice, our study provides fundamental insights into consequences of a  sea ice-free Arctic by demonstrating that limited sea ice presence in the Arctic Ocean and Iceland Sea together with a high Early Pliocene atmospheric CO45. Ages for the three uppermost studied samples were calculated using the astronomically tuned IRD record from ref.46. All paleomagnetic reversals were updated to the most recent Astronomically Tuned Neogene Timescale 201247  of ODP Site 907. The age model is based on paleomagnetostratigraphy907 Fig.  were pla6 (10.5 µl/sample), and squalane (2.4 µl/sample), were added before analytical treatment. Separation of the extract into fractions hydrocarbon and sterol fraction was achieved via open-column chromatography with 5 ml n-hexane, and 6 ml n-hexane:ethylacetate (4:1 v/v), respectively with silica gel (SiO2) as stationary phase. The latter fraction was silylated with 200 µl BSTFA (bis-trimethylsilyl-trifluoroacet-amide) .Biomarkers were analyzed at the Alfred Wegener Institute in Bremerhaven, Germany. Between 4 and 7 g freeze-dried and homogenized sediment was extracted using an accelerated solvent extractor  with dichlormethane:methanol (2:1) as solvent. For quantification, internal standards, 7-hexylnonadecane, , cholesterol-d25 was analyzed using an Agilent 7890B GC coupled to an Agilent 5977A MSD using following heating program: 60 °C (3 min), 150 °C (rate: 15 °C/min), 320 °C (rate: 10 °C/min), 320 °C . Sterols  were analyzed using an Agilent 6850 GC  coupled to an Agilent 5975C MSD . The GC oven was heated as follows: 60 °C (2 min), 150 °C (rate: 15 °C/min), 320 °C (rate: 3 °C/min), 320 °C . For both analyses, helium was used as carrier gas (1 ml/min constant gas flow). The injection volume was 1 µl (splitless). The identification and quantification of the IP25 monoene and sterols were performed by comparison of GC retention times with those of reference compounds and published mass spectra51.Compound analysis was performed by gas chromatography mass spectrometry (GC-MS). IP52 and for additional samples27 involving cold acid digestion  of the mineral fraction, but no oxidation (full details in refs52). One Lycopodium clavatum tablet (batch #483216) was added prior to acid treatment. Occasionally mild ultrasonic treatment was applied before sieving at 10 µm and before mounting the organic residue  on microscope slides. Slides were then counted using a light microscope at x400 magnification along non-overlapping traverses until at least 250 specimens were counted, or until the slide was completely scanned.Samples (10 cc) were dried, weighed and prepared using a standard palynological maceration procedure details inSupplementary Figures


SAMHD1 is the major catabolic enzyme regulating the intracellular concentrations of DNA precursors (dNTPs). The S-phase kinase CDK2-cyclinA phosphorylates SAMHD1 at Thr-592. How this modification affects SAMHD1 function is highly debated. We investigated the role of endogenous SAMHD1 phosphorylation during the cell cycle. Thr-592 phosphorylation occurs first at the G1/S border and is removed during mitotic exit parallel with Thr-phosphorylations of most CDK1 targets. Differential sensitivity to the phosphatase inhibitor okadaic acid suggested different involvement of the PP1 and PP2 families dependent upon the time of the cell cycle. SAMHD1 turn-over indicates that Thr-592 phosphorylation does not cause rapid protein degradation. Furthermore, SAMHD1 influenced the size of the four dNTP pools independently of its phosphorylation. Our findings reveal that SAMHD1 is active during the entire cell cycle and performs an important regulatory role during S-phase by contributing with ribonucleotide reductase to maintain dNTP pool balance for proper DNA replication. The reaction was quenched with Laemmli buffer and boiled for 5 min. Proteins were separated by SDS-PAGE, the gel was stained with Coomassie Brilliant Blue and autoradiographed.Cyclin E/CDK2 and Cyclin A/CDK2 were expressed in recombinant baculovirus infected Hi5 insect cells and purified as in Hossain and Stillman . The pho35]-labeled cyclin A2 and cyclin E were produced using Quick TNT-coupled reticulocyte lysate system (Promega) according to the manufacturer’s instruction in the presence of [S35]-methionine (PerkinElmer). For each reaction 8 µl of [S35]-labeled cyclin proteins and the beads containing 3 µg of GST-tagged protein were incubated in 400 µl of binding buffer overnight at 4°C. The resin with bound proteins was washed four times with binding buffer and the proteins were eluted in Laemmli buffer and analyzed by SDS-PAGE followed by PhosphorImaging analysis.The GST and GST-SAMHD1 peptides were bound to Gluthatione agarose resin (Pierce) and the beads were washed three times with binding buffer . -labeled dUMP as substrate, as described by Rampazzo et al [−1 (1 mU = 1nmol product/min−1).Total 5ʹ-deoxynucleotidase  activity was determined in crude whole cell extracts with 5 mM [Hzo et al . The enz


Mitogen-activated protein kinases (MAPK): Erk1 and Erk2 are key players in negative-feedback regulation of fibroblast growth factor (FGF) signaling. Upon activation, Erk1 and Erk2 directly phosphorylate FGF receptor 1 (FGFR1) at a specific serine residue in the C-terminal part of the receptor, substantially reducing the tyrosine phosphorylation in the receptor kinase domain and its signaling. Similarly, active Erks can also phosphorylate multiple threonine residues in the docking protein FGF receptor substrate 2 (FRS2), a major mediator of FGFR signaling. Here, we demonstrate that in NIH3T3 mouse fibroblasts and human osteosarcoma U2OS cells stably expressing FGFR1, in addition to Erk1 and Erk2, p38 kinase is able to phosphorylate FRS2. Simultaneous inhibition of Erk1/2 and p38 kinase led to a significant change in the phosphorylation pattern of FRS2 that in turn resulted in prolonged tyrosine phosphorylation of FGFR1 and FRS2 and in sustained signaling, as compared to the selective inhibition of Erks. Furthermore, excessive activation of p38 with anisomycin partially compensated the lack of Erks activity. These experiments reveal a novel crosstalk between p38 and Erk1/2 in downregulation of FGF-induced signaling. Fibroblast growth factor (FGF) receptor (FGFR) -dependent signaling plays a crucial role during embryonic development, as well as in adult life. It stimulates growth, differentiation, survival, injury repair, regeneration, and metabolism. Consequently, excessive activation of FGFRs may result in severe abnormalities, such as cancer development and progression, and skeletal disorders .Downregulation of FGFR signaling consists of a number of mechanisms that enable precise control of cellular outcome. They include regulation of FGFR synthesis, receptor internalization, followed by degradation and modulation of FGFR tyrosine phosphorylation via the activity of several negative regulators and feedbacks ,3,4,5,6.Previously we showed that phosphorylation of Ser777 of FGFR1 by activated MAPK Erk1 and Erk2 significantly reduces the tyrosine phosphorylation in the kinase domain of the receptor. We suggested that the phosphorylated Ser777 could act as a binding site for tyrosine phosphatases responsible for receptor inactivation ,9. In adFurthermore, FGFR downstream signaling molecules are also affected by inhibitory loops and negative regulators, including Sprouty proteins (SPRY1–SPRY4), MAPK phosphatase 3 (MKP3), SEF (similar expression to FGF), and protein tyrosine phosphatase receptor type G (PTPRG). MKP3 directly dephosphorylates MAPK turning off the Ras cascade . SproutyHowever, one of the most effective downregulation mechanism described so far is based on Erk1/2-FRS2 negative feedback loop . FRS2, aBesides Erks, the MAPK family includes also p38 and c-Jun N-terminal kinases (JNKs). Erks are activated by mitogenic factors and are associated with growth, differentiation, and proliferation, whereas p38 and JNKs take part mainly in the cell response to stress conditions and inflammatory cytokines, and are activated only weakly by proliferative stimuli . There aInterestingly, all MAPKs share specificity for a common consensus phosphorylation site . We showHere, we found that in addition to Erks, p38 can also phosphorylate FRS2 and modulate its phosphorylation at tyrosine residues. Simultaneous inhibition of both types of MAPKs resulted in prolonged activation of FGFR1, FRS2, and downstream signaling, as compared to the elimination of Erks activity alone. Our results reveal a novel regulatory feedback mechanism, where p38 is able to partially substitute Erk1 and Erk2 in the regulation of FGFR activity.We analyzed by immunoblotting the activation of FGF1-induced signaling in NIH3T3 mouse fibroblast cells upon 15-min stimulation with FGF1 in the presence of different combinations of MAP kinases inhibitors  and p38 kinase activator (anisomycin) a. As expAs conventional SDS-PAGE is not optimal for separation of phosphorylated populations of a protein from a non-modified fraction, we studied FRS2 migration upon treatment with various kinases inhibitors using a Phos-Tag technology that is well suited for phosphorylation profiling of proteins ,25. CellIn the serum starved NIH3T3 cells, FRS2 was observed mainly as a single, fast migrating band on Phos-Tag gel, likely representing non-phosphorylated FRS2 c, lane 1Since the addition of either p38 inhibitor or p38 activator resulted in FRS2 mobility changes in SDS-PAGE and Phos-Tag PAGE, we hypothesized that p38, in addition to Erks, is also able to phosphorylate FRS2. To verify such possibility, we performed in vitro phosphorylation using recombinant FRS2 and recombinant active form of p38α kinase. Using autoradiography we observed a clear band corresponding to phosphorylated FRS2 when active p38α was present during the reaction d, lane 5Next, we studied the impact of p38 activity on the kinetics of signaling cascades activated by FGF1 in NIH3T3 a. ExperiFinding a synergistic effect of the inhibition of both types of MAP kinases, Erks and p38, we asked if they were able to compensate for each other. Indeed, we observed that FGF1-dependent Erk1/2 phosphorylation in the presence of p38 inhibitor was slightly stronger a, lane 2Next, we verified the impact of p38 inhibition on the activity of Erks without FGF1 stimulation. We found that in the presence of increasing concentrations of the specific p38 kinase inhibitor, SB203580, the basal level of phosphorylated Erk1/2 in serum-starved NIH3T3 was augmented a, showinSeveral mechanisms to attenuate FGFR activity have been reported, however, the overall picture of how the FGFR signaling is controlled has not been yet fully described . FRS2 deOur results show that p38 kinase phosphorylates FRS2 in vitro, and together with Erk1 and Erk2 takes part in modulation of the duration and the intensity of FGFR signaling. Experiments with anisomycin, a p38 activator, revealed that in specific conditions , p38 can compensate for Erks’ action. Despite the similar activity in vitro, the effect of p38 on FRS2 phosphorylation in cells is much weaker than the effect of Erk1 and Erk2. It is probably caused by the fact that growth factors, including FGF1, evoke stronger activation of pro-proliferative MAPKs, i.e., Erks, than stress-response MAPKs, such as p38 kinase . We alsoAll MAPK family members share a common phosphorylation site motif . Their sMAPK signaling seems to be a dynamic map of non-linear interactions rather than static connections. Different MAPK cascades operate in parallel, but at the same time they constitute a network and modulate each other’s activity . Here, wTherapeutic targeting of components of the MAPK cascades is an urgent medical need. Inhibitors of Erks and p38 signaling pathways are in many clinical trials dedicated to treating different types of cancer, inflammation, pain, rheumatoid arthritis, asthma, and neurodegenerative diseases, including Alzheimer’s ,36. HoweThe following primary antibodies were used: rabbit anti-MAPK , mouse anti-phospho-MAPK  , mouse anti-phospho-FGFR , and rabbit anti-phospho-FRS2α  from Cell Signaling Technology , rabbit anti-FRS2α , from Santa Cruz Biotechnology , mouse anti-phospho-p38 MAPK antibody  and mouse anti-Hsp90 (610418) from BD Transduction Laboratory , mouse anti-tubulin (T6557) from Sigma-Aldrich . Specific anti-phospho-FGFR1 (Ser777) (pS777-FGFR1) antibody was made by GenScript  using the following phospho-specific peptide CSMPLDQYpSPSFPDTR. The antibody was purified using the phosphopeptide and by cross-adsorption to the corresponding non-phosphopeptide. HRP-conjugated secondary antibodies were from Jackson Immuno Research Laboratories . Heparin-Sepharose CL-6B affinity resin was from GE Healthcare . Brefeldin A, SB203580, anisomycin, and SL327 were from Calbiochem . Heparin, sodium orthovanadate, and U0126 were from Sigma-Aldrich. Phos-tag gels were from Wako Chemicals . All other chemicals were from Sigma-Aldrich.Escherichia coli strain Bl21(DE3)pLysS from New England Biolabs  was used.NIH3T3 cells were grown in DMEM from Thermo Fisher Scientific  or  supplemented with 10% bovine serum (Thermo Fisher Scientific) and 100 U/mL penicillin and 100 µg/mL streptomycin (Thermo Fisher Scientific). The U2OS cells stably expressing FGFR1 (U2OS-R1) have been described previously . The celE. coli, as described previously  ATP in reaction buffer  at 30 °C for 30 min. The proteins were separated by SDS-PAGE, electroblotted, and analyzed by autoradiography. Equal loading was ensured by membrane staining with Coomassie Blue.p < 0.05 was considered statistically significant.For statistical analysis, one-way analysis of variance (ANOVA) with Tukey’s posttest was applied using SigmaPlot 12 software from ;


Also AKR1B10-mediated farnesal reduction was effectively inhibited by α-acid congeners with Ki-values ranging from 16.79 ± 1.33 µM (adhumulone) to 3.94 ± 0.33 µM (n-humulone). Overall, α-acids showed a strong inhibition with selectivity (115–137 fold) for AKR1B10. The results presented herein characterise hop-derived α-acids as a promising basis for the development of novel and selective AKR1B10-inhibitors.Hop-derived compounds have been subjected to numerous biomedical studies investigating their impact on a wide range of pathologies. Isomerised bitter acids  from hops, used in the brewing process of beer, are known to inhibit members of the aldo-keto-reductase superfamily. Aldo-keto-reductase 1B10 (AKR1B10) is upregulated in various types of cancer and has been reported to promote carcinogenesis. Inhibition of AKR1B10 appears to be an attractive means to specifically treat RAS-dependent malignancies. However, the closely related reductases AKR1A1 and AKR1B1, which fulfil important roles in the detoxification of endogenous and xenobiotic carbonyl compounds oftentimes crossreact with inhibitors designed to target AKR1B10. Accordingly, there is an ongoing search for selective AKR1B10 inhibitors that do not interact with endogeneous AKR1A1 and AKR1B1-driven detoxification systems. In this study, unisomerised α-acids (adhumulone, cohumulone and  Humulus lupulus). In particular, hop-derived chalcones (xanthohumol), prenylflavonoids  and (iso-) α- and β-bitter acids ((iso-)humulone and (iso-)lupulone) are among the bioactive compounds accounting for various modes of action in the prevention or potential treatment of many (lifestyle) diseases. These include metabolic and inflammatory diseases as well as carcinogenesis . In this case, the loss of an isoprenyl group in 1,5-DIMX and 1,7-DIMX might have also contributed to deteriorating the inhibitory effect when compared to the parent substance [We further determined inhibition parameters of compounds ogenesis . Thus, iposition . Also, pubstance . With respect to the mechanism of inhibition, Zhang et al. suggested a more accessible anionic site at TRP112, allowing the entrance of more bulky and rigid inhibitors at the broader active site of AKR1B10 . MoleculM = 5 µM), compound 3 was the best inhibitor with a relatively low Ki (3.94 ± 0.33 µM) when compared to its congeners, compound 2 (Ki = 16.53 ± 1.74 µM) and 1 (Ki = 16.79 ± 1.33 µM). Among the natural-based derivatives serving as selective AKR1B10 inhibitors, hop-derived α-acids have not been investigated so far. For the substances tested in this study, non-competitive and competitive modes of inhibition have been observed . With re50 and Ki values stated herein, inhibition of AKR1B10 through α-acids during glyceraldehyde or farnesal reduction, might also be compared to the inhibitory efficiency of unsaturated fatty acids on this enzyme . Unsaturated fatty acids show a competitive inhibition pattern with a specificity towards AKR1B10 [Based on the IC AKR1B10 . Accordi AKR1B10 , which ii, IC50) stated herein, fall within the bioavailable spectrum of iso-α-acids reported by others: a study on the bioavailability of iso-α-acids in rabbits report of cumulative iso-α-acid concentrations between 7 and 20 µM [Under physiological conditions, the inhibitory effect might be further strengthened with increasing uptake of lipophilic congeners. In this context, a study by Cattoor et al. reported efficient epithelial absorption of α-acids, which might as well point towards a rather high bioavailability ,37. Datand 20 µM . As prenIn general, research has made great advances in terms of designing new, effective AKR1B10 inhibitors. Unfortunately, though, the clinical safety of their use has in many cases not been evaluated yet . In cont3 showed the strongest inhibition. Moreover, there is evidence of isoprenoid side chains tending to affect the binding behaviour of AKR1B10 inhibitors. With regard to AKR1B10 selectivity, our results provide a structural basis for the development of future QSAR models and new drugs/inhibitors targeting cancers characterized by AKR1B10-specific actions or AKR1B10 upregulation.In conclusion, the results presented in this study identify α-acids as potent inhibitors with a selectivity for AKR1B10 versus homologous AKR1A1 and AKR1B1. Of the three α-acid congeners tested, inhibition by compound 2 hop extract (30% w/w) was obtained from Barth Haas UK Limited . Mixtures of α-acids were kindly provided by Dr. Martin Biendl . Organic solvents for chromatography, MS grade water and MS grade formic acid were obtained from VWR . Organic solvents used for preparative, semi-preparative and analytical chromatography were of gradient grade quality and water was bi-distilled water. Solvents used for LC-MS analyses were of MS grade quality. Formic acid used for chromatography was of MS grade quality. NADPH was obtained from Carl Roth GmbH & Co. KG . DL-glyceraldehyde and farnesal were purchased from Sigma-Aldrich Co. . A standardised solution of iso-α-acids produced from COm/z. Preparative LC was accomplished using a Büchi PrepChrom C-700 and Büchi PrepChrom C18 column  . Semi-preparative chromatography was carried out on a Waters Alliance e2695 Separations Module equipped with an Alliance 2998 PDA detector and a WFC III fraction collector  using a Phenomenex Aqua column (5 µm. 250 × 10.0 mm). Fractions and pure compounds were analysed by a VWR-Hitachi Chromaster Ultra RS  using a Nucleodur C18 Pyramid column . LC-MS was conducted with a Shimadzu Nexera X2 UHPLC system and a Shimadzu LC-MS 8030 triple quadrupole mass spectrometer using electrospray ionization  and a Nucleodur C18 Gravity-SB column . LC-conditions: isocratic elution with 0.4 mL/min at 30 °C using 0.1% formic acid (30%) and acetonitrile (70%). MS-conditions: nebulizer gas 3 L/min, drying gas 15 L/min, DL temperature 250 °C, heat block temperature 400 °C. Mass range was 100 to 1000 2) while fraction 4 yielded 67 mg of n-humulone (3) and 28 mg of adhumulone (1) after separation by semi-preparative chromatography using 0.025% formic acid in water and acetonitrile (30:70). Compounds were assigned according to their molecular masses and their retention times in comparison with a reference chromatogram [900 mg of α-acids extract were dissolved in 15 mL of 85% methanol and subjected to preparative chromatography using 0.025% formic acid in water and methanol (15:85) yielding 5 fractions. Fraction 2 contained 125 mg of cohumulone  cells. For overexpression of 6× His-tagged enzymes, a 400 mL culture  was grown to optical density of 0.6 at 600 nm at 37 °C. Expression was induced by adding isopropyl-1-thio-galactopyranoside to the culture medium . After 3 h, cells were harvested by centrifugation  and resuspended in 20 mL PBS-I buffer . Cell disruption was performed by ultrasonication with cooling on ice to avoid heating. The sample was subsequently centrifuged at 100,000× g at 4 °C for 1 h. The obtained supernatants containing the respective enzymes were purified using Ni-affinity chromatography  using PBS-II buffer . Purification progress was monitored by SDS-PAGE of the obtained fractions (not shown). Enzyme concentrations were determined using a Qubit 2.0 fluorometric quantitation system  according to the manufacturer’s instructions. The carbonyl-reducing enzymes AKR1A1, AKR1B1, AKR1B10 were prepared in an mir Wsol  and Dr. mir Wsol  has been2PO4 buffer (pH 7.4) and an appropriate amount of enzyme in a total assay volume of 0.8 mL. Final enzyme concentrations in the assay ranged from 222 nM (AKR1A1) to 899 nM (AKR1B10). KM values were obtained by fitting the kinetic data (mean ± SD from at least three experiments) to the Michaelis‒Menten model, as implemented in GraphPad Prism6 . Catalytic properties were determined by measuring the decrease in absorbance at 340 nm . A reaction mixture without inhibitor consisted of different concentrations of DL-glyceraldehyde or farnesal, 200 μM NADPH, 0.1 M NaH2O (iso-α-acid mixture) and DMSO (α-acid mixture and compounds 1–3 purified from the same mixture). The final concentration of DMSO in the assay was ≤ 1% and did not affect enzyme activity. When collecting data for dose–response curves initial velocities of DL-glyceraldehyde or farnesal reduction (substrate concentration at KM) in the presence of inhibitors were assayed as described above. The percentage of inhibition was calculated considering the activity in the absence of inhibitor to be 100%.For inhibition studies, stock solutions of inhibitors were prepared in H50 values) were determined for each inhibitor in presence of each enzyme, using the shared substrate DL-glyceraldehyde  to assess specificity amongst the structurally similar members of the AKR-superfamily.Initially, the half maximal inhibitory concentrations . Whenever tight-binding inhibition was observed, the inhibition constant Ki was determined by fitting inhibition data to the Morrison equation [M = 5 µM) was used to determine inhibition parameters. Enzyme inhibition parameters were assayed as described above. The inhibition mechanism of each compound for AKR1B10 was analysed by plotting IC50-values at different substrate concentrations (at least five inhibitor and substrate concentrations) [For ICequation . In orderations) ,44. All