Introduction

The goal of Professor Merz's research is to develop and exploit molecular modeling techniques in order to further our understanding of biomolecular systems. We are particularly interested in the study of the structure, dynamics, and biological function of metalloenzymes. We are also very interested in the development and application of so-called "coupled" quantum/classical simulation methods as well as linear scaling quantum mechanical methods to problems of biological interest. Using these latter techniques we are also developing a "Quantum Bioinformatics" system that will give researchers Web-based access to quantum mechanically derived information on biomolecular systems. Finally, we are using our linear-scaling QM approaches to facilitate and improve NMR and X-ray refinement studies.

Zinc metalloenzymes are an important class of enzymes that carry out a myriad of biological functions. One system of interest is human carbonic anhydrase II (HCA II), whose only known biological function is to balance the pH of blood by converting carbon dioxide (CO2) into bicarbonate (HCO3) and vice versa. Inhibitors (i.e.,drugs) of HCAII are used in the treatment of glaucoma. Another class of zinc enzymes of interest are the matrix metalloproteinases (MMPs) whose biological function is to degrade intracellular proteins. Inhibitors of MMPs are potentially useful in the treatment of diseases ranging from cancer and arthritis to periodontal disease. Recently, the X-ray structures of several beta-lactamases have become available. These are enzymes that allow bacteria to degrade common antibiotics, thereby leading to antibiotic resistant bacteria. Using quantum mechanical and molecular mechanical calculations we have studied the active site structure and protonation state of a binuclear beta-lactamasess. Recently, we have become interested in the zinc enzyme farnesyltransferase (FFTase), which is a potential anti-cancer target. Besides studies of zinc metalloenzymes we are also investigating the Ni containing enzyme urease that converts urea into ammonia and cyanic acid. These are very biologically important and interesting enzymes and will be the subject of continuing interest in my research group. Overall, our research projects on these classes of enzymes include the study of drug and substrate binding, the catalytic mechanism, and the dynamics of these enzymes in solution.

Most of our research projects described above involve, at some level, the development of new theoretical techniques, but one that is of special interest to us is the development of "coupled" quantum/classical simulation methods. In this approach, we use quantum mechanical techniques to model the portion of the system that is undergoing a reaction or a bond reorganization, while the remainder of the system is treated by classical mechanics. The major advantage of this approach is that we minimize the computational expense of a calculation, but we retain the ability to study reactive processes in condensed phases (i.e., solution or in enzyme.). However, a drawback of this method is the use of only a small quantum mechanical region. Hence, we have become interested in the development of an approach that will allow us to carry out fully quantum mechanical calculations on systems as large as enzymes.

In the adjacent figure we show the cpu time it takes to carry out a typical semiempirical quantum mechanical ("standard") calculation. Clearly the time to carry out this calculation as a function of the size of the system behaves in an exponential manner. It is this exponential behavior that precludes the use of quantum mechanical calculations on large molecular systems. However, through the use of a method termed "divide-and-conquer" we have been able to achieve linear scaling as a function of the size of the system. Several examples of how this method scales as a function of size is also given in Figure 2. From this figure one can readily see that the cost of these types of calculations (i.e., Schemes 1-3) scale linearly with system size as opposed to the standard approach which behaves exponentially. This approach represents a radical departure from how typical semiempirical quantum mechanical calculations are carried out, and we expect that through the use of this method we will be able to obtain novel insights into biomolecular structure, function, and dynamics. 

Using our linear-scaling technology we are studying protein-ligand interactions, protein-protein contacts, solvation of biomolecules and the detection of decoy protein structures from the native fold. We have also developed the capability to compute NMR chemical shifts using our linear-scaling technology and are using this method to predict the structure of protein-ligand complexes and we it in protein structure refinement using experimental NMR chemical shifts. Linear-scaling QM approaches are also being applied to X-ray refinement at both the high and low resolution regimes.