Computational Analysis of Triazole-Based Kojic Acid Analogs as Tyrosinase Inhibitors by Molecular Dynamics and Free Energy Calculations

Molecular docking, molecular dynamics (MD) simulations and the linear interaction energy (LIE) method were used here to predict binding modes and free energy for a set of 1,2,3-triazole-based KA analogs as potent inhibitors of Tyrosinase (TYR), a key metalloenzyme of the melanogenesis process. Initially, molecular docking calculations satisfactorily predicted the binding mode of evaluated KA analogs, where the KA part overlays the crystal conformation of the KA inhibitor into the catalytic site of TYR. The MD simulations were followed by the LIE method, which reproduced the experimental binding free energies for KA analogs with an r² equal to 0.97, suggesting the robustness of our theoretical model. Moreover, the van der Waals contributions performed by some residues such as Phe197, Pro201, Arg209, Met215 and Val218 are responsible for the binding recognition of 1,2,3-triazole-based KA analogs in TYR catalytic site. Finally, our calculations provide suitable validation of the combination of molecular docking, MD, and LIE approaches as a powerful tool in the structure-based drug design of new and potent TYR inhibitors.     

Rapid prediction of solvation free energy. 3. Application to the SAMPL2 challenge

The SAMPL2 hydration free energy blind prediction challenge consisted of a data set of 41 molecules divided into three subsets: explanatory, obscure and investigatory, where experimental hydration free energies were given for the explanatory, withheld for the obscure, and not known for the investigatory molecules. We employed two solvation models for this challenge, a linear interaction energy (LIE) model based on explicit-water molecular dynamics simulations, and the first-shell hydration (FiSH) continuum model previously calibrated to mimic LIE data. On the 23 compounds from the obscure (blind) dataset, the prospectively submitted LIE and FiSH models provided predictions highly correlated with experimental hydration free energy data, with mean-unsigned-errors of 1.69 and 1.71 kcal/mol, respectively. We investigated several parameters that may affect the performance of these models, namely, the solute flexibility for the LIE explicit-solvent model, the solute partial charging method, and the incorporation of the difference in intramolecular energy between gas and solution phases for both models. We extended this analysis to the various chemical classes that can be formed within the SAMPL2 dataset. Our results strengthen previous findings on the excellent accuracy and transferability of the LIE explicit-solvent approach to predict transfer free energies across a wide spectrum of functional classes. Further, the current results on the SAMPL2 test dataset provide additional support for the FiSH continuum model as a fast yet accurate alternative to the LIE explicit-solvent model. Overall, both the LIE explicit-solvent model and the FiSH continuum solvation model show considerable improvement on the SAMPL2 data set over our previous continuum electrostatics-dispersion solvation model used in the SAMPL1 blind challenge.     

Computational prediction of monosaccharide binding free energies to lectins with linear interaction energy models

The linear interaction energy (LIE) method to compute binding free energies is applied to lectin‐monosaccharide complexes. Here, we calculate the binding free energies of monosaccharides to the Ralstonia solanacearum lectin (RSL) and the Pseudomonas aeruginosa lectin‐II (PA‐IIL). The standard LIE model performs very well for RSL, whereas the PA‐IIL system, where ligand binding involves two calcium ions, presents a major challenge. To overcome this, we explore a new variant of the LIE model, where ligand–metal ion interactions are scaled separately. This model also predicts the saccharide binding preference of PA‐IIL on mutation of the receptor, which may be useful for protein engineering of lectins. © 2012 Wiley Periodicals, Inc.     

Continuum solvation models in the linear interaction energy method

The linear interaction energy (LIE) method in combination with two different continuum solvent models has been applied to calculate protein-ligand binding free energies for a set of inhibitors against the malarial aspartic protease plasmepsin II. Ligand-water interaction energies are calculated from both Poisson-Boltzmann (PB) and Generalized Born (GB) continuum models using snapshots from explicit solvent simulations of the ligand and protein-ligand complex. These are compared to explicit solvent calculations, and we find close agreement between the explicit water and PB solvation models. The GB model overestimates the change in solvation energy, and this is caused by consistent underestimation of the effective Born radii in the protein-ligand complex. The explicit solvent LIE calculations and LIE-PB, with our standard parametrization, reproduce absolute experimental binding free energies with an average unsigned error of 0.5 and 0.7 kcal/mol, respectively. The LIE-GB method, however, requires a constant offset to approach the same level of accuracy.     

Coupled semiempirical quantum mechanics and molecular mechanics (QM/MM) calculations on the aqueous solvation free energies of ionized molecules

The aqueous solvation free energies of ionized molecules were computed using a coupled quantum mechanical and molecular mechanical (QM/MM) model based on the AM1, MNDO, and PM3 semiempirical molecular orbital methods for the solute molecule and the TIP3P molecular mechanics model for liquid water. The present work is an extension of our model for neutral solutes where we assumed that the total free energy is the sum of components derived from the electrostatic/polarization terms in the Hamiltonian plus an empirical “nonpolar” term. The electrostatic/polarization contributions to the solvation free energies were computed using molecular dynamics (MD) simulation and thermodynamic integration techniques, while the nonpolar contributions were taken from the literature. The contribution to the electrostatic/polarization component of the free energy due to nonbonded interactions outside the cutoff radii used in the MD simulations was approximated by a Born solvation term. The experimental free energies were reproduced satisfactorily using variational parameters from the vdW terms as in the original model, in addition to a parameter from the one-electron integral terms. The new one-electron parameter was required to account for the short-range effects of overlapping atomic charge densities. The radial distribution functions obtained from the MD simulations showed the expected H-bonded structures between the ionized solute molecule and solvent molecules. We also obtained satisfactory results by neglecting both the empirical nonpolar term and the electronic polarization of the solute, i.e., by implementing a nonpolarization model. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 1028–1038, 1999     

MM/GBSA and LIE estimates of host–guest affinities: dependence on charges and solvation model

The affinities of two sets of guest–host systems were estimated using the popular end-point methods MM/GBSA (molecular-mechanics with generalised Born and surface-area solvation) and LIE (linear interaction energy). A set of six primary alcohols that bind to α-cyclodextrin (α-CD) and a set of eight guest molecules to cucurbit[8]uril (CB8) were considered. Three different charge schemes were used to obtain charges for the host and guest molecules, viz., AM1-BCC, RESP, and the recently suggested xAvESP (which average ESP charges over a number of molecular dynamics snapshots). Furthermore, both the generalised Born and Poisson–Boltzmann solvation models were used in the MM/GBSA calculations. The two solvation models perform equally well in predicting relative affinities, and hence there is no point in using the more expensive Poisson–Boltzmann model for these systems. Both the LIE and MM/GBSA estimates are shown to be robust with respect to the charge model, and therefore it is recommended to use the cheapest AM1-BCC charges. Using AM1-BCC charges, the MM/GBSA method gave a MADtr (mean absolute deviation after removal of systematic error) of 17 kJ/mol and a correlation coefficient (r ²) of 0.67 for the CB8 complexes, and a MADtr of 10 kJ/mol and an r ² of 0.96 for the α-CD complexes. The LIE method gave a MADtr of 20 kJ/mol and an r ² of 0.10 for the CB8 complexes, after optimisation of the non-polar scaling parameter. For the α-CD complexes, no optimisation was necessary and the method gave a MADtr of 2 kJ/mol and a r ² of 0.96. These results indicate that both MM/GBSA and LIE are able to estimate host–guest affinities accurately.     

Electronic Structure Insights into the Solvation of Magnesium Ions with Cyclic and Acyclic Carbonates

A computational framework to rank the solvation behavior of Mg²⁺ in carbonates by using molecular dynamics simulations and density functional theory is reported. Based on the binding energies and enthalpies of solvation calculated at the M06‐2X/6‐311++G(d,p) level of theory and the free energies of solvation from ABF‐MD simulations, we find that ethylene carbonate (EC) and the ethylene carbonate:propylene carbonate (EC:PC) binary mixture are the best carbonate solvents for interacting with Mg²⁺. Natural bond orbital and quantum theory of atoms in molecules analyses support the thermochemistry calculations with the highest values of charge transfer, perturbative stabilization energies, electron densities, and Wiberg bond indices being observed in the Mg²⁺(EC) and Mg²⁺(EC:PC) complexes. The plots of the noncovalent interactions indicate that those responsible for the formation of Mg²⁺ carbonate complexes are strong‐to‐weak attractive interactions, depending on the regions that are interacting. Finally, density of state calculations indicate that the interactions between Mg²⁺ and the carbonate solvents affects the HOMO and LUMO states of all carbonate solvents and moves them to more negative energy values.     

Binding affinity prediction with different force fields: examination of the linear interaction energy method

A systematic study of the linear interaction energy (LIE) method and the possible dependence of its parameterization on the force field and system (receptor binding site) is reported. We have calculated the binding free energy for nine different ligands in complex with P450cam using three different force fields (Amber95, Gromos87, and OPLS-AA). The results from these LIE calculations using our earlier parameterization give relative free energies of binding that agree remarkably well with the experimental data. However, the absolute energies are too positive for all three force fields, and it is clear that an additional constant term (gamma) is required in this case. Out of five examined LIE models, the same one emerges as the best for all three force fields, and this, in fact, corresponds to our earlier one apart from the addition of the constant gamma, which is almost identical for the three force fields. Thus, the present free energy calculations clearly indicate that the coefficients of the LIE method are independent of the force field used. Their relation to solvation free energies is also demonstrated. The only free parameter of the best model is gamma, which is found to depend on the hydrophobicity of the binding site. We also attempt to quantify the binding site hydrophobicity of four different proteins which shows that the ordering of gamma's for these sites reflects the fraction of hydrophobic surface area.     

Comparative study of free energies of solvation of phenylimidazole inhibitors of cytochrome P450cam by free energy simulation,AMSOL, and Poisson Boltzmann methods

Free energies of solvation of phenylimidazole inhibitors of cytochrome P450cam were determined using (1) free energy simulation, (2) AMSOL-SM2 semiempirical methods, and (3) Poisson-Boltzmann methods. The goals of this study were threefold: (1) to compare the results obtained from the three different methods, (2) to investigate the effect of inclusion of intraperturbed group interactions on free energy simulation estimates of solvation free energy differences, and (3) to investigate to what extent differences in free energies of solvation among three of these inhibitors could account for observed differences in their enzyme binding free energies. In general, relative solvation free energies obtained from the free energy simulations and AMSOL-SM2 methods give comparable results (i.e., the same rank ordering and similar quantitative results, differing significantly from results obtained using Poisson-Boltzmann methods). The free energy simulation studies suggest that the neglect of intraperturbed group interactions had little effect on rank order of free energies of solvation of the polar phenylimidazoles. The relative desolvation free energies of the three inhibitors of P450cam—1-phenylimidazole (1-PI), 2-phenylimidazole (2-PI), and 4-phenylimidazole (4-PI)—with known enzyme bound X-ray structures parallel that of their known binding affinities and could account for most of the differences in the free energies of binding of these three inhibitors to P450cam. The origin of the difference of the free energies of solution of these three inhibitors is primarily the additional interaction between solvent and N(SINGLE BOND)H group in the imidazole ring of 2- and 4-phenylimidazole that is absent in the 1-phenylimidazole isomer. This hypothesis is substantiated by a second comparison of the relative solvation free energies of 4-phenylimidazole with its methylated derivative, 3-methyl-4-phenylimidazole, also lacking an N(SINGLE BOND)H group. © 1996 by John Wiley & Sons, Inc.     

Comparison of two simulation methods to compute solvation free energies and partition coefficients

The thermodynamic integration (TI) and expanded ensemble (EE) methods are used here to calculate the hydration free energy in water, the solvation free energy in 1‐octanol, and the octanol‐water partition coefficient for a six compounds of varying functionality using the optimized potentials for liquid simulations (OPLS) all‐atom (AA) force field parameters and atomic charges. Both methods use the molecular dynamics algorithm as a primary component of the simulation protocol, and both have found wide applications in fields such as the calculation of activity coefficients, phase behavior, and partition coefficients. Both methods result in solvation free energies and 1‐octanol/water partition coefficients with average absolute deviations (AAD) from experimental data to within 4 kJ/mol and 0.5 log units, respectively. Here, we find that in simulations the OPLS‐AA force field parameters (with fixed charges) can reproduce solvation free energies of solutes in 1‐octanol with AAD of about half that for the solute hydration free energies using a extended simple point charge (SPC/E) model of water. The computational efficiency of the two simulation methods are compared based on the time (in nanoseconds) required to obtain similar standard deviations in the solvation free energies and 1‐octanol/water partition coefficients. By this analysis, the EE method is found to be a factor of nine more efficient than the TI algorithm. For both methods, solvation free energy calculations in 1‐octanol consume roughly an order of magnitude more CPU hours than the hydration free energy calculations. © 2012 Wiley Periodicals, Inc.     

An application of coupled reference interaction site model/molecular dynamics to the conformational analysis of the alanine dipeptide

We present an application of our recently proposed coupled reference interaction site model (RISM) molecular dynamics (MD) solvation free energy methodology [Freedman and Truong, Chem. Phys. Lett. 381, 362 (2003); J. Chem. Phys. 121, 2187 (2004)] to study the conformational stability of alanine dipeptide in aqueous solution. In this methodology, radial distribution functions obtained from a single MD simulation are substituted into a RISM expression for solvation free energy. Consequently, iterative solution of the RISM equation is not needed. The relative solvation free energies of seven different conformations of the alanine dipeptide in aqueous solution are calculated. Results from the coupled RISM/MD methodology are in good agreement with those from earlier simulations using the accurate free energy perturbation approach, showing that the alphaR conformation is most stabilized by solution. This study establishes a framework for applying this coupled RISM/MD method to larger biological systems.     

A challenging system: free energy prediction for factor Xa

Factor Xa (fXa) is a promising target for antithrombotic drugs. Recently, we presented a molecular dynamics study on fXa, which highlighted the need for a careful system setup to obtain stable simulations. Here, we show that these simulations can be used to predict the free energy of binding of several fXa inhibitors. We tested molecular mechanics/Poisson-Boltzmann surface area, molecular mechanics/Generalized Born surface area, and linear interaction energy (LIE) on a small data set of fXa ligands. The continuum solvent approaches only yield satisfying correlations to the experimental results if some of the water molecules are explicitly included in the free energy calculations. LIE gave reasonable results if a sufficiently large data set is used. In general, our procedure of setting up the fXa simulation system enabled MD simulations, which produce adequate ensembles for free energy calculations.     

Predicting hydration free energies of polychlorinated aromatic compounds from the SAMPL-3 data set with FiSH and LIE models

Next-generation solvation models are devised to mimic the accuracy and generality of explicit solvation models at the speed of current popular implicit solvation models. One such method is the first-shell of hydration (FiSH) continuum model that was trained on hydration energetics from LIE calculations and molecular dynamics simulations in explicit solvent. Here we tested prospectively the FiSH model on the SAMPL-3 hydration data set that zooms in the effect of chlorination on solvation. We compare these FiSH predictions with those from retrospective LIE calculations. We find that neither FiSH nor LIE can reproduce well the absolute values and the trend of hydration free energies in the biphenyl and dioxin aromatic chlorination series. Some of the hypotheses behind this performance are discussed and tested. The LIE explicit-solvent model shows some improvement relative to the FiSH continuum model, and we correct a systematic deviation in the continuum van der Waals term of FiSH associated with aromatic Cl atom type.     

Parameterization of the Hamiltonian Dielectric Solvent (HADES) Reaction‐Field Method for the Solvation Free Energies of Amino Acid Side‐Chain Analogs

Optimization of the Hamiltonian dielectric solvent (HADES) method for biomolecular simulations in a dielectric continuum is presented with the goal of calculating accurate absolute solvation free energies while retaining the model’s accuracy in predicting conformational free‐energy differences. The solvation free energies of neutral and polar amino acid side‐chain analogs calculated by using HADES, which may optionally include nonpolar contributions, were optimized against experimental data to reach a chemical accuracy of about 0.5 kcal mol^?1. The new parameters were evaluated for charged side‐chain analogs. The HADES results were compared with explicit‐solvent, generalized Born, Poisson–Boltzmann, and QM‐based methods. The potentials of mean force (PMFs) between pairs of side‐chain analogs obtained by using HADES and explicit‐solvent simulations were used to evaluate the effects of the improved parameters optimized for solvation free energies on intermolecular potentials.     

A QM/MM study of the binding of RAPTA ligands to cathepsin B

We have carried out quantum mechanical (QM) and QM/MM (combined QM and molecular mechanics) calculations, as well as molecular dynamics (MD) simulations to study the binding of a series of six RAPTA (Ru(II)-arene-1,3,5-triaza-7-phosphatricyclo-[3.3.1.1] decane) complexes with different arene substituents to cathepsin B. The recently developed QM/MM-PBSA approach (QM/MM combined with Poisson–Boltzmann solvent-accessible surface area solvation) has been used to estimate binding affinities. The QM calculations reproduce the antitumour activities of the complexes with a correlation coefficient (r ²) of 0.35–0.86 after a conformational search. The QM/MM-PBSA method gave a better correlation (r ² = 0.59) when the protein was fixed to the crystal structure, but more reasonable ligand structures and absolute binding energies were obtained if the protein was allowed to relax, indicating that the ligands are strained when the protein is kept fixed. In addition, the best correlation (r ² = 0.80) was obtained when only the QM energies were used, which suggests that the MM and continuum solvation energies are not accurate enough to predict the binding of a charged metal complex to a charged protein. Taking into account the protein flexibility by means of MD simulations slightly improves the correlation (r ² = 0.91), but the absolute energies are still too large and the results are sensitive to the details in the calculations, illustrating that it is hard to obtain stable predictions when full flexible protein is included in the calculations.     

Evaluating the Free Energies of Solvation and Electronic Structures of Lithium‐Ion Battery Electrolytes

Adaptive biasing force molecular dynamics simulations and density functional theory calculations were performed to understand the interaction of Li⁺ with pure carbonates and ethylene carbonate (EC)‐based binary mixtures. The most favorable Li carbonate cluster configurations obtained from molecular dynamics simulations were subjected to detailed structural and thermochemistry calculations on the basis of the M06‐2X/6‐311++G(d,p) level of theory. We report the ranking of these electrolytes on the basis of the free energies of Li‐ion solvation in carbonates and EC‐based mixtures. A strong local tetrahedral order involving four carbonates around the Li⁺ was seen in the first solvation shell. Thermochemistry calculations revealed that the enthalpy of solvation and the Gibbs free energy of solvation of the Li⁺ ion with carbonates are negative and suggested the ion–carbonate complexation process to be exothermic and spontaneous. Natural bond orbital analysis indicated that Li⁺ interacts with the lone pairs of electrons on the carbonyl oxygen atom in the primary solvation sphere. These interactions lead to an increase in the carbonyl (C=O) bond lengths, as evidenced by a redshift in the vibrational frequencies [ν(C=O)] and a decrease in the electron density values at the C=O bond critical points in the primary solvation sphere. Quantum theory of atoms in molecules, localized molecular orbital energy decomposition analysis (LMO‐EDA), and noncovalent interaction plots revealed the electrostatic nature of the Li⁺ ion interactions with the carbonyl oxygen atoms in these complexes. On the basis of LMO‐EDA, the strongest attractive interaction in these complexes was found to be the electrostatic interaction followed by polarization, dispersion, and exchange interactions. Overall, our calculations predicted EC and a binary mixture of EC/dimethyl carbonate to be appropriate electrolytes for Li‐ion batteries, which complies with experiments and other theoretical results.     

Absolute free energies of biomolecules from unperturbed ensembles

Computing the absolute free energy of a macromolecule's structural state, F, is a challenging problem of high relevance. This study presents a method that computes F using only information from an unperturbed simulation of the macromolecule in the relevant conformational state, ensemble, and environment. Absolute free energies produced by this method, dubbed V aluation of L ocal C onfiguration I ntegral with D ynamics (VALOCIDY), enable comparison of alternative states. For example, comparing explicitly solvated and vaporous states of amino acid side‐chain analogs produces solvation free energies in good agreement with experiments. Also, comparisons between alternative conformational states of model heptapeptides (including the unfolded state) produce free energy differences in agreement with data from μs molecular‐dynamics simulations and experimental propensities. The potential of using VALOCIDY in computational protein design is explored via a small design problem of stabilizing a β‐turn structure. When VALOCIDY‐based estimation of folding free energy is used as the design metric, the resulting sequence folds into the desired structure within the atomistic force field used in design. The VALOCIDY‐based approach also recognizes the distinct status of the native sequence regardless of minor details of the starting template structure, in stark contrast with a traditional fixed‐backbone approach. © 2013 Wiley Periodicals, Inc.     

Relative solvation free energies calculated using an ab initio QM/MM-based free energy perturbation method: dependence of results on simulation length

Molecular dynamics (MD) simulations in conjunction with thermodynamic perturbation approach was used to calculate relative solvation free energies of five pairs of small molecules, namely; (1) methanol to ethane, (2) acetone to acetamide, (3) phenol to benzene, (4) 1,1,1 trichloroethane to ethane, and (5) phenylalanine to isoleucine. Two studies were performed to evaluate the dependence of the convergence of these calculations on MD simulation length and starting configuration. In the first study, each transformation started from the same well-equilibrated configuration and the simulation length was varied from 230 to 2,540 ps. The results indicated that for transformations involving small structural changes, a simulation length of 860 ps is sufficient to obtain satisfactory convergence. In contrast, transformations involving relatively large structural changes, such as phenylalanine to isoleucine, require a significantly longer simulation length (>2,540 ps) to obtain satisfactory convergence. In the second study, the transformation was completed starting from three different configurations and using in each case 860 ps of MD simulation. The results from this study suggest that performing one long simulation may be better than averaging results from three different simulations using a shorter simulation length and three different starting configurations.     

Improving the performance of the coupled reference interaction site model-hyper-netted chain (RISM-HNC)/simulation method for free energy of solvation

The coupled reference interaction site model-hyper-netted chain (RISM-HNC)/ simulation methodology determines solvation free energies as a function of the set of all radial distribution functions of solvent atoms about atomic solute sites. These functions are determined from molecular dynamics (MD) or Monte Carlo (MC) simulations rather than from solving the RISM and HNC equations iteratively. Previous applications of the method showed that it can predict relative free energies of solvation for small solutes accurately. However, the errors scale with the system size. In this study, we propose the use of the hard-sphere free energy as the reference and a linear response approximation to improve the performance, i.e., accuracy and robustness, of the method, particularly removing the size dependency of the error. The details of the new formalism are presented. To validate the proposed formalism, solvation free energies of N-methylacetamide and methylamine are computed using the new RISM-HNC-based expressions in addition to a linear response expression, which are compared to previous thermodynamic integration and thermodynamic perturbation results performed with the same force field. Additionally, free energies of solvation for cyclohexane, pyridine, benzene and derivatives, and other small organic molecules are calculated and compared to experimental values.     

Charge-charge and cation-<Emphasis Type="Italic">π</Emphasis> interactions in ligand binding to G protein-coupled receptors

To study the importance of charge–charge and cation-π interactions for the binding of positively charged amine ligands to their receptors, the energies of interaction between [(CH₃)₄–N]⁺, [(CH₃)₃–NH]⁺, and [(CH₃)₄–NH₃]⁺ and acetate, as a model of Asp and Glu, and with benzene, as a model of aromatic side chains, were obtained at the MP2/aug-cc-pVDZ level of theory. The free energies of solvation in water were also calculated for the different amines. It was found that, although primary amines form stronger charge–charge interactions with acetate than tertiary or quaternary amines, the difference is not large enough to compensate their higher solvation energy. Quaternary amines show the weakest interaction with acetate. However, their alkyl groups can interact with various aromatic groups, enhancing ligand binding to the receptor. The analysis was completed with MD calculations on amine binding to the G protein-coupled receptors β₂AR and CCR5. The calculations on the model systems were found to be in good agreement with the simulations of the ligand-receptor complexes. Contribution to the Serafin Fraga Memorial Issue.