Computational simulations of chemical systems play an ever-increasing role in many areas of biochemical research from rational drug design to probing fundamental physiological processes. Depending on the method, a vast array of properties are able to be predicted. Here we report the design and implementation of two methods for investigating diverse problems in protein biochemistry. In order to better understand protein–metal interactions—most importantly for the difficult to model transition metal ions— empirical force field parameters were developed for Pt(II), cisplatin, and other Pt(II) coordination compounds. Two force field frameworks were used: a modified version of the fixed- charge OPLS-AA and the polarizable POSSIM force field. A seven-site model was used for the Pt(II) ion. The produced parameters are compatible with the OPLS-AA and POSSIM force fields and can be used in protein–metal binding simulations in which—contrary to the common treatment of metal ions in such simulations—the position or even coordination of the ion does not have to be constrained using preexisting knowledge. It has been demonstrated that the produced models are capable of reproducing key properties of relevant Pt(II) complexes but that the POSSIM formalism yields more accurate values for energies of formation than the OPLS-AA model. This Pt(II) model was employed—along with previously developed Cu(I) parameters—to investigate the binding of platinum to the protein Atox1, a human copper chaperone implicated in the resistance mechanism of cisplatin and other platinum antitumor compounds. In collaboration with the Dmitriev and Bernholc groups, we used our models to inform and refine spectroscopic experiments as well as to serve as starting points for high-performance quantum calculations. It was shown that under physiological redox conditions, copper(I) and cisplatin can form large polymers with glutathione. These polymers were capable of transferring copper(I) to apo-Atox1 or to platinum(II) to copper-loaded Atox1. Analysis of the simultaneous binding of copper(I) and platinum(II) to Atox1 was found to occur through the formation of copper–sulfur–platinum bridges, where copper is coordinated by three sulfur atoms and platinum by four sulfur atoms. With the goal of using a simple model to be able to quickly estimate the acid disassociation constants of proteins, PKA17 has been developed and tested. PKA17 is a coarse-grain grid-based method and software tool for accurately and rapidly calculating protein pKa values given an input PDB structure file. During development, parameter fitting was carried out using a compilation of 442 Asp, Glu, His, and Lys residues that had both high-resolution PDB structures and published experimental pKa values available. Applying our PKA17 model, the calculated average unsigned error and RMSD for the residue set were found to be 0.628 and 0.831 pH units, respectively. As a benchmark for comparison, the same residue set was evaluated with the PROPKA software package which resulted in an average unsigned error of 0.761 pH units and an RMSD of 1.063 pH units. Finally, a web interface for the PKA17 software was developed and deployed (http://users.wpi.edu/~jpcvitkovic/pka_calc.html) to make PKA17 available to the wider scientific community.

"The accurate, fast and low cost computational tools are indispensable for studying the structure and dynamics of biological macromolecules in aqueous solution. The goal of this thesis is development and validation of continuum Fuzzy-Border (FB) solvation model to work with the Polarizable Simulations Second-order Interaction Model (POSSIM) force field for proteins developed by Professor G A Kaminski. The implicit FB model has advantages over the popularly used Poisson Boltzmann (PB) solvation model. The FB continuum model attenuates the noise and convergence issues commonly present in numerical treatments of the PB model by employing fixed position cubic grid to compute interactions. It also uses either second or first-order approximation for the solvent polarization which is similar to the second-order explicit polarization applied in POSSIM force field. The FB model was first developed and parameterized with nonpolarizable OPLS-AA force field for small molecules which are not only important in themselves but also building blocks of proteins and peptide side chains. The hydration parameters are fitted to reproduce the experimental or quantum mechanical hydration energies of the molecules with the overall average unsigned error of ca. 0.076kcal/mol. It was further validated by computing the absolute pKa values of 11 substituted phenols with the average unsigned error of 0.41pH units in comparison with the quantum mechanical error of 0.38pH units for this set of molecules. There was a good transferability of hydration parameters and the results were produced only with fitting of the specific atoms to the hydration energy and pKa targets. This clearly demonstrates the numerical and physical basis of the model is good enough and with proper fitting can reproduce the acidity constants for other systems as well. After the successful development of FB model with the fixed charges OPLS-AA force field, it was expanded to permit simulations with Polarizable Simulations Second-order Interaction Model (POSSIM) force field. The hydration parameters of the small molecules representing analogues of protein side chains were fitted to their solvation energies at 298.15K with an average error of ca.0.136kcal/mol. Second, the resulting parameters were used to reproduce the pKa values of the reference systems and the carboxylic (Asp7, Glu10, Glu19, Asp27 and Glu43) and basic residues (Lys13, Lys29, Lys34, His52 and Lys55) of the turkey ovomucoid third domain (OMTKY3) protein. The overall average unsigned error in the pKa values of the acid residues was found to be 0.37pH units and the basic residues was 0.38 pH units compared to 0.58pH units and 0.72 pH units calculated previously using polarizable force field (PFF) and Poisson Boltzmann formalism (PBF) continuum solvation model. These results are produced with fitting of specific atoms of the reference systems and carboxylic and basic residues of the OMTKY3 protein. Since FB model has produced improved pKa shifts of carboxylic residues and basic protein residues in OMTKY3 protein compared to PBF/PFF, it suggests the methodology of first-order FB continuum solvation model works well in such calculations. In this study the importance of explicit treatment of the electrostatic polarization in calculating pKa of both acid and basic protein residues is also emphasized. Moreover, the presented results demonstrate not only the consistently good degree of accuracy of protein pKa calculations with the second-degree POSSIM approximation of the polarizable calculations and the first-order approximation used in the Fuzzy-Border model for the continuum solvation energy, but also a high degree of transferability of both the POSSIM and continuum solvent Fuzzy Border parameters. Therefore, the FB model of solvation combined with the POSSIM force field can be successfully applied to study the protein and protein-ligand systems in water. "

Protein pK(a)s and metalloprotein reduction potentials are studied with computational methodologies based on an ab initio quantum mechanics (QM) description of the protein and a linearized Poisson-Boltzmann Equation (LPBE) description of the solvent. The practical applicability of the QM/LPBE method is extended to proteins by using a QM description of the ionizable residue and a molecular mechanics (MM) description of the rest of the protein. This QM/MM/LPBE method is used to predict the pKa of Lys55 in the serine protease inhibitor turkey ovomucoid third domain (OMTKY3) and the prediction of 11.0 is in good agreement with the experimental value of 11.1. This is the first time a protein pKa value has been predicted with QM/MM methods. The QM/LPBE method is used to predict and interpret the pKa values of the five carboxyl residues (Asp7, Glu10, Glu19, Asp27, and Glu43) in OMTKY3. All the predicted pKa values are within 0.5 pH units of experiment, with a root mean square deviation of 0.31 pH units. We find that the decreased pKa values observed for some of the residues are primarily due to hydrogen bonds to the carboxyl oxygens. Hydrophobic effects are also shown to be important in raising the pKa. Interactions with charged residues are shown to have relatively little effect on the carboxyl pKa values in this protein, in general agreement with experiment. The relative Cu2+/Cu+ reduction potentials of six type-1 copper sites (cucumber stellacyanin, P. aeruginosa azurin, poplar plastocyanin, C. cinereus laccase, T. ferrooxidans rusticyanin and human ceruloplasmin), which lie in a reduction potential range from 260 mV to over 1000 mV, have been studied with the QM/LPBE method. For the first time, the range and relative orderings of the reduction potentials are reproduced well compared to experimental values. The study suggests that the main interactions determing the relative reduction potentials of blue copper sites are located within 6 Å of the Cu atoms. Further analysis suggests that the reduction potential differences of type-1 copper sites are caused by axial ligand interactions, hydrogen bonding to the S(Cys), and protein constraints on the inner sphere ligand orientations.

<p>Understanding and predicting chemical phenomena is the main goal of computational chemistry. In this thesis I present my work on applying computational approaches to study chemical processes in biological and supramolecular systems.</p> <p>pH-responsive molecular tweezers have been proposed as an approach for targeting drug-delivery to tumors, which tend to have a lower pH than normal cells. In chapter 2 I present a computational study I performed on a pH-responsive molecular tweezer using <em>ab initio</em> quantum chemistry in the gas phase and molecular dynamics simulations in solution. The binding free energy in solution was calculated using Steered Molecular Dynamics. We observe, in atomistic detail, the pH-induced conformational switch of the tweezer and the resulting release of the drug molecule. Even when the tweezer opens, the drug molecule remains near a hydrophobic arm of the molecular tweezer. Drug release cannot occur, it seems, unless the tweezer is a hydrophobic environment with low pH.</p> <p>The protonation state of amino acid residues in proteins depends on their respective pK_a values. Computational methods are particularly important for estimating the pK_a values of buried and active site residues, where experimental data is scarce. In chapter 3 I used the cluster model approach to predict the pK_a of some challenging protein residues and for which methods based on the numerical solution of the Poisson-Boltzmann equation and empirical approaches fail. The ionizable residue and its close environment were treated quantum mechanically, while the rest of the protein was replaced by a uniform dielectric continuum. The approach was found to overestimate the electrostatic interaction leading to predicting lower pK_a values.</p> / Master of Science (MSc)