Kenneth M. Merz, Jr., Ph.D.

Kenneth M. Merz, Jr., Ph.D.

Professor of Chemistry

College of Liberal Arts and Sciences

2011 Awardee

Kenneth M. Merz, Jr. studies computational chemistry approaches aimed at the design of novel drugs or focused on predicting the folding of proteins into complex three-dimensional shapes.

Merz developed innovative linear-scaling quantum-mechanical methods that are uniquely applicable to these complex chemical problems occurring in biology and drug design. Through the use of these novel quantum-mechanical methods, Merz has explored the limitations of the extant approaches, identifying, in several instances, cases where current models have failed or succeeded. This has lead to a deeper understanding of how intra- and intermolecular interactions are modeled and have suggested novel research directions.

Classical force fields are built by considering simple models of intermolecular interactions, for example the water dimer, which consists of two water molecules hydrogen bonded to one another. By understanding a series of simple interactions that are present in protein systems, the notion is that these insights can be directly applied to macromolecules like proteins without real justification. In order to validate or invalidate this expectation, highly accurate experimental or computational information is required.

Indeed, modern quantum chemical approaches can achieve a remarkable level of realism in representing these interactions to the point where they are termed “chemically accurate”. Presently, Merz is using the capabilities of these chemically accurate calculations to evaluate the ability of simpler models to accurately predict inter and intramolecular interactions within protein and between proteins and ligands.

The results from this effort have begun to allow Merz to assess, for the first time, the expected errors in simple models, while, at the same, time giving direction to approaches aimed at improving existing molecular models. The outcome of this work will be the creation of better validated and more accurate models of molecular structure that can be routinely applied to drug and protein design problems.