Correcting for Heat Capacity and 5鈥?TA Type Terminal Nearest Neighbors Improves Prediction of DNA Melting Temperatures Using Nearest-Neighbor Thermodynamic Models

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• 作者：Curtis B. Hughesman ; Robin F. B. Turner ; Charles Haynes
• 刊名：Biochemistry
• 出版年：2011
• 出版时间：April 5, 2011
• 年：2011
• 卷：50
• 期：13
• 页码：2642-2649
• 全文大小：803K
• 年卷期：v.50,no.13(April 5, 2011)
• ISSN：1520-4995

文摘

Nearest-neighbor thermodynamic (NNT) models currently provide some of the most accurate predictions of melting thermodynamics, including melting temperature (T_m) values, for short DNA duplexes. Inherent to all existing NNT models is the assumption that 螖H掳 and 螖S掳 for the helix-to-coil transition are temperature invariant. Here we investigate the impact that this zero-螖C_p assumption has on the accuracy of T_m predictions for 128 DNA duplexes. Previous and new melting thermodynamic data are analyzed to establish an estimate of 螖C_p^bp, the heat capacity change per base pair, of 42 卤 16 cal mol^鈭? K^鈭? bp^鈭?, as well as an optimal thermodynamic reference temperature (T_ref) of 53 卤 5 掳C. These results were used to modify the unified NNT model to properly account for the temperature dependence of 螖H掳 and 螖S掳 and thereby extend the range over which T_m is accurately predicted. This new approach is shown to be especially useful for duplexes that melt at a T_m greater than 70 掳C. Thermodynamic data collected by differential scanning calorimetry (DSC) for 16 duplexes designed to melt over a broad temperature range were used to verify the values of 螖C_p^bp and T_ref and to show that 螖C_p^bp is essentially constant above 37 掳C. Additional DSC analysis of 12 duplex sequences containing all 10 nearest neighbors allowed for errors associated with different terminal nearest neighbors to be examined and showed that duplexes containing one or more terminal 5鈥?TA groups are significantly more stable than predicted by the unified NNT model. A correction to improve prediction of the hybridization thermodynamics of duplexes with terminal 5鈥?TA groups is provided.