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.     

Microscopic and semimicroscopic calculations of electrostatic energies in proteins by the POLARIS and ENZYMIX programs

Different microscopic and semimicroscopic approaches for calculations of electrostatic energies in macromolecules are examined. This includes the Protein Dipoles Langevin Dipoles (PDLD) method, the semimicroscopic PDLD (PDLD/S) method, and a free energy perturbation (FEP) method. The incorporation of these approaches in the POLARIS and ENZYMIX modules of the MOLARIS package is described in detail. The PDLD electrostatic calculations are augmented by estimates of the relevant hydrophobic and steric contributions, as well as the effects of the ionic strength and external pH. Determination of the hydrophobic energy involves an approach that considers the modification of the effective surface area of the solute by local field effects. The steric contributions are analyzed in terms of the corresponding reorganization energies. Ionic strength effects are studied by modeling the ionic environment around the given system using a grid of residual charges and evaluating the relevant interaction using Coulomb's law with the dielectric constant of water. The performance of the FEP calculations is significantly enhanced by using special boundary conditions and evaluating the long-range electrostatic contributions using the Local Reaction Field (LRF) model. A diverse set of electrostatic effects are examined, including the solvation energies of charges in proteins and solutions, energetics of ion pairs in proteins and solutions, interaction between surface charges in proteins, and effect of ionic strength on such interactions, as well as electrostatic contributions to binding and catalysis in solvated proteins. Encouraging results are obtained by the microscopic and semimicroscopic approaches and the problems associated with some macroscopic models are illustrated. The PDLD and PDLD/S methods appear to be much faster than the FEP approach and still give reasonable results. In particular, the speed and simplicity of the PDLD/S method make it an effective strategy for calculations of electrostatic free energies in interactive docking studies. Nevertheless, comparing the results of the three approaches can provide a useful estimate of the accuracy of the calculated energies. © 1993 John Wiley & Sons, Inc.     

Implicit solvent models: Combining an analytical formulation of continuum electrostatics with simple models of the hydrophobic effect

The recent development of approximate analytical formulations of continuum electrostatics opens the possibility of efficient and accurate implicit solvent models for biomolecular simulations. One such formulation (ACE, Schaefer & Karplus, J. Phys. Chem., 1996, 100:1578) is used to compute the electrostatic contribution to solvation and conformational free energies of a set of small solutes and three proteins. Results are compared to finite-difference solutions of the Poisson equation (FDPB) and explicit solvent simulations and experimental data where available. Small molecule solvation free energies agree with FDPB within 1–1.5 kcal/mol, which is comparable to differences in FDPB due to different surface treatments or different force field parameterizations. Side chain conformation free energies of aspartate and asparagine are in qualitative agreement with explicit solvent simulations, while 74 conformations of a surface loop in the protein Ras are accurately ranked compared to FDPB. Preliminary results for solvation free energies of small alkane and polar solutes suggest that a recent Gaussian model could be used in combination with analytical continuum electrostatics to treat nonpolar interactions. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 322–335, 1999     

The configurational dependence of binding free energies: A Poisson–Boltzmann study of Neuraminidase inhibitors

The linear finite difference Poisson-Boltzmann (FDPB) equation is applied to the calculation of the electrostatic binding free energies of a group of inhibitors to the Neuraminidase enzyme. An ensemble of enzyme-inhibitor complex conformations was generated using Monte Carlo simulations and the electrostatic binding free energies of subtly different configurations of the enzyme-inhibitor complexes were calculated. It was seen that the binding free energies calculated using FDPB depend strongly on the configuration of the complex taken from the ensemble. This configurational dependence was investigated in detail in the electrostatic hydration free energies of the inhibitors. Differences in hydration energies of up to 7 kcal mol^–1 were obtained for root mean square (RMS) structural deviations of only 0.5 Å. To verify the result, the grid size and parameter dependence of the calculated hydration free energies were systematically investigated. This showed that the absolute hydration free energies calculated using the FDPB equation were very sensitive to the values of key parameters, but that the configurational dependence of the free energies was independent of the parameters chosen. Thus just as molecular mechanics energies are very sensitive to configuration, and single-structure values are not typically used to score binding free energies, single FDPB energies should be treated with the same caution.     

Thermodynamic Parameters for the Association of Fluorinated Benzenesulfonamides with Bovine Carbonic Anhydrase II

This paper describes a calorimetric study of the association of a series of seven fluorinated benzenesulfonamide ligands (C₆H_nF_5?nSO₂NH₂) with bovine carbonic anhydrase II (BCA). Quantitative structure–activity relationships between the free energy, enthalpy, and entropy of binding and pK_a and log P of the ligands allowed the evaluation of the thermodynamic parameters in terms of the two independent effects of fluorination on the ligand: its electrostatic potential and its hydrophobicity. The parameters were partitioned to the three different structural interactions between the ligand and BCA: the Zn^II cofactor–sulfonamide bond (≈65 % of the free energy of binding), the hydrogen bonds between the ligand and BCA (≈10 %), and the contacts between the phenyl ring of the ligand and BCA (≈25 %). Calorimetry revealed that all of the ligands studied bind in a 1:1 stoichiometry with BCA; this result was confirmed by ¹⁹F NMR spectroscopy and X‐ray crystallography (for complexes with human carbonic anhydrase II).     

Linear free energy relationships implicate three modes of binding for fluoroaromatic inhibitors to a mutant of carbonic anhydrase II

[figure: see text] Linear free energy relationships between binding affinity and hydrophobicity for a library of fluoroaromatic inhibitors of F131V carbonic anhydrase II (CA) implicate three modes of interaction. X-ray crystal structures suggest that F131 interacts with fluoroaromatic inhibitors, while P202, on the opposite side of the active site cleft, serves as the site of the hydrophobic contact in the case of the F131V mutant. 2-Fluorinated compounds bind more tightly, perhaps due to the field effect of the nearby fluorine on the acidity of the amide proton.     

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.     

Estimation of relative binding free energy based on a free energy variational principle for the FKBP-ligand system

Predicting an accurate binding free energy between a target protein and a ligand can be one of the most important steps in a drug discovery process. Often, many molecules must be screened to find probable high potency ones. Thus, a computational technique with low cost is highly desirable for the estimation of binding free energies of many molecules. Several techniques have thus far been developed for estimating binding free energies. Some techniques provide accurate predictions of binding free energies but high large computational cost. Other methods give good predictions but require tuning of some parameters to predict them with high accuracy. In this study, we propose a method to predict relative binding free energies with accuracy comparable to the results of prior methods but with lower computational cost and with no parameter needing to be carefully tuned. Our technique is based on the free energy variational principle. FK506 binding protein (FKBP) with 18 ligands is taken as a test system. Our results are compared to those from other widely used techniques. Our method provides a correlation coefficient (r ² ) of 0.80 between experimental and calculated relative binding free energies and yields an average absolute error of 0.70 kcal/mol compared to experimental values. These results are comparable to or better than results from other techniques. We also discuss the possibility to improve our method further.     

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.     

Evaluation of the 1-octanol/water partition coefficient of nucleoside analogs via free energy estimated in quantum chemical calculations

The partition coefficients (logP) of nucleoside analogs determined by the difference in the free energies of hydration and solvation in water-saturated octanol using the thermodynamic integration method are reported. The logP values calculated in this approach are closer to the experimental values compared to other ab initio methods. Solvation free energy in water and octanol, free energy of cavity formation in water and Henry’s constants, and some other parameters are estimated at the density functional theory (DFT) and Hartree-Fock level with 6–31G*, 6–31G, and 6–31+G basis sets. Surface area, mass, refractivity, volume, polarizability, and dipole moment are calculated for some drugs with HF and DFT methods. The results show that log P decreases with the decrease in polarizability and the increase in dipole moment.     

Frozen density functional free energy simulations of redox proteins: computational studies of the reduction potential of plastocyanin and rusticyanin

The evaluation of reduction potentials of proteins by ab initio approaches presents a major challenge for computational chemistry. This is addressed in the present investigation by reporting detailed calculations of the reduction potentials of the blue copper proteins plastocyanin and rusticyanin using the QM/MM all-atom frozen density functional theory, FDFT, method. The relevant ab initio free energies are evaluated by using a classical reference potential. This approach appears to provide a general consistent and effective way for reproducing the configurational ensemble needed for consistent ab initio free energy calculations. The FDFT formulation allows us to treat a large part of the protein quantum mechanically by a consistently coupled QM/QM/MM embedding method while still retaining a proper configurational sampling. To establish the importance of proper configurational sampling and the need for a complete representation of the protein+solvent environment, we also consider several classical approaches. These include the semi-macroscopic PDLD/S-LRA method and classical all-atom simulations with and without a polarizable force field. The difference between the reduction potentials of the two blue copper proteins is reproduced in a reasonable way, and its origin is deduced from the different calculations. It is found that the protein permanent dipole tunes down the reduction potential for plastocyanin compared to the active site in regular water solvent, whereas in rusticyanin it is instead tuned up. This electrostatic environment, which is the major effect determining the reduction potential, is a property of the entire protein and solvent system and cannot be ascribed to any particular single interaction.     

The pattern of fluorine substitution affects binding affinity in a small library of fluoroaromatic inhibitors for carbonic anhydrase

[formula: see text] A library of fluoroaromatic inhibitors of carbonic anhydrase has been found to bind in a manner dependent on both hydrophobicity and the pattern of substitution of the fluoroaromatic ring. All of the compounds in the library bind to the protein with Kd < 3 nM. We have inferred two distinct binding modes from our data, which suggest two types of interactions that should be considered when designing fluorinated drugs.     

Specific empirical free energy function for automated docking of carbohydrates to proteins

We present an automated docking protocol specifically optimized to predict the structure and affinity of a protein-carbohydrate complex. A scoring function was developed based on a training set of 30 protein-carbohydrate complexes of known structure and affinity. Combinations of several models for hydrogen bonding, torsional entropy loss, and solvation were tested for their ability to fit the training set data, and the best model was used with AutoDock. The electrostatic empirical coefficient is larger than in a previously obtained model using a training set comprised of various types of protein-ligand complexes, indicating that electrostatic interactions play a more important role in determining the affinity between a carbohydrate and a protein. The differences in the relative weighting of the empirical coefficients in the model yields predicted free energies for the training set with a standard error of 1.403 kcal/mol. The new scoring function was tested on 17 Aspergillus niger glucoamylase inhibitors for which binding energies had been determined experimentally. Free energies of complex formation were predicted with a residual standard error of 1.101 kcal/mol. The new scoring function therefore provides a robust method for predicting free energies of formation and optimal conformations of carbohydrate-protein complexes.     

Electrostatic binding energy calculation using the finite difference solution to the linearized Poisson-Boltzmann equation: Assessment of its accuracy

A full account of how to calculate the electrostatic binding energy using the finite difference solution to the linearized Poisson-Boltzmann equation (FDPB) for protein-ligand systems is described. The following tests show that the statistical and systematic errors due to discrete grid representation of molecular shape and charges amount to about 1% and 5% of calculated binding energy difference, respectively. The greater accuracy results from a three-stage error cancellation: first in ΔG_s, then ΔΔGd_s, and finally ΔΔG_ele. We conclude in this study that the intrinsic error of FDPB is mostly canceled in computing binding energy differences. Among the parameters examined, the partial charge, dielectric constant, and radius of solvent can influence the calculated results most. © 1996 by John Wiley & Sons, Inc.     

Computation of the binding affinities of catechol‐O‐methyltransferase inhibitors: Multisubstate relative free energy calculations

Alchemical free energy simulations are amongst the most accurate techniques for the computation of the free energy changes associated with noncovalent protein–ligand interactions. A procedure is presented to estimate the relative binding free energies of several ligands to the same protein target where multiple, low‐energy configurational substates might coexist, as opposed to one unique structure. The contributions of all individual substates were estimated, explicitly, with the free energy perturbation method, and combined in a rigorous fashion to compute the overall relative binding free energies and dissociation constants. It is shown that, unless the most stable bound forms are known a priori, inaccurate results may be obtained if the contributions of multiple substates are ignored. The method was applied to study the complex formed between human catechol‐O‐methyltransferase and BIA 9‐1067, a newly developed tight‐binding inhibitor that is currently under clinical evaluation for the therapy of Parkinson's disease. Our results reveal an exceptionally high‐binding affinity (K_d in subpicomolar range) and provide insightful clues on the interactions and mechanism of inhibition. The inhibitor is, itself, a slowly reacting substrate of the target enzyme and is released from the complex in the form of O‐methylated product. By comparing the experimental catalytic rate (k_cat) and the estimated dissociation rate (k_off) constants of the enzyme‐inhibitor complex, one can conclude that the observed inhibition potency (K_i) is primarily dependent on the catalytic rate constant of the inhibitor's O‐methylation, rather than the rate constant of dissociation of the complex. © 2012 Wiley Periodicals, Inc.     

Models of F.H contacts relevant to the binding of fluoroaromatic inhibitors to carbonic anhydrase II

[formula: see text] Complexes formed between fluorobenzene and N-methylformamide or benzene have been used as models of the interaction of fluoroaromatic drugs with carbonic anhydrase II. These structures have been investigated via ab initio and density functional methods, including HF, B3LYP, and MP2 procedures. The results of the calculations are consistent with the hypothesis, suggested originally by experimental X-ray crystal structures of the drug-receptor complexes, that favorable fluorine-hydrogen interactions affect binding affinity.     

The SGB/NP hydration free energy model based on the surface generalized born solvent reaction field and novel nonpolar hydration free energy estimators

The development and parameterization of a solvent potential of mean force designed to reproduce the hydration thermodynamics of small molecules and macromolecules aimed toward applications in conformation prediction and ligand binding free energy prediction is presented. The model, named SGB/NP, is based on a parameterization of the Surface Generalized Born continuum dielectric electrostatic model using explicit solvent free energy perturbation calculations and a newly developed nonpolar hydration free energy estimator motivated by the results of explicit solvent simulations of the thermodynamics of hydration of hydrocarbons. The nonpolar model contains, in addition to the more commonly used solvent accessible surface area term, a component corresponding to the attractive solute-solvent interactions. This term is found to be important to improve the accuracy of the model, particularly for cyclic and hydrogen bonding compounds. The model is parameterized against the experimental hydration free energies of a set of small organic molecules. The model reproduces the experimental hydration free energies of small organic molecules with an accuracy comparable or superior to similar models employing more computationally demanding estimators and/or a more extensive set of parameters.     

Calculation of solvation and binding free energy differences between VX-478 and its analogs by free energy perturbation and AMSOL methods

Summary VX-478 belongs to a novel class of HIV-1 protease inhibitors that are based on N,N-disubstituted benzene sulfonamides. Force field parameters for the N,N-dialkyl benzene sulfonamide moiety have been assembled from the literature and from our own ab initio calculations. These parameters were employed to calculate solvation and binding free energy differences between VX-478 and two analogs. The free energy perturbation method has been used to determine these differences using two approaches. In the first approach, intergroup interaction terms only were included in the calculation of free energies (as in most reports of free energy calculations using AMBER). In the second approach, both the inter- and intragroup interaction terms were included. The results obtained with the two approaches are in excellent agreement with each other and are also in close agreement with the experimental results. The solvation free energies of N,N-dimethyl benzene sulfonamide derivatives (truncated models of the inhibitors), calculated using continuum solvation (AMSOL) methods, are found to be in qualitative agreement with the experimental and free energy perturbation results. The binding and solvation free energy results are discussed in the context of structure-based drug design to show how physicochemical properties (for example aqueous solubilities and bioavailabilities) of these HIV-1 protease inhibitors were improved, while maintaining their inhibitory potency.     

Electrostatic energy calculations by a Finite-difference method: Rapid calculation of charge–solvent interaction energies

Finite-difference Poisson–Boltzmann (FDPB) methods allow a fast and accurate calculations of the reaction field (charge–solvent) energies for molecular systems. Unfortunately, the energy in the FDPB calculations includes the self-energies and the finite-difference approximation to the Coulombic energies as well as the reaction field energy. A second finite-difference calculation, in a uniform dielectric, is therefore necesssary to eliminate these contributions. In this article we describe a rapid and accurate method to calculate the self energy and finite-difference Coulombic energies in a uniform dielectric thus eliminating the need for a second finite-difference calculation. The computational savings for this method range from a factor of 4 for a typical protein to a factor of 10³ for small molecules. © 1992 by John Wiley & Sons, Inc.