Improvements on the protein–dipole Langevin–dipole model

The protein–dipole Langevin–dipole (PDLD) model developed by Warshel and co-workers is an approach to evaluate electrostatic interactions in protein systems from microscopic sights. This model grasped the main physical factors and required little computations. But it might need the tests from every aspect. In the present work, we have chosen the solvation energies of Asp3, Glu7, Glu49, and Asp50 in bovine pancreatic trypsin inhibitor (BPTI) as a calibration to discuss the influences of parameters and conditions on the simulation results in the PDLD model. Some improvements have been proposed. The calculated solvation energies associated with ionizing the four acidic groups in BPTI and aspartic acid in solution are found in good agreement with the corresponding observed results if the improved PDLD approach and computational methods are used. © 1992 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.     

On the transferability of hydration-parametrized continuum electrostatics models to solvated binding calculations

Using molecular mechanics force field partial atomic charges, we show the nonuniqueness of the parametrization of continuum electrostatics models with respect to solute atomic radii and interior dielectric constant based on hydration (vacuum-to-water transfer) free energy data available for small molecules. Moreover, parameter sets that are optimal and equivalent for hydration free energy calculations lead to large variations of calculated absolute and relative electrostatic binding free energies. Hence, parametrization of solvation effects based on hydration data, although a necessary condition, is not sufficient to guarantee its transferability to the calculation of binding free energies in solution.     

Adding explicit solvent molecules to continuum solvent calculations for the calculation of aqueous acid dissociation constants

Aqueous acid dissociation free energies for a diverse set of 57 monoprotic acids have been calculated using a combination of experimental and calculated gas and liquid-phase free energies. For ionic species, aqueous solvation free energies were calculated using the recently developed SM6 continuum solvation model. This model combines a dielectric continuum with atomic surface tensions to account for bulk solvent effects. For some of the acids studied, a combined approach that involves attaching a single explicit water molecule to the conjugate base (anion), and then surrounding the resulting anion-water cluster by a dielectric continuum, significantly improves the agreement between the calculated pK(a) value and experiment. This suggests that for some anions, particularly those concentrating charge on a single exposed heteroatom, augmenting implicit solvent calculations with a single explicit water molecule is required, and adequate, to account for strong short-range hydrogen bonding interactions between the anion and the solvent. We also demonstrate the effect of adding several explicit waters by calculating the pK(a) of bicarbonate (HCO(3)(-)) using as the conjugate base carbonate (CO(3)(2-)) bound by up to three explicit water molecules.     

Surface-integral QSPR models: local energy properties

Surface-integral models based on AM1 semiempirical molecular orbital calculations are presented for the free energies of solvation in water, n-octanol, and chloroform and for the enthalpy of solvation in water. A parametrized function of four local properties calculated at the isodensity surface (the molecular electrostatic potential, local ionization energy, electron affinity, and polarizability) is integrated over the triangulated surface area to obtain the target quantity. The resulting models give results only slightly less accurate than those reported for parametrized generalized Born/polar surface area models despite relying only on gas-phase calculations. The water and octanol free-energy models were validated by calculating the water-octanol partition coefficient for a test set of organic compounds with moderate success. The models lead to a local solvation energy, which can be projected onto the molecular isodensity surface and provides insight into "hot" areas for solvation in water or the other solvents.     

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.     

Solvent effect on La to Nd ion mutation: a Monte Carlo simulation study

A Monte Carlo simulation of statistical perturbation theory (SPT) has been applied to investigate solvent effects on the relative free energies of solvation of La³⁺ to Nd³⁺ ion mutation in several solvents. Comparing the relative free energies for interconversion of La³⁺ to Nd³⁺, in H₂O (TIP3P) from this Letter with computer simulation and experiments, there is good agreement among the three studies, There is also reasonable agreement between calculated structural properties from this Letter and other works. For these ion pairs, the Born's function of the solvents and the differences in solvation dominate the differences in the relative free energies of solvation and partition coefficients.     

Prediction of internal standards in reversed-phase liquid chromatography. III. Evaluation of an alternative solvation parameter model to correlate and predict the retention of ionizable compounds

This paper describes the results of the evaluation of an alternative solvation parameter model for ionizable compounds. The new model is described as Log(k) = Int + rR2 + spi2(H) + asigmaalpha2(H) + bsigmabeta2(H) + mVx + U/(1 + V10 (+/-(pH-Pk))). The first six terms are the usual solvation parameter equation for neutral solutes, and the last term represents the contribution to retention from the ionization of solutes. Retention data obtained for 30 solutes in acetonitrile/aqueous buffer mobile phases are used to evaluate the capability of the function using different pH/pK scales. Because the function is not linear, nonlinear least-squares analysis is used to perform the data processing. It is concluded that the model function describes similarly the retention of ionizable compounds to the literature model without the need to accurately measure the mobile phase pH and solute's pK. Accordingly, the function simplifies the application of linear solvation energy relationships (LSERs) to ionizable compounds, and allows us to easily predict their retention for chromatographic optimization.     

Hydrogen exchange rates in proteins from water (1)H transverse magnetic relaxation

Access to the fast exchange kinetics of labile protein hydrogens in solution is provided by exchange broadening of the water 1H NMR line. We analyzed the chemical shift modulation contribution of labile hydrogens in bovine pancreatic trypsin inhibitor (BPTI) to the transverse 1H spin relaxation rate, R2, of the bulk solvent. Both the experimental pH dependence and the CPMG dispersion of R2 could be quantitatively accounted for on the basis of known chemical shifts, exchange rates, and ionization constants for BPTI. This analysis provided, for the first time, the hydrogen exchange rate constants for Lys and Arg side chains in a protein and pointed to an internal catalysis of the N-terminal amino protons in BPTI by a salt bridge. The method can be used for mapping the hydrogen exchange rates in protein solutions and biomaterials, which may be important for the control of relaxation-weighted contrast in biological MRI.     

The treatment of solvation by a generalized Born model and a self-consistent charge-density functional theory-based tight-binding method

We present a model to calculate the free energies of solvation of small organic compounds as well as large biomolecules. This model is based on a generalized Born (GB) model and a self-consistent charge-density functional theory-based tight-binding (SCC-DFTB) method with the nonelectrostatic contributions to the free energy of solvation modeled in terms of solvent-accessible surface areas (SA). The parametrization of the SCC-DFTB/GBSA model has been based on 60 neutral and six ionic molecules composed of H, C, N, O, and S, and spanning a wide range of chemical groups. Effective atomic radii as parameters have been obtained through Monte Carlo Simulated Annealing optimization in the parameter space to minimize the differences between the calculated and experimental free energies of solvation. The standard error in the free energies of solvation calculated by the final model is 1.11 kcal mol(-1). We also calculated the free energies of solvation for these molecules using a conductor-like screening model (COSMO) in combination with different levels of theory (AM1, SCC-DFTB, and B3LYP/6-31G*) and compared the results with SCC-DFTB/GBSA. To assess the efficiency of our model for large biomolecules, we calculated the free energy of solvation for a HIV protease-inhibitor complex containing 3,204 atoms using the SCC-DFTB/GBSA and the SCC-DFTB/COSMO models, separately. The computed relative free energies of solvation are comparable, while the SCC-DFTB/GBSA model is three to four times more efficient, in terms of computational cost.     

An electrospray ionization mass spectrometry investigation of 1-anilino-8-naphthalene-sulfonate (ANS) binding to proteins

The binding of 1-anilino-8-naphthalene-sulfonic acid (ANS) to various globular proteins at acidic pH has been investigated by electrospray ionization mass spectrometry (ESI-MS). Maximal ANS binding is observed in the pH range 3-5. As many as seven species of dye-bound complexes are detected for myoglobin. Similar studies were carried out with cytochrome c, carbonic anhydrase, triosephosphate isomerase, lysozyme, alpha-lactalbumin, and bovine pancreatic trypsin inhibitor (BPTI). Strong ANS binding was observed wherever molten globule states were postulated in solution. ANS binding is not observed for lysozyme and BPTI, which have tightly folded structures in the native form. Alpha-lactalbumin, which is structurally related to lysozyme but forms a molten globule at acidic pH, exhibited ANS binding. Reduction of disulfide bonds in these proteins leads to the detection of ANS binding even at neutral pH. Binding was suppressed at very low pH (<2.5), presumably due to neutralization of the charge on the sulfonate moiety. The distribution of the relative intensities of the protein bound ANS species varies with the charge state, suggesting heterogeneity of gas phase conformations. The binding strength of these complexes was qualitatively estimated by dissociating them using enhanced nozzle skimmer potentials. The skimmer voltages also affected the lower and higher charge states of these complexes in a different manner.     

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.     

Calculations of pH-dependent binding of proteins to biological membranes

Binding of proteins to membranes is often accompanied by titration of ionizable residues and is, therefore, dependent on pH. We present a theoretical treatment and computational approach for predicting absolute, pH-dependent membrane binding free energies. The standard free energy of binding, DeltaG, is defined as -RTln(P(b)/P(f)), where P(b) and P(f) are the amounts of bound and free protein. The apparent pK(a) of binding is the pH value at which P(b) and P(f) are equal. Proteins bind to the membrane in the pH range where DeltaG is negative. The components of the binding free energy are (a) the free energy cost of ionization state changes (DeltaG(ion)), (b) the effective energy of transfer from solvent to the membrane surface, (c) the translational/rotational entropy cost of binding, and (d) an ideal entropy term that depends on the relative volume of the bound and free state and therefore depends on lipid concentration. Calculation of the first term requires determination of pK(a) values in solvent and on the membrane surface. All energies required by the method are obtained from molecular dynamics trajectories on an implicit membrane (IMM1-GC). The method is tested on pentalysine and the helical peptide VEEKS, derived from the membrane-binding domain of phosphocholine cytidylyltransferase. The agreement between the measured and the calculated free energies of binding of pentalysine is good. The extent of membrane binding of VEEKS is, however, underestimated compared to experiment. Calculations of the interaction energy between two VEEKS helices on the membrane suggest that the discrepancy is mainly due to the neglect of protein-protein interactions on the membrane surface.     

基于原子表面的蛋白质水合自由能预测模型

提出了一种计算蛋白质水合自由能的简化模型（SAWSA 2）.模型把蛋白质分子中的原子分为20种不同的原子类型,通过每类原子的溶剂可及化表面以及相应的溶剂化参数,就可以得到分子的水合自由能.不同原子类型的溶剂化参数通过110个蛋白质分子水合自由能拟合得到,水合自由能的标准值采用了基于求解Possion-Boltzmann方程（PB）以及分子表面计算（SA） 相结合的方法.采用得到的模型,预测了20个蛋白质分子的水合自由能,预测值的相对值和绝对值都能和PB/SA的计算值很好地吻合,大大优于两种已报导的水合自由能模型.     

Converging free energy estimates: MM-PB(GB)SA studies on the protein-protein complex Ras-Raf

Estimating protein-protein interaction energies is a very challenging task for current simulation protocols. Here, absolute binding free energies are reported for the complex H-Ras/C-Raf1 using the MM-PB(GB)SA approach, testing the internal consistency and model dependence of the results. Averaging gas-phase energies (MM), solvation free energies as determined by Generalized Born models (GB/SA), and entropic contributions calculated by normal mode analysis for snapshots obtained from 10 ns explicit-solvent molecular dynamics in general results in an overestimation of the binding affinity when a solvent-accessible surface area-dependent model is used to estimate the nonpolar solvation contribution. Applying the sum of a cavity solvation free energy and explicitly modeled solute-solvent van der Waals interaction energies instead provides less negative estimates for the nonpolar solvation contribution. When the polar contribution to the solvation free energy is determined by solving the Poisson-Boltzmann equation (PB) instead, the calculated binding affinity strongly depends on the atomic radii set chosen. For three GB models investigated, different absolute deviations from PB energies were found for the unbound proteins and the complex. As an alternative to normal-mode calculations, quasiharmonic analyses have been performed to estimate entropic contributions due to changes of solute flexibility upon binding. However, such entropy estimates do not converge after 10 ns of simulation time, indicating that sampling issues may limit the applicability of this approach. Finally, binding free energies estimated from snapshots of the unbound proteins extracted from the complex trajectory result in an underestimate of binding affinity. This points to the need to exercise caution in applying the computationally cheaper "one-trajectory-alternative" to systems where there may be significant changes in flexibility and structure due to binding. The best estimate for the binding free energy of Ras-Raf obtained in this study of -8.3 kcal mol(-1) is in good agreement with the experimental result of -9.6 kcal mol(-1), however, further probing the transferability of the applied protocol that led to this result is necessary.     

Calculation of the free energy of solvation for neutral analogs of amino acid side chains

The ability of the GROMOS96 force field to reproduce partition constants between water and two less polar solvents (cyclohexane and chloroform) for analogs of 18 of the 20 naturally occurring amino acids has been investigated. The estimations of the solvation free energies in water, in cyclohexane solution, and chloroform solution are based on thermodynamic integration free energy calculations using molecular dynamics simulations. The calculations show that while the force field reproduces the experimental solvation free energies of nonpolar analogs with reasonable accuracy the solvation free energies of polar analogs in water are systematically overestimated (too positive). The dependence of the calculated free energies on the atomic partial charges was also studied.     

Second derivatives in generalized Born theory

Generalized Born solvation models offer a popular method of including electrostatic aspects of solvation free energies within an analytical model that depends only upon atomic coordinates, charges, and dielectric radii. Here, we describe how second derivatives with respect to Cartesian coordinates can be computed in an efficient manner that can be distributed over multiple processors. This approach makes possible a variety of new methods of analysis for these implicit solvation models. We illustrate three of these methods here: the use of Newton-Raphson optimization to obtain precise minima in solution; normal mode analysis to compute solvation effects on the mechanical properties of DNA; and the calculation of configurational entropies in the MM/GBSA model. An implementation of these ideas, using the Amber generalized Born model, is available in the nucleic acid builder (NAB) code, and we present examples for proteins with up to 45,000 atoms. The code has been implemented for parallel computers using both the OpenMP and MPI environments, and good parallel scaling is seen with as many as 144 OpenMP processing threads or MPI processing tasks.     

Efficient evaluation of the effective dielectric function of a macromolecule in aqueous solution

We propose an analytical approach to calculate the effective dielectric function of proteins in aqueous solution. The screening effect if quantified by a measure of enclosure which is based on the distribution of solute atomic volumes around a pair of charges in a macromolecule. For protein conformations that vary significantly in size and shape, a comparison with finite difference Poisson calculations shows that pair interaction energies, their sums and solvation energies are well reproduced. The approach rivals the speed of simple distance dependent dielectric functions and the accuracy of the generalized Born model.     

A residue-pairwise generalized born scheme suitable for protein design calculations

We describe an efficient generalized Born (GB) approximation for proteins, in which the interaction energy between two amino acids depends on the whole protein structure, but can be accurately computed from residue-pairwise information. Two results make the scheme pairwise. First, an accurate expression exists for the interaction energy between two residues R and R' that depends on the product B = BRBR' of their residue Born solvation radii. Second, this expression is accurately fitted by a parabolic function of B; the (three) fitting coefficients depend only on the pair RR', not on its environment. In effect, the quantity B captures all the information that is relevant about the pair's dielectric environment. The method is tested with calculations on several hundred structures of the proteins trpcage, BPTI, ubiqutin, and thoredoxin. It yields solvation energies in better agreement with Poisson calculations than a traditional GB formulation. We also compute the effect of the protein/solvent environment on the interactions between pairs of charged residues in the active site of the enzyme aspartyl-tRNA synthetase. Our method captures this effect as accurately as traditional GB. Because it is residue-pairwise, the method can be incorporated into efficient protocols for rotamer placement and computational protein design.     

Structural studies of the interactions of normal and abnormal human plasmins with bovine basic pancreatic trypsin inhibitor

Catalytic activity of human plasmin is inhibited by bovine basic pancreatic trypsin inhibitor (BPTI, also known as aprotinin). In spite of increased interest in the function of BPTI as an inhibitor of plasmin, the 3-D structure of the plasmin-BPTI complex has not yet been determined. Therefore, in the present paper, the structure of the plasmin-BPTI complex was constructed by the homology modeling method, which provided information about the high affinity of plasmin for BPTI. Moreover, normal mode analyses of free plasmin, free BPTI and the plasmin-BPTI complex were carried out to investigate the changes in dynamics following complex formation. After study of the plasmin-BPTI interaction, we also investigated the binding of BPTI with abnormal plasmin, theoretically and experimentally. The result showing that BPTI binds to abnormal plasmin in the same way as it does to normal plasmin supports the previous finding that the difference between normal and abnormal plasmins is very small and that the abnormality is localized to the catalytic site.