Role of protein structure and the role of individual fingers in zinc finger protein–DNA recognition: a molecular dynamics simulation study and free energy calculations

Molecular dynamics and MM_GBSA energy calculations on various zinc finger proteins containing three and four fingers bound to their target DNA gave insights into the role of each finger in the DNA binding process as part of the protein structure. The wild type Zif 268 (PDB code: 1AAY) gave a ΔG value of ??76.1 (14) kcal/mol. Zinc fingers ZF1, ZF2 and ZF3 were mutated in one experiment and in another experiment one finger was cut and the rest of the protein was studied for binding. The ΔΔG values for the Zinc Finger protein with both ZF1 and ZF2 mutated was +?80 kcal/mol, while mutating only ZF1 the ΔΔG value was +?52 kcal/mol (relative to the wild type). Cutting ZF3 and studying the protein consisting only of ZF1 linked to ZF2 gave a ΔΔG value of +?68 kcal/mol. Upon cutting ZF1, the resulting ZF2 linked to ZF3 protein gave a ΔΔG value of +?41 kcal/mol. The above results shed light on the importance of each finger in the binding process, especially the role of ZF1 as the anchoring finger followed in importance by ZF2 and ZF3. The energy difference between the binding of the wild type protein Zif268 (1AAY) and that for individual finger binding to DNA according to the formula: ΔΔG_{linkers, otherstructuralfactors}?=?ΔG_zif268???(ΔG_F1+F2+F3) gave a value?=???44.5 kcal/mol. This stabilization can be attributed to the contribution of linkers and other structural factors in the intact protein in the DNA binding process. DNA binding energies of variant proteins of the wild type Zif268 which differ in their ZF1 amino acid sequence gave evidence of a good relationship between binding energy and recognition and specificity, this finding confirms the reported vital role of ZF1 in the ZF protein scanning and anchoring to the target DNA sequence. The role of hydrogen bonds in both specific and nonspecific amino acid-DNA contacts is discussed in relation to mutations. The binding energies of variant Zinc Finger proteins confirmed the role of ZF1 in the recognition, specificity and anchoring of the zinc finger protein to DNA.     

Protein‐specific force field derived from the fragment molecular orbital method can improve protein–ligand binding interactions

Accurate computational estimate of the protein–ligand binding affinity is of central importance in rational drug design. To improve accuracy of the molecular mechanics (MM) force field (FF) for protein–ligand simulations, we use a protein‐specific FF derived by the fragment molecular orbital (FMO) method and by the restrained electrostatic potential (RESP) method. Applying this FMO‐RESP method to two proteins, dodecin, and lysozyme, we found that protein‐specific partial charges tend to differ more significantly from the standard AMBER charges for isolated charged atoms. We did not see the dependence of partial charges on the secondary structure. Computing the binding affinities of dodecin with five ligands by MM PBSA protocol with the FMO‐RESP charge set as well as with the standard AMBER charges, we found that the former gives better correlation with experimental affinities than the latter. While, for lysozyme with five ligands, both charge sets gave similar and relatively accurate estimates of binding affinities. © 2013 Wiley Periodicals, Inc.     

Homology modeling and molecular dynamic simulation of UDP-N-acetylmuramoyl-l-alanine-d-glutamate ligase (MurD) from Mycobacterium tuberculosis H37Rv using in silico approach

The present study aimed to identify the prospective inhibitors of MurD, a cytoplasmic enzyme that catalyzes the addition of d-glutamate to the UDP-N-acetylmuramoyl-l-alanine nucleotide precursor in Mycobacterium tuberculosis (MTB), using virtual screening, docking studies, pharmacokinetic analysis, Molecular Dynamic (MD) simulation, and Molecular Mechanics Generalized Born and Surface Area (MM-GBSA) analyses. The three dimensional (3D) structure was determined based on the homology technique using a template from Streptococcus agalactiae. The modeled structure had three binding sites, namely; substrate binding site (Val18, Thr19, Asp39, Asp40, Gly75, Asn147, Gln171 and His192), the ATP binding site (Gly123, Lys124, Thr125, Thr126, Glu166, Asp283, and Arg314) and the glutamic acid binding site (Arg382, Ser463, and Tyr470). These residues mentioned above play a critical role in the catalytic activity of the enzyme, and their inhibition could serve as a stumbling block to the normal function of the enzyme. A total of 10,344 obtained from virtual screened of Zinc and PubChem databases. These compounds further screened for Lipinski rule of five, docking studies and pharmacokinetic analysis. Four compounds with good binding energies (ZINC11881196 = −10.33 kcal/mol, ZINC12247644 = −8.90 kcal/mol, ZINC14995379 =−8.42 kcal/mol, and PubChem6185 = −8.20 kcal/mol), better than the binding energies of the ATP (−2.31 kcal/mol) and the ligand with known IC₅₀, Aminothiazole (−7.11 kcal/mol) were selected for the MD simulation and MM-GBSA analyses. The result of the analyses showed that all the four ligands formed a stable complex and had the binding free energies better than the binding energy of ATP. Therefore, these ligands considered as suitable prospective inhibitors of the MurD after experimental validation.     

Biophysical limits of protein-ligand binding

In classic work, Kuntz et al. (Proc. Nat. Acad. Sci. USA1999, 96, 9997-10002) introduced the concept of ligand efficiency. Though that study focused primarily on drug-like molecules, it also showed that metal binding led to the greatest ligand efficiencies. Here, the physical limits of binding are examined across the wide variety of small molecules in the Binding MOAD database. The complexes with the greatest ligand efficiencies share the trait of being small, charged ligands bound in highly charged, well buried binding sites. The limit of ligand efficiency is -1.75 kcal/mol·atom for the protein-ligand complexes within Binding MOAD, and 95% of the set have efficiencies below a "soft limit" of -0.83 kcal/mol·atom. On the basis of buried molecular surface area, the hard limit of ligand efficiency is -117 cal/mol·?(2), which is in surprising agreement with the limit of macromolecule-protein binding. Close examination of the most efficient systems reveals their incredibly high efficiency is dictated by tight contacts between the charged groups of the ligand and the pocket. In fact, a misfit of 0.24 ? in the average contacts inherently decreases the maximum possible efficiency by at least 0.1 kcal/mol·atom.     

Protein/ligand binding free energies calculated with quantum mechanics/molecular mechanics

The calculation of binding affinities for flexible ligands has hitherto required the availability of reliable molecular mechanics parameters for the ligands, a restriction that can in principle be lifted by using a mixed quantum mechanics/molecular mechanics (QM/MM) representation in which the ligand is treated quantum mechanically. The feasibility of this approach is evaluated here, combining QM/MM with the Poisson-Boltzmann/surface area model of continuum solvation and testing the method on a set of 47 benzamidine derivatives binding to trypsin. The experimental range of the absolute binding energy (DeltaG = -3.9 to -7.6 kcal/mol) is reproduced well, with a root-mean-square (RMS) error of 1.2 kcal/mol. When QM/MM is applied without reoptimization to the very different ligands of FK506 binding protein the RMS error is only 0.7 kcal/mol. The results show that QM/MM is a promising new avenue for automated docking and scoring of flexible ligands. Suggestions are made for further improvements in accuracy.     

Insilico validation and comparison of antifungal competence and druglikeness of some natural xanthones – A step towards antimycotic therapeutics

In the current work, the xanthones (from the plant source) that possess strong experimental evidences for their antifungal properties are chosen from the literatures and docking studies were employed with a fungal protein for computational validation to simplify the process of electing the top hits among a large set of naturally occurring substituted xanthones. The results indicate that computationally 86% of xanthones under study exhibits good binding affinity towards (B.E ≥ ?7 kcal/mol) the target protein (GlcN-6-P). The current docking analysis established the Garcinone D (?10.25 kcal/mol: Garcinia Mangostana), Caledol (?10.14 kcal/mol: Calophyllum Caledonicum), Jacareubin (?9.82 kcal/mol: Calophyllum Brasiliensis), γ-mangostin (?9.79 kcal/mol: Garcinia Mangostana) and 2-deprenylrheedia xanthone (?9.64 kcal/mol: Hypericum Roperanum) as good inhibitors of GlcN-6-P among a large set of natural xanthones. And also, most of xanthones have greater binding ability than the compared antifungal drugs. The effect of substituents on binding energy have also been investigated. A detailed analysis of drug likeness for 50 xanthones were also performed and found that most of the xanthone derivatives falls under the category of drug templates.     

A molecular docking study of potential inhibitors and repurposed drugs against SARS-CoV-2 main protease enzyme

COVID-19 has affected millions of people. Although many drugs are in use to combat disease, there is not any sufficient treatment yet. Having critical role in propagation of the novel coronavirus (SARS-CoV-2) works Main Protease up into a significant drug target. We have performed a molecular docking study to define possible inhibitor candidates against SARS-CoV-2 Main Protease enzyme. Besides docking Remdesivir, Ribavirin, Chloroquine and 28 other antiviral inhibitors (totally 31 inhibitors) to Main Protease enzyme, we have also performed a molecular docking study of 2177 ligands, which are used against Main Protease for the first time by using molecular docking program Autodock4. All ligands were successfully docked into Main Protease enzyme binding site. Among all ligands, EY16 coded ligand which previously used as EBNA1-DNA binding blocker candidate showed the best score for Main Protease with a binding free energy of −10.83 ​kcal/mol which was also lower than re-docking score of N3 ligand (−10.72 ​kcal/mol) contained in crystal structure of Main Protease. After analyzing the docking modes and docking scores we have found that our ligands have better binding free energy values than the inhibitors in use of treatment. We believe that further studies such as molecular dynamics or Molecular Mechanic Poisson Boltzmann Surface Area studies can make contribution that is more exhaustive to the docking results.     

Synthesis and greener pastures biological study of bis-thiadiazoles as potential Covid-19 drug candidates

A novel series of bis- (Abdelhamid et al., 2017, Banerjee et al., 2018, Bharanidharan et al., 2022)thiadiazoles was synthesized from the reaction of precursor dimethyl 2,2′-(1,2-diphenylethane-1,2-diylidene)-bis(hydrazine-1-carbodithioate) and hydrazonyl chlorides in ethanol under ultrasonic irradiation. Spectral tools (IR. NMR, MS, elemental analyses, molecular dynamic simulation, DFT and LUMO and HOMO) were used to elucidate the structure of the isolated products. Molecular docking for the precursor, 3 and ligands 6a-i to two COVID-19 important proteins M^pro and RdRp was compared with two approved drugs, Remdesivir and Ivermectin. The binding affinity varied between the ligands and the drugs. The highest recorded binding affinity of 6c with M^pro was (?9.2 kcal/mol), followed by 6b and 6a, (?8.9 and ?8.5 kcal/mol), respectively. The lowest recorded binding affinity was (?7.0 kcal/mol) for 6 g. In comparison, the approved drugs showed binding affinity (?7.4 and ?7.7 kcal/mol), for Remdesivir and Ivermectin, respectively, which are within the range of the binding affinity of our ligands. The binding affinity of the approved drug Ivermectin against RdRp recoded the highest (?8.6 kcal/mol), followed by 6a, 6 h, and 6i are the same have (?8.2 kcal/mol). The lowest reading was found for compound 3 ligand (?6.3 kcal/mol). On the other side, the amino acids also differed between the compounds studied in this project for both the viral proteins. The ligand 6a forms three H-bonds with Thr 319(A), Sr 255(A) and Arg 457(A), whereas Ivermectin forms three H-bonds with His 41(A), Gly143(A) and Gln 18(A) for viral M^pro. The RdRp amino acids residues could be divided into four groups based on the amino acids that interact with hydrogen or hydrophobic interactions. The first group contained 6d, 6b, 6 g, and Remdesivir with 1–4 hydrogen bonds and hydrophobic interactions 1 to 10. Group 2 is 6a and 6f exhibited 1 and 3 hydrogen bonds and 15 and 14 hydrophobic interactions. Group 3 has 6e and Ivermectin shows 4 and 3 hydrogen bonds, respectively and 11 hydrophobic interactions for both compounds. The last group contains ligands 3, 6c, 6 h, and 6i gave 1–3 hydrogen bonds and 6c and 3 recorded the highest number of hydrophobic interactions, 14 for both 6c and 6 h. Pro Tox-II estimated compounds’ activities as Hepatoxic, Carcinogenic and Mutagenic, revealing that 6f-h were inactive in all five similar to that found with Remdesivir and Ivermectin. The drug-likeness prediction was carried out by studying physicochemical properties, lipophilicity, size, polarity, insolubility, unsaturation, and flexibility. Generally, some properties of the ligands were comparable to that of the standards used in this study, Remdesivir and Ivermectin.     

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.     

Calculation of absolute ligand binding free energy to a ribosome-targeting protein as a function of solvent model

A comparative analysis is provided of the effect of different solvent models on the calculation of a potential of mean force (PMF) for determining the absolute binding affinity of the small molecule inhibitor pteroic acid bound to ricin toxin A-chain (RTA). Solvent models include the distance-dependent dielectric constant, several different generalized Born (GB) approximations, and a hybrid explicit/GB-based implicit solvent model. We found that the simpler approximation of dielectric screening and a GB model, with Born radii fitted to a switching-window dielectric-boundary surface Poisson solvent model, severely overpredicted the binding affinity as compared to the experimental value, estimated to range from -4.4 to -6.0 kcal/mol. In contrast, GB models that are parametrized to fit the Lee-Richards molecular surface performed much better, predicting binding free energy within 1-3 kcal/mol of experimental estimates. However, the predicted free-energy profiles of these GB models displayed alternative binding modes not observed in the crystal structure. Finally, the most rigorous and computationally costly approach in this work, which used a hybrid explicit/implicit solvent model, correctly determined a binding funnel in the PMF near the crystallographic bound state and predicted an absolute binding affinity that was 2 kcal/mol more favorable than the estimated experimental binding affinity.     

Prediction of SAMPL4 host–guest binding affinities using funnel metadynamics

Accurately predicting binding affinities between ligands and macromolecules has been a much sought-after goal. A tremendous amount of resources can be saved in the pharmaceutical industry through accurate binding-affinity prediction and hence correct decision-making for the drug discovery processes. Owing to the structural complexity of macromolecules, one of the issues in binding affinity prediction using molecular dynamics is the adequate sampling of the conformational space. Recently, the funnel metadynamics method (Limongelli et al. in Proc Natl Acad Sci USA 110:6358, 2013) was developed to enhance the sampling of the ligand at the binding site as well as in the solvated state, and offer the possibility to predict the absolute binding free energy. We apply funnel metadynamics to predict host–guest binding affinities for the cucurbit[7]uril host as part of the SAMPL4 blind challenge. Using total simulation times of 300–400 ns per ligand, we show that the errors due to inadequate sampling are below 1 kcal/mol. However, despite the large investment in terms of computational time, the results compared to experiment are not better than a random guess. As we obtain differences of up to 11 kcal/mol when switching between two commonly used force fields (with automatically generated parameters), we strongly believe that in the pursuit of accurate binding free energies a more careful force-field parametrization is needed to address this type of system.     

A free energy calculation study of the effect of H-->F substitution on binding affinity in ligand-antibody interactions

Changes in binding affinity to catalytic antibody 6D9 of chloramphenicol phosphonate derivatives (CPDs) containing H or F were investigated by performing free energy calculations based on molecular dynamics simulations. We calculated the binding free energy, enthalpy, and entropy changes (DeltaDeltaG, DeltaDeltaH, and -TDeltaDeltaS) attributable to H-->F substitution by comparing results for CPDs containing a trifluoroacetylamino group (CPD-F) or an acetylamino group (CPD-H). The calculated DeltaDeltaG, DeltaDeltaH, and -TDeltaDeltaS values were -2.9, -6.3, and 3.5 kcal mol(-1) and close to experimental values observed for a series of similar ligands, chloramphenicol phosphonates with F and H (-1.4, -3.5, and 2.1 kcal mol(-1)). Therefore, CPD-F binds more strongly to 6D9 than does CPD-H. To clarify the origin of the large difference in DeltaDeltaG, we apportioned the calculated values of DeltaDeltaG and DeltaG for the associated and dissociated states into contributions from various atomic interactions. We found that the H-->F substitution increased the binding affinity mainly by decreasing the hydration free energy and not by increasing favorable interactions with the antibody. The decreased hydration free energy of the ligand was mainly due to unfavorable coulombic interactions between the trifluoroacetylamino group and solvent waters, which increased the free energy of the dissociated state (by about 3.7 kcal mol(-1)). Also, the trifluoroacetylamino group slightly increased the free energy level of the associated state (about 0.8 kcal mol(-1)) because favorable van der Waals interactions compensated for unfavorable coulombic interactions with antibody atoms. In addition, the enthalpy and entropy changes, DeltaDeltaH and -TDeltaDeltaS (computationally -6.3 and 3.5 kcal mol(-1)), originated mainly from a decrease in hydration free energy in the dissociated state. The CPD-F and CPD-H ligands had substantially different structures in the dissociated and complexed states.     

Density functional theory investigation of the binding interactions between phosphoryl,carbonyl, imino,and thiocarbonyl ligands and the pentaaqua nickel(II) complex: Coordination affinity and associated parameters

Density Functional Theory (UB3LYP/6‐311++G(d,p)) calculations of the affinity of the pentaaqua nickel(II) complex for a set of phosphoryl [O?P(H)(CH₃)(PhR)], imino [HN?C(CH₃)(PhR)], thiocarbonyl [S?C(CH₃)(PhR)] and carbonyl [O?C(CH₃)(PhR)] ligands were performed, where R?NH₂, OCH₃, OH, CH₃, H, Cl, CN, and NO₂ is a substituent at the para‐position of a phenyl ring.The affinity of the pentaaqua nickel(II) complex for these ligands was analized and quantified in terms of interaction enthalpy (ΔH), Gibbs free energy (ΔG²⁹⁸), geometric and electronic parameters of the resultant octahedral complexes. The ΔH and ΔG²⁹⁸ results show that the ligand coordination strength increases in the following order: carbonyl < thiocarbonyl < imino < phosphoryl. This coordination strength order is also observed in the analysis of the metal‐ligand distances and charges on the ligand atom that interacts with the Ni(II) cation. The electronic character of the substituent R is the main parameter that affects the strength of the metal‐ligand coordination. Ligands containing electron‐donating groups (NH₂, OCH₃, OH) have more exothermic ΔH and ΔG²⁹⁸ than ligands with electron‐withdrawing groups (Cl, CN, NO₂). The metal‐ligand interaction decomposed by means of the energy decomposition analysis (EDA) method shows that the electronic character of the ligand modulates all the components of the metal‐ligand interaction. The absolute softness of the free ligands is correlated with the covalent contribution to the instantaneous interaction energy calculated using the EDA method. © 2013 Wiley Periodicals, Inc.     

Icotinib,Almonertinib, and Olmutinib: A 2D Similarity/Docking-Based Study to Predict the Potential Binding Modes and Interactions into EGFR

In the current study, a 2D similarity/docking-based study was used to predict the potential binding modes of icotinib, almonertinib, and olmutinib into EGFR. The similarity search of icotinib, almonertinib, and olmutinib against a database of 154 EGFR ligands revealed the highest similarity scores with erlotinib (0.9333), osimertinib (0.9487), and WZ4003 (0.8421), respectively. In addition, the results of the docking study of the three drugs into EGFR revealed high binding free energies (ΔG_b = −6.32 to −8.42 kcal/mol) compared to the co-crystallized ligands (ΔG_b = −7.03 to −8.07 kcal/mol). Analysis of the top-scoring poses of the three drugs was done to identify their potential binding modes. The distances between Cys797 in EGFR and the Michael acceptor sites in almonertinib and olmutinib were determined. In conclusion, the results could provide insights into the potential binding characteristics of the three drugs into EGFR which could help in the design of new more potent analogs.     

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.     

Combined molecular dynamics and continuum solvent approaches (MM-PBSA/GBSA) to predict noscapinoid binding to γ-tubulin dimer

γ-tubulin plays crucial role in the nucleation and organization of microtubules during cell division. Recent studies have also indicated its role in the regulation of microtubule dynamics at the plus end of the microtubules. Moreover, γ-tubulin has been found to be over-expressed in many cancer types, such as carcinomas of the breast and glioblastoma multiforme. These studies have led to immense interest in the identification of chemical leads that might interact with γ-tubulin and disrupt its function in order to explore γ-tubulin as potential chemotherapeutic target. Recently a colchicine-interacting cavity was identified at the interface of γ-tubulin dimer that might also interact with other similar compounds. In the same direction we theoretically investigated binding of a class of compounds, noscapinoids (noscapine and its derivatives) at the interface of the γ-tubulin dimer. Molecular interaction of noscapine and two of its derivatives, amino-noscapine and bromo-noscapine, was investigated by molecular docking, molecular dynamics simulation and binding free energy calculation. All noscapinoids displayed stable interaction throughout simulation of 25 ns. The predictive binding free energy (ΔG_bind) indicates that noscapinoids bind strongly with the γ-tubulin dimer. However, bromo-noscapine showed the best binding affinity (ΔG_bind = –37.6 kcal/mol) followed by noscapine (ΔG_bind = –29.85 kcal/mol) and amino-noscapine (ΔG_bind = –23.99 kcal/mol) using the MM-PBSA method. Similarly using the MM-GBSA method, bromo-noscapine showed highest binding affinity (ΔG_bind = –43.64 kcal/mol) followed by amino-noscapine (ΔG_bind = –37.56 kcal/mol) and noscapine (ΔG_bind = –34.57 kcal/mol). The results thus generate compelling evidence that these noscapinoids may hold great potential for preclinical and clinical evaluation.     

Direct calculation of the binding free energies of FKBP ligands

Direct calculations of the absolute free energies of binding for eight ligands to FKBP protein were performed using the Fujitsu BioServer massively parallel computer. Using the latest version of the general assisted model building with energy refinement (AMBER) force field for ligand model parameters and the Bennett acceptance ratio for computing free-energy differences, we obtained an excellent linear fit between the calculated and experimental binding free energies. The rms error from a linear fit is 0.4 kcal/mol for eight ligand complexes. In comparison with a previous study of the binding energies of these same eight ligand complexes, these results suggest that the use of improved model parameters can lead to more predictive binding estimates, and that these estimates can be obtained with significantly less computer time than previously thought. These findings make such direct methods more attractive for use in rational drug design.     

Combining the polarizable Drude force field with a continuum electrostatic Poisson–Boltzmann implicit solvation model

In this work, we have combined the polarizable force field based on the classical Drude oscillator with a continuum Poisson–Boltzmann/solvent‐accessible surface area (PB/SASA) model. In practice, the positions of the Drude particles experiencing the solvent reaction field arising from the fixed charges and induced polarization of the solute must be optimized in a self‐consistent manner. Here, we parameterized the model to reproduce experimental solvation free energies of a set of small molecules. The model reproduces well‐experimental solvation free energies of 70 molecules, yielding a root mean square difference of 0.8 kcal/mol versus 2.5 kcal/mol for the CHARMM36 additive force field. The polarization work associated with the solute transfer from the gas‐phase to the polar solvent, a term neglected in the framework of additive force fields, was found to make a large contribution to the total solvation free energy, comparable to the polar solute–solvent solvation contribution. The Drude PB/SASA also reproduces well the electronic polarization from the explicit solvent simulations of a small protein, BPTI. Model validation was based on comparisons with the experimental relative binding free energies of 371 single alanine mutations. With the Drude PB/SASA model the root mean square deviation between the predicted and experimental relative binding free energies is 3.35 kcal/mol, lower than 5.11 kcal/mol computed with the CHARMM36 additive force field. Overall, the results indicate that the main limitation of the Drude PB/SASA model is the inability of the SASA term to accurately capture non‐polar solvation effects. © 2018 Wiley Periodicals, Inc.     

Calculation of relative free energy differences for the covalent hydration of organic compounds: A combined quantum mechanical and free energy perturbation study

The relative free energy difference (ΔΔG_hyd) for the reversible addition of water to two unsaturated molecules is accurately computed using a combination of ab initio quantum mechanical calculations and free energy perturbation methods. Initial attempts to calculate the absolute hydration free energy difference (ΔG_hyd) for formaldehyde and trichloroacetaldehyde gave values that differed substantially from experimental results even after inclusion of electron correlation energy contributions using third-order (MP3) and fourth-order (MP4) Møller-Plesset perturbation theory and QCISD(T) correlation methods at the 6-31G** basis set level. Inaccuracies in ΔG_hyd were attributed to errors in the calculation of both ΔG_gas and ΔΔG_sol. Gas phase quantum mechanical free energies (ΔG_gas) varied significantly (2–3 kcal/mol) depending on the level of theory. Errors in ΔΔG_sol were attributed to slow convergence of the calculations using the thermodynamic cycle perturbation (TCP) method with explicit solvent. These errors were minimized or canceled, however, when relative hydration free energy differences (ΔΔG_hyd) were calculated using a combination of ab initio quantum mechanical calculations and free energy perturbation methods. Calculated values for a variety of aldehydes and ketones were consistent with experimental data. © 1995 John Wiley & Sons, Inc.