Tao Ye1 2 Qufei Gu2 Warren Nanney1 Huan Cao1

1, Univ of California-Merced, Merced, California, United States
2, Univ of California-Merced, Merced, California, United States

An outstanding question in molecular recognition at interfaces is how the spatial organization of the ligand/probe molecules impacts the energetics and kinetics of this process. Unlike a ligand molecule in a dilute solution, the ability of an immobilized ligand (or probe) to recognize targets may be profoundly influenced by interactions with the local chemical environment, which consists of the neighboring probe molecules, the spacer molecules near the probe molecules, and the substrate. An increasing body of evidence suggests that the molecular components are often not uniformly distributed. It is difficult to derive molecular level insight from existing ensemble averaging measurement of highly heterogeneous systems.

We have focused on DNA functionalized self-assembled monolayers (DNA SAMs) as the model system to understand how the complex interactions between the probe molecules impact molecular recognition on biosensors. We have developed new atomic force microscopy (AFM) techniques to image the single DNA probe molecules on model E-DNA sensor surfaces with substantially improved spatial resolution (a few nanometers). For the first time, we can map the spatial organization of DNA probe molecules on DNA SAMs at probe densities relevant to electrochemical DNA sensors. Our in situ AFM has provided new insight into the conformational changes and hybridization of single molecules. We have developed and applied spatial statistical models that allow us to correlate the spatial patterns of molecular components to the hybridization kinetics as well as electrochemical signaling. Our results not only confirmed the “crowding” effect at short spatial scales<15nm but also revealed a surprising cooperative effect: a probe molecule may increase the rate of target capture of another probe molecule that is 20-30 nm away. The origin of this effect will be discussed.

The results from our single molecule measurement revealed a new level of complexity of interfacial molecular recognition on a simple model system. The findings showcase the importance of high resolution, in situ, single molecule studies of such heterogeneous systems. With the improved knowledge of how complex interactions at the interface impact molecular recognition, we may begin to rationally tailor interfacial properties to enable biosensors that are more sensitive, selective and reliable.