Experimental Dissociation Research Articles

Kinetics and Dynamics of Cyclopentanone Thermal Decomposition in Gas Phase.

Cyclopentanone is a potential bio-fuel which can be produced from bio-mass. Its gas phase dissociation chemistry has attracted several experimental and theoretical investigations. In the photochemical and thermal decomposition studies of cyclopentanone, ethylene and carbon monoxide were found to be dominant reaction products along with several other compounds in smaller quantities. For the formation of ethylene and carbon monoxide, a concerted mechanism has been proposed as primary reaction pathway. In addition, a step-wise mechanism involving ring-opened radical intermediate has also been considered. The present work reports gas phase thermal decomposition of cyclopentanone at high temperatures investigated using electronic structure theory methods, Rice-Ramsperger-Kassel-Marcus (RRKM) rate constant calculations, and Born-Oppenheimer direct classical trajectory simulations. The trajectory calculations were performed on density functional PBE96/6-31+G* potential energy surface using initial conditions selected from fixed energy normal mode distributions. Simulations showed that ethylene and carbon monoxide formed primarily via the concerted mechanism confirming the earlier predictions. In addition, stepwise pathways were also observed for same products in lower fraction of trajectories. Furthermore, several other reaction products in smaller quantities and new mechanistic pathways were observed. The computed RRKM rate constants and simulation data are agreement with experimental results and detailed atomic level dissociation mechanisms presented.

Critical dynamics in spontaneous EEG predict anesthetic-induced loss of consciousness and perturbational complexity

Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigate dynamical properties of the resting-state electroencephalogram (EEG) of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. Importantly, all participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams), enabling an experimental dissociation between unresponsiveness and unconsciousness. For each condition, we measure (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related metrics, revealing that states of unconsciousness are characterized by a distancing from both avalanche criticality and the edge of chaos. We then ask whether these same dynamical properties are predictive of the perturbational complexity index (PCI), a TMS-based measure that has shown remarkably high sensitivity in detecting consciousness independently of behavior. We successfully predict individual subjects’ PCI values with considerably high accuracy from resting-state EEG dynamical properties alone. Our results establish a firm link between perturbational complexity and criticality, and provide further evidence that criticality is a necessary condition for the emergence of consciousness.

Navigating the complexities of docking tools with nicotinic receptors and acetylcholine binding proteins in the realm of neonicotinoids

Molecular docking, pivotal in predicting small-molecule ligand binding modes, struggles with accurately identifying binding conformations and affinities. This is particularly true for neonicotinoids, insecticides whose impacts on ecosystems require precise molecular interaction modeling. This study scrutinizes the effectiveness of prominent docking software (Ledock, ADFR, Autodock Vina, CDOCKER) in simulating interactions of environmental chemicals, especially neonicotinoid-like molecules with nicotinic acetylcholine receptors (nAChRs) and acetylcholine binding proteins (AChBPs). We aimed to assess the accuracy and reliability of these tools in reproducing crystallographic data, focusing on semi-flexible and flexible docking approaches. Our analysis identified Ledock as the most accurate in semi-flexible docking, while Autodock Vina with Vinardo scoring function proved most reliable. However, no software consistently excelled in both accuracy and reliability. Additionally, our evaluation revealed that none of the tools could establish a clear correlation between docking scores and experimental dissociation constants (Kd) for neonicotinoid-like compounds. In contrast, a strong correlation was found with drug-like compounds, bringing to light a bias in considered software towards pharmaceuticals, thus limiting their applicability to environmental chemicals. The comparison between semi-flexible and flexible docking revealed that the increased computational complexity of the latter did not result in enhanced accuracy. In fact, the higher computational cost of flexible docking with its lack of enhanced predictive accuracy, rendered this approach useless for this class of compounds. Conclusively, our findings emphasize the need for continued development of docking methodologies, particularly for environmental chemicals. This study not only illuminates current software capabilities but also underscores the urgency for advancements in computational molecular docking as it is a relevant tool to environmental sciences.

In vitro selection of DNA aptamers against staphylococcal enterotoxin A

Staphylococcal enterotoxin A (SEA) is the most frequently reported in staphylococcal food poisoning (SFP) outbreaks. Aptamers are single-stranded nucleic acids that are seen as promising alternatives to antibodies in several areas, including diagnostics. In this work, systematic evolution of ligands by exponential enrichment (SELEX) was used to select DNA aptamers against SEA. The SELEX protocol employed magnetic beads as an immobilization matrix for the target molecule and real-time quantitative PCR (qPCR) for monitoring and optimizing sequence enrichment. After 10 selection cycles, the ssDNA pool with the highest affinity was sequenced by next generation sequencing (NGS). Approximately 3 million aptamer candidates were identified, and the most representative cluster sequences were selected for further characterization. The aptamer with the highest affinity showed an experimental dissociation constant (KD) of 13.36 ± 18.62 nM. Increased temperature negatively affected the affinity of the aptamer for the target. Application of the selected aptamers in a lateral flow assay demonstrated their functionality in detecting samples containing 100 ng SEA, the minimum amount capable of causing food poisoning. Overall, the applicability of DNA aptamers in SEA recognition was demonstrated and characterized under different conditions, paving the way for the development of diagnostic tools.

Cassini-oval description of atomic binding: New insights into the quantitative relationship between hardness coefficient and bond energy energy.

In this paper, the research hypothesis of conservation of hardness coefficient is put forward, and a mathematical formula for describing and analyzing the relationship between hardness coefficient and bond energy is established in this model. The binding process of two heteronuclear atoms can be represented by Cassini oval in dynamic form, every molecular state corresponds to one of these graphs; then the critical phenomena of molecular deformation are discovered and the calculated potential energy at the critical point is consistent with the experimental dissociation energy of molecules (R is 0.99999, P < 0.0001).

Quantitative Prediction of Dissociation Rates of PYK2 Ligands Using Umbrella Sampling and Milestoning.

We used umbrella sampling and the milestoning simulation method to study the dissociation of multiple ligands from protein kinase PYK2. The activation barriers obtained from the potential of mean force of the umbrella sampling simulations correlated well with the experimental dissociation rates. Using the zero-temperature string method, we obtained optimized paths along the free-energy surfaces for milestoning simulations of three ligands with a similar structure. The milestoning simulations gave an absolute dissociation rate within 2 orders of magnitude of the experimental value for two ligands but at least 3 orders of magnitude too high for the third. Despite the similarity in their structures, the ligands took different pathways to exit from the binding site of PYK2, making contact with different sets of residues. In addition, the protein experienced different conformational changes for dissociation of the three ligands.

A physical organic strategy to predict and interpret stabilities of chemical bonds in energetic compounds for the discovery of thermal-resistant properties.

The in-depth understanding about the stability of chemical bonds in energetic compounds plays a central role for molecular design and safety-related evaluations. Most energetic compounds contain nitro as explosophores, and nitro cleavage is fundamental for thermal and mechanical stability. However, the quantum chemistry approach to accurately predict energy and temperature properties related to bond stability is challenging, due to the tradeoff between computational costs and deviations. Herein, the bond orders are proposed as accurate and computational-cost efficient descriptors for predicting the chemical bond stability and thermal-resistant properties. The intrinsic bond strength index (IBSI) demonstrates the best prediction for experimental homolytic bond dissociation energies (R2 > 0.996), which is on par with the results from high-precision quantum chemistry methods. The effects from bond connectivity and steric hindrance hierarchy were analyzed to reveal underlying mechanisms. Additionally, the IBSI descriptors are successfully applied to predict the thermal decomposition temperatures of 24 heat-resistant energetic compounds (R2 = 0.995), thus validating the effectiveness for the prediction and interpretation of chemical bond stability in energetic compounds via a physical organic approach. All DFT calculations were performed with Gaussian 09 software. To investigate the dependence of the method on functionals and basis sets, 9 DFT methods were considered (B3LYP/6-31G(d,p), B3LYP/6-311G(d,p), B3LYP/def2-TZVP, M062X/6-31G(d,p), M062X/6-311G(d,p), M062X/def2-TZVP, ωB97XD/6-31G(d,p), ωB97XD/6-311G(d,p), and ωB97XD/def2-TZVP). The bond order descriptors LBO and IBSI are obtained through the bond order analysis module in the Multiwfn software.

GradDFT. A software library for machine learning enhanced density functional theory.

Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when dealing with strongly correlated systems. To address these shortcomings, recent work has begun to explore how machine learning can expand the capabilities of DFT: an endeavor with many open questions and technical challenges. In this work, we present GradDFT a fully differentiable JAX-based DFT library, enabling quick prototyping and experimentation with machine learning-enhanced exchange-correlation energy functionals. GradDFT employs a pioneering parametrization of exchange-correlation functionals constructed using a weighted sum of energy densities, where the weights are determined using neural networks. Moreover, GradDFT encompasses a comprehensive suite of auxiliary functions, notably featuring a just-in-time compilable and fully differentiable self-consistent iterative procedure. To support training and benchmarking efforts, we additionally compile a curated dataset of experimental dissociation energies of dimers, half of which contain transition metal atoms characterized by strong electronic correlations. The software library is tested against experimental results to study the generalization capabilities of a neural functional across potential energy surfaces and atomic species, as well as the effect of training data noise on the resulting model accuracy.

A generalized interface reaction kinetic model for describing heterogeneous processes driven by contracting mechanisms

The correct determination of the kinetic model and the kinetic parameters that describe a heterogeneous process is key to accurately predicting its progress within a wide range of conditions, which is one of the main purposes of kinetic analysis. Albeit ideal kinetic models continue to be used to gain insight about the process mechanism, they are constrained by certain assumptions that are rarely met in real experiments and limit their applicability. This is the case of contracting (or interface) kinetic models, which are one of the most commonly used. Thus, the ideal kinetic model R2 is derived by assuming a cylindrical contraction in the radial direction but not contemplating the possibility of a contraction in the direction of the axis of the cylinder. Moreover, in the case of the ideal model R3, it is assumed that contraction takes place simultaneously in particles of identical dimensions in all three directions of space (spheres or cubes). Here, it is revisited this type of model, and it is considered the contraction of particles with different geometries, namely cylinders with different aspect ratios and rectangular cuboids. Besides, a novel generalized interface reaction model is proposed, which covers all the studied cases and broadens the range of applicability to more complex situations involving different geometries and inhomogeneous particle sizes. Finally, the proposed model is applied to the analysis of the experimental thermal dissociation of ammonium nitrate, previously described in the literature as a sublimation process. It is proved that the novel kinetic model provides a more accurate description of the kinetics of the reaction and better prediction capabilities.

Semiempirical molecular-orbital calculations of dissociation energies of small molecules containing light elements

A semiempirical molecular-orbital approach has been developed to calculate the dissociation energies of 57 second-row neutral and charged diatomic molecules. One-electron energies and wave functions were used. The 2s and 2p electrons have separate energies and separate values of Z 2S and Z 2P . Calculations were made with a CNDO/INDO FORTRAN programme modified to a level of approximation that is more similar to extended Hückel calculations than to either CNDO or INDO. The correlation between calculated and experimental dissociation energies was favourable with a relative standard deviation of 15%. Additionally, dipole moments for the molecules were calculated concurrently with the same parameters. The correlation between calculated and experimental dipole moments was favourable for seventeen molecules with a relative standard deviation of 19%. The correlation between calculated and experimental ionisation potentials for fourteen molecules was also favourable with a relative standard deviation of 11%. Also, a repulsion work function was formulated and used in this work between pairs of atoms. For 90% of the molecules studied, the maximum calculated dissociation energy occurred within ±0.1 Å of the experimental bond distance. The semiempirical methods used in the present work could be used for future studies of larger molecules, including organic molecules.

A closer look at amyloid ligands, and what they tell us about protein aggregates.

The accumulation of amyloid fibrils is characteristic of neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease. Detecting these fibrils with fluorescent or radiolabelled ligands is one strategy for diagnosing and better understanding these diseases. A vast number of amyloid-binding ligands have been reported in the literature as a result. To obtain a better understanding of how amyloid ligands bind, we have compiled a database of 3457 experimental dissociation constants for 2076 unique amyloid-binding ligands. These ligands target Aβ, tau, or αSyn fibrils, as well as relevant biological samples including AD brain homogenates. From this database significant variation in the reported dissociation constants of ligands was found, possibly due to differences in the morphology of the fibrils being studied. Ligands were also found to bind to Aβ(1-40) and Aβ(1-42) fibrils with similar affinities, whereas a greater difference was found for binding to Aβ and tau or αSyn fibrils. Next, the binding of ligands to fibrils was shown to be largely limited by the hydrophobic effect. Some Aβ ligands do not fit into this hydrophobicity-limited model, suggesting that polar interactions can play an important role when binding to this target. Finally several binding site models were outlined for amyloid fibrils that describe what ligands target what binding sites. These models provide a foundation for interpreting and designing site-specific binding assays.

Experimental measurements and thermodynamic modeling of hydrate dissociation conditions for CO2 + THF + MgCl2 + water systems

• Experimental hydrate dissociation conditions for (CO2 + THF + MgCl2 + Water) system are reported. • A thermodynamic model has been developed and its results are in acceptable agreement with the experimental data. • The addition of low-medium concentration THF to the system has a promotion effect. • The addition of MgCl2 has an inhibition effect In this study, experimental and thermodynamic modeling on hydrate dissociation conditions of CO 2 + water systems in the absence/presence of MgCl 2 + THF aqueous solutions at various concentrations were investigated. The ternary systems, including different aqueous solutions of tetrahydrofuran and magnesium chloride (0.05 mass fraction of MgCl 2 , 0.05 mass fraction of THF: solution A; 0.15 mass fraction of MgCl 2 , 0.05 mass fraction of THF: solution B; 0.05 mass fraction of MgCl 2 , 0.20 mass fraction of THF: solution C; 0.15 mass fraction of MgCl 2 , 0.20 mass fraction of THF: solution D) were conducted in the temperature range between 280.9 to 292.9 K and pressure ranges 0.92 to 3.89 MPa. An isochoric pressure–search method was applied to undertake all measurements. The results demonstrated that MgCl 2 acts as an inhibitor in all experiments, while THF acts as a promoter. Comparing mentioned data with the same system in the absence of MgCl 2 , a shift is observed toward the left in the equilibrium curve that this kind of shifting left is more observable at high pressures. In addition, a thermodynamic model was developed utilizing the Peng-Robinson equation of state with classical mixing rules and the UNIQUAC activity coefficient model to predict the equilibrium conditions of the aforementioned system. The model results implied a reasonable agreement with the experimental dissociation data with an average absolute deviation of pressure below 0.3%.

Probing protein misfolding and dissociation with an infrared free-electron laser.

Misfolding is observed in the mutant proteins that are causative for neurodegenerative disorders such as polyglutamine diseases. These proteins are prone to aggregate in the cytoplasm and nucleus of cells. To reproduce cells with the aggregated proteins, gene expression system is usually applied, in which the expression construct having the mutated DNA sequence of the interest is transfected into cells. The transfected DNA is finally converted into the mutant protein, which is gradually aggregated in the cells. In addition, a simple method to prepare the cells having aggregates inside has been recently applied. Peptides were first aggregated by incubating them in water. The aggregates are spontaneously taken up by cells because aggregated proteins generally transfer between cells. Peptides with different degrees of aggregation can be made by changing the incubation times and temperatures, which enables to examine contribution of aggregation to the toxicity to the recipient cells. Moreover, such cells can be used for therapeutic researches of diseases in which aggregates are involved. In this chapter, we show methods to induce aggregation of peptides. The functional analyses of the cells with aggregates are also described. Then, experimental dissociation of the aggregates produced using this method by mid infrared free electron laser irradiation and its theoretical support by molecular dynamics simulation are introduced as the therapeutic research for neurodegenerative disorders.

Threshold photoelectron spectroscopy and dissociative photoionization of benzonitrile.

The threshold photoionization and dissociative ionization of benzonitrile (C6H5CN) were studied using double imaging photoelectron photoion coincidence (i2PEPICO) spectroscopy at the Vacuum Ultraviolet (VUV) beamline of the Swiss Light Source (SLS). The threshold photoelectron spectrum was recorded from 9.6 to 12.7 eV and Franck-Condon simulations of ionization into the ionic ground state, X̃+, as well as the B̃+ and C̃+ states were performed to assign the observed vibronic structures. The adiabatic ionization energies of the X̃+, B̃+ and C̃+ states are determined to be (9.72 ± 0.02), (11.85 ± 0.03) and, tentatively, (12.07 ± 0.04) eV, respectively. Threshold ionization mass spectra were recorded from 13.75 to 19.75 eV and the breakdown diagram was constructed by plotting the fractional abundances of the parent ion and ionic dissociation products as a function of photon energy. The seven lowest energy dissociative photoionization channels of benzonitrile were found to yield CN˙ + c-C6H5+, HCN + C6H4˙+, C2H4 + HC5N˙+, HC3N + C4H4˙+, H2C3N˙ + C4H3+, CH2CHCN + C4H2˙+ and H2C4N˙ + c-C3H3+. HCN loss from the benzonitrile cation is the dominant dissociation channel from the dissociation onset of up to 18.1 eV and CH2CHCN loss becomes dominant from 18.1 eV and up. We present extensive potential energy surface calculations on the C6H5CN˙+ surface to rationalize the detected products. The breakdown diagram and time-of-flight mass spectra are fitted using a Rice-Ramsperger-Kassel-Marcus statistical model. Anchoring the fit to the CBS-QB3 result (3.42 eV) for the barrier to HCN loss, we obtained experimental dissociation barriers for the products of 4.30 eV (CN loss), 5.53 eV (C2H4 loss), 4.33 eV (HC3N loss), 5.15 eV (H2C3N loss), 4.93 eV (CH2CHCN loss) and 4.41 eV (H2C4N loss). We compare our work to studies of the electron-induced dissociative ionization of benzonitrile and isoelectronic phenylacetylene (C8H6), as well as the VUV-induced dissociation of protonated benzonitrile (C6H5CNH+). Also, we discuss the potential role of barrierless association reactions found for some of the identified fragments as a source of benzonitrile(˙+) in interstellar chemistry and in Titan's atmosphere.

The kihara potential function parameters of methane, ethane, propane, and i-butane: The effects on clathrate hydrate structure determination

Gas hydrates, or clathrate hydrates, are solid crystalline compounds, which are formed by combination of water and gas and/or some volatile liquid molecules. Prediction of hydrate stability/dissociation/equilibrium conditions of natural gases is important in separation processes, gas storage, and in preventing blockage of gas transmission pipelines. In this study, initially, the different sets of the Kihara Potential Function Parameters, KPFP, reported in the literature were used to predict the experimental hydrate dissociation conditions of methane, ethane, propane and i-butane and mixtures of these four compounds. In most cases, however, based on these sets of KPFP, the hydrate structure cannot be predicted correctly. Consequently due to incorrect estimation of the hydrate structure, especially for natural gas mixture, the predicted hydrate dissociation conditions are found inaccurate. For overcoming this fault and by using a genetic algorithm, a new set of KPFP were optimized based on the new definition of the objective function considering hydrate structure. The results show good agreement with experimental data, both in the prediction of hydrate dissociation conditions and hydrate structure.

The quantum dynamics of H2 on Cu(111) at a surface temperature of 925K: Comparing state-of-the-art theory to state-of-the-art experiments.

We present results of our recently expanded static corrugation model (SCM) approach that included the relevant surface temperature effects, applied to the dissociative chemisorption reaction of H2 on a Cu(111) surface. The reaction and rovibrationally elastic scattering probabilities that we obtain at a quantum dynamical (QD) level, as an average of many statically distorted surface configurations, show great agreement with those of a dynamic surface model, which reinforces the validity of the sudden approximation inherent to the SCM. We further investigate several simple methods of binning the final rovibrational state of quasi-classical dynamics simulations, to find those best suited to reproduce the QD results for our system. Finally, we show that the SCM obtained results reproduce experimental dissociation curves very well, when the uncertainty in experimental saturation values is taken into account. Some indication of a slow channel, so far only observed in experiment, can also be found at low incidence energies, although more rigorous QD simulations are required to reduce the noise inherent to our propagation methods.

Spectroscopic and QM/MM studies of the Cu(I) binding site of the plant ethylene receptor ETR1

Herein, we present, to our knowledge, the first spectroscopic characterization of the Cu(I) active site of the plant ethylene receptor ETR1. The x-ray absorption (XAS) and extended x-ray absorption fine structure (EXAFS) spectroscopies presented here establish that ETR1 has a low-coordinate Cu(I) site. The EXAFS resolves a mixed first coordination sphere of N/O and S scatterers at distances consistent with potential histidine and cysteine residues. This finding agrees with the coordination of residues C65 and H69 to the Cu(I) site, which are critical for ethylene activity and well conserved. Furthermore, the Cu K-edge XAS and EXAFS of ETR1 exhibit spectroscopic changes upon addition of ethylene that are attributed to modifications in the Cu(I) coordination environment, suggestive of ethylene binding. Results from umbrella sampling simulations of the proposed ethylene binding helix of ETR1 at a mixed quantum mechanics/molecular mechanics level agree with the EXAFS fit distance changes upon ethylene binding, particularly in the increase of the distance between H69 and Cu(I), and yield binding energetics comparable with experimental dissociation constants. The observed changes in the copper coordination environment might be the triggering signal for the transmission of the ethylene response.

Density functional theory and CCSD(T) evaluation of ionization potentials, redox potentials, and bond energies related to zirconocene polymerization catalysts.

Quantum-mechanical-based computational design of molecular catalysts requires accurate and fast electronic structure calculations to determine and predict properties of transition-metal complexes. For Zr-based molecular complexes related to polyethylene catalysis, previous evaluation of density functional theory (DFT) and wavefunction methods only examined oxides and halides or select reaction barrier heights. In this work, we evaluate the performance of DFT against experimental redox potentials and bond dissociation enthalpies (BDEs) for zirconocene complexes directly relevant to ethylene polymerization catalysis. We also examined the ability of DFT to compute the fourth atomic ionization potential of zirconium and the effect the basis set selection has on the ionization potential computed with CCSD(T). Generally, the atomic ionization potential and redox potentials are very well reproduced by DFT, but we discovered relatively large deviations of DFT-calculated BDEs compared to experiment. However, evaluation of BDEs with CCSD(T) suggests that experimental values should be revisited, and our CCSD(T) values should be taken as most accurate.

Public Data Set of Protein-Ligand Dissociation Kinetic Constants for Quantitative Structure-Kinetics Relationship Studies.

Protein–ligand binding affinity reflects the equilibrium thermodynamics of the protein–ligand binding process. Binding/unbinding kinetics is the other side of the coin. Computational models for interpreting the quantitative structure–kinetics relationship (QSKR) aim at predicting protein–ligand binding/unbinding kinetics based on protein structure, ligand structure, or their complex structure, which in principle can provide a more rational basis for structure-based drug design. Thus far, most of the public data sets used for deriving such QSKR models are rather limited in sample size and structural diversity. To tackle this problem, we have compiled a set of 680 protein–ligand complexes with experimental dissociation rate constants (koff), which were mainly curated from the references accumulated for updating our PDBbind database. Three-dimensional structure of each protein–ligand complex in this data set was either retrieved from the Protein Data Bank or carefully modeled based on a proper template. The entire data set covers 155 types of protein, with their dissociation kinetic constants (koff) spanning nearly 10 orders of magnitude. To the best of our knowledge, this data set is the largest of its kind reported publicly. Utilizing this data set, we derived a random forest (RF) model based on protein–ligand atom pair descriptors for predicting koff values. We also demonstrated that utilizing modeled structures as additional training samples will benefit the model performance. The RF model with mixed structures can serve as a baseline for testifying other more sophisticated QSKR models. The whole data set, namely, PDBbind-koff-2020, is available for free download at our PDBbind-CN web site (http://www.pdbbind.org.cn/download.php).

Potassium Binding Interactions with Aliphatic Amino Acids: Thermodynamic and Entropic Effects Analyzed via a Guided Ion Beam and Computational Study.

Noncovalent interactions between alkali metals and amino acids are critical for many biological processes, especially for proper function of protein ion channels; however, many precise binding affinities between alkali metals and amino acids still need to be measured. This study addresses this need by using threshold collision-induced dissociation with a guided ion beam tandem mass spectrometer to measure binding affinities between potassium cations and the aliphatic amino acids: Gly, Ala, hAla, Val, Leu, and Ile. These measurements are supplemented by theoretical calculations and include commentary on effects of enthalpy, entropy, and structural preference. Notably, all levels of theory indicate that the lowest-lying isomers at 298 K have K+ binding to the carbonyl oxygen in either a monodentate ([CO]) or bidentate ([CO,OH]) fashion, isomers that are linked in a double-well potential. This complicates the analysis of the data, although does not greatly influence the final results. Analysis of the resulting cross sections includes accounting for multiple ion-molecule collisions, internal energy of reactant ions, and unimolecular decay rates. The resulting experimental bond dissociation energies generally increase as the polarizability of the amino acid increases, results that agree well with quantum chemical calculations done at the B3LYP, B3P86, and MP2(full) levels of theory, with B3LYP-GD3BJ predicting systematically larger values.