Predicting the Prevalence of Alternative Warfarin Tautomers in Solution

Perturbation Free-Energy Toolkit: An Automated Alchemical Topology Builder

Free-energy calculations play an important role in the application of computational chemistry to a range of fields, including protein biochemistry, rational drug design, or materials science. Importantly, the free-energy difference is directly related to experimentally measurable quantities such as partition and adsorption coefficients, water activity, and binding affinities. Among several techniques aimed at predicting free-energy differences, perturbation approaches, involving the alchemical transformation of one molecule into another through intermediate states, stand out as rigorous methods based on statistical mechanics. However, despite the importance of free-energy calculations, the applicability of the perturbation approaches is still largely impeded by a number of challenges, including the definition of the perturbation path, i.e., alchemical changes leading to the transformation of one molecule to the other. To address this, an automatic perturbation topology builder based on a graph-matching algorithm is developed, which can identify the maximum common substructure (MCS) of two or multiple molecules and provide the perturbation topologies suitable for free-energy calculations using the GROMOS and the GROMACS simulation packages. Various MCS search options are presented leading to alternative definitions of the perturbation pathway. Moreover, perturbation topologies generated using the default multistate MCS search are used to calculate the changes in free energy between lysine and its two post-translational modifications, 3-methyllysine and acetyllysine. The pairwise free-energy calculations performed on this test system led to a cycle closure of 0.5 ± 0.3 and 0.2 ± 0.2 kJ mol-1, with GROMOS and GROMACS simulation packages, respectively. The same relative free energies between the three states are obtained by employing the enveloping distribution sampling (EDS) approach when compared to the pairwise perturbations. Importantly, this toolkit is made available online as an open-source Python package (https://github.com/drazen-petrov/SMArt).

The Curious Case of Aqueous Warfarin: Structural Isomers or Distinct Excited States?

Warfarin is a potent anti-coagulant drug and is on the World Health Organization's List of Essential Medicines. Additionally, it displays fluorescence enhancement upon binding to human serum albumin, making warfarin a prototype fluorescent probe in biology. Despite its biological significance, the current structural assignment of warfarin in aqueous solution is based on indirect evidence in organic solvents. Warfarin is known to exist in different isomeric forms-open-chain, hemiketal, and anionic forms-based on the solvent and pH. Moreover, warfarin displays a dual absorption feature in several solvents, which has been employed to study the ring-chain isomerism between its open-chain and hemiketal isomers. In this study, our pH-dependent experiments on warfarin and structurally constrained warfarin derivatives in aqueous solution demonstrate that the structural assignment of warfarin solely on the basis of its absorption spectrum is erroneous. Using a combination of steady-state and time-resolved spectroscopic experiments, along with quantum chemical calculations, we assign the observed dual absorption to two distinct π → π* transitions in the 4-hydroxycoumarin moiety of warfarin. Furthermore, we unambiguously identify the isomeric form of warfarin that binds to human serum albumin in aqueous buffer.

Pattern-free generation and quantum mechanical scoring of ring-chain tautomers

In contrast to the computational generation of conventional tautomers, the analogous operation that would produce ring-chain tautomers is rarely available in cheminformatics codes. This is partly due to the perceived unimportance of ring-chain tautomerism and partly because specialized algorithms are required to realize the non-local proton transfers that occur during ring-chain rearrangement. Nevertheless, for some types of organic compounds, including sugars, warfarin analogs, fluorescein dyes and some drug-like compounds, ring-chain tautomerism cannot be ignored. In this work, a novel ring-chain tautomer generation algorithm is presented. It differs from previously proposed solutions in that it does not rely on hard-coded patterns of proton migrations and bond rearrangements, and should therefore be more general and maintainable. We deploy this algorithm as part of a workflow which provides an automated solution for tautomer generation and scoring. The workflow identifies protonatable and deprotonatable sites in the molecule using a previously described approach based on rapid micro-pK_a prediction. These data are used to distribute the active protons among the protonatable sites exhaustively, at which point alternate resonance structures are considered to obtain pairs of atoms with opposite formal charge. These pairs are connected with a single bond and a 3D undistorted geometry is generated. The scoring of the generated tautomers is performed with a subsequent density functional theory calculation employing an implicit solvent model. We demonstrate the performance of our workflow on several types of organic molecules known to exist in ring-chain tautomeric equilibria in solution. In particular, we show that some ring-chain tautomers not found using previously published algorithms are successfully located by ours.

Effect of Triclosan and Chloroxylenol on Bacterial Membranes

Triclosan and chloroxylenol are broad-spectrum biocides used extensively in healthcare and consumer products. They have been suggested to perturb the structure of bacterial membranes, but studies so far have not considered that most bacterial membranes contain large amounts of branched-chain lipids. Here, molecular dynamics simulation is used to examine the effect of the two biocides on membranes consisting of lipids with methyl-branched chains, cyclopropanated chains, and nonbranched chains. It is shown that triclosan and chloroxylenol induced a phase transition in membranes from a liquid-crystalline to a liquid-ordered phase irrespective of the presence and nature of branching groups. At high concentration, chloroxylenol promoted chain interdigitation. Our results suggest that triclosan and chloroxylenol decrease the degree of fluidity of membranes and that this effect is more pronounced in bacterial membranes. As a result, their biocidal activity could be associated with a change in the function of membrane proteins.

Generation of Tautomers Using Micro-p Ka's

Solutions of organic molecules containing one or more heterocycles with conjugated bonds may exist as a mixture of tautomers, but typically only a few of them are significantly populated even though the potential number grows combinatorially with the number of protonation and deprotonation sites. Generating the most stable tautomers from a given input structure is an important and challenging task, and numerous algorithms to tackle it have been proposed in the literature. This work describes a novel approach for tautomer prediction that involves the combined use of molecular mechanics, semiempirical quantum chemistry, and density functional theory. The key idea in our method is to identify the protonation and deprotonation sites using estimated micro-p K_a's for every atom in the molecule as well as in its nearest protonated and deprotonated forms. To generate tautomers in a systematic way with minimal bias, we then consider the full set of tautomers that arise from the combinatorial distribution of all such mobile protons among all protonatable sites, with efficient postprocessing to screen away high-energy species. To estimate the micro-p K_a's, we present a new method designed for the current task, but we emphasize that any alternative method can be used in conjunction with our basic algorithm. Our approach is therefore grounded in the computational prediction of physical properties in aqueous solution, in contrast to other approaches that may rely on the use of hard-coded rules of proton distribution, previously observed tautomerization patterns from a known chemical space, or human input. We present examples of the application of our algorithm to organic and drug-like molecules, with a focus on novel structures where traditional methods are expected to perform worse.

Automated Topology Builder Version 3.0: Prediction of Solvation Free Enthalpies in Water and Hexane

The ability of atomic interaction parameters generated using the Automated Topology Builder and Repository version 3.0 (ATB3.0) to predict experimental hydration free enthalpies (Δ G^water) and solvation free enthalpies in the apolar solvent hexane (Δ G^hexane) is presented. For a validation set of 685 molecules the average unsigned error (AUE) between Δ G^water values calculated using the ATB3.0 and experiment is 3.8 kJ·mol^-1. The slope of the line of best fit is 1.00, the intercept -1.0 kJ·mol^-1, and the R² 0.90. For the more restricted set of 239 molecules used to validate OPLS3 ( J. Chem. Theory Comput. 2016 , 12 , 281 - 296 , DOI: 10.1021/acs.jctc.5b00864 ) the AUE using the ATB3.0 is just 2.7 kJ·mol^-1 and the R² 0.93. A roadmap for further improvement of the ATB parameters is presented together with a discussion of the challenges of validating force fields against the available experimental data.