Importance of electrostatic polarizability in calculating cysteine acidity constants and copper(I) binding energy of Bacillus subtilis CopZ

AMOEBA Force Field Trajectories Improve Predictions of Accurate pKa Values of the GFP Fluorophore: The Importance of Polarizability and Water Interactions

Precisely quantifying the magnitude, direction, and biological functions of electric fields in proteins has long been an outstanding challenge in the field. The most widely implemented experimental method to measure such electric fields at a particular residue in a protein has been through changes in pKa of titratable residues. While many computational strategies exist to predict these values, it has been difficult to do this accurately or connect predicted results to key structural or mechanistic features of the molecule. Here, we used experimentally determined pKa values of the fluorophore in superfolder green fluorescent protein (GFP) with amino acid mutations made at position Thr 203 to evaluate the pKa prediction ability of molecular dynamics (MD) simulations using a polarizable force field, AMOEBA. Structure ensembles from AMOEBA were used to calculate pKa values of the GFP fluorophore. The calculated pKa values were then compared to trajectories using a conventional fixed charge force field (Amber03 ff). We found that the position of water molecules included in the pKa calculation had opposite effects on the pKa values between the trajectories from AMOEBA and Amber03 force fields. In AMOEBA trajectories, the inclusion of water molecules within 35 Å of the fluorophore decreased the difference between the predicted and experimental values, resulting in calculated pKa values that were within an average of 0.8 pKa unit from the experimental results. On the other hand, in Amber03 trajectories, including water molecules that were more than 5 Å from the fluorophore increased the differences between the calculated and experimental pKa values. The inaccuracy of pKa predictions determined from Amber03 trajectories was caused by a significant stabilization of the deprotonated chromophore's free energy compared to the result in AMOEBA. We rationalize the cutoffs for explicit water molecules when calculating pKa to better predict the electrostatic environment surrounding the fluorophore buried in GFP. We discuss how the results from this work will assist the prospective prediction of pKa values or other electrostatic effects in a wide variety of folded proteins.

Cu(I) Controls Conformational States in Human Atox1 Metallochaperone: An EPR and Multiscale Simulation Study

Atox1 is a human copper metallochaperone that is responsible for transferring copper ions from the main human copper transporter, hCtr1, to ATP7A/B in the Golgi apparatus. Atox1 interacts with the Ctr1 C-terminal domain as a dimer, although it transfers the copper ions to ATP7A/B in a monomeric form. The copper binding site in the Atox1 dimer involves Cys12 and Cys15, while Lys60 was also suggested to play a role in the copper binding. We recently showed that Atox1 can adopt various conformational states, depending on the interacting protein. In the current study, we apply EPR experiments together with hybrid quantum mechanics–molecular mechanics molecular dynamics simulations using a recently developed semiempirical density functional theory approach, to better understand the effect of Atox1’s conformational states on copper coordination. We propose that the flexibility of Atox1 occurs owing to protonation of one or more of the cysteine residues, and that Cys15 is an important residue for Atox1 dimerization, while Cys12 is a critical residue for Cu(I) binding. We also show that Lys60 electrostatically stabilizes the Cu(I)–Atox1 dimer.

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.

Metal Ion Modeling Using Classical Mechanics

Metal ions play significant roles in numerous fields including chemistry, geochemistry, biochemistry, and materials science. With computational tools increasingly becoming important in chemical research, methods have emerged to effectively face the challenge of modeling metal ions in the gas, aqueous, and solid phases. Herein, we review both quantum and classical modeling strategies for metal ion-containing systems that have been developed over the past few decades. This Review focuses on classical metal ion modeling based on unpolarized models (including the nonbonded, bonded, cationic dummy atom, and combined models), polarizable models (e.g., the fluctuating charge, Drude oscillator, and the induced dipole models), the angular overlap model, and valence bond-based models. Quantum mechanical studies of metal ion-containing systems at the semiempirical, ab initio, and density functional levels of theory are reviewed as well with a particular focus on how these methods inform classical modeling efforts. Finally, conclusions and future prospects and directions are offered that will further enhance the classical modeling of metal ion-containing systems.

Membrane Anchoring and Ion-Entry Dynamics in P-type ATPase Copper Transport

Cu+-specific P-type ATPase membrane protein transporters regulate cellular copper levels. The lack of crystal structures in Cu+-binding states has limited our understanding of how ion entry and binding are achieved. Here, we characterize the molecular basis of Cu+ entry using molecular-dynamics simulations, structural modeling, and in vitro and in vivo functional assays. Protein structural rearrangements resulting in the exposure of positive charges to bulk solvent rather than to lipid phosphates indicate a direct molecular role of the putative docking platform in Cu+ delivery. Mutational analyses and simulations in the presence and absence of Cu+ predict that the ion-entry path involves two ion-binding sites: one transient Met148-Cys382 site and one intramembranous site formed by trigonal coordination to Cys384, Asn689, and Met717. The results reconcile earlier biochemical and x-ray absorption data and provide a molecular understanding of ion entry in Cu+-transporting P-type ATPases.

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.

Polarizable simulations with second order interaction model (POSSIM) force field: developing parameters for protein side-chain analogues

A previously introduced polarizable simulations with second-order interaction model (POSSIM) force field has been extended to include parameters for small molecules serving as models for peptide and protein side-chains. Parameters have been fitted to permit reproducing many-body energies, gas-phase dimerization energies, and geometries and liquid-phase heats of vaporization and densities. Quantum mechanical and experimental data have been used as the target for the fitting. The POSSIM framework combines accuracy of a polarizable force field and computational efficiency of the second-order approximation of the full-scale induced point dipole polarization formalism. The resulting parameters can be used for simulations of the parameterized molecules themselves or their analogues. In addition to this, these force field parameters are currently being used in further development of the POSSIM fast polarizable force field for proteins.

Calculating pKa values for substituted phenols and hydration energies for other compounds with the first-order Fuzzy-Border continuum solvation model

We have computed pK(a) values for 11 substituted phenol compounds using the continuum Fuzzy-Border (FB) solvation model. Hydration energies for 40 other compounds, including alkanes, alkenes, alkynes, ketones, amines, alcohols, ethers, aromatics, amides, heterocycles, thiols, sulfides, and acids have been calculated. The overall average unsigned error in the calculated acidity constant values was equal to 0.41 pH units and the average error in the solvation energies was 0.076 kcal/mol. We have also reproduced pK(a) values of propanoic and butanoic acids within about 0.1 pH units from the experimental values by fitting the solvation parameters for carboxylate ion carbon and oxygen atoms. The FB model combines two distinguishing features. First, it limits the amount of noise which is common in numerical treatment of continuum solvation models by using fixed-position grid points. Second, it uses either second- or first-order approximation for the solvent polarization, depending on a particular implementation. These approximations are similar to those used for solute and explicit solvent fast polarization treatment which we developed previously. This article describes results of using the first-order technique. This approximation places the presented methodology between the Generalized Born and Poisson-Boltzmann continuum solvation models with respect to their accuracy of reproducing the many-body effects in modeling a continuum solvent.

Effects of lysine substitution on stability of polyalanine alpha-helix

We have studied stability of polyalanine alpha-helices with lysine residues added at C-and N-termini in gas-phase and aqueous solution. Monte Carlo simulations with the fixed-charges OPLS-AA and our polarizable POSSIM force fields were carried out. The results of the simulations confirm previously observed phenomena of the helix being stable with the LYS residue on the C-terminus and losing its helical structure if the charged LYS residue is located at the N-terminus of the polypeptide in gas-hase. Both OPLS-AA and POSSIM force fields performed essentially similarly, thus validity of the both for reproducing and predicting structures of such polypeptides has been confirmed. We have also studied the effect of replacing the normal N- and C-termini with methyl capping (this approach is often used in computational studies). Our results have demonstrated that the structure and stability of the polypeptides do not depend significantly on such a substitution although details of the resulting structure may change. The liquid-state simulations produced stable alpha-helixes regardless of the position of the protonated lysine residue. Overall, we have validated our polarizable POSSIM force field and the techniques used in the simulations, since the change of the helix structure as a function of the position of the LYS residue depends on a fine balance of energy contributions, and our methodology reproduced this balance well.