Prediction of cyclohexane-water distribution coefficients for the SAMPL5 data set using molecular dynamics simulations with the OPLS-AA force field

International audienceAll-atom molecular dynamics (MD) simulations were used to predict water-cyclohexane distribution coefficients D cw of a range of small molecules as part of the SAMPL5 blind prediction challenge. Molecules were parameterized with the trans-ferable all-atom OPLS-AA force field, which required the derivation of new parameters for sulfamides and heterocycles and validation of cyclohexane parameters as a solvent. The distribution coefficient was calculated from the solvation free energies of the compound in water and cyclohexane. Absolute solvation free energies were computed by an established protocol using windowed alchemical free energy perturbation with thermodynamic integration. This protocol resulted in an overall root mean square error (RMSE) in log D cw of almost 4 log units and an overall signed error of −3 compared to experimental data. There was no substantial overall difference in accuracy between simulating in NV T and NPT ensembles. The signed error suggests a systematic error but the experimental D cw data on their own are insufficient to Manuscript Click here to download Manuscript sampl5-manuscript.pdf Click here to view linked References 2 Ian M. Kenney et al. uncover the source of this error. Preliminary work suggests that the major source of error lies in the hydration free energy calculations

Evaluating parameterization protocols for hydration free energy calculations with the AMOEBA polarizable force field

Hydration free energy (HFE) calculations are often used to assess the performance of biomolecular force fields and the quality of assigned parameters. The AMOEBA polarizable force field moves beyond traditional pairwise additive models of electrostatics and may be expected to improve upon predictions of thermodynamic quantities such as HFEs over and above fixed point charge models. The recent SAMPL4 challenge evaluated the AMOEBA polarizable force field in this regard, but showed substantially worse results than those using the fixed point charge GAFF model. Starting with a set of automatically generated AMOEBA parameters for the SAMPL4 dataset, we evaluate the cumulative effects of a series of incremental improvements in parameterization protocol, including both solute and solvent model changes. Ultimately the optimized AMOEBA parameters give a set of results that are not statistically significantly different from those of GAFF in terms of signed and unsigned error metrics. This allows us to propose a number of guidelines for new molecule parameter derivation with AMOEBA, which we expect to have benefits for a range of biomolecular simulation applications such as protein ligand binding studie

Development and analysis of Tinker-OpenMM as a GPU-based free energy perturbation engine

The utilization of computational technologies for the lead optimization process is one of the biggest challenges in the computational chemistry field. In this dissertation, I describe the addition of GPU-based absolute and relative free energy calculation methods using polarizable force field AMOEBA to Tinker-OpenMM. I then proceed to test the capabilities of this platform by studying the binding free energy and binding structures of derivatives of the MELK inhibitor IN17. Also, I present the implementation of virial-based pressure control to the Tinker-OpenMM platform that is needed for performing isobaric simulations.Cellular and Molecular Biolog

SAMPL6: calculation of macroscopic pKa values from ab initio quantum mechanical free energies

International audienceMacroscopic pKa values were calculated for all compounds in the SAMPL6 blind prediction challenge, based on quantum chemical calculations with a continuum solvation model and a linear correction derived from a small training set. Microscopic pKa values were derived from the gas-phase free energy difference between protonated and deprotonated forms together with the Conductor-like Polarizable Continuum Solvation Model and the experimental solvation free energy of the proton. pH-dependent microstate free energies were obtained from the microscopic pKas with a maximum likelihood estimator and appropriately summed to yield macroscopic pKa values or microstate populations as function of pH. We assessed the accuracy of three approaches to calculate the microscopic pKas: direct use of the quantum mechanical free energy differences and correction of the direct values for short-comings in the QM solvation model with two different linear models that we independently derived from a small training set of 38 compounds with known pKa. The predictions that were corrected with the linear models had much better accuracy [root-mean-square error (RMSE) 2.04 and 1.95 pKa units] than the direct calculation (RMSE 3.74). Statistical measures indicate that some systematic errors remain, likely due to differences in the SAMPL6 data set and the small training set with respect to their interactions with water. Overall, the current approach provides a viable physics-based route to estimate macroscopic pKa values for novel compounds with reasonable accuracy

Predicting Relative Binding Affinity Using Nonequilibrium QM/MM Simulations

Calculating binding free energies with quan-tum-mechanical (QM) methods is notoriously time-consum-ing. In this work, we studied whether such calculations can beaccelerated by using nonequilibrium (NE) moleculardynamics simulations employing Jarzynski’s equality. Westudied the binding of nine cyclic carboxylate ligands to theocta-acid deep-cavity host from the SAMPL4 challenge withthe reference potential approach. The binding free energieswere first calculated at the molecular mechanics (MM) levelwith free energy perturbation using the generalized Amberforce field with restrained electrostatic potential charges forthe host and the ligands. Then the free energy corrections for going from the MM Hamiltonian to a hybrid QM/MM Hamiltonian were estimated by averaging over many short NE molecular dynamics simulations. In the QM/MM calculations, the ligand was described at the semiempirical PM6-DH+ level. We show that this approach yields MM → QM/MM free energy corrections that agree with those from other approaches within statistical uncertainties. The desired precision can be obtained by running a proper number of independent NE simulations. For the systems studied in this work, a total simulation length of 20 ps was appropriate for most of the ligands, and 36−324 simulations were necessary in order to reach a precision of 0.3 kJ/ mol

Evaluation and Development of Quantum Chemical Methodologies for Noncovalent Interactions and Supramolecular Thermochemistry

This thesis focuses on the application and development of electronic structure methods for noncovalent interactions in general and the evaluation of multilevel methodologies for an accurate description of supramolecular thermochemistry in particular. Noncovalent interactions are omnipresent in systems of various domains of science, such as supramolecular chemistry, structural biology, and surface science. Within supramolecular chemistry, host-guest complexes are of particular importance due to their diverse applicability in various fields like molecular recognition or self-assembly. The binding situation in a supramolecular complex is often unknown and sampling many different conformations is desired. Therefore, the first part of this thesis is concerned with cost-efficient density functional theory (DFT) and Hartree-Fock (HF) based electronic structure methods for noncovalent interactions, which are about a factor of 50 to 100 faster than calculations in a large basis set. The main errors in a DFT or HF calculation with small atomic orbital basis sets are the missing London dispersion and the basis set superposition error (BSSE). An exemplary benchmark study shows that modern correction strategies clearly outperform plain DFT or HF for energies and geometries of small dimers, large supramolecular complexes, and molecular crystals. Further, the development and evaluation of a minimal basis set Hartree--Fock method with three atom-pairwise corrections for London dispersion, BSSE, and basis set incompleteness (HF-3c) is presented. With nine global parameters, the empiricism of HF-3c is moderate, the method is self-interaction error free, and noiseless analytical frequencies can be obtained. HF-3c provides accurate geometries of organic supramolecular systems and small proteins, and good noncovalent interaction energies. The mean absolute deviations (MADs) for the S22 set of small noncovalently bound dimers and the S12L set of supramolecular host-guest association energies are 0.6 and 4.4 kcal mol-1, respectively. This is excellent compared to dispersion corrected DFT methods whose MADs are in the range of 0.3-0.5 and 2-5 kcal mol-1, respectively. The second part focuses on the application and evaluation of multilevel methodologies for an accurate description of Gibbs free energies of association (Δ Ga) for supramolecular host-guest complexes in solution. First, state-of-the-art dispersion corrected DFT (DFT-D3ATM) is used together with a large quadruple-zeta (QZ) basis set to obtain association energies in the gas phase. A semiempirical method is utilized to compute the thermostatistical corrections from energy to free energy and last, a continuum solvation model is employed. The general procedure is illustrated with a case study on eight typical complexes. The SAMPL4 blind test challenge provides a unique opportunity to test this methodology in a realistic setting. Relative Δ Ga in water are predicted for a cucurbit[7]uril host and 14 guest molecules containing ammonia groups. The HF-3c method was employed to sample possible binding conformations and the final Δ Ga were calculated on the PW6B95-D3ATM/QZ level with HF-3c thermal corrections and COSMO-RS solvation contributions. Compared to other methods theses predictions rank in the top three of all statistical measurements. The MAD and RMSD are only 2.0 and 2.6 kcal mol-1, respectively. Further, the S30L benchmark set is proposed as an extension of the S12L set for association (free) energies of host-guest complexes. Larger systems with up to 200 atoms, more divers interaction motifs, and higher charges are represented by experimentally measured complexes with Δ Ga values in the range from -0.7 to -24.7 kcal mol-1. In order to obtain a theoretical best estimate for Δ Ga different dispersion corrected density functionals, semiempirical methods, and continuum solvation models are tested. The best method combination is similar to the one used for the SAMPL4 bind test and yields an MAD with respect to experiment of only 2.4 kcal mol-1. Inclusion of counterions for the charged systems (S30L-CI) were found to improve the results overall. Synergy between theory and experiment is demonstrated in the last part of this thesis with the application of quantum chemical methods to two specific chemical problems related to supramolecular chemistry. Experimentally, it was found that titanocene(III) catalysts can be stabilized by chloride additives and the calculations reveal that the stabilities of these adducts are determined by the extent of hydrogen bonding between the catalyst and the ammonium cation. 1,1'-Binaphthol based ligands can be used to obtain enantiomerically pure double- and triple-stranded helicates with transition-metal ions in a completely diastereoselective self-assembly process. Electronic circular dichroism spectra of precursors for paracyclophane based ligands have been investigated computationally in order to identify their absolute configuration

Evaluation of log P, pKa, and log D predictions from the SAMPL7 blind challenge

The Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges focuses the computational modeling community on areas in need of improvement for rational drug design. The SAMPL7 physical property challenge dealt with prediction of octanol-water partition coefficients and pKa for 22 compounds. The dataset was composed of a series of N-acylsulfonamides and related bioisosteres. 17 research groups participated in the log P challenge, submitting 33 blind submissions total. For the pKa challenge, 7 different groups participated, submitting 9 blind submissions in total. Overall, the accuracy of octanol-water log P predictions in the SAMPL7 challenge was lower than octanol-water log P predictions in SAMPL6, likely due to a more diverse dataset. Compared to the SAMPL6 pKa challenge, accuracy remains unchanged in SAMPL7. Interestingly, here, though macroscopic pKa values were often predicted with reasonable accuracy, there was dramatically more disagreement among participants as to which microscopic transitions produced these values (with methods often disagreeing even as to the sign of the free energy change associated with certain transitions), indicating far more work needs to be done on pKa prediction methods