Faculty Advisor or Committee Member

George A. Kaminski, Advisor

Faculty Advisor or Committee Member

Christopher R. Lambert, Committee Member

Faculty Advisor or Committee Member

Ronald L. Grimm, Committee Member

Faculty Advisor or Committee Member

Erkan Tüzel, Committee Member

Identifier

etd-042419-212001

Abstract

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.

Publisher

Worcester Polytechnic Institute

Degree Name

PhD

Department

Chemistry & Biochemistry

Project Type

Dissertation

Date Accepted

2019-04-25

Accessibility

Restricted-WPI community only

Subjects

computational chemistry, force field, protein pka

Available for download on Monday, April 25, 2022

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