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. 2023 Jan 4;25(2):1220-1235.
doi: 10.1039/d2cp02879d.

Recalibrating the calcium trap in amino acid carboxyl groups via classical molecular dynamics simulations

Janou A Koskamp  1 , Sergio E Ruiz Hernandez  1 , Nora H de Leeuw  1   2 , Mariette Wolthers  1
Affiliations

Recalibrating the calcium trap in amino acid carboxyl groups via classical molecular dynamics simulations

Janou A Koskamp et al. Phys Chem Chem Phys. .

Abstract

In order to use classical molecular dynamics to complement experiments accurately, it is important to use robust descriptions of the system. The interactions between biomolecules, like aspartic and glutamic acid, and dissolved ions are often studied using standard biomolecular force-fields, where the interactions between biomolecules and cations are often not parameterized explicitly. In this study, we have employed metadynamics simulations to investigate different interactions of Ca with aspartic and glutamic acid and constructed the free energy profiles of Ca2+-carboxylate association. Starting from a generally accepted, AMBER-based force field, the association was substantially over and under-estimated, depending on the choice of water model (TIP3P and SPC/fw, respectively). To rectify this discrepancy, we have replaced the default calcium parameters. Additionally, we modified the σij value in the hetero-atomic Lennard-Jones interaction by 0.5% to further improve the interaction between Ca and carboxylate, based on comparison with the experimentally determined association constant for Ca with the carboxylate group of L-aspartic acid. The corrected description retrieved the structural properties of the ion pair in agreement with the original biomolecule - Ca2+ interaction in AMBER, whilst also producing an association constant comparable to experimental observations. This refined force field was then used to investigate the interactions between amino acids, calcium and carbonate ions during biogenic and biomimetic calcium carbonate mineralisation.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Fig. 1
Fig. 1. Free energy profiles for the interaction between Ca2+ and the Ocarboxyl. (a) l-Asp and (b) glutamic acid. Set_1TIP3P (purple; ), Set_1SPC/fw (red; ), Set_2 (pink; ), Set_3unmodified (brown; ), Set_3σ+0.5%σ (blue; ), Set_3σ+1.0%σ (orange; ), Set_3σ+2.0%σ (green; ).
Fig. 2
Fig. 2. Radial distribution function (after B-spline interpolation) (left axis) and corresponding integral (N(r)) (right axis) between Ocarboxylate and Ow, after 10 ns of classical MD (a) l-Asp, Set_3unmodified (orange; ), Set_3σ+0.5%σ (blue; ), and (b) glutamic acid, Set_3unmodified (red; ), Set_3σ+0.5%σ (green; ) when Ca–Ocarboxylate were in CIP state.
Fig. 3
Fig. 3. Angular distribution function between Ocarboxylate, Ow, Hw after 10 ns of classical MD (a) l-Asp, Set_3unmodified (orange; ), Set_3σ+0.5%σ (blue; ), and (b) glutamic acid, Set_3unmodified (red; ), Set_3σ+0.5%σ (green; ) when Ca–Ocarboxylate were in CIP state.
Fig. 4
Fig. 4. Radial distribution function (after B-spline interpolation) between Ca2+ and Ow, after 10 ns of classical MD (a) l-Asp, Set_3unmodified (orange; ), Set_3σ+0.5%σ (blue; ), and (b) glutamic acid, Set_3unmodified (red; ), Set_3σ+0.5%σ (green; ) when Ca–Ocarboxylate were in CIP state.
Fig. 5
Fig. 5. Free energy as a function of distance Ca2+ and Ocarboxylate and coordination number of Ca2+ and Owater.
Fig. 6
Fig. 6. Radial distribution function (after B-spline interpolation) (left axis) and corresponding integral (N(r)) (right axis) between Ca2+, Cc, Oc, and Ow, after 30 ns of simulation. Pure (purple; ), l-Asp with Set_1SPC/fw (transparent blue; ), l-Asp Set_3σ+0.5%σ (blue; ), d-Asp Set_1SPC/fw (transparent orange; ), d-Asp Set_3σ+0.5%σ (orange; ).
Fig. 7
Fig. 7. Radial distribution function (after B-spline interpolation) between Ca2+, Cc, Oc, with the different functional groups in aspartic acid after 30 ns of simulation. l-Asp with Set_1SPC/fw (transparent blue; ), l-Asp Set_3σ+0.5%σ (blue; ), d-Asp Set_1SPC/fw (transparent orange; ), d-Asp Set_3σ+0.5%σ (orange; ). The data from Set_3σ+0.5%σ was averaged over the four duplicates, Set_1SPC/fw was a single simulation.
Fig. 8
Fig. 8. Probability intensity plots of different biomolecule–CaCO3-systems showing the probability of an ion to be in a cluster with a certain size as a function of time (averaged over four simulations).
Fig. 9
Fig. 9. Probability (%) of an aggregate of certain size (consisting of a number of ions) taken from the last 10 ns of the 30 ns simulation. Pure (), l-Asp Set_3σ+0.5%σ (blue; ), d-Asp Set_3σ+0.5%σ (orange; ).
Fig. 10
Fig. 10. SASA analysis using the Shrake and Rupley algorithm of Pure (), l-Asp with Set_1SPC/fw (pink; ), l-Asp Set_3σ+0.5%σ (blue; ), d-Asp Set_1SPC/fw (brown; ), d-Asp Set_3σ+0.5%σ (orange; ), the transparent lines represent the individual calculations.
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