Predictive modelling of the solid-liquid solubility and chemical equilibrium of amino acids and oligopeptides: Exploring the influence of charges within a group-contribution framework
File(s)
Author(s)
Alyazidi, Ahmed
Type
Thesis
Abstract
The accurate prediction of thermodynamic properties of amino-acid and peptide solutions is critical in the pharmaceutical industry, where amino acids and oligopeptides are gaining increasing prominence as active pharmaceutical ingredients (APIs). A major challenge in this regard is the development of predictive models with broad applicability, parameter transferability, and minimal reliance on system-specific experimental data. In this thesis, this challenge is addressed by developing group-contribution (GC) thermodynamic models to predict the solubility of amino acids and oligopeptides across a wide range of solvent systems and thermodynamic conditions, with a particular focus on the complex effects of pH-dependent speciation and charge interactions.
The SAFT-γ Mie GC equation of state (EoS) is employed to describe solid–liquid equilibria in systems containing amino acids and oligopeptides. Parameter optimisation is carried out using experimental data from chemically related systems, demonstrating the high degree of transferability and reducing the dependency on direct solubility measurements. Chemical-equilibrium equations are coupled with phase-equilibrium equations to capture speciation effects accurately. Additionally, an exploratory molecular simulation study benchmarks the treatment of electrostatic interactions in ionic systems using the expanded-ensemble method, providing critical insights into modelling ionic chains within primitive-model expressions.
The resulting model delivers accurate solubility predictions for a wide variety of systems, underscoring its robustness and potential for application in drug development. However, the study also highlights the limitations imposed by the scarcity and inconsistency of experimental data, especially for melting properties and solid–liquid solubility. The molecular simulation study provides important insights into the treatment of electrostatic interactions in ionic-chain molecules, providing potential directions for future improvements to the primitive-model expressions used within the model.
The SAFT-γ Mie GC equation of state (EoS) is employed to describe solid–liquid equilibria in systems containing amino acids and oligopeptides. Parameter optimisation is carried out using experimental data from chemically related systems, demonstrating the high degree of transferability and reducing the dependency on direct solubility measurements. Chemical-equilibrium equations are coupled with phase-equilibrium equations to capture speciation effects accurately. Additionally, an exploratory molecular simulation study benchmarks the treatment of electrostatic interactions in ionic systems using the expanded-ensemble method, providing critical insights into modelling ionic chains within primitive-model expressions.
The resulting model delivers accurate solubility predictions for a wide variety of systems, underscoring its robustness and potential for application in drug development. However, the study also highlights the limitations imposed by the scarcity and inconsistency of experimental data, especially for melting properties and solid–liquid solubility. The molecular simulation study provides important insights into the treatment of electrostatic interactions in ionic-chain molecules, providing potential directions for future improvements to the primitive-model expressions used within the model.
Version
Open Access
Date Issued
2024-04-23
Date Awarded
01/08/2025
License URL
Advisor
Galindo, Amparo
Jackson, George
Publisher Department
Department of Chemical Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)