Bound Ligand Concentration Research Articles

Solving the Competitive Binding Equilibria between Many Ligands: Application to High-Throughput Screening and Affinity Optimization.

Modern small-molecule drug discovery relies on the selective targeting of biological macromolecules by low-molecular weight compounds. Therefore, the binding affinities of candidate drugs to their targets are key for pharmacological activity and clinical use. For drug discovery methods where multiple drug candidates can simultaneously bind to the same target, a competition is established, and the resulting equilibrium depends on the dissociation constants and concentration of all the species present. Such coupling between all equilibrium-governing parameters complicates analysis and development of improved mixture-based, high-throughput drug discovery techniques. In this work, we present an iterative computational algorithm to solve coupled equilibria between an arbitrary number of ligands and a biomolecular target that is efficient and robust. The algorithm does not require the estimation of initial values to rapidly converge to the solution of interest. We explored binding equilibria under ligand/receptor conditions used in mixture-based library screening by affinity selection-mass spectrometry (AS-MS). Our studies support a facile method for affinity-ranking hits. The ranking method involves varying the receptor-to-ligand concentration ratio in a pool of candidate ligands in two sequential AS-MS analyses. The ranking is based on the relative change in bound ligand concentration. The method proposed does not require a known reference ligand and produces a ranking that is insensitive to variations in the concentration of individual compounds, thereby enabling the use of unpurified compounds generated by mixture-based combinatorial synthesis techniques.

Mapping Tyrosine Kinase Receptor Dimerization to Receptor Expression and Ligand Affinities

Tyrosine kinase receptor (RTK) ligation and dimerization is a key mechanism for translating external cell stimuli into internal signaling events. This process is critical to several key cell and physiological processes, such as in angiogenesis and embryogenesis, among others. While modulating RTK activation is a promising therapeutic target, RTK signaling axes have been shown to involve complicated interactions between ligands and receptors both within and across different protein families. In angiogenesis, for example, several signaling protein families, including vascular endothelial growth factors and platelet-derived growth factors, exhibit significant cross-family interactions that can influence pathway activation. Computational approaches can provide key insight to detangle these signaling pathways but have been limited by the sparse knowledge of these cross-family interactions. Here, we present a framework for studying known and potential non-canonical interactions. We constructed generalized models of RTK ligation and dimerization for systems of two, three and four receptor types and different degrees of cross-family ligation. Across each model, we developed parameter-space maps that fully determine relative pathway activation for any set of ligand-receptor binding constants, ligand concentrations and receptor concentrations. Therefore, our generalized models serve as a powerful reference tool for predicting not only known ligand: Receptor axes but also how unknown interactions could alter signaling dimerization patterns. Accordingly, it will drive the exploration of cross-family interactions and help guide therapeutic developments across processes like cancer and cardiovascular diseases, which depend on RTK-mediated signaling.

The Biogeochemistry of Electroactive Humic Substances and Its Connection to Iron Chemistry in the North East Atlantic and the Western Mediterranean Sea

AbstractWe present the zonal distribution of electroactive humic‐like substances (eHS) along a section from Offshore Portugal in the North East Atlantic to the Sicily Channel in the Mediterranean Sea. The concentrations were normalized to Suwannee River Fulvic Acid and ranged from 11 μg/L to 81 μg/L. The vertical distributions were typical of those previously reported for dissolved organic carbon in the Mediterranean Sea. High eHS concentrations were measured in surface water and concentrations decreased with depth before increasing again toward benthic maxima measured at some stations. We estimate that eHS represented a relatively small fraction of the natural organic matter in the Mediterranean Sea (2–5%) but considering their important role in the complexation and the solubility of key trace elements (e.g., iron and copper), the eHS cycle could influence the entire biogeochemistry of these marine systems. We identified key processes controlling the concentration of eHS. While biologically mediated production was the major source of eHS, riverine and rain inputs as well as sediment release were also likely external sources. Low eHS concentrations at subsurface depths pointed to photodegradation as a possible sink of eHS, but degradation by heterotrophic bacteria seemed to be the main sink in the deep sea. Finally, we found a positive correlation between dissolved iron and eHS concentrations. Estimation of eHS contribution to iron binding ligand concentrations indicates the complexation of iron by eHS in the Mediterranean Sea. These observations suggest links between the cycles of eHS and iron in the Mediterranean Sea.

Voltammetric Investigation of Hydrothermal Iron Speciation

Hydrothermal vent fluids are highly enriched in iron (Fe) compared to ambient seawater, and organic ligands may play a role in facilitating the transport of some hydrothermal Fe into the open ocean. This is important since Fe is a limiting micronutrient for primary production in large parts of the world`s surface ocean. We have investigated the concentration and speciation of Fe in several vent fluid and plume samples from the Nifonea vent field, Coriolis Troughs, New Hebrides Island Arc, South Pacific Ocean using competitive ligand exchange - adsorptive cathodic stripping voltammetry (CLE - AdCSV) with salicylaldoxime (SA) as the artificial ligand. Our results for total dissolved Fe (dFe) in the buoyant hydrothermal plume samples showed concentrations up to 3.86 µM dFe with only a small fraction between 1.1% and 11.8% being chemically labile. Iron binding ligand concentrations ([L]) were found in µM level with strong conditional stability constants up to log K[L],Fe3+ of 22.9. Within the non-buoyant hydrothermal plume above the Nifonea vent field, up to 84.7% of the available Fe is chemically labile and [L] concentrations up to 97 nM were measured. [L] was consistently in excess of Felab, indicating that all available Fe is being complexed, which in combination with high Felab values in the non-buoyant plume, signifies that a high fraction of hydrothermal dFe is potentially being transported away from the plume into the surrounding waters, contributing to the global oceanic Fe budget.

Molecular Occupancy of Nanodot Arrays.

Single-molecule nanodot arrays, in which a biomolecule of choice (protein, nucleic acid, etc.) is bound to a metallic nanoparticle on a solid substrate, are becoming an increasingly important tool in the study of biomolecular and cellular interactions. We have developed an on-chip measurement protocol to monitor and control the molecular occupancy of nanodots. Arrays of widely spaced nanodots and nanodot clusters were fabricated on glass surfaces by nanolithography and functionalized with fluorescently labeled proteins. The molecular occupancy was determined by monitoring individual fluorophore bleaching events, while accounting for fluorescence quenching effects. We found that the occupancy can be interpreted as a packing problem, and depends on nanodot size and binding ligand concentration, where the latter is easily adjusted to compensate the flexibility of dimension control in nanofabrication. The results are scalable with nanodot cluster size, extending to large area close packed arrays. As an example, the nanoarray platform was used to probe the geometric requirement of T-cell activation at the single-molecule level.

Organic Cu-complexation at the shallow marine hydrothermal vent fields off the coast of Milos (Greece), Dominica (Lesser Antilles) and the Bay of Plenty (New Zealand)

Hydrothermal vents at the seafloor release large volumes of metal-rich fluids into the ocean. Some of these metals are biologically essential (such as Fe), while others may be toxic (e.g. Cu). Organisms living at these habitats produce small organic molecules, ligands that are able to form complexes with different metals, to either enhance their bioavailability or to decrease their toxicity. While some deep-sea vents have been studied with respect to metal complexation, comparable studies at shallow marine hydrothermal vent systems are rather rare. In this study, total dissolved Cu concentrations ([Cu]T) and corresponding Cu binding ligand concentrations ([L]Cu) at the shallow water hydrothermal vent fields off the coast of Milos (Greece), Dominica (Lesser Antilles) and the Bay of Plenty (New Zealand) were examined by a voltammetric ligand titration, using competitive ligand equilibration–adsorptive stripping voltammetry (CLE–AdCSV).Milos, Dominica and the Bay of Plenty are three very different environments and our data show that they are relatively depleted in total dissolved Cu, compared to deep-sea hydrothermal vents where [Cu]T and [L]Cu concentrations up to 400nM and 4000nM have been found, respectively. In this data set, [Cu]T rises up to 21.53nM, however, most samples are in the range of 0.5nM–3nM. [L]Cu varies between 2.07nM and 23.9nM, with one exception, reaching 56.8nM. Conditional stability constants (Log K) range between 11.57 and 14.01.Assuming that the three investigated sites are representative for shallow marine hydrothermal vents, the Cu-flux into the ocean due to complexation appears to be relatively low compared to deep-sea systems. Our data indicate a stable complexation of Cu in most cases, which may lower the toxic effect of Cu on these mixed photic–chemosynthetic communities. However one pore water sample from Dominica showed an excess [Cu]T over [L]Cu, which would create a highly toxic environment for most marine organisms. We further show that ligand–Cu ratios and complex stability constants are in a similar range as the ones at deep-sea vents, which may indicate similar complexation parameters and processes at shallow and deep-sea hydrothermal vents.

Introduction to project DUNE, a DUst experiment in a low Nutrient, low chlorophyll Ecosystem

Introduction to project DUNE, a DUst experiment in a low Nutrient, low chlorophyll Ecosystem

Impacts of dust deposition on dissolved trace metal concentrations (Mn, Al and Fe) during a mesocosm experiment

Abstract. The deposition of atmospheric dust is the primary process supplying trace elements abundant in crustal rocks (e.g. Al, Mn and Fe) to the surface ocean. Upon deposition, the residence time in surface waters for each of these elements differs according to their chemical speciation and biological utilization. Presently, however, the chemical and physical processes occurring after atmospheric deposition are poorly constrained, principally because of the difficulty in following natural dust events in situ. In the present work we examined the temporal changes in the biogeochemistry of crustal metals (in particular Al, Mn and Fe) after an artificial dust deposition event. The experiment was contained inside trace metal clean mesocosms (0–12.5 m depths) deployed in the surface waters of the northwestern Mediterranean, close to the coast of Corsica within the frame of the DUNE project (a DUst experiment in a low Nutrient, low chlorophyll Ecosystem). Two consecutive artificial dust deposition events, each mimicking a wet deposition of 10 g m−2 of dust, were performed during the course of this DUNE-2 experiment. The changes in dissolved manganese (Mn), iron (Fe) and aluminum (Al) concentrations were followed immediately after the seeding with dust and over the following week. The Mn, Fe and Al inventories and loss or dissolution rates were determined. The evolution of the inventories after the two consecutive additions of dust showed distinct behaviors for dissolved Mn, Al and Fe. Even though the mixing conditions differed from one seeding to the other, Mn and Al showed clear increases directly after both seedings due to dissolution processes. Three days after the dust additions, Al concentrations decreased as a consequence of scavenging on sinking particles. Al appeared to be highly affected by the concentrations of biogenic particles, with an order of magnitude difference in its loss rates related to the increase of biomass after the addition of dust. In the case of dissolved Fe, it appears that the first dust addition resulted in a decrease as it was scavenged by sinking dust particles, whereas the second seeding induced dissolution of Fe from the dust particles due to the excess Fe binding ligand concentrations present at that time. This difference, which might be related to a change in Fe binding ligand concentration in the mesocosms, highlights the complex processes that control the solubility of Fe. Based on the inventories at the mesocosm scale, the estimations of the fractional solubility of metals from dust particles in seawater were 1.44 ± 0.19% and 0.91 ± 0.83% for Al and 41 ± 9% and 27 ± 19% for Mn for the first and the second dust addition. These values are in good agreement with laboratory-based estimates. For Fe no fractional solubility was obtained after the first seeding, but 0.12 ± 0.03% was estimated after the second seeding. Overall, the trace metal dataset presented here makes a significant contribution to enhancing our knowledge on the processes influencing trace metal release from Saharan dust and the subsequent processes of bio-uptake and scavenging in a low nutrient, low chlorophyll area.

In Vivo Measurement of the Affinity and Density of Metabotropic Glutamate Receptor Subtype 1 in Rat Brain Using 18F-FITM in Small-Animal PET

Metabotropic glutamate receptor subtype 1 (mGluR1) is a crucial molecular target in the central nervous system disorders. 4-(18)F-fluoro-N-[4-[6-(isopropylamino)pyrimidin-4-yl]-1,3-thiazol-2-yl]-N-methylbenzamide ((18)F-FITM) has been recently developed as a useful PET ligand for mGluR1 imaging in our laboratory. In this study, we aimed to measure the affinity and density of mGluR1 using PET with (18)F-FITM in rat brain under the in vivo conditions. Binding potentials (BP(ND)) and amounts of specific binding (bound ligand concentration) at equilibrium state in brain regions were noninvasively estimated using the equilibrium analysis combined with the receptor-blocked approach (EA RBA) for kinetic analysis of (18)F-FITM PET results in place of reference tissue methods. Using BP(ND) and specific binding values of rats treated with multidose ligand, we performed Scatchard analyses for in vivo measurements of mGluR1 density (maximum number of binding sites, or B(max)) and ligand affinity (dissociation constant, or K(d)) in brain regions, respectively. The pretreatment of rats with unlabeled FITM (1 mg/kg) occupied an mGluR1 binding site of (18)F-FITM by more than 99% and did not affect the input function. Hence, we used the tissue time-activity curve for receptor-blocked rats as representative of the nondisplaceable (free and nonspecific binding of radioligand) compartment. The BP(ND) based on EA RBA showed a high correlation with the BP(ND) based on invasive Logan plot graphical analysis in the thalamus, hippocampus, striatum, and cingulate cortex. The K(d) (nM) and B(max) (pmol/mL) obtained by the Scatchard analyses with the multidose ligand assays were 2.1 and 36.3, respectively, for the thalamus; 2.1 and 27.5, respectively, for the hippocampus; 1.5 and 22.2, respectively, for the striatum; and 1.5 and 20.5, respectively, for the cingulate cortex with a high confidence. Our study is the first to our knowledge to measure the in vivo affinity (K(d) and binding potential) of (18)F-FITM and mGluR1 density (B(max)) with a high correlation to in vitro values in rat brain regions. This measurement using PET with (18)F-FITM would be a useful index for research about mGluR1 functions in central nervous system disorders and development of new pharmaceuticals.

A nanoelectronic enzyme-linked immunosorbent assay for detection of proteins in physiological solutions.

Semiconducting nanowires are promising ultrasensitive, label-free sensors for small molecules, DNA, proteins, and cellular function. Nanowire field-effect transistors (FETs) function by sensing the charge of a bound molecule. However, solutions of physiological ionic strength compromise the detection of specific binding events due to ionic (Debye) screening. A general solution to this limitation with the development of a hybrid nanoelectronic enzyme-linked immunosorbent assay (ne-ELISA) that combines the power of enzymatic conversion of a bound substrate with electronic detection is demonstrated. This novel configuration produces a local enzyme-mediated pH change proportional to the bound ligand concentration. It is shown that nanowire FETs configured as pH sensors can be used for the quantitative detection of interleukin-2 in physiologically buffered solution at concentrations as low as 1.6 pg mL(-1). By successfully bypassing the Debye screening inherent in physiological fluids, the ne-ELISA promises wide applicability for ligand detection in a range of relevant solutions.

A Fluorescence Analysis of ANS Bound to Bovine Serum Albumin: Binding Properties Revisited by Using Energy Transfer

Determination of binding parameters such as the number of ligands and the respective binding constants require a considerable number of experiments to be performed. These involve accurate determination of either free and/or bound ligand concentration irrespective of the measurement technique applied. Then, an appropriate theoretical model is used to fit the experimental data, and to extract the binding parameters. In this work, the interaction between bovine serum albumin (BSA) and 1-anilino-8-naphthalene sulphonate (ANS) is revisited. Using steady state fluorescence spectroscopy, the binding isotherm of BSA/ANS was obtained applying the Halfman-Nishida approach. The binding parameters, site number, and binding site association constants, were determined from the stoichiometric Adair model and Job's plot. The binding parameters obtained were then correlated to the distance of the respective binding site to the tryptophan residues using the energy transfer technique. This approach, that uses both tryptophans independently from each other, is presented as a tool to help understand the binding mechanism of the albumin fluorescent complex. The results show that ANS molecules bind to BSA in up to five different binding sites. Energy transfer from the tryptophan residues to the BSA/ANS complex shows that the four highest affinity binding sites (>10(4) M(-1)) are located at a reasonably close distance (18-27 A) to at least one of two tryptophan residues, while the lowest affinity binding site (approximately 10(4) M(-1)) is located over 34 A away from the both tryptophans.

The binding of the flavour of lactones by soya protein, amino acids and casein

SummaryThe binding of certain lactones to soya protein isolate, amino acids and casein in different concentrations was investigated using capillary column gas chromatography. The analysis of lactones was conducted by solid phase microextraction and by the standard method of headspace analysis. The percentage of binding of lactones γ‐9, γ‐10, δ‐10 and δ‐11 on the soya protein is almost the same. According to the Klotz equation, the bound ligand concentration was calculated as the number of moles of ligand bound per mole of protein. γ‐lactones are bound less than δ‐lactones and that the competitive binding ability of lactones δ‐11 and γ‐10 is similar. δ‐11 has a greater binding capacity with each of the amino acids used and with casein than γ‐10 because of its greater ability to form hydrophobic binding than γ‐10. The techniques of gas chromatography/mass spectrometry and infrared spectroscopy confirmed that the binding of the ligand on the protein substrate was attributed to secondary bonds, such as hydrogen bonds, hydrophobic bonds and van der Waals forces.

Factors affecting the flavour binding properties of lactones with soya protein

PurposeThe objective of this article is to investigate the binding of several lactones to soya protein isolate and soya protein under different conditions and, particularly, the extent of binding of the lactones γ‐9, γ‐10, δ‐10 and δ‐11, in different concentrations as well as the effect of various parameters on their binding ability.Design/methodology/approachCapillary column gas chromatography was used for the determination of lactones and the manual system was used for taking samples and for headspace analysis. Infrared spectroscopy was used for confirmation and investigation.FindingsThe percentage of binding of lactones γ‐9, γ‐10, δ‐10, δ‐11 on the soya protein is almost the same (about 33‐34 per cent). According to the Klotz equation, the bound ligand concentration was calculating as the number of moles of ligand bound per mole of protein. The results varied, but were similar. Specific experiments in water system with soya protein isolate (1 per cent) showed that the time taken for lactones γ‐10 and δ‐11 to reach equilibrium, the factors of temperature and pH affected the percentage of lactone bound.Research limitations/implicationsThe amount of added lactone in products containing soya protein isolate should be investigated by using panel tests to confirm the improvement of flavour.Practical implicationsFlavour binding of lactones can be used to provide some foods with the required flavour impression by adding lactones to a bland soy protein base.Originality/valueThe flavour binding of lactones, which was investigated in the present paper, has not been adequately investigated in previous scientific research and the effects of the factors that influence their binding are very important.

Major deviations of iron complexation during 22 days of a mesoscale iron enrichment in the open Southern Ocean

The speciation of strongly chelated iron during the 22-day course of an iron enrichment experiment in the Atlantic sector of the Southern Ocean deviates strongly from ambient natural waters. Three iron additions (ferrous sulfate solution) were conducted, resulting in elevated dissolved iron concentrations ( Nishioka, J., Takeda, S., de Baar, H.J.W., Croot, P.L., Boye, M., Laan, P., Timmermans, K.R., in press. Changes in the concentration of iron in different size fractions during an iron enrichment experiment in the open Southern Ocean. Marine Chemistry. ) and significant Fe(II) levels ( Croot, P.L., Laan, P., Nishioka, J., Strass, V., Cisewski, B., Boye, M., Timmermans, K.R., Bellerby, R.G., Goldson, L., Nightingale, P., de Baar, H.J.W., in press. Spatial and Temporal distribution of Fe(II) and H 2O 2 during EisenEx, an open ocean mescoscale iron enrichment. Marine Chemistry. ). Repeated vertical profiles for dissolved (filtrate < 0.2 μm) Fe(III)-binding ligands indicated a production of chelators in the upper water column induced by iron fertilizations. Abiotic processes (chemical reactions) and an inductive biologically mediated mechanism were the likely sources of the dissolved ligands which existed either as inorganic amorphous phases and/or as strong organic chelators. Discrete analysis on ultra-filtered samples (< 200 kDa) suggested that the produced ligands would be principally colloidal in size (> 200 kDa–< 0.2 μm), as opposed to the soluble fraction (< 200 kDa) which dominated prior to the iron infusions. Yet these colloidal ligands would exist in a more transient nature than soluble ligands which may have a longer residence time. The production of dissolved Fe-chelators was generally smaller than the overall increase in dissolved iron in the surface infused mixed layer, leaving a fraction (about 13–40%) of dissolved Fe not bound by these dissolved Fe-chelators. It is suggested that this fraction would be inorganic colloids. The unexpected persistence of such high inorganic colloids concentrations above inorganic Fe-solubility limits illustrates the peculiar features of the chemical iron cycling in these waters. Obviously, the artificial about hundred-fold increase of overall Fe levels by addition of dissolved inorganic Fe(II) ions yields a major disruption of the natural physical–chemical abundances and reactivity of Fe in seawater. Hence the ensuing responses of the plankton ecosystem, while in itself significant, are not necessarily representative for a natural enrichment, for example by dry or wet deposition of aeolian dust. Ultimately, the temporal changes of the Fe(III)-binding ligand and iron concentrations were dominated by the mixing events that occurred during EISENEX, with storms leading to more than an order of magnitude dilution of the dissolved ligands and iron concentrations. This had strongest impact on the colloidal size class (> 200 kDa–< 0.2 μm) where a dramatic decrease of both the colloidal ligand and the colloidal iron levels ( Nishioka, J., Takeda, S., de Baar, H.J.W., Croot, P.L., Boye, M., Laan, P., Timmermans, K.R., in press. Changes in the concentration of iron in different size fractions during an iron enrichment experiment in the open Southern Ocean. Marine Chemistry. ) was observed.

Monitoring magnesium to guide magnesium therapy for heart surgery.

ionized Mg (iMg). Measurement of TMg requires the isolation of plasma (centrifugation of blood sample) or serum (clotting and centrifugation of blood sample). Measurement is made by atomic absorption spectrophotometry or colorimetry. Reference values for plasma and serum TMg typically range from 0.66 to 1.07 mmol·l 1. There is virtually no correlation between plasma/serum TMg and intracellular TMg. Ionized magnesium (iMg Mg2 ) represents the activity of unbound Mg in whole blood plasma, plasma, and/or serum. It is the physiologically active Mg fraction, i.e., the fraction to which tissues respond. Reference values typically range from 0.45 to 0.62mmol·l 1. The fact that it can be measured in a whole blood sample by electrode produces a rapid result ( 150s) on a small sample ( 200μl). A rapid result can be very helpful for patients (1) with arrhythmia, (2) with changes in cardiac output, (3) receiving cardiovascular drugs, (4) sustaining hypoxic damage, and (5) receiving Mg therapy. Blood plasma iMg correlates with intracellular iMg and therefore represents a better indicator of Mg status than TMg. It is typically 70% of the TMg value, but varies with the protein and small ligand concentrations in the blood. The iMg value may be substantially less than 70% of the TMg value in critically ill patients where binding ligand concentrations (heparin, citrate, lactate, phosphate, bicarbonate, etc.) have increased. Comparisons of iMg to TMg were illustrated in nine clinical settings (hypertension, acute myocardial infarction, head trauma, noninsulin-dependent diabetes, stroke, pregnancy, ischemic heart disease, cyclosporin recipients, and asthma) [3]. Ionized magnesium was found to be a better indicator of disease than TMg. In summary, iMg (1) represents the physiologically important Mg measurement, (2) is a better indicator of disease than TMg, and (3) is a more rapid measurement. The literature should be interpreted with caution. Frequently, if not generally, the Mg values reported in

Complexation of cobalt by natural organic ligands in the Sargasso Sea as determined by a new high-sensitivity electrochemical cobalt speciation method suitable for open ocean work

Abstract A high-sensitivity cobalt speciation method was developed and applied to a profile in the North Atlantic. Method development included examining the redox chemistry of the analytical system and calibrating the electroactive cobalt ligand dimethylglyoxime (DMG) using EDTA as a model ligand. The method was applied to a depth profile at the Bermuda Atlantic Time Series Station (BATS) during a September 1999 cruise. Total dissolved cobalt, measured using adsorptive cathodic stripping voltammetry (ACSV) on ultraviolet light irradiated samples, revealed a nutrient-like profile for cobalt. Co speciation, measured using CLE–ACSV (competitive ligand exchange), showed a cobalt binding ligand concentration that was similar to that of total cobalt throughout the profile. An excess of ligand was observed in the chlorophyll maximum where Prochlorococcus and Synechococcus numbers were highest. A conditional stability constant for CoHDMG2 was measured to be logKCoHDMG2cond=11.5±0.3 at pH 8.0. A pH dependence for KCoHDMG2cond was observed and is consistent with model calculations based on the protonation constants for H2DMG. The conditional stability constant for CoL was determined to be logKCoLcond=16.3±0.9 and total ligand concentrations varied from 9 to 83 pM as calculated by a one-ligand non-linear fit using the Levenberg–Marquardt algorithm. Alternate interpretations of the data are discussed, including the possibility for an underestimation of ligand concentrations and stability constants caused by the existence of Co(III) ligands, and kinetic and thermodynamic competition for natural ligands by Ni and Co(II).

Determination of equilibrium constant of alkylbenzenes binding to bovine serum albumin by solid phase microextraction.

Solid phase microextraction (SPME) coupled with GC has been applied to study the binding properties between bovine serum albumin (BSA) and volatile organic compounds such as benzene, toluene, ethylbenzene, propylbenzene and butylbenzene. Their protein-ligand equilibrium constants have been determined. The measurement of free and bound ligand concentrations in the aqueous solution was based on the equilibrium among the analyte in the fiber coating (Cf), headspace (Ch) and aqueous solution (Cs). The work demonstrated that SPME is a simple and effective method in the study of protein binding to measure the freely dissolved analyte concentration as well as the equilibrium constant. The theoretical aspect of the SPME applied to the equilibrium constant measurement in two-phase (liquid sample-fiber coating) and three-phase (liquid sample-headspace-fiber coating) systems has been thoroughly discussed. The results demonstrated that the interpretation of the calibration data is crucial to the determination of freely dissolved analyte concentration and the equilibrium constant especially when the sample volume is small. The error in the experimental system is discussed. It is demonstrated in this study that for the three-phase system the amount of the analyte partitioned in the headspace could be ignored only in certain circumstances, where the Henry's law constant and the ratio between headspace volume and sample volume are sufficiently small.

The role of organic complexation on ambient iron chemistry in the equatorial Pacific Ocean and the response of a mesoscale iron addition experiment

We participated on the Iron‐Ex II study in the equatorial Pacific to investigate ambient iron chemistry and its response to a mesoscale iron addition experiment. As expected, dissolved iron values in the high‐nutrient, low‐chlorophyll surface waters of the South Equatorial Current (4–6°S, 105–109°W) were extremely low (∼20 pM). In studies of the chemical speciation of dissolved iron, we found two classes of Fe(III)‐binding organic ligands—a strong ligand class (L1) with a conditional stability constant and a mean concentration of 310 pM, and a weaker class (L2) with a conditional stability constant and a mean concentration of 190 pM. The total Fe(III)‐binding organic ligand concentrations were ∼25× higher than total dissolved iron concentrations (∼20 pM). Thermodynamic equilibrium calculations indicate that &gt;99.9% of the ambient dissolved Fe(III) would be complexed with these organic ligands and exist as low‐molecular‐weight Fe(III) chelates, with &lt;0.1% (15 fM or ∼10−14 M) existing as an inorganic Fe(III)′ fraction. In the primary Iron‐Ex II study, the total Fe(III)‐binding ligand concentrations increased by 400% to ∼2 nM within a day or two after the initial 2 nM mesoscale iron injection. Most of this increase was due to the stronger ligand class, L1, which increased from 0.3 nM to 1.3 nM. The weaker ligand class increased by a similar percentage, although the total magnitude was smaller. Similar increases in Fe(III)‐binding ligand concentrations were observed in a secondary Iron‐Ex II experiment within 17 h after an initial low‐iron 0.4 nM infusion. Results obtained from samples collected throughout the entire course of the iron‐enrichment experiments suggest that these Fe(III)‐binding organic ligands are produced rapidly in response to small iron additions to this low‐iron regime. The chelated iron appears to be directly or indirectly accessible for growth.

Heavy-metal ion complexation by particulate matter in the leachate of solid waste: a multi-method approach

The metal ion binding characteristics of particulate matter obtained from column experiments on the anaerobic digestion of solid waste were studied using a titrimetric approach. The experimental set-up allowed us to study the dynamics of particle bound ligand concentrations during digestion processes typically found in landfills. We developed a continuous titration method by simultaneously using a Cd-sensitive and p H electrode and combining metal and acid/base titrations. This technique allows for a more precise determination of p K a-log K M pairs for each ligand than metal titrations alone. The results were compared with titration methods using differential pulse anodic stripping voltammetry (DPASV) and atomic absorption spectroscopy (AAS) with longer equilibration times in order to further characterize ligand properties such as reaction kinetics, the electrochemical lability of the respective complex during DPASV, the distinction between metal adsorption to particulate matter and metal complexation by soluble ligands adhered to particles, reversibility of the binding process by competition studies, and resistance against purging with nitrogen gas. The properties of seven major metal binding ligands were identified and assignments to the most likely functional groups were made. The most important ligand properties are for ligand A: p K a ≈ 9.2, log K cd ≈ 7.0 fast reaction kinetics (mercapto groups); ligand B: p K a = 4.8, log K Cd ≈ 6.0, slow reaction kinetics (chelates with 3 or 4 carboxylic groups); ligand C: p K a ≈ 6.0, log K Cd ≈ 13.0, irreversible metal binding at basic p H-values (uptake inside bacterial cells); ligand D: p K a = 7.7, log K Cd = 4.0, runs parallel to N content of particulate matter with digestion time (primary amines neighboring oxo groups); ligand E: p K a ≈ 12.0, log K Cd = 9.0, runs parallel to P content of particulate matter (phosphate); ligand F:p K a ⪢ > 9.0, log K Cd f = p K a + 0.4 , runs parallel to N content of particulate matter (primary amines neighboring SH groups); and ligand G: p K a ≤ 4.8, log K Pb ≈ 4.3, strong Pb 2+ ligand, even at low p H-values. Metal ions were found to be irreversibly bound by ligand C at low heavy-metal concentratins, whereas at higher concentrations the binding is reversible and can be predicted using the mass of the digestion process (methanogenic phase). All other ligands have their concentration maximum in the transition phase between acetogenic and methanogenic phase.

Approximating the effects of diffusion on reversible reactions at the cell surface: ligand-receptor kinetics

We consider the problem of determining the time dependence of the bound ligand concentration for the reversible binding of a diffusing monovalent ligand to receptors uniformly distributed over the surface of a spherical cell. We start by formulating a boundary value problem that captures the essential physics of this situation. We then introduce a systematic approximation scheme based on the method of weighted residuals. By this means we convert the initial boundary value problem into a simpler problem that requires solving only a small number of ordinary differential equations. We show how, at the lowest order of approximation, the method can be used to obtain modified chemical rate equations where, in place of fundamental rate constants, effective rate coefficients appear. These rate coefficients are functions of the ligand diffusion coefficient, the cell radius, the receptor density and other variables. We compare exact and approximate solutions and discuss under what conditions the approximate equations can be used. We also apply the method of weighted residuals to obtain approximate descriptions of the binding kinetics when (1) there are two different cell surface receptor populations that bind the ligand and (2) the cell secretes a ligand that can bind back to receptors on the cell (autocrine binding).