Predictions of the physicochemical properties of amino acid side chain analogs using molecular simulation
Literature Information
Alauddin Ahmed, Stanley I. Sandler
A candidate drug compound is released for clinical trails (in vivo activity) only if its physicochemical properties meet desirable bioavailability and partitioning criteria. Amino acid side chain analogs play vital role in the functionalities of protein and peptides and as such are important in drug discovery. We demonstrate here that the predictions of solvation free energies in water, in 1-octanol, and self-solvation free energies computed using force field-based expanded ensemble molecular dynamics simulation provide good accuracy compared to existing empirical and semi-empirical methods. These solvation free energies are then, as shown here, used for the prediction of a wide range of physicochemical properties important in the assessment of bioavailability and partitioning of compounds. In particular, we consider here the vapor pressure, the solubility in both water and 1-octanol, and the air–water, air–octanol, and octanol–water partition coefficients of amino acid side chain analogs computed from the solvation free energies. The calculated solvation free energies using different force fields are compared against each other and with available experimental data. The protocol here can also be used for a newly designed drug and other molecules where force field parameters and charges are obtained from density functional theory.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.











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