Abstract
With a view to high-throughput simulations, we present an automated system for mapping and parameterizing organic molecules for use with the coarse-grained Martini force field. The method scales to larger molecules and a broader chemical space than existing schemes. The core of the mapping process is a graph-based analysis of the molecule’s bonding network, which has the advantages of being fast, general, and preserving symmetry. The parameterization process pays special attention to coarse-grained beads in aromatic rings. It also includes a method for building efficient and stable frameworks of constraints for molecules with structural rigidity. The performance of the method is tested on a diverse set of 87 neutral organic molecules and the ability of the resulting models to capture octanol–water and membrane–water partition coefficients. In the latter case, we introduce an adaptive method for extracting partition coefficients from free-energy profiles to take into account the interfacial region of the membrane. We also use the models to probe the response of membrane–water partitioning to the cholesterol content of the membrane.
Highlights
Computational screening is important in a variety of fields, from drug discovery[1] to toxicology.[2]
We present a method for generating coarsegrained Martini models that cover a wider chemical space than other methods
Our three priorities for an automated mapping algorithm are that (1) the method must generate mapping schemes compatible with the Martini framework, (2) the mappings must respect the symmetry of the molecule as much as possible, and (3) the algorithm must readily scale to large molecules
Summary
Computational screening is important in a variety of fields, from drug discovery[1] to toxicology.[2] The aim of screening is to narrow down a large chemical search space, thereby guiding time-consuming experimental testing toward formulations that are likely to have the desired behavior. Computational methods must generally be capable of high throughput to be viable for screening. In the field of toxicity and environmental impact, one of the important physical quantities in screening is the membrane− water partition coefficient or its logarithm log KMW, which is a measure of the extent to which a molecule accumulates in biological tissues.[3−8] Computational methods for predicting values of log KMW vary widely in their sophistication and accuracy. Multiparameter linear free-energy relationships, based on the correlation of partitioning free energies with various molecular descriptors, have been used to predict partitioning of solutes between different phases, including between lipid bilayers and water.[10−13] The
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