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A Statistical Thermodynamic Model for Investigating the Stability of DNA Sequences from Oligonucleotides to Genomes
Authors:Garima Khandelwal,Rebecca   A. Lee,B. Jayaram,David   L. Beveridge
Affiliation: Department of Chemistry, Indian Institute of Technology, Hauz Khas, New Delhi, India; Supercomputing Facility for Bioinformatics and Computational Biology, Indian Institute of Technology, Hauz Khas, New Delhi, India;§ Kasuma School of Biological Sciences, Indian Institute of Technology, Hauz Khas, New Delhi, India; Department of Chemistry and Molecular Biophysics Program, Wesleyan University, Middletown, Connecticut
Abstract:We describe the development and testing of a simple statistical mechanics methodology for duplex DNA applicable to sequences of any composition and extensible to genomes. The microstates of a DNA sequence are modeled in terms of blocks of basepairs that are assumed to be fully closed (paired) or open. This approach generates an ensemble of bubblelike microstates that are used to calculate the corresponding partition function. The energies of the microstates are calculated as additive contributions from hydrogen bonding, basepair stacking, and solvation terms parameterized from a comprehensive series of molecular dynamics simulations including solvent and ions. Thermodynamic properties and nucleotide stability constants for DNA sequences follow directly from the partition function. The methodology was tested by comparing computed free energies per basepair with the experimental melting temperatures of 60 oligonucleotides, yielding a correlation coefficient of −0.96. The thermodynamic stability of genic/nongenic regions was tested in terms of nucleotide stability constants versus sequence for the Escherichia coli K-12 genome. It showed clear differentiation of the genes from promoters and captures genic regions with a sensitivity of 0.94. The statistical thermodynamic model presented here provides a seemingly new handle on the challenging problem of interpreting genomic sequences.
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