ComplexMixtures.jl

Package to perform minimum-distance distribution analyses of complex solute-solvent interactions
Author m3g
Popularity
15 Stars
Updated Last
2 Months Ago
Started In
March 2020

Stable Dev Tests Aqua QA

ComplexMixtures.jl

A package to study the structure of solutions formed by solutes and solvents of complex molecular shapes.

Documentation:

The documentation is available at: https://m3g.github.io/ComplexMixtures.jl

Examples

A series of examples of applications can be found at: https://m3g.github.io/ComplexMixtures.jl/stable/examples

Overview

ComplexMixtures is a package to study the solute and solvent interactions of mixtures of molecules of complex shape. Conventional radial distribution functions are not appropriate to represent the structure of a solvent around a solute with many atoms, and a variable, non-spherical shape.

Typical solutes of complex shape are proteins, nucleic acids, and polymers in general. Smaller molecules like lipids, carbohydrates, etc, are also complex enough such that representing the structure of the solution of those molecules with distribution functions is not trivial.

Minimum-Distance Distribution Functions (MDDFs) are a very general and practical way to represent solute-solvent interactions for molecules with arbitrarily complex sizes and geometries. Briefly, instead of computing the density distribution function of a particular atom or the center-of-mass of the molecules, one computes the distribution function of the minimum-distance between any solute and solvent atoms. This provides a size and shape-independent distribution which is very natural to interpret in terms of molecular interactions.

Minimum-distance distribution function and its decomposition into molecular groups.

Additionally, the MDDFs can be decomposed into contributions of each type of atom (or groups of atoms) of the solute and solvent molecules, such that the profiles of the distributions can be interpreted in terms of the chemical nature of the species involved in the interactions at each distance.

Finally, as with radial distribution functions, MDDFs can be used to compute Kirkwood-Buff integrals to connect the accumulation or depletion of the solvents components to thermodynamic properties, like protein structural stability, solubility, and others.

Density map of a solvent in the vicinity of each protein residue.

References

If this package was useful to you, please cite the following articles:

  • L. Martínez, ComplexMixtures.jl: Investigating the structure of solutions of complex-shaped molecules from a solvent-shell perspective. J. Mol. Liq. 347, 117945, 2022. [Full Text]

  • L. Martínez, S. Shimizu, Molecular interpretation of preferential interactions in protein solvation: a solvent-shell perspective by means of minimum-distance distribution functions. J. Chem. Theor. Comp. 13, 6358–6372, 2017. [Full Text]

Additional resources

Please go to http://m3g.iqm.unicamp.br to find additional resources and publications associated with this project.

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