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Scanning confocal interference microscopy (SCIM) and molecular dynamics (MD) simulations were used to investigate the adsorption of the synthetic polypeptide poly(l-glutamic acid) (poly-glu) to calcium oxalate monohydrate (COM) crystals and its effect on COM formation. At low concentrations (1 μg/mL), poly-glu inhibits growth most effectively in ⟨001⟩ directions, indicating strong interactions of the polypeptide with {121} crystal faces. Growth in <010> directions was inhibited only marginally by 1 μg/mL poly-glu, while growth in <100> directions did not appear to be affected. This suggests that, at low concentrations, poly-glu inhibits lattice-ion addition to the faces of COM in the order {121} > {010} ≥ {100}. At high concentrations (6 μg/mL), poly-glu resulted in the formation of dumbbell-shaped crystals featuring concave troughs on the {100} faces. The effects on crystal growth indicate that, at high concentrations, poly-glu interacts with the faces of COM in the order {100} > {121} > {010}. This mirrors MD simulations, which predicted that poly-glu will adsorb to a {100} terrace plane (most calcium-rich) in preference to a {121} (oblique) riser plane but will adsorb to {121} riser plane in preference to an {010} terrace plane (least calcium-rich). The effects of different poly-glu concentration on COM growth (1-6 μg/mL) may be due to variations between the faces in terms of growth mechanism and/or (nano)roughness, which can affect surface energy. In addition, 1 μg/mL might not be adequate to reach the critical concentration for poly-glu to significantly pin step movement on {100} and {010} faces. Understanding the mechanisms involved in these processes is essential for the development of agents to reduce recurrence of kidney stone disease.

This chapter provides an overview of the various techniques that are commonly used in classical molecular dynamics simulations. It describes suitable algorithms for the integration of Newton's equation of motion over many time steps for systems containing a large number of particles, different choices of boundary conditions as well as available force fields for biological systems, that is, the mathematical description of the interactions of atoms and molecules with each other. It also illustrates algorithms used to simulate systems at constant temperature and/or pressure and discusses their advantages and disadvantages. It presents a few methods to save CPU time and a summary of popular software for biomolecular molecular dynamics simulations.

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