Trends In Binding Affinity Research Articles

The role of multivalent cations in determining the cross-linking affinity of alginate hydrogels: A combined experimental and modeling study

This study explores the development of a comprehensive mathematical model to predict the cross-link density of alginate hydrogels using varying concentrations of divalent and trivalent ions. By systematically investigating the effects of Ca²⁺, Ba²⁺, Cu²⁺, Sr²⁺, Mg²⁺, Fe3⁺ and Al³⁺, the research describes the relationship between ion concentration and cross-link density. Experimental data reveals that the type and concentration of these ions critically influence the mechanical properties of the resulting hydrogels, with trivalent ions such as Fe³⁺ forming stronger, triple cross-links that significantly enhance the hydrogel's mechanical strength. Among the divalent ions, the trend in binding affinity is as follows: Ba²⁺ with the highest affinity followed by Sr²⁺, Ca²⁺ and Cu²⁺, while Mg²⁺ stands out with the lowest affinity, significantly differing from the others. The deviation of Cu²⁺ (transition metal ion) from the expected trend in ion interactions suggests that coordination chemistry, along with ionic radius, valence, and cation coordination abilities, plays a significant role in determining interaction strength with alginate. The proposed model, enhanced with fitting parameters k1 and k2 to account for ion-specific effects, leverages the unique binding affinities and coordination chemistry of each ion to tailor alginate hydrogels for specific applications. The parameter k1 reflects the affinity of the ions for the alginate chains, while k2 captures the coordination abilities and cross-linking efficiency. This work not only advances the understanding of ion-mediated cross-linking in alginate systems but also offers a valuable tool for the design and optimization of hydrogels with precise mechanical properties governed by various applications.

Determination of Binding Constants and Gas Phase Stabilities of Artificial Carbohydrate Receptor Complexes Using Electrospray Mass Spectrometry.

In recent years, binding studies to determine complex stabilities and selectivities of artificial carbohydrate receptors with glycosides have been mainly performed using 1H NMR, isothermal titration calorimetry (ITC), and other spectroscopic titration techniques. Native electrospray ionization (ESI) mass spectrometry is used only to verify the complex stoichiometries, although determination of dissociation constants is also possible. Herein, the binding of a 1,3,5-substituted 2,4,6-triethylbenzene-based receptor (CHR) to four alkyl-β-d-glucosides with varying alkyl side chain lengths (methyl (MGP), hexyl (HGP), octyl (OGP), and dodecyl (DGP)-β-d-glucosides), which was analyzed by ESI Fourier transform ion cyclotron resonance mass spectrometry (ESI-FT-ICR-MS) under optimized spray conditions in both ion modes, is reported. The complexes of the receptor with different sugars could be detected in 1:1 and 2:1 stoichiometries. Dissociation constants calculated for the 1:1 complexes showed a stability trend depending on the length of the alkyl side chain of the sugar: CHR:DGP > CHR:OGP > CHR:HGP > CHR:MGP. Gas phase stabilities determined by CID-MS confirm this relative trend in binding affinities. These findings substantiate the validity and applicability of ESI-MS as a method for investigating noncovalent complex stabilities and thus support research in the field of molecular recognition of carbohydrates by artificial receptors.

AI-driven prediction of SARS-CoV-2 variant binding trends from atomistic simulations

We present a novel technique to predict binding affinity trends between two molecules from atomistic molecular dynamics simulations. The technique uses a neural network algorithm applied to a series of images encoding the distance between two molecules in time. We demonstrate that our algorithm is capable of separating with high accuracy non-hydrophobic mutations with low binding affinity from those with high binding affinity. Moreover, we show high accuracy in prediction using a small subset of the simulation, therefore requiring a much shorter simulation time. We apply our algorithm to the binding between several variants of the SARS-CoV-2 spike protein and the human receptor ACE2.Graphic abstract

Modeling Kinetics and Thermodynamics of Guest Encapsulation into the [M4L6]12- Supramolecular Organometallic Cage.

The encapsulation of molecular guests into supramolecular hosts is a complex molecular recognition process in which the guest displaces the solvent from the host cavity, while the host deforms to let the guest in. An atomistic description of the association would provide valuable insights on the physicochemical properties that guide it. This understanding may be used to design novel host assemblies with improved properties (i.e., affinities) toward a given class of guests. Molecular simulations may be conveniently used to model the association processes. It is thus of interest to establish efficient protocols to trace the encapsulation process and to predict the associated magnitudes ΔGbind and ΔGbind⧧. Here, we report the calculation of the Gibbs energy barrier and Gibbs binding energy by means of explicit solvent molecular simulations for the [Ga4L6]12– metallocage encapsulating a series of cationic molecules. The ΔGbind⧧ for encapsulation was estimated by means of umbrella sampling simulations. The steps involved were identified, including ion-pair formation and naphthalene rotation (from L ligands of the metallocage) during the guest’s entrance. The ΔGbind values were computed using the attach–pull–release method. The results reveal the sensitivity of the estimates on the force field parameters, in particular on atomic charges, showing that higher accuracy is obtained when charges are derived from implicit solvent quantum chemical calculations. Correlation analysis identified some indicators for the binding affinity trends. All computed magnitudes are in very good agreement with experimental observations. This work provides, on one side, a benchmarked way to computationally model a highly charged metallocage encapsulation process. This includes a nonstandard parameterization and charge derivation procedure. On the other hand, it gives specific mechanistic information on the binding processes of [Ga4L6]12– at the molecular level where key motions are depicted. Taken together, the study provides an interesting option for the future design of metal–organic cages.

Toward Reducing hERG Affinities for DAT Inhibitors with a Combined Machine Learning and Molecular Modeling Approach.

Psychostimulant drugs, such as cocaine, inhibit dopamine reuptake via blockading the dopamine transporter (DAT), which is the primary mechanism underpinning their abuse. Atypical DAT inhibitors are dissimilar to cocaine and can block cocaine- or methamphetamine-induced behaviors, supporting their development as part of a treatment regimen for psychostimulant use disorders. When developing these atypical DAT inhibitors as medications, it is necessary to avoid off-target binding that can produce unwanted side effects or toxicities. In particular, the blockade of a potassium channel, human ether-a-go-go (hERG), can lead to potentially lethal ventricular tachycardia. In this study, we established a counter screening platform for DAT and against hERG binding by combining machine learning-based quantitative structure-activity relationship (QSAR) modeling, experimental validation, and molecular modeling and simulations. Our results show that the available data are adequate to establish robust QSAR models, as validated by chemical synthesis and pharmacological evaluation of a validation set of DAT inhibitors. Furthermore, the QSAR models based on subsets of the data according to experimental approaches used have predictive power as well, which opens the door to target specific functional states of a protein. Complementarily, our molecular modeling and simulations identified the structural elements responsible for a pair of DAT inhibitors having opposite binding affinity trends at DAT and hERG, which can be leveraged for rational optimization of lead atypical DAT inhibitors with desired pharmacological properties.

Modelling peptide adsorption energies on gold surfaces with an effective implicit solvent and surface model

The interaction of proteins and peptides with inorganic surfaces is relevant in a wide array of technological applications. A rational approach to design peptides for specific surfaces would build on amino-acid and surface specific interaction models, which are difficult to characterize experimentally or by modeling. Even with such a model at hand, the large number of possible sequences and the large conformation space of peptides make comparative simulations challenging. Here we present a computational protocol, the effective implicit surface model (EISM), for efficient in silico evaluation of the binding affinity trends of peptides on parameterized surface, with a specific application to the widely studied gold surface. In EISM the peptide surface interactions are modeled with an amino-acid and surface specific implicit solvent model, which permits rapid exploration of the peptide conformational degrees of freedom. We demonstrate the parametrization of the model and compare the results with all-atom simulations and experimental results for specific peptides.

Polymeric Membrane Electrodes Using Calix[4]pyrrole Bis/Tetra-Phosphonate Cavitands as Ionophores for Potentiometric Acetylcholine Sensing with High Selectivity.

A handful of bis/tetra-phosphonate calix[4]pyrroles with recognition sites embedding in hydrophobic cavitands were evaluated for the first time as ionophores for polymeric membrane Ach+-selective electrodes. Highly selective potentiometric Ach+ could be achieved over its analogues, especially for Ch+, which differs only by an acetate tail from Ach+. The superior performance of the proposed ISEs might be ascribed to a dual-site binding mode, in which the trimethylammonium head and acetate tail were accommodated by the phosphonate group-bridged aryl walls and the bowl-shaped aromatic cavity, through cation-π/charge-dipole interaction and the convergent four N-H···O hydrogen bonds, respectively. To gain more insight into the performance of the proposed ISEs, the cation-ionophore complex constants in the membrane phase were determined, and the binding affinity trend correlates well with the selectivity pattern. These results suggest that conformational preorganization of the ionophores and complementary weak interactions do change the selectivity of the ionophores. Studies on the influence of the sample solution pH demonstrated that the developed ISEs can be employed in a wide pH range of 4.0-9.6 with a fast response (<60 s), good reversibility, and long lifetime. Optimizing the membrane components, such as ionophores, lipophilic additives, and plasticizers, yielded ISEs, showing Nernstian responses to Ach+ with improved linear ranges and detection limits (a slope of -59.5 mV/dec in the linear range of 1 × 10-6-1 × 10-2 M with a detection limit of 3 × 10-7 M), which led to the success of the determination of Ach+ in spiked urine and milk samples.

Binding Capacity and Selectivity of Functionalized and Un-functionalized Carbon Nanotubes for Development of Copper-Detecting Printable Sensor.

Carbon nanotubes (CNTs) have unique properties which can be modified through surface functionalization. The ability of several functionalized and un-functionalized CNTs to bind copper was investigated as a first step toward developing a printable CNT-based sensor to detect copper in aqueous systems. Binding capacity and specificity were shown to vary by functionalization and vendor. CNTs from two vendors were tested, and the equilibrium binding data was fitted using two isotherm models. Calculated qmax (mg/g) values indicated one vendor's carboxyl-functionalized CNTs had the greatest binding capacity (94-115mg/g), while other carboxyl-functionalized CNTs and amine-functionalized CNTs had similar capacities to un-functionalized CNTs (15-30mg/g). Hydroxyl-functionalized CNTs had the lowest copper binding capacity (7-8mg/g) of the CNTs tested. Freundlich isotherms showed no obvious trends in binding affinity, but suggested that binding was primarily due to chemisorption. Variations in CNT size, functionalization percentage, and purity could explain, partially, the observed adsorption differences.

The influence of biotinylation on the ability of a computer designed protein to detect B-cells producing anti-HIV-1 2F5 antibodies

Antibodies against the HIV-1 2F5 epitope are known as one of the most powerful and broadly protective anti-HIV antibodies. Therefore, vaccine strategies that include the 2F5 epitope in their formulation require a robust method to detect specific anti-2F5 antibody production by B cells. Towards this goal, we have biotinylated a previously reported computer-designed protein carrying the HIV-1 2F5 epitope aiming the further development of a platform to detect human B-cells expressing anti-2F5 antibodies through flow cytometry. Biophysical and immunological properties of our devised protein were characterized by computer simulation and experimental methods. Biotinylation did not affect folding and improved protein stability and solubility. The biotinylated protein exhibited similar binding affinity trends compared to its unbiotinylated counterpart and was recognized by anti-HIV-1 2F5 antibodies expressed on the surface of patient-derived peripheral blood mononuclear cells. Moreover, we present a high affinity marker for the identification of epitope-specific B cells that can be used to measure the efficacy of vaccine strategies based on the HIV-1 envelope protein.

Electrospray Ionisation Mass Spectrometric (ESI MS) Screening and Characterisation of Beryllium Complexes with Potentially Encapsulating Aminopolycarboxylate and Related Ligands

A fundamental issue in beryllium research is the search for suitable chelating ligands for environmental and biomedical application. In this paper, the speciation of beryllium ions with several multidentate aminopolycarboxylic acids, which are well‐known commercial and biomedical chelating agents, has been investigated using electrospray ionisation mass spectrometry (ESI MS). Stoichiometric information, which was readily obtained from the ESI mass spectra, was found to be effective for the preliminary screening of potential encapsulation by tetradentate coordination from a single ligand. Ions observed by ESI MS revealed that the pre‐existing solution species and binding affinity trends were preserved into the gas phase in good agreement with previous solution speciation data, suggesting the ability of ESI MS to be developed as a quick, sensitive and safe screening technique to observe beryllium speciation with ligands of interest at low concentrations. The disruption of beryllium‐ligand binding by addition of other di‐ or trivalent metal cations is also reported.

Computational Study of Butyrylcholinesterase Inhibition by Aryl Alkyl Cholinyl Phosphorus Derivatives

Acetylcholine (ACh) is a neurotransmitter that is released from nerve cells to send signals to other cells, and acetylcholinesterase (AChE) is a highly specific enzyme that hydrolyzes ACh to regulate intercellular communication. However, butyrylcholinesterase (BChE), a non-specific AChE imposter, also breaks down choline based esters such as ACh. The activity of BChE has been found to gradually increase over time in patients with Alzheimer's disease (AD), which has been linked to a significant decrease in synaptic ACh levels, thus disrupting intercellular communication. In the treatment of AD, discovering inhibitors that prevent the activity of BChE and that do not interfere with the activity of AChE is vital. Aryl alkyl cholinyl phosphorous (AACP) derivatives are organophosphates that are expected to reversibly bind within the BChE binding pocket in the same manner as natural physiological substrates. This study utilizes massive flexible inhibitor docking calculations to predict the relative binding affinities between the enzyme and a number of AACP derivatives and to predict the optimal binding orientation(s) of each AACP derivative within the BChE active site. When compared to their previously studied dialkyl phenyl phosphate (DAPP) analogs, AACP derivatives are predicted to interact more strongly with the binding site of BChE, thus serving as more potent inhibitors. Our results reproduce experimental trends in binding affinity, indicating that derivatives with longer alkyl chains show increased inhibitory strength (as observed for DAPP derivatives), and the neutralization of the charge of the choline group and protonation of the neutral choline group had little effect on inhibitor strength, offering insight into the structural preferences of BChE for specific AACP derivatives. This study thus provides a framework for both future inhibitor design and more rigorous molecular dynamics studies of cholinesterase-inhibitor interaction.

Unravelling the mechanistic details of metal binding to mammalian metallothioneins from stoichiometric, kinetic, and binding affinity data.

Metallothioneins (MTs) are small, cysteine-rich proteins, found throughout Nature. Their ability to bind a number of different metals with a range of stoichiometric ratios means that this protein family is critically important for essential metal (Zn2+ and Cu+) homeostasis, metal storage, metal donation to nascent metalloenzymes as well as heavy metal detoxification. With its 20 cysteines, metallothionein is also considered to protect cells against oxidative stress. MT has been studied by a large number of researchers over the last 6 decades using a variety of spectroscopic techniques. The lack of distinguishing chromophores for the multitude of binding sites has made the evaluation of stoichiometric properties for different metals challenging. Initially, only 113Cd-NMR spectroscopy could provide strong evidence for the proposed cluster formation of Cd-MT. The extraordinary development of electrospray ionization mass spectrometry (ESI-MS), where all coexisting species in solution are observed, revolutionized MT research. Prior to the use of ESI-MS data, a range of "magic numbers" representing metal-to-MT molar ratios were reported from optical spectroscopic studies. The availability of ESI mass spectral data led to (i) the confirmation of cluster formation, (ii) a conceptual understanding of the cooperativity involved in multiple metal binding events, (iii) the presence of domain specificity between regions of the protein and (iv) mechanistic details involving both binding affinities and rate constants. The kinetic experiments identified the presence of multiple individual binding sites, each with a unique rate constant and an analogous binding affinity. The almost linear trend in rate constants as a function of bound As3+ provided a unique insight that became a critical step in the complete understanding of the mechanistic details of the metalation of MT. To fully define the biological function of this sulfur-rich protein it is necessary to determine kinetic rate constants and binding affinities for the essential metals. Recently, Zn2+ competition experiments between both of the isolated fragments (α and β) and the full-length protein (βα-MT 1a) as well as Zn2+ competition between βα-MT 1a and carbonic anhydrase were reported. From these data, the trend in binding affinities and the values of the Kf of the 7 bimolecular reactions involved in metalation were determined. From the analysis of ESI-MS data for Cu+ binding to βα-MT 1a at different pH-values, a trend in the 20 binding affinities for the complete metalation mechanism was reported. This review details a personal view of the historical development of the determination of stoichiometry for metal binding, the structure of the binding sites, the rates of the metalation reactions and the underlying binding affinities for each metalation step. We have attempted to summarize the experimental developments that led to the publication in May 2017 of the experimental determination of the 20 binding constants for the 20 sequential bimolecular reactions for Cu+ binding to the 20 Cys of apoMT as a function of pH that show the appearance and disappearance of clusters. We report both published data and in a series of tables an assembly of stoichiometries, and equilibrium constants for Zn2+ and Cu+ for many different metallothioneins.

Chemical Editing of Macrocyclic Natural Products and Kinetic Profiling Reveal Slow, Tight-Binding Histone Deacetylase Inhibitors with Picomolar Affinities.

Histone deacetylases (HDACs) are validated targets for treatment of certain cancer types and play numerous regulatory roles in biology, ranging from epigenetics to metabolism. Small molecules are highly important as tool compounds for probing these mechanisms as well as for the development of new medicines. Therefore, detailed mechanistic information and precise characterization of the chemical probes used to investigate the effects of HDAC enzymes are vital. We interrogated Nature's arsenal of macrocyclic nonribosomal peptide HDAC inhibitors by chemical synthesis and evaluation of more than 30 natural products and analogues. This furnished surprising trends in binding affinities for the various macrocycles, which were then exploited for the design of highly potent class I and IIb HDAC inhibitors. Furthermore, thorough kinetic investigation revealed unexpected inhibitory mechanisms of important tool compounds as well as the approved drug Istodax (romidepsin). This work provides novel inhibitors with varying potencies, selectivity profiles, and mechanisms of inhibition and, importantly, affords insight into known tool compounds that will improve the interpretation of their effects in biology and medicine.

Mercaptobenzoheterocyclic compounds functionalized silver nanoparticle, an ultrasensitive colorimetric probe for Hg(II) detection in water with picomolar precision: A correlation between sensitivity and binding affinity

Toxic heavy metal ions, specially Hg(II) pose lethal threat to the environment and human beings. To this end, there is a strong need to establish a simple, inexpensive method for the detection of Hg(II) ions with high selectivity and sensitivity in aqueous medium. Herein, we report an ultra-sensitive colorimetric detection of Hg(II) ions following a simple protocol by synthesizing silver nanoparticles functionalized with mercaptobenzoheterocyclic compounds (viz. mercaptobenzooxazole (MBO), mercaptobenzoimidazole (MBI) and mercaptobenzothiazole (MBT). These nanoparticles are found to show a limit of detection (LOD) of 1.8ppt (9.2pM), 9.2ppt (46pM) and 18.4ppt (92pM) for MBO, MBI and MBT respectively). In addition, the binding affinity trend of the mercaptobenzoheterocyclic ligands seems to be in tune with the observed sensitivity trait of Hg2+ sensing.

Molecular Modeling of the Interactions between Carborane-Containing Analogs of Indomethacin and Cyclooxygenase-2.

Molecular modeling studies were performed in order to gain insight into the binding mode and interaction of carborane-containing derivatives of indomethacin methyl ester with the cyclooxygenase-2 (COX-2) isoform, and to assess the predictive capability of the computational tools available for studying carboranes, a unique class of pharmacophores. Docking simulations were able to identify the correct binding mode and reproduced the experimental binding affinity trends with encouraging quality. Nevertheless, the docking results needed to be verified through extensive and resource-intensive quantum chemical calculations, and the interpretation of the theoretical results would not have been straightforward without the supporting experimental data. The inclusion of full receptor and ligand flexibility into the molecular modeling of carborane-containing drug molecules may yield more definitive results, but is currently hindered by the lack of appropriate carborane force field parameters.

Monitoring interfacial lectin binding with nanomolar sensitivity using a plasmon field effect transistor

By immobilizing glycopolymers onto the surface of the recently developed plasmonic field effect transistor (FET), the recognition between lectins and surface-immobilized glycopolymers can be detected over a wide dynamic range (10-10 to 10-4 M) in an environment that resembles the glycocalyx. The binding to the sensor surface by various lectins was tested, and the selectivities and relative binding affinity trends observed in solution were maintained on the sensor surface, and the significantly higher avidities are attributed to cluster-glycoside effects that occur on the surface. The combination of polymer surface chemistry and optoelectronic output in this device architecture produces amongst the highest reported detection sensitivity for ConA. This work demonstrates the benefits that arise from combining emerging device architectures and soft-matter systems to create cutting edge nanotechnologies that lend themselves to fundamental biological studies and integration into point-of-use diagnostics and sensors.

Iodide Recognition and Sensing in Water by a Halogen-Bonding Ruthenium(II)-Based Rotaxane.

The synthesis and anion‐recognition properties of the first halogen‐bonding rotaxane host to sense anions in water is described. The rotaxane features a halogen‐bonding axle component, which is stoppered with water‐solubilizing permethylated β‐cyclodextrin motifs, and a luminescent tris(bipyridine)ruthenium(II)‐based macrocycle component. 1H NMR anion‐binding titrations in D2O reveal the halogen‐bonding rotaxane to bind iodide with high affinity and with selectively over the smaller halide anions and sulfate. The binding affinity trend was explained through molecular dynamics simulations and free‐energy calculations. Photo‐physical investigations demonstrate the ability of the interlocked halogen‐bonding host to sense iodide in water, through enhancement of the macrocycle component’s RuII metal–ligand charge transfer (MLCT) emission.

Comprehensive Benchmark of Association (Free) Energies of Realistic Host-Guest Complexes.

The S12L test set for supramolecular Gibbs free energies of association ΔGa (Grimme, S. Chem. Eur. J. 2012, 18, 9955-9964) is extended to 30 complexes (S30L), featuring more diverse interaction motifs, anions, and higher charges (-1 up to +4) as well as larger systems with up to 200 atoms. Various typical noncovalent interactions like hydrogen and halogen bonding, π-π stacking, nonpolar dispersion, and CH-π and cation-dipolar interactions are represented by "real" complexes. The experimental Gibbs free energies of association (ΔGa exp) cover a wide range from -0.7 to -24.7 kcal mol-1. In order to obtain a theoretical best estimate for ΔGa, we test various dispersion corrected density functionals in combination with quadruple-ζ basis sets for calculating the association energies in the gas phase. Further, modern semiempirical methods are employed to obtain the thermostatistical corrections from energy to Gibbs free energy, and the COSMO-RS model with several parametrizations as well as the SMD model are used to include solvation contributions. We investigate the effect of including counterions for the charged systems (S30L-CI), which is found to overall improve the results. Our best method combination consists of PW6B95-D3 (for neutral and charged systems) or ωB97X-D3 (for systems with counterions) energies, HF-3c thermostatistical corrections, and Gibbs free energies of solvation obtained with the COSMO-RS 2012 parameters for nonpolar solvents and 2013-fine for water. This combination gives a mean absolute deviation for ΔGa of only 2.4 kcal mol-1 (S30L) and 2.1 kcal mol-1 (S30L-CI), with a mean deviation of almost zero compared to experiment. Regarding the relative Gibbs free energies of association for the 13 pairs of complexes which share the same host, the correct trend in binding affinities could be reproduced except for two cases. The MAD compared to experiment amounts to 1.2 kcal mol-1, and the MD is almost zero. The best-estimate theoretical corrections are used to back-correct the experimental ΔGa values in order to get an empirical estimate for the "experimental", zero-point vibrational energy exclusive, gas phase binding energies. These are then utilized to benchmark the performance of various "lowcost" quantum chemical methods for noncovalent interactions in large systems. The performance of other common DFT methods as well as the use of semiempirical methods for structure optimizations is discussed.

QM-polarized ligand docking accurately predicts the trend in binding affinity of a series of arylmethylene quinuclidine-like derivatives at the α4β2 and α3β4 nicotinic acetylcholine receptors (nAChRs)

Compounds containing a quinuclidine scaffold are promising drug candidates for pharmacological management of the central nervous system (CNS) pathologies implicating nAChRs. We have carried out binding affinity and in-silico docking studies of arylmethylene quinuclidine-like derivatives at the α4β2 receptor using in-vitro receptor binding assay and comparative modeling, respectively. We found that introducing a hydrogen-bond acceptor into the 3-benzylidene quinuclidine derivative resulted in a 266-fold increase in binding affinity and confers agonism properties. By contrast, addition of a phenyl group to 3-benzylidene quinuclidine derivative only results in an 18-fold increase in binding affinity, without conferring agonism. We also found that docking into the orthosteric binding site of the α4β2 nAChR is consistent with the fact that the basic nitrogen atom donates a hydrogen-bond to the carbonyl group of the highly conserved Trp-149, as initially observed by Dougherty and co-workers.1 The experimentally-observed trend in binding affinity at both α4β2 and α3β4 nAChRs was accurately and independently confirmed by quantum mechanics (QM)-polarized docking. The reduction in binding affinity to the α3β4 subtype primarily results from a dampening of both coulombic and cation–π interactions.

Metal Cation Dependence of Interactions with Amino Acids: Bond Energies of Rb+ and Cs+ to Met, Phe, Tyr, and Trp

The interactions of rubidium and cesium cations with four amino acids (AA) including methionine (Met), phenylalanine (Phe), tyrosine (Tyr), and tryptophan (Trp) are examined in detail. Experimentally, the bond dissociation energies (BDEs) are determined using threshold collision-induced dissociation of the Rb(+)(AA) and Cs(+)(AA) complexes with xenon in a guided ion beam tandem mass spectrometer. Analyses of the energy dependent cross sections include consideration of unimolecular decay rates, internal energy of the reactant ions, and multiple ion-neutral collisions. 0 K BDEs of 121.0 ± 7.0 (102.8 ± 6.6), 123.8 ± 7.2 (112.9 ± 5.5), 125.8 ± 7.4 (115.6 ± 6.9), and 138.1 ± 7.5 (125.0 ± 6.8) kJ/mol are determined for complexes of Rb(+) (Cs(+)) with Met, Phe, Tyr, and Trp, respectively. Quantum chemical calculations are conducted at the B3LYP, MP2(full), and M06 levels of theory with geometries and zero point energies calculated at the B3LYP level using def2-TZVPPD basis sets. Results obtained using all three levels show good agreement with experiment, with B3LYP values being systematically low and MP2(full) and M06 values being systematically high. At 0 and 298 K, theory predicts the ground-state conformers for M(+)(Met) either have tridentate binding of the metal cation to the carbonyl, amino, and sulfur groups (MP2 and M06) or to both oxygens of a zwitterionic conformation (B3LYP). At 298 K, binding to the carboxylic acid group and the sulfur also becomes competitive. For the aromatic amino acids at 0 K, most levels of theory favor tridentate binding of the metal ions to the backbone carbonyl and amino groups along with the π-cloud of the ring, whereas for Rb(+)(Trp) and Cs(+)(AA), B3LYP theory favors binding to only the carbonyl and ring groups. At 298 K, B3LYP favors the latter binding mode for all three Rb(+)(aromatic AA) complexes. Comparison of these results to those for the smaller alkali cations provides insight into the trends in binding affinities and structures associated with metal cation variations.