RECCR Rensselaer Exploratory Center for Cheminformatics Research

Presentation: Fuzzy Bar-code Representations of DNA-Protein Interactions

Predicting Target Sites of Transcription Factors

DNA Electronic Surface Property Reconstruction

DIXEL Coordinate System for DNA

Preliminary Studies of the Discriminant Potential of DIXELS

References

PI: Curt M. Breneman
Co-PI:N. Sukumar

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Beyond ATCG: “Dixel” representations of DNA-protein interactions

DNA Electronic Surface Property Reconstruction

To explore this hypothesis, we undertook a preliminary investigation of the best ways of utilizing a quantum mechanical electron density characterization of major groove van der Waals surfaces. Our aim was to identify features of these surfaces that improve the identification of sequences of specific protein binding sites. To begin, we sought to construct accurate representations of the properties of DNA electron density distributions at a reasonably high level of theory. Since Hartree-Fock or DFT computations (Foresman and Frisch, 1996) of large fragments of DNA consisting of many base pairs is clearly beyond the scope of conventional methods, we adopted a variant of the Transferable Atom Equivalent (TAE) method (Breneman, 1995; Rhem, 1996; Breneman, 1997; Breneman, 2002; Mazza, 2001; Song, 2002) for reconstructing the chemical properties of DNA fragments. This was accomplished by extracting electron density information from ab initio electronic structure calculations of all possible sets of three stacked base pairs - where the central base pair resides in the specific electronic environment generated by the flanking base pairs. The resulting library of base pair “triples” was then employed to reconstruct the DNA sequence based on the exposed electron density properties of the central base pair of each triplet. Our focus on triples permitted us to explore the potential of substituting quantum mechanical calculations for more sequence data. Specifically, we wished to explore electron density characteristics derived from these calculations to look for higher-order multiple-base effects without requiring additional sequence data.

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