(673d) Predicting the Solubility of Amino-Acid Mixtures with the SAFT-? Mie Group-Contribution Method

As peptide drugs gain increasing attention in academic and industrial arenas as active pharmaceutical ingredients (APIs) due to their therapeutic value, more resources are directed to building robust computational models for estimating their solubility in a wide variety of solvent mixtures at variable thermodynamic conditions. Since amino acids are the building blocks of peptide molecules, they provide a key to the structure and, thus, to the modelling of peptides. This role of amino acids as building blocks of peptides can be exploited within a group-contribution (GC) method, such as the SAFT-γ Mie, in which the physico-chemical properties of the fluid are derived from a thermodynamic description between the groups comprising its molecules; the solubility, is one such physico-chemical property that is derivable from the fundamental equations of phase equilibrium. This property plays a critical role in the design, synthesis, and purification of drug molecules.

We use the SAFT-γ Mie [1–4] GC equation of state, in which molecules are treated as heteronuclear chains of fused spherical segments interacting via attractive Mie potentials of variable range, with short-range association sites added to mediate directional interactions. The thermodynamic properties of the molecules are derived from the Helmholtz free-energy expression summing the different contributions (ideal, monomer, chain, and association). An expression for the solubility of the solid solute in the liquid solvent can be derived from the equality of chemical potentials in the solid and liquid phases. The SAFT-γ Mie GC is used to calculate the activity coefficient of the amino acid in solution; this is input to the solubility expression, together with the experimental values of the enthalpy of fusion, the melting temperature, and the change in constant-pressure heat capacity between the solid and liquid phases. The required SAFT-γ Mie group interaction parameters of the amino acids are obtained by adjustment using pure and mixture thermodynamic data of molecules that contain the groups of interest. This SAFT-γ Mie GC approach is found to be very satisfactory for predicting the solubility of various naturally-occurring and synthetic amino acids in pure and mixed solvent environments and in multi-solute mixtures.

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