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The SAMPL8 blind prediction challenge, which addresses the acid/base dissociation constants (pKa) and the distribution coefficients (logD), was addressed by the Conductor like Screening Model for Realistic Solvation (COSMO-RS). Using the COSMOtherm implementation of COSMO-RS together with a rigorous conformational sampling, yielded logD predictions with a root mean square deviation (RMSD) of 1.36 log units over all 11 compounds and seven bi-phasic systems of the data set, which was the most accurate of all contest submissions (logD). For the SAMPL8 pKa competition, participants were asked to report the standard state free energies of all microstates, which were then used to calculate the macroscopic pKa. We have used COSMO-RS based linear free energy fit models to calculate the requested energies. The assignment of the calculated and experimental pKa values was made on the basis of the popular transitions, i.e. the transition hat was predicted by the majority of the submissions. With this assignment and a model that covers both, pKa and base pKa, we achieved an RMSD of 3.44 log units (18 pKa values of 14 molecules), which is the second place of the six ranked submissions. By changing to an assignment that is based on the experimental transition curves, the RMSD reduces to 1.65. In addition to the ranked contribution, we submitted two more data sets, one for the standard pKa model and one or the standard base pKa model of COSMOtherm. Using the experiment based assignment with the predictions of the two sets we received a RMSD of 1.42 log units (25 pKa values of 20 molecules). The deviation mainly arises from a single outlier compound, the omission of which leads to an RMSD of 0.89 log units. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Conformational equilibria are at the heart of drug design, yet their energetic description is often hampered by the insufficient accuracy of low-cost methods. Here we present a flexible and semi-automatic workflow based on quantum chemistry, ReSCoSS, designed to identify relevant conformers and predict their equilibria across different solvent environments in the Conductor-like Screening Model for Real Solvents (COSMO-RS) framework. We demonstrate the utility and accuracy of the workflow through conformational case studies on several drug-like molecules from literature where relevant conformations are known. We further show that including ReSCoSS conformers significantly improves COSMO-RS based predictions of physicochemical properties over single-conformation approaches. ReSCoSS has found broad adoption in the in-house drug discovery and development work streams and has contributed to establishing quantum-chemistry methods as a strategic pillar in ligand discovery. [ABSTRACT FROM AUTHOR]

We investigate the minimum-energy path for the rotation of formal C=N double bonds in molecules with guanidine-like substructures as present in the chemical class of neonicotinoids. The transitions between the E- and Z-isomers of several neonicotinoids using scans of the torsional potential energy hypersurfaces are quantified at the DFT-level of theory. The validity of using this ansatz is checked by single-point CCSD(T) calculations for model systems like nitroguanidine. A combined approach of theory and experiment permits to unambiguously identify the relevant isomers present at ambient conditions. As an example, MP2-GIAO predictions of the NMR spectra of E- and Z-Clothianidin are experimentally confirmed by low-temperature NMR-experiments identifying for the first time the hitherto unknown Z-Isomer of Clothianidin. [ABSTRACT FROM AUTHOR]

Within the framework of the 6th physical property blind challenge (SAMPL6) the authors have participated in predicting the octanol–water partition coefficients (logP) for several small drug like molecules. Those logP values where experimentally known by the organizers but only revealed after the submissions of the predictions. Two different sets of predictions were submitted by the authors, both based on the COSMOtherm implementation of COSMO-RS theory. COSMOtherm predictions using the FINE parametrization level (hmz0n) obtained the highest accuracy among all submissions as measured by the root mean squared error. COSMOquick predictions using a fast algorithm to estimate σ-profiles and an a posterio machine learning correction on top of the COSMOtherm results (3vqbi) scored 3rd out of 91 submissions. Both results underline the high quality of COSMO-RS derived molecular free energies in solution. [ABSTRACT FROM AUTHOR]

Performance of COSMO-RS method as a tool for partition and distribution modeling in 20 solvent pairs—composed of neutral or acidic aqueous solution and organic solvents of different polarity, ranging from alcohols to toluene and hexane—was evaluated. Experimental partition/distribution data of lignin-related and drug-like compounds (neutral, acidic, moderately basic) were used as reference. Several aspects of partition modeling were addressed: accounting for mutual saturation of aqueous and organic phases, variability of systematic prediction errors across solvent pairs, taking solute ionization into account. COSMO-RS was found to predict extraction outcome for both ligneous and drug-like compounds in various solvent pairs fairly well without any additional empirical input. The solvent-specific systematic errors were found to be moderate, despite being statistically significant, and related to the solvent hydrophobicity. Accounting for mutual solubilities of the two liquids was proven crucial in cases where water was considerably soluble in the organic solvent. The root mean square error of a priori logP prediction varied, depending mainly on the solvent pair, from 0.2 to 0.7, overall value being 0.6 log units. The accuracy was higher in case of hydrophilic than hydrophobic solvents. The logD predictions were less accurate, due to pKa prediction being an additional source of error, and also because of the complexity of modeling the behaviour of ionic species in the two-phase system. A simple correction for partitioning of free ions was found to notably improve logD prediction accuracy in case of the most hydrophilic organic phase (butanol/water). [ABSTRACT FROM AUTHOR]

We have tried to calculate the free energy for the binding of six small ligands to two variants of the octa-acid deep cavitand host in the SAMPL5 blind challenge. We employed structures minimised with dispersion-corrected density-functional theory with small basis sets and energies were calculated using large basis sets. Solvation energies were calculated with continuum methods and thermostatistical corrections were obtained from frequencies calculated at the HF-3c level. Care was taken to minimise the effects of the flexibility of the host by keeping the complexes as symmetric and similar as possible. In some calculations, the large net charge of the host was reduced by removing the propionate and benzoate groups. In addition, the effect of a restricted molecular dynamics sampling of structures was tested. Finally, we tried to improve the energies by using the DLPNO-CCSD(T) approach. Unfortunately, results of quite poor quality were obtained, with no correlation to the experimental data, systematically too positive affinities (by ~50 kJ/mol) and a mean absolute error (after removal of the systematic error) of 11-16 kJ/mol. DLPNO-CCSD(T) did not improve the results, so the accuracy is not limited by the energy function. Instead, four likely sources of errors were identified: first, the minimised structures were often incorrect, owing to the omission of explicit solvent. They could be partly improved by performing the minimisations in a continuum solvent with four water molecules around the charged groups of the ligands. Second, some ligands could bind in several different conformations, requiring sampling of reasonable structures. Third, there is an indication the continuum-solvation model has problems to accurately describe the binding of both the negatively and positively charged guest molecules. Fourth, different methods to calculate the thermostatistical corrections gave results that differed by up to 30 kJ/mol and there is an indication that HF-3c overestimates the entropy term. In conclusion, it is a challenge to calculate binding affinities for this octa-acid system with quantum-mechanical methods. [ABSTRACT FROM AUTHOR]

The Conductor-Like-Screening-Model for Real Solvents (COSMO-RS) method has been used for the blind prediction of cyclohexane-water distribution coefficients logD within the SAMPL challenge. The partition coefficient logP of the neutral species was calculated first and then corrected for dissociation or protonation, as appropriate for acidic or basic solutes, to obtain the cyclohexane-water logD. Using the latest version of the COSMO therm implementation, this approach in combination with a rigorous conformational sampling yielded a predictive accuracy of 2.11 log units (RMSD) for the 53 compounds of the blind prediction dataset. By that it was the most accurate of all contest submissions and it also achieved the best rank order. The RMSD mainly arises from a group of outliers in the negative logD range, which at least partly may arise from dimerization or other experimental problems coming up for very polar molecules in very non-polar solvents. [ABSTRACT FROM AUTHOR]

The COSMO-RS method has been used for the prediction of free energies of hydration on a dataset of 47 complex multifunctional compounds considered in the SAMPL4 challenge. Straight application of the COSMO therm software with the parameterization C21_0108 yields a predictive accuracy of 1.46 kcal/mol root mean square error overall and 1.18 kcal/mol if a single dominant outlier is removed. [ABSTRACT FROM AUTHOR]

The COSMO-RS method has been used for the prediction of free energies of hydration on the dataset of 36 chlorinated ethanes, biphenyls and dioxins considered in the SAMPL3 challenge. Straight application of the latest version of the COSMO therm software yields an overall predictive accuracy of 1.05 kcal/mol (RMSE). The predictions for the chlorinated ethanes and dioxins are much better with 0.40 and 0.49 kcal/mol RMSE, respectively. The predictions for the chlorinated biphenyls show a systematic shift of approximately 1 kcal/mol, but the large RMSE of 1.59 kcal/mol mainly arises from two exceptional outliers. Possible reasons for this observation are discussed. [ABSTRACT FROM AUTHOR]

The COSMO-RS method, a combination of the quantum chemical dielectric continuum solvation model COSMO with a COSMO based statistical thermodynamics of surface interactions, has been used in its COSMOtherm implementation for the direct, blind prediction of tautomeric equilibria within the SAMPL2 challenge. Since the quantum chemical level underlying COSMOtherm, i.e. BP/TZVP DFT-calculations, is known to be of limited accuracy with respect to reaction energies, we tested MP2 reaction energy corrections in addition. As expected, the straight application of the latest version of COSMOtherm yielded a poor predictive accuracy of ~4 kcal/mol (RMSE) for the eight compounds of the blind prediction data set, and the MP2-corrected predictions reduced the average error considerably to ~1.2 kcal/mol. But a more detailed analysis shows that this improvement is not systematic and mostly a lucky coincidence on the small data set. The systematic results of COSMOtherm allow for an efficient empirical correction with an RMSE of 0.61 kcal/mol. This allows for systematic predictions for the most important case of generalized keto-enol tautomerism. [ABSTRACT FROM AUTHOR]

Both, dielectric continuum solvation models as well as surface or group based methods using polarity and lipophilicity parameters have been proven to be useful tools for the analysis of solvation and partition questions. For the first time, COSMO-RS provides an integrated theory, which combines the aspects of continuum solvation and surface interactions, and which ends up with chemical potentials of molecules in almost arbitrary solvents and mixtures. Due to its sound theoretical basis, COSMO-RS does not only provide a new quantitative access to solvation and partition properties in well defined solvents, but it also opens a novel view and gives a better understanding of the general problem of solvation. Finally, this allows for a generalisation of COSMO-RS to sophisticated physiological partition problems involving as complex phases as blood, brain, or cell membranes. The use of COSMO-RS for drug discovery and design is demonstrated by applications to blood-brain partition coefficients, and water solubility. [ABSTRACT FROM AUTHOR]