Detailed Research Description
DNA is a life-sustaining molecule that enables the storage, retrieval and inheritance of genetic information. It is composed of two complementary polymer chains twisted and base-paired together forming the well-known double helix. Based on their discovery of the structure of DNA some fifty years ago, Watson and Crick immediately proposed a possible copying mechanism for genetic information. Their work laid the foundation for our understanding of the important relationship between the structure and function of DNA.
Current Research
My research goes beyond the static structure of DNA and considers how the mechanical properties and dynamics of DNA influence its function. Spanning about 2 cm in length and only 2 nm in diameter, individual human DNA molecules are very long and flexible. Consequently, a DNA molecule’s conformation is continuously changing in response to essential forces induced by cellular processes (e.g., transcription) and thermal energy. Interestingly, the mechanical state of DNA has been shown to play a significant role in gene regulation. Unfortunately, however, our current understanding of how the mechanics and dynamics of DNA molecules influence their function is very limited. Understanding this key relationship will not only deepen our understanding of the molecule, but will enable us to develop novel therapies for diseases.
My approach to understanding the mechanics and dynamics of DNA has been to develop and utilize computational models for DNA. The disparate scales of a DNA molecule’s length and diameter create a significant computational modeling challenge. Therefore, I have focused on representing the long-length and -time scale dynamics of DNA while sacrificing resolution of the fast vibrations of its individual atoms. In particular, I have applied an elastic rod model to represent DNA in two biologically relevant systems detailed below: (1) gene regulation by lac repressor, and (2) supercoil relaxation by topoisomerase I.
Gene Regulation by Lac Repressor. The lac repressor protein in the bacteria E. Coli is a paradigm for gene regulation and is known as a genetic switch. In response to biochemical signals, it prevents local gene transcription by simultaneously binding two specific sites on a DNA molecule and thereby forming a loop of the intervening DNA. Although, the structure of the lac repressor protein has been determined by x-ray crystallography, the topology and energetics of the loop remain unknown. Understanding the energetic cost of loop formation is a key to understanding this gene regulatory system. To this end, I have employed a computational elastic rod model to explore loops formed from a large family of DNA sequences with differing lengths and intrinsic curvatures. The results of these computations have motivated an exciting collaboration with the Kahn lab at the University of Marylandto experimentally test my model predictions.
Supercoil Relaxation by Topoisomerase I. Long flexible DNA molecules (~2 cm in length), are compacted into the confines of human cell nuclei (~5 μm in diameter); and as a result of this and other cellular processes, DNA molecules become interwound. Topoisomerase I enzymes are responsible for regulating the accumulation of these DNA supercoils. They function by (1) locally breaking a single backbone of the double helix, (2) allowing the DNA to relieve torsional stress, and finally (3) repairing the broken backbone. I have undertaken a multi-scale modeling effort in collaboration with the Andricioaei lab at the University of California - Irvine to overcome the challenge of modeling at the length scales for both local topoisomerase I action (~0.1 nm) and long-length scale DNA supercoil relaxation (~100 nm). The Andricioaei lab models short-length scale deformations of topoisomerase I using molecular dynamics simulations, while I model the long-length scale deformations of the supercoiled DNA using the rod theory. By interfacing the two models we overcome limitations of the individual modeling strategies and represent the entire system. As a significant part of this research I have also extended the computational elastic rod model to better account for hydrodynamic drag, electrostatic self interactions, and self contact forces.
Future Research Directions
Although my research area is traditionally pursued by biophysicists, I believe that my perspective, as an engineer, uniquely positions me to make significant contributions to our understanding of DNA. Below I outline two future research directions.
Stochastic Elastic Rod Model. Previously, my research focused on modeling strain energy dominated DNA dynamics. Under these circumstances, the trajectory of DNA can be well described with a deterministic model, such as the one mentioned above, which neglects thermal energy. However, during many cellular processes, random thermal excitation contributes significantly to the molecule’s dynamics and in some cases is the driving force behind the process. Models that include the associated stochastic forces face the challenge of sampling the ensemble of possible trajectories a molecule may follow. Several of these ‘Brownian dynamics’ models have been developed; however, they lack the rich mechanical description provided by the elastic rod model. Therefore, I plan to develop a stochastic elastic rod model. In addition to providing an improved description of DNA mechanics, this new model has the potential of being computationally more efficient than existing Brownian dynamics models.
Multi-resolution Model. As already emphasized, the dynamics of DNA during many biological processes occur on many different length scales. During the process of transcription, for example, an enzyme (RNA polymerase) locally untwists a full turn of the double helix (about 3.5 nm) and thereby induces conformational changes (including the formation of supercoils) which can effect the molecule on a longer length scale (>75 nm). However, on much longer length scales (1 μm to 2 cm), RNA polymerase will have almost unnoticeable effects. Therefore, it’s not only excessive to model an entire length of DNA with high spatial resolution, but it’s also computationally prohibitive. To this end, I plan to develop a multi-resolution model for long DNA molecules that patches together several DNA domains. Each domain will have a different resolution and will interface with its neighbors through the transfer of boundary conditions. For the case of transcription, this model could utilize an all-atom molecular dynamics description of RNA polymerase and the locally untwisted DNA. This detailed description could then provide boundary conditions for an elastic rod used to represent DNA conformational changes on the length scale of about 100 nm. At yet another level of resolution, a new reduced order model would be developed to describe interwound supercoiled structures. Finally, a lump model would be developed to represent the influence of the remaining bulk of the DNA.
These research efforts will contribute to a fundamental understanding of how the mechanics and dynamics of DNA influence its function. Although very limited, our present understanding of this key relationship has already led to significant drug therapies. For example, a chemotherapy drug (topotecan) prevents topoisomerase I enzymes from relaxing DNA supercoils in cancerous cells and thereby initiates cell death. Deepening our understanding of the mechanics and dynamics of DNA will therefore enable the development of new drug therapies that target diseases such as cancer. This research has additional broad implications in many areas of biology and engineering. In biology, these modeling strategies could also be applied to other biopolymers and bio-filaments such as RNA, microtubules, and actin. While in engineering, these modeling strategies could be applied to the design of nano structures and mechanisms that utilize long slender filaments (e.g., carbon nano-tubes) or even DNA molecules.