Evaluation Of Solvation Free Energies Research Articles

Chemically Interpretable Graph Interaction Network for Prediction of Pharmacokinetic Properties of Drug-Like Molecules

Solubility of drug molecules is related to pharmacokinetic properties such as absorption and distribution, which affects the amount of drug that is available in the body for its action. Computational or experimental evaluation of solvation free energies of drug-like molecules/solute that quantify solubilities is an arduous task and hence development of reliable computationally tractable models is sought after in drug discovery tasks in pharmaceutical industry. Here, we report a novel method based on graph neural network to predict solvation free energies. Previous studies considered only the solute for solvation free energy prediction and ignored the nature of the solvent, limiting their practical applicability. The proposed model is an end-to-end framework comprising three phases namely, message passing, interaction and prediction phases. In the first phase, message passing neural network was used to compute inter-atomic interaction within both solute and solvent molecules represented as molecular graphs. In the interaction phase, features from the preceding step is used to calculate a solute-solvent interaction map, since the solvation free energy depends on how (un)favorable the solute and solvent molecules interact with each other. The calculated interaction map that captures the solute-solvent interactions along with the features from the message passing phase is used to predict the solvation free energies in the final phase. The model predicts solvation free energies involving a large number of solvents with high accuracy. We also show that the interaction map captures the electronic and steric factors that govern the solubility of drug-like molecules and hence is chemically interpretable.

A study on the transferability of the sigma enlarging bridge function for an accurate evaluation of solvation free energy: The case of homonuclear Lennard-Jones diatomic solute solvated in a Lennard-Jones monatomic solvent

We study the applicability of sigma enlarging bridge (SEB) function to a homonuclear Lennard-Jones (LJ) diatomic solute molecule solvated in an LJ monatomic solvent, where the SEB was originally proposed for a monatomic solute molecule to improve the accuracy of the solvation free energy (SFE) [T. Miyata, Bull. Chem. Soc. Jpn. 90, 1095 (2017)]. Our interest is focused on the transferability of the SEB parameter, which is a parameter included in the SEB function. We employ the two-dimensional Ornstein-Zernike (OZ) theory. Hypernetted chain (HNC), Kovalenko-Hirata (KH) and Percus-Yevick (PY) closures are considered. The HNC closure with the SEB correction (SEB-HNC) and the counterpart for the KH closure (SEB-KH) are also examined in terms of the SFE. It is found that by comparing with the molecular dynamics simulation, the SFE is overestimated under both HNC and KH closures, whereas it tends to be underestimated under PY closures. These results are similar to those obtained for systems of LJ monatomic solute molecules. Both the SEB-HNC and the SEB-KH closures provide quite an accurate SFE, when the SEB parameter values that were originally evaluated for a monatomic solute molecule are applied to the homonuclear LJ diatomic solute. This indicates that the SEB parameter is transferable. The transferability of the SEB parameter is also confirmed in terms of the angular-dependent one-dimensional distribution function, which is obtained from the two-dimensional distribution function. The validity of the partial molar volume correction is also discussed by examining the dependence of the SFE errors on the solute volume.

Evaluation of solvation free energies for small molecules with the AMOEBA polarizable force field.

The effects of electronic polarization in biomolecular interactions will differ depending on the local dielectric constant of the environment, such as in solvent, DNA, proteins, and membranes. Here the performance of the AMOEBA polarizable force field is evaluated under nonaqueous conditions by calculating the solvation free energies of small molecules in four common organic solvents. Results are compared with experimental data and equivalent simulations performed with the GAFF pairwise‐additive force field. Although AMOEBA results give mean errors close to “chemical accuracy,” GAFF performs surprisingly well, with statistically significantly more accurate results than AMOEBA in some solvents. However, for both models, free energies calculated in chloroform show worst agreement to experiment and individual solutes are consistently poor performers, suggesting non‐potential‐specific errors also contribute to inaccuracy. Scope for the improvement of both potentials remains limited by the lack of high quality experimental data across multiple solvents, particularly those of high dielectric constant. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

A modified repulsive bridge correction to accurate evaluation of solvation free energy in integral equation theory for molecular liquids

Integral equation theory for molecular liquids is one of the powerful frameworks to evaluate solvation free energy (SFE). Different from molecular simulation methods, the theory computes SFE in an analytical manner. In particular, the correction method proposed by Kovalenko and Hirata [Chem. Phys. Lett. 290, 237 (1998); and J. Chem. Phys. 113, 2793 (2000)] is quite efficient in the accurate evaluation of SFE. However, the application has been limited to aqueous solution systems. In the present study, an improved method is proposed that is applicable to a wide range of solution systems. The SFE of a variety of solute molecules in chloroform and benzene solvents is evaluated. A key is the adequate treatment of excluded volume in SFE calculation. By utilizing the information of chemical bonds in the solvent molecule, the accurate computation of SFE is achieved.

Accelerating QM/MM free energy calculations: representing the surroundings by an updated mean charge distribution.

Reliable studies of enzymatic reactions by combined quantum mechanical/molecular mechanics (QM(ai)/MM) approaches with an ab initio description of the quantum region presents a major challenge to computational chemists. The main problem is the need for very large computer time to evaluate the QM energy, which in turn makes it extremely challenging to perform proper configurational sampling. One of the most obvious options for accelerating QM/MM simulations is the use of an average solvent potential. In fact, the idea of using an average solvent potential is rather obvious and has implicitly been used in Langevin dipole/QM calculations. However, in the case of explicit solvent models the practical implementations are more challenging, and the accuracy of the averaging approach has not been validated. The present study introduces the average effect of the fluctuating solvent charges by using equivalent charge distributions, which are updated every m steps. Several models are evaluated in terms of the resulting accuracy and efficiency. The most effective model divides the system into an inner region with N explicit solvent atoms and an external region with two effective charges. Different models are considered in terms of the division of the solvent system and the update frequency. Another key element of our approach is the use of the free energy perturbation (FEP) and/or linear response approximation treatments that guarantees the evaluation of the rigorous solvation free energy. Special attention is paid to the convergence of the calculated solvation free energies and the corresponding solute polarization. The performance of the method is examined by evaluating the solvation of a water molecule and a formate ion in water and also the dipole moment of water in water solution. Remarkably, it is found that different averaging procedures eventually converge to the same value but some protocols provide optimal ways of obtaining the final QM(ai)/MM converged results. The current method can provide computational time saving of 1000 for properly converging simulations relative to calculations that evaluate the QM(ai)/MM energy every time step. A specialized version of our approach that starts with a classical FEP charging and then evaluates the free energy of moving from the classical potential to the QM/MM potential appears to be particularly effective. This approach should provide a very powerful tool for QM(ai)/MM evaluation of solvation free energies in aqueous solutions and proteins.

A general treatment of solubility. 1. The QSPR correlation of solvation free energies of single solutes in series of solvents.

We present an extended QSPR modeling of solubilities of about 500 substances in series of up to 69 diverse solvents. The models are obtained with our new software package, CODESSA PRO, which is furnished with an advanced variable selection procedure and a large pool of theoretically derived molecular descriptors. The squared correlation coefficients and squared standard deviations (variances) range from 0.837 and 0.1 for 2-pyrrolidone to 0.998 and 0.02 for dipropyl ether, respectively. The predictive power of the models was verified by using the "leave-one-out" cross-validation procedure. The QSPR models presented are suitable for the rapid evaluation of solvation free energies of organic compounds.

Solving the Poisson equation for solute–solvent systems using fast Fourier transforms

An iterative algorithm based on fast Fourier transforms is proposed to solve the Poisson equation for systems of heterogeneous permittivity (e.g., solute cavity in a solvent) under periodic boundary conditions. The method makes explicit use of the dipole–dipole interaction tensor, and is thus easily generalizable to arbitrary forms of electrostatic interactions (e.g., Coulomb’s law with straight or smooth cutoff truncation). The convergence properties of the algorithm and the influence of various model parameters are investigated in detail, and a set of appropriate values for these parameters is determined. The algorithm is further tested by application to three types of systems (a single spherical ion, two spherical ions, and small biomolecules), and comparison with analytical results (single ion) and with results obtained using a finite-difference solver under periodic boundary conditions. The proposed algorithm performs very well in terms of accuracy and convergence properties, with an overall speed comparable in the current implementation to that of a typical finite-difference solver. Future developments and applications of the algorithm will include: (i) the assessment of periodicity- and cutoff-induced artifacts in explicit-solvent simulations; (ii) the design of new electrostatic schemes for explicit-solvent simulations mimicking more accurately bulk solution; (iii) a faster evaluation of solvation free energies based on continuum electrostatics in cases where periodicity-induced artifacts can be neglected.

On the use of potential derived (PD) atomic charges for the evaluation of solvation free energy

The electrostatic portion of the solvation free energy ΔG sol was computed for a representative set of molecules by using ab initio SCF wavefunctions (6–31G ∗ and 6–31G ∗∗) and atomic charges obtained by fitting the molecular electrostatic potential (PD charges). Several versions of PD charges, related to 3–21G, 6–31G and 6–31G ∗∗ SCF calculations and to MNDO and AM 1 semiempirical wavefunctions were examined. The effects due to the polarization of the solute induced by the solvent reaction field were also examined. The calculations were all performed using the same program, based on a continuum distribution of the solvent, and keeping constant the relevant computational parameters (solute geometry, cavity, etc.). The results indicate that PD charges give reasonable descriptions of ΔG sol, the best fitting ab initio results being obtained by the Singh-Kollman procedure.