PKA17-A Coarse-Grain Grid-Based Methodology and Web-Based Software for Predicting Protein pK a Shifts.

We have developed and tested PKA17, a coarse-grain grid-based model for predicting protein pK a shifts. Our pK a predictor is currently deployed via a website interface. We have carried out parameter fitting using 442 Asp, Glu, His, Lys, and Arg residues for which experimental results are available in the literature. PROPKA software has been used for benchmarking. The average unsigned error and root-mean-square deviation (RMSD) have been found to be 0.628 and 0.831 pH units, respectively, for PKA17. The corresponding results with PROPKA are 0.761 and 1.063 units. We have assessed the robustness of the developed PKA17 methodology with a number of tests and have also explored the possibility of using a combination of PROPKA and PKA17 calculations in order to improve the accuracy of predicted pK a values for protein residues. We have also once again confirmed that protein acidity constants are influenced almost entirely by residues in the immediate spatial proximity of the ionizable amino acids. The resulting PKA17 software has been deployed online with a web-based interface at http://users.wpi.edu/~jpcvitkovic/pka_calc.html. © 2019 Wiley Periodicals, Inc.

Binding of Copper and Cisplatin to Atox1 Is Mediated by Glutathione through the Formation of Metal-Sulfur Clusters.

Copper is an essential nutrient required for many biological processes involved in primary metabolism, but free copper is toxic due to its ability to catalyze formation of free radicals. To prevent toxic effects, in the cell copper is bound to proteins and low molecular weight compounds, such as glutathione, at all times. The widely used chemotherapy agent cisplatin is known to bind to copper-transporting proteins, including copper chaperone Atox1. Cisplatin interactions with Atox1 and other copper transporters are linked to cancer resistance to platinum-based chemotherapy. Here we analyze the binding of copper and cisplatin to Atox1 in the presence of glutathione under redox conditions that mimic intracellular environment. We show that copper(I) and glutathione form large polymers with a molecular mass of approximately 8 kDa, which can transfer copper to Atox1. Cisplatin also can form polymers with glutathione, albeit at a slower rate. Analysis of simultaneous binding of copper and cisplatin to Atox1 under physiological conditions shows that both metals are bound to the protein through copper-sulfur-platinum bridges.

Developing multisite empirical force field models for Pt(II) and cisplatin.

We have developed empirical force field parameters for Pt(II) and cisplatin. Two force field frameworks were used-modified OPLS-AA and our second-order polarizable POSSIM. A seven-site model was used for the Pt(II) ion. The goal was to create transferable parameter sets compatible with the force field models for proteins and general organic compounds. A number of properties of the Pt(II) ion and its coordination compounds have been considered, including geometries and energies of the complexes, hydration free energy, and radial distribution functions in water. Comparison has been made with experimental and quantum mechanical results. We have demonstrated that both versions are generally capable of reproducing key properties of the system, but the second-order polarizable POSSIM formalism permits more accurate quantitative results to be obtained. For example, the energy of formation of cisplatin as calculated with the modified OPLS-AA exhibited an error of 9.9%, while the POSSIM error for the same quantity was 6.2%. The produced parameter sets are transferable and suitable to be used in protein-metal binding simulations in which position or even coordination of the ion does not have to be constrained using preexisting knowledge. © 2016 Wiley Periodicals, Inc.

POSSIM: Parameterizing Complete Second-Order Polarizable Force Field for Proteins.

Previously, we reported development of a fast polarizable force field and software named POSSIM (POlarizable Simulations with Second order Interaction Model). The second-order approximation permits the speed up of the polarizable component of the calculations by ca. an order of magnitude. We have now expanded the POSSIM framework to include a complete polarizable force field for proteins. Most of the parameter fitting was done to high-level quantum mechanical data. Conformational geometries and energies for dipeptides have been reproduced within average errors of ca. 0.5 kcal/mol for energies of the conformers (for the electrostatically neutral residues) and 9.7° for key dihedral angles. We have also validated this force field by running Monte Carlo simulations of collagen-like proteins in water. The resulting geometries were within 0.94 Å root-mean-square deviation (RMSD) from the experimental data. We have performed additional validation by studying conformational properties of three oligopeptides relevant in the context of N-glycoprotein secondary structure. These systems have been previously studied with combined experimental and computational methods, and both POSSIM and benchmark OPLS-AA simulations that we carried out produced geometries within ca. 0.9 Å RMSD of the literature structures. Thus, the performance of POSSIM in reproducing the structures is comparable with that of the widely used OPLS-AA force field. Furthermore, our fitting of the force field parameters for peptides and proteins has been streamlined compared with the previous generation of the complete polarizable force field and relied more on transferability of parameters for nonbonded interactions (including the electrostatic component). The resulting deviations from the quantum mechanical data are similar to those achieved with the previous generation; thus, the technique is robust, and the parameters are transferable. At the same time, the number of parameters used in this work was noticeably smaller than that of the previous generation of our complete polarizable force field for proteins; thus, the transferability of this set can be expected to be greater, and the danger of force field fitting artifacts is lower. Therefore, we believe that this force field can be successfully applied in a wide variety of applications to proteins and protein-ligand complexes.