Decisions with Confidence: Application to the Conformation Sampling of Molecules in the Solid State.

Accurate conformations of a molecule are critical for reliable prediction of its properties, so good predictive models require good conformations. Here, we present a method for conformer sampling based on distance geometry, implemented in our conformation generator OMEGA, which we apply to both macrocycles and druglike molecules. We validate it in the usual fashion, reproducing conformations from the solid state, and compare its performance in detail to other methods. We find that OMEGA performs well on three key criteria: accuracy, speed, and ensemble size. To support our conclusions quantitatively, particularly on accuracy, we developed a workflow for method comparison that uses parameter estimation, inference from confidence intervals, classical null hypothesis significance testing, Bayesian estimation, and effect size. The workflow is designed to be robust to the highly skewed performance data often found when validating tools in computational chemistry and to provide reliable, easy to interpret results. In this workflow, we emphasize the importance of confidently distinguishing between methods, with particular reference to a priori estimation of sample size and statistical power (false negative or Type II error rate), a topic almost completely ignored hitherto in computational chemistry.

Conformational Sampling of Macrocyclic Drugs in Different Environments: Can We Find the Relevant Conformations?

Conformational flexibility is a major determinant of the properties of macrocycles and other drugs in beyond rule of 5 (bRo5) space. Prediction of conformations is essential for design of drugs in this space, and we have evaluated three tools for conformational sampling of a set of 10 bRo5 drugs and clinical candidates in polar and apolar environments. The distance-geometry based OMEGA was found to yield ensembles spanning larger structure and property spaces than the ensembles obtained by MOE-LowModeMD (MOE) and MacroModel (MC). Both MC and OMEGA but not MOE generated different ensembles for polar and apolar environments. All three conformational search methods generated conformers similar to the crystal structure conformers for 9 of the 10 compounds, with OMEGA performing somewhat better than MOE and MC. MOE and OMEGA found all six conformers of roxithromycin that were identified by NMR in aqueous solutions, whereas only OMEGA sampled the three conformers observed in chloroform. We suggest that characterization of conformers using molecular descriptors, e.g., the radius of gyration and polar surface area, is preferred to energy- or root-mean-square deviation-based methods for selection of biologically relevant conformers in drug discovery in bRo5 space.

Efficient calculation of SAMPL4 hydration free energies using OMEGA, SZYBKI, QUACPAC, and Zap TK.

Several submissions for the SAMPL4 hydration free energy set were calculated using OpenEye tools, including many that were among the top performing submissions. All of our best submissions used AM1BCC charges and Poisson-Boltzmann solvation. Three submissions used a single conformer for calculating the hydration free energy and all performed very well with mean unsigned errors ranging from 0.94 to 1.08 kcal/mol. These calculations were very fast, only requiring 0.5-2.0 s per molecule. We observed that our two single-conformer methodologies have different types of failure cases and that these differences could be exploited for determining when the methods are likely to have substantial errors.

Force-field and quantum-mechanical binding study of selected SAMPL3 host-guest complexes.

A Merck molecular force field classical potential combined with Poisson-Boltzmann electrostatics (MMFF/PB) has been used to estimate the binding free energy of seven guest molecules (six tertiary amines and one primary amine) into a synthetic receptor (acyclic cucurbit[4]uril congener) and two benzimidazoles into cyclic cucurbit[7]uril (CB[7]) and cucurbit[8]uril (CB[8]) hosts. In addition, binding enthalpies for the benzimidazoles were calculated with density functional theory (DFT) using the B3LYP functional and a polarizable continuum model (PCM). Although in most cases the MMFF/PB approach returned reasonable agreements with the experiment (±2 kcal/mol), significant, much larger deviations were reported in the case of three host-guest pairs. All four binding enthalpy predictions with the DFT/PCM method suffered 70% or larger deviations from the calorimetry data. Results are discussed in terms of the molecular models used for guest-host complexation and the quality of the intermolecular potentials.

SAMPL2 and continuum modeling.

An account is given of our contributions to the SAMPL2 challenge for vacuum-water transfer energies. These contributions include different charge sets and radii used with Poisson-Boltzmann continuum theory applied to a single low-energy conformation. A rationale for this approach is given, including a summary of what we have learnt over previous SAMPL events. The results strongly suggest the need for new and repeated experimental measurements, both to clarify what appears to be experimental discrepancies in older measurements and to advance the field in a statistically sound manner.

The SAMP1 solvation challenge: further lessons regarding the pitfalls of parametrization.

This paper describes an investigation into the performance of different charges and radii with the Poisson-Boltzmann method for the calculation of vacuum-water transfer energies. The test set consisted of 63 drug-like molecules used in a blind-test challenge. The results are consistent with earlier reports, namely, that more physical charges perform better and that radii parametrization can both improve and also dramatically worsen results, with the latter suggesting a failure to capture all of the basic physics of solvation.