Improved GNNs for Log D7.4 Prediction by Transferring Knowledge from Low-Fidelity Data.

The n-octanol/buffer solution distribution coefficient at pH = 7.4 (log D7.4) is an indicator of lipophilicity, and it influences a wide variety of absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties and druggability of compounds. In log D7.4 prediction, graph neural networks (GNNs) can uncover subtle structure-property relationships (SPRs) by automatically extracting features from molecular graphs that facilitate the learning of SPRs, but their performances are often limited by the small size of available datasets. Herein, we present a transfer learning strategy called pretraining on computational data and then fine-tuning on experimental data (PCFE) to fully exploit the predictive potential of GNNs. PCFE works by pretraining a GNN model on 1.71 million computational log D data (low-fidelity data) and then fine-tuning it on 19,155 experimental log D7.4 data (high-fidelity data). The experiments for three GNN architectures (graph convolutional network (GCN), graph attention network (GAT), and Attentive FP) demonstrated the effectiveness of PCFE in improving GNNs for log D7.4 predictions. Moreover, the optimal PCFE-trained GNN model (cx-Attentive FP, Rtest2 = 0.909) outperformed four excellent descriptor-based models (random forest (RF), gradient boosting (GB), support vector machine (SVM), and extreme gradient boosting (XGBoost)). The robustness of the cx-Attentive FP model was also confirmed by evaluating the models with different training data sizes and dataset splitting strategies. Therefore, we developed a webserver and defined the applicability domain for this model. The webserver (http://tools.scbdd.com/chemlogd/) provides free log D7.4 prediction services. In addition, the important descriptors for log D7.4 were detected by the Shapley additive explanations (SHAP) method, and the most relevant substructures of log D7.4 were identified by the attention mechanism. Finally, the matched molecular pair analysis (MMPA) was performed to summarize the contributions of common chemical substituents to log D7.4, including a variety of hydrocarbon groups, halogen groups, heteroatoms, and polar groups. In conclusion, we believe that the cx-Attentive FP model can serve as a reliable tool to predict log D7.4 and hope that pretraining on low-fidelity data can help GNNs make accurate predictions of other endpoints in drug discovery.

Bioderivatization as a concept for renewable production of chemicals that are toxic or poorly soluble in the liquid phase.

Bio-based production technologies may complement or replace petroleum-based production of chemicals, but they face a number of technical challenges, including product toxicity and/or water insolubility. Plants and microorganisms naturally biosynthesize chemicals that often are converted into derivatives with reduced toxicity or enhanced solubility. Inspired by this principle, we propose a bioderivatization strategy for biotechnological chemicals production, defined as purposeful biochemical derivatization of intended target molecules. As proof of principle, the effects of hydrophobic (e.g., esterification) and hydrophilic (e.g., glycosylation) bioderivatization strategies on the biosynthesis of a relatively toxic and poorly soluble chemical, 1-octanol, were evaluated in Escherichia coli and Synechocystis sp. PCC 6803. The 1-octanol pathway was first optimized to reach product titers at which the host displayed symptoms of toxicity. Solvent overlay used to capture volatile products partially masked product toxicity. Regardless of whether solvent overlay was used, most strains with bioderivatization had a higher molar product titer and product yield, as well as improved cellular growth and glucose consumption, compared with strains without bioderivatization. The positive effect on bioproduction was observed with both the hydrophobic and hydrophilic strategies. Interestingly, in several combinations of genotype/induction strength, bioderivatization had a positive effect on productivity without any apparent effect on growth. We attribute this to enhanced product solubility in the aqueous or solvent fraction of the bioreactor liquid phase (depending on the derivative and medium used), with consequent enhanced product removal. Overall, under most conditions, a benefit of bioproduction was observed, and the bioderivatization strategy could be considered for other similar chemicals as well.

Effective Parameters Controlling Sterol Transfer: A Time-Resolved Small-Angle Neutron Scattering Study.

Though cholesterol is the most prevalent and essential sterol in mammalian cellular membranes, its precursors, post-synthesis cholesterol products, as well as its oxidized derivatives play many other important physiological roles. Using a non-invasive in situ technique, time-resolved small angle neutron scattering, we report on the rate of membrane desorption and corresponding activation energy for this process for a series of sterol precursors and post-synthesis cholesterol products that vary from cholesterol by the number and position of double bonds in B ring of cholesterol's steroid core. In addition, we report on sterols that have oxidation modifications in ring A and ring B of the steroid core. We find that sterols that differ in position or the number of double bonds in ring B have similar time and energy characteristics, while oxysterols have faster transfer rates and lower activation energies than cholesterol in a manner generally consistent with known sterol characteristics, like Log P, the n-octanol/water partitioning coefficient. We find, however, that membrane/water partitioning which is dependent on lipid-sterol interactions is a better predictor, shown by the correlation of the sterols' tilt modulus with both the desorption rates and activation energy.

Fast Prediction of Lipophilicity of Organofluorine Molecules: Deep Learning-Derived Polarity Characters and Experimental Tests.

Fast and accurate estimation of lipophilicity for organofluorine molecules is in great demand for accelerating drug and materials discovery. A lipophilicity data set of organofluorine molecules (OFL data set), containing 1907 samples, is constructed through density functional theory (DFT) calculations and experimental measurements. An efficient and interpretable model, called PoLogP, is developed to predict the n-octanol/water partition coefficient, log Po/w, of organofluorine molecules on the basis of the descriptors of polarization, which is a combination of polarity descriptors, including the molecular polarity index and molecular polarizability (α), and hydrogen bond (HBs) index, consisting of the number of donors (NHBD) and acceptors (NHBA and NHB-FA). The present PoLogP with a combination of polarity descriptors is demonstrated to perform better than the dipole moment (µ) alone for the F-contained molecules. With the aid of a multilevel attention graph convolutional neural network model, the fast generation of polarity descriptors of organofluorine molecules could be achieved with the DFT accuracy based only on a topological molecular graph structure. The performance of PoLogP is further validated on synthesized organofluorine molecules and 2626 non-fluorinated molecules with satisfactory accuracy, highlighting the potential usage of PoLogP in high-throughput screening of the functional molecules with the desired solubility in various solvent media.

The antifungal mechanisms of plant volatile compound 1-octanol against Aspergillus flavus growth.

The exploitation of active ingredients from plant volatile organic compounds as natural gaseous fungicides shows remarkable potential for controlling fungal decay in postharvest agroproducts. Although 1-octanol is a common component of cereal volatiles, its antifungal potency against spoilage fungi in postharvest grains remains unclear. In this study, we studied the effectiveness of 1-octanol against Aspergillus flavus growth in postharvest grains and its mechanisms of action. 1-Octanol vapor and liquid contact dose-dependently inhibited A. flavus spore germination and mycelial growth at a low concentration. The simulated storage experiment demonstrated that 300 µL/L of 1-octanol vapor completely controlled A. flavus growth in wheat, corn, and paddy grains with 20% moisture content. 1-Octanol treatment irreversibly damaged the conidial and mycelial morphology of A. flavus and caused electrolyte leakage due to reduced plasma membrane integrity. It induced apoptosis along with morphological abnormalities, phosphatidylserine externalization, mitochondrial membrane potential depolarization, intracellular reactive oxygen species accumulation, and DNA fragmentation in A. flavus cells. Metabolomic analysis revealed that 1-octanol treatment disrupted the biosynthesis of unsaturated fatty acids, ATP-binding cassette transporters, amino acid metabolism, and glycerophospholipid metabolism. This study demonstrated the promising application potential of 1-octanol as a biofumigant for preventing fungal spoilage of postharvest cereal grains. KEY POINTS: • (1) 1-Octanol inhibits Aspergillus flavus growth in the vapor phase and liquid contact; • (2) 1-Octanol damages membrane integrity and induces apoptosis of A. flavus; • (3) Metabolomic changes in A. flavus mycelia were analyzed after 1-octanol treatment.

A case study on the influence of hydrophilicity on the signal enhancement by dynamic nuclear polarization.

In this work, the behavior of four different commercially available polarizing agents is investigated employing the non-ionic model surfactant 1-octanol as analyte. A relative method for the comparison of the proportion of the direct and indirect polarization transfer pathways is established, allowing a direct comparison of the polarization efficacy for different radicals and different parts of the 1-octanol molecule despite differences in radical concentration or sample amount. With this approach, it could be demonstrated that the hydrophilicity is a key factor in the way polarization is transferred from the polarizing agent to the analyte. These findings are confirmed by the determination of buildup times Tb, illustrating that the choice of polarizing agent plays an essential role in ensuring an optimal polarization transfer and therefore the maximum amount of enhancement possible for DNP enhanced NMR measurements.

Effects of Physicochemical Properties of Constituent Ions of Ionic Liquid on Its Permeation through a Silicone Membrane.

Ionic liquids (ILs), defined as liquid salts composed of anions and cations, have the advantage of allowing constituent ions to be stably absorbed through biological membranes, such as skin. However, limited information is currently available on the effects of the physicochemical properties of constituent ions on the membrane permeation of ILs. Therefore, we herein investigated the effects of the polarity of constituent cations on the membrane permeation of each constituent ion from IL. Various ILs were prepared by selecting lidocaine (LID) as a cation and a series of p-alkylbenzoic acids with different n-octanol/water partition coefficients (Ko/w) as anions. These ILs were applied to a skin model, a silicone membrane, and membrane permeability was investigated. The membrane permeabilities of p-alkylbenzoic acids from their single aqueous suspensions were also measured for comparison. The membrane permeability of p-alkylbenzoic acid from the aqueous suspension increased at higher Ko/w. However, the membrane permeability of ILs was similar regardless of the Ko/w of the constituent p-alkylbenzoic acid. Furthermore, the membrane permeability of the counterion LID remained unchanged regardless of the constituent p-alkylbenzoic acid. These results suggest that even when the Ko/w of IL constituents markedly differs, the resulting IL does not affect membrane permeability.

Effects of Lipophilicity and Structural Features on the Antiherpes Activity of Digitalis Cardenolides and Derivatives.

There is growing interest in exploring Digitalis cardenolides as potential antiviral agents. Hence, we herein investigated the influence of structural features and lipophilicity on the antiherpes activity of 65 natural and semisynthetic cardenolides assayed in vitro against HSV-1. The presence of an α,ß-unsaturated lactone ring at C-17, a ß-hydroxy group at C-14 and C-3ß-OR substituents were considered essential requirements for this biological activity. Glycosides were more active than their genins, especially monoglycosides containing a rhamnose residue. The activity enhanced in derivatives bearing an aldehyde group at C-19 instead of a methyl group, whereas inserting a C-5ß-OH improved the antiherpes effect significantly. The cardenolides lipophilicity was accessed by measuring experimentally their log P values (n-octanol-water partition coefficient) and disclosed a range of lipophilicity (log P 0.75±0.25) associated with the optimal antiherpes activity. In silico studies were carried out and resulted in the establishment of two predictive models potentially useful to identify and/or optimize novel antiherpes cardenolides. The effectiveness of the models was confirmed by retrospective analysis of the studied compounds. This is the first SAR study addressing the antiherpes activity of cardenolides. The developed computational models were able to predict the active cardenolides and their log P values.

Inside out Approach to Rotator State in Hydrogen-Bonded System-Experimental and Theoretical Cross-Examination in n-Octanol.

The experimental and theoretical description of premelting behavior is one of the most challenging tasks in contemporary material science. In this paper, n-octanol was studied using a multi-method approach to investigate it at macroscopic and molecular levels. The experimental infrared (IR) spectra were collected in the solid state and liquid phase at temperature range from -84∘C to -15 ∘C to detect temperature-related indicators of pretransitional phenomena. Next, the nonlinear dielectric effect (NDE) was measured at various temperatures (from -30 ∘C to -15 ∘C) to provide insight into macroscopic effects of premelting. As a result, a two-step mechanism of premelting in n-octanol was established based on experimental data. It was postulated that it consists of a rotator state formation followed by the surface premelting. In order to shed light onto molecular-level processes, classical molecular dynamics (MD) was performed to investigate the time evolution of the changes in metric parameters as a function of simulation temperature. The applied protocol enabled simulations in the solid state as well as in the liquid (the collapse of the ordered crystal structure). The exact molecular motions contributing to the rotator state formation were obtained, revealing an enabling of the rotational freedom of the terminal parts of the chains. The Car-Parrinello molecular dynamics (CPMD) was applied to support and interpret experimental spectroscopic findings. The vibrational properties of the stretching of OH within the intermolecular hydrogen bond were studied using Fourier transformation of the autocorrelation function of both dipole moments and atomic velocity. Finally, path integral molecular dynamics (PIMD) was carried out to analyze the quantum effect's influence on the bridged proton position in the hydrogen bridge. On the basis of the combined experimental and theoretical conclusions, a novel mechanism of the bridged protons dynamics has been postulated-the interlamellar hydrogen bonding pattern, resulting in an additional OH stretching band, visible in the solid-state experimental IR spectra.

Separation of Mandelic Acid by a Reactive Extraction Method Using Tertiary Amine in Different Organic Diluents.

Mandelic acid is a valuable chemical that is commonly used in the synthesis of various drugs, in antibacterial products, and as a skin care agent in cosmetics. As it is an important chemical, various methods are used to synthesize and extract this compound. However, the yields of the used processes is not significant. A dilute aqueous solution is obtained when using several production methods, such as a fermentation, etc. In this study, the reactive extraction of mandelic acid from aqueous solutions using tri-n-octylamine extractant at 298.15 K was investigated. Dimethyl phthalate (DMP), methyl isobutyl ketone (MIBK), 2-octanone, 1-octanol, n-pentane, octyl acetate, and toluene were used as diluents. The batch extraction results of the mandelic acid experiments were obtained for the development of a process design. Calculations of the loading factor (Z), distribution coefficient (D), and extraction efficiency (E%) were based on the experimental data. The highest separation yield was obtained as 98.13% for 0.458 mol.L-1 of tri-n-octylamine concentration in DMP. The overall extraction constants were analyzed for the complex of acid-amine by the Bizek approach, including K11, K12, and K23.

Predictive Models of Gas/Particulate Partition Coefficients (KP) for Polycyclic Aromatic Hydrocarbons and Their Oxygen/Nitrogen Derivatives.

Polycyclic aromatic hydrocarbons (PAHs) and their oxygen/nitrogen derivatives released into the atmosphere can alternate between a gas phase and a particulate phase, further affecting their environmental behavior and fate. The gas/particulate partition coefficient (KP) is generally used to characterize such partitioning equilibrium. In this study, the correlation between log KP of fifty PAH derivatives and their n-octanol/air partition coefficient (log KOA) was first analyzed, yielding a strong linear correlation (R2 = 0.801). Then, Gaussian 09 software was used to calculate quantum chemical descriptors of all chemicals at M062X/6-311+G (d,p) level. Both stepwise multiple linear regression (MLR) and support vector machine (SVM) methods were used to develop the quantitative structure-property relationship (QSPR) prediction models of log KP. They yield better statistical performance (R2 > 0.847, RMSE < 0.584) than the log KOA model. Simulation external validation and cross validation were further used to characterize the fitting performance, predictive ability, and robustness of the models. The mechanism analysis shows intermolecular dispersion interaction and hydrogen bonding as the main factors to dominate the distribution of PAH derivatives between the gas phase and particulate phase. The developed models can be used to predict log KP values of other PAH derivatives in the application domain, providing basic data for their ecological risk assessment.

Experimental Examination of Solubility and Lipophilicity as Pharmaceutically Relevant Points of Novel Bioactive Hybrid Compounds.

The important physicochemical properties of three novel bioactive hybrid compounds with different groups (-CH3, -F and -Cl) were studied, including kinetic and thermodynamic solubility in pharmaceutically relevant solvents (buffer solutions and 1-octanol) as well as partition coefficient in system 1-octanol/buffer pH 7.4. The aqueous solubility of these chemicals is poor and ranged from 0.67 × 10-4 to 1.98 × 10-3 mol·L-1. The compounds studied are more soluble in the buffer pH 2.0, simulating the gastrointestinal tract environment (by an order of magnitude) than in the buffer pH 7.4 modelling plasma of blood. The solubility in 1-octanol is significantly higher; that is because of the specific interactions of the compounds with the solvent. The prediction solubility behaviour of the hybrid compounds using Hansen's three-parameter approach showed acceptable results. The experimental solubility of potential drugs was successfully correlated by means of two commonly known equations: modified Apelblat and van't Hoff. The temperature dependencies of partition coefficients of new hybrids in the model system 1-octanol/buffer pH 7.4 as a surrogate lipophilicity were measured by the shake flask method. It was found that compounds demonstrated a lipophilic nature and have optimal values of partition coefficients for oral absorption. Bioactive assay manifested that prepared compounds showed antifungal activities equal to or greater than fluconazole. In addition, the thermodynamic aspects of dissolution and partition processes have been examined. Bioactive assay manifested that prepared compounds showed antifungal activities equal to or greater than the reference drug.

Preparation of an isorhamnetin phospholipid complex for improving solubility and anti-hyperuricemia activity.

To improve the solubility and anti-hyperuricemia activity of the insoluble natural flavonoid isorhamnetin (ISO), an isorhamnetin phospholipid complex (ISO-PC) was prepared. ISO-PC was prepared through solvent evaporation and its prescription process was optimized. The formation of ISO-PC was verified via multiple characterization methods. Parameters such as drug loading, solubility, octanol-water partition coefficient, stability, and in vivo anti-hyperuricemia activity of ISO-PC were investigated. The complexation efficiency of ISO-PC was 95.1% ± 0.56%. The characterization results confirmed that ISO-PC was bound by intermolecular interactions between ISO and phospholipids. Compared with ISO, the solubility of ISO-PC in water and 1-octanol increased by 122 and 16.5 times, respectively. In addition, the octanol-water partition coefficient decreased to 1.08. Pharmacodynamic studies have reported that ISO-PC has a more significant effect on reducing serum uric acid levels and renal protection. In conclusion, the findings of this study suggested that ISO-PC could be used as a promising formulation to improve the solubility and the anti-hyperuricemia activity of ISO.

Experimental investigation into the oxidation reactivity, morphology and graphitization of soot particles from diesel/n-octanol mixtures.

Aiming to investigate the impacts of n-octanol addition on the oxidation reactivity, morphology and graphitization of diesel exhaust particles, soot samples were collected from a four-cylinder turbocharged diesel engine fueled with D100 (neat diesel fuel), DO15 (85% diesel and 15% n-octanol, V/V) and DO30 (70% diesel and 30% n-octanol, V/V). All tests were conducted at two engine speeds of 1370 and 2150 r/min under a fixed torque of 125 N·m. The soot properties were characterized by thermogravimetric analyzer (TGA), transmission electron microscopy (TEM) and Raman spectroscopy (RS). The higher volatile organic fraction content, lower soot oxidation temperatures and lower activation energy from TGA results indicated that both the increasing n-octanol concentration and engine speed enhanced the soot oxidation reactivity. Additionally, quantitative analysis of TEM images showed that the soot derived from DO30 had the smallest primary particle diameters and fractal dimension, followed by those of soot produced by DO15 and D100. The RS results demonstrated that the n-octanol addition and higher engine speed led to a larger D1-FWHM (D1-full width at half maximum), AD1/AT (area ratio of D1 band and the total spectral) and AD3/AT (area ratio of D3 band and the total spectral) as well as a smaller La (crystallite width), revealing a lower degree of graphitization. Furthermore, the correlations between characterization parameters of soot properties and reactivity were nonlinear.

Predicting octanol/water partition coefficients using molecular simulation for the SAMPL7 challenge: comparing the use of neat and water saturated 1-octanol.

Blind predictions of octanol/water partition coefficients at 298.15 K for 22 drug-like compounds were made for the SAMPL7 challenge. The octanol/water partition coefficients were predicted using solvation free energies computed using molecular dynamics simulations, wherein we considered the use of both pure and water-saturated 1-octanol to model the octanol-rich phase. Water and 1-octanol were modeled using TIP4P and TrAPPE-UA, respectively, which have been shown to well reproduce the experimental mutual solubility, and the solutes were modeled using GAFF. After the close of the SAMPL7 challenge, we additionally made predictions using TIP4P/2005 water. We found that the predictions were sensitive to the choice of water force field. However, the effect of water in the octanol-rich phase was found to be even more significant and non-negligible. The effect of inclusion of water was additionally sensitive to the chemical structure of the solute.

SAMPL7 physical property prediction from EC-RISM theory.

Inspired by the successful application of the embedded cluster reference interaction site model (EC-RISM), a combination of quantum-mechanical calculations with three-dimensional RISM theory to predict Gibbs energies of species in solution within the SAMPL6.1 (acidity constants, pKa) and SAMPL6.2 (octanol-water partition coefficients, log P) the methodology was applied to the recent SAMPL7 physical property challenge on aqueous pKa and octanol-water log P values. Not part of the challenge but provided by the organizers, we also computed distribution coefficients log D7.4 from predicted pKa and log P data. While macroscopic pKa predictions compared very favorably with experimental data (root mean square error, RMSE 0.72 pK units), the performance of the log P model (RMSE 1.84) fell behind expectations from the SAMPL6.2 challenge, leading to reasonable log D7.4 predictions (RMSE 1.69) from combining the independent calculations. In the post-submission phase, conformations generated by different methodology yielded results that did not significantly improve the original predictions. While overall satisfactory compared to previous log D challenges, the predicted data suggest that further effort is needed for optimizing the robustness of the partition coefficient model within EC-RISM calculations and for shaping the agreement between experimental conditions and the corresponding model description.

Multiple linear regression models for predicting the n­octanol/water partition coefficients in the SAMPL7 blind challenge.

A multiple linear regression model called MLR-3 is used for predicting the experimental n-octanol/water partition coefficient (log PN) of 22 N-sulfonamides proposed by the organizers of the SAMPL7 blind challenge. The MLR-3 method was trained with 82 molecules including drug-like sulfonamides and small organic molecules, which resembled the main functional groups present in the challenge dataset. Our model, submitted as "TFE-MLR", presented a root-mean-square error of 0.58 and mean absolute error of 0.41 in log P units, accomplishing the highest accuracy, among empirical methods and also in all submissions based on the ranked ones. Overall, the results support the appropriateness of multiple linear regression approach MLR-3 for computing the n-octanol/water partition coefficient in sulfonamide-bearing compounds. In this context, the outstanding performance of empirical methodologies, where 75% of the ranked submissions achieved root-mean-square errors < 1 log P units, support the suitability of these strategies for obtaining accurate and fast predictions of physicochemical properties as partition coefficients of bioorganic compounds.

COSMO-RS predictions of logP in the SAMPL7 blind challenge.

We applied the COSMO-RS method to predict the partition coefficient logP between water and 1-octanol for 22 small drug like molecules within the framework of the SAMPL7 blind challenge. We carefully collected a set of thermodynamically meaningful microstates, including tautomeric forms of the neutral species, and calculated the logP using the current COSMOtherm implementation on the most accurate level. With this approach, COSMO-RS was ranked as the 6st most accurate method (Measured by the mean absolute error (MAE) of 0.57) over all 17 ranked submissions. We achieved a root mean square deviation (RMSD) of 0.78. The largest deviations from experimental values are exhibited by five SAMPL molecules (SM), which seem to be shifted in most SAMPL7 contributions. In context with previous SAMPL challenges, COSMO-RS demonstrates a wide range of applicability and one of the best in class reliability and accuracy among the physical methods.

SAMPL7 blind challenge: quantum-mechanical prediction of partition coefficients and acid dissociation constants for small drug-like molecules.

The physicochemical properties of a drug molecule determine the therapeutic effectiveness of the drug. Thus, the development of fast and accurate theoretical approaches for the prediction of such properties is inevitable. The participation to the SAMPL7 challenge is based on the estimation of logP coefficients and pKa values of small drug-like sulfonamide derivatives. Thereby, quantum mechanical calculations were carried out in order to calculate the free energy of solvation and the transfer energy of 22 drug-like compounds in different environments (water and n-octanol) by employing the SMD solvation model. For logP calculations, we studied eleven different methodologies to calculate the transfer free energies, the lowest RMSE value was obtained for the M06L/def2-TZVP//M06L/def2-SVP level of theory. On the other hand, we employed an isodesmic reaction scheme within the macro pKa framework; this was based on selecting reference molecules similar to the SAMPL7 challenge molecules. Consequently, highly well correlated pKa values were obtained with the M062X/6-311+G(2df,2p)//M052X/6-31+G(d,p) level of theory.

Energy-entropy prediction of octanol-water logP of SAMPL7 N-acyl sulfonamide bioisosters.

Partition coefficients quantify a molecule's distribution between two immiscible liquid phases. While there are many methods to compute them, there is not yet a method based on the free energy of each system in terms of energy and entropy, where entropy depends on the probability distribution of all quantum states of the system. Here we test a method in this class called Energy Entropy Multiscale Cell Correlation (EE-MCC) for the calculation of octanol-water logP values for 22 N-acyl sulfonamides in the SAMPL7 Physical Properties Challenge (Statistical Assessment of the Modelling of Proteins and Ligands). EE-MCC logP values have a mean error of 1.8 logP units versus experiment and a standard error of the mean of 1.0 logP units for three separate calculations. These errors are primarily due to getting sufficiently converged energies to give accurate differences of large numbers, particularly for the large-molecule solvent octanol. However, this is also an issue for entropy, and approximations in the force field and MCC theory also contribute to the error. Unique to MCC is that it explains the entropy contributions over all the degrees of freedom of all molecules in the system. A gain in orientational entropy of water is the main favourable entropic contribution, supported by small gains in solute vibrational and orientational entropy but offset by unfavourable changes in the orientational entropy of octanol, the vibrational entropy of both solvents, and the positional and conformational entropy of the solute.