DNA microarrays are a potentially disruptive technology in the medical field, but their use in such settings is limited by poor reliability. Microarrays work on the principle of hybridization and can only be as reliable as this process is robust, yet little is known at the molecular level about how the surface affects the hybridization process. This work uses advanced molecular simulation techniques and an experimentally-parameterized coarse-grain model to determine the mechanism by which hybridization occurs on surfaces and to identify key factors that influence the accuracy of DNA microarrays. Comparing behavior in the bulk and on the surface showed, contrary to previous assumptions, that hybridization on surfaces is more energetically favorable than in the bulk. The results also show that hybridization proceeds through a mechanism where the untethered (target) strand often flips orientation. For evenly-lengthed strands, the surface stabilizes hybridization (compared to the bulk system) by reducing the barriers involved in the flipping event. Additional factors were also investigated, including the effects of stretching or compressing the probe strand as a model system to test the hypothesis that improving surface hybridization will improve microarray performance. The results in this regard indicate that selectivity can be increased by reducing overall sensitivity by a small degree. Another factor that was investigated was the effect of unevenly-lengthed strands. It was found that, when unevenly-lengthed strands were hybridized on a surface, the surface may destabilize hybridization compared to the bulk, but the degree of destabilization is dependent on the location of the matching sequence. Taken as a whole, the results offer an unprecedented view into the hybridization process on surfaces and provide some insights as to the poor reproducibility exhibited by microarrays. Namely, the prediction methods that are currently used to design microarrays based on duplex stability in the bulk do a poor job of estimating the stability of those duplexes in a microarray environment.



College and Department

Ira A. Fulton College of Engineering and Technology; Chemical Engineering



Date Submitted


Document Type





DNA, hybridization, molecular modeling, microarray