DNA Thermodynamics & Hybridization

Frequently Asked Questions

How do I use the tool?

Sequence box is used to enter an oligonucleotide sequence. Sequences containing native DNA (A, T, C, G, I) and LNA nucleotides (+A, +C, +G, +T) can be calculated.

Oligo Conc box is used to enter the oligo concentration and has the upper limit of 10⁴ µM (10 mM). Default value is 0.25 µM.

Target Conc box is used to enter concentration of the target sequence that is complementary to the oligo. Concentrations up to 10⁴ µM (10 mM) are allowed. If the target concentration is significantly less than the oligo concentration ([target] < 15% of [oligo]), the target concentration does not affect results and the default value of 0.0 µM is appropriate. This is often the case in molecular biology experiments where the oligo probe is present in vast excess and concentration of the target sequence is unknown.
Target concentration is also ignored in the case of a selfcomplementary oligonucleotide because the target and the oligo are the same chemical species.

Na⁺, K⁺ Conc box is used to enter total concentration of monovalent ions (Na⁺, K⁺, Tris⁺) up to the maximum value of 1500 mM (1.5 M). Default concentration is 50.0 mM.

Mg²⁺ Conc box is used to enter total concentration of divalent ions. The maximum value is 1000 mM and default concentration is 0.0 mM. When magnesium concentration is smaller than the concentration of oligonucleotide phosphate groups, association of Mg²⁺ with DNA is different than under saturating conditions and predicted T_m, ΔS^o, ΔG^o values are likely to be less accurate.

dNTPs Conc box is used to enter total concentration of deoxynucleoside triphosphates and accepts values in range from 0.0 mM to 1000 mM. However, the dNTP concentration may not exceed 120% of the Mg²⁺ concentration. Default concentration is 0.0 mM.

How is melting temperature calculated?
Melting temperatures (T_m) of short DNA duplex oligomers (< 70 base pairs) are predicted using the following equation,


where R is the ideal gas constant (1.9865 cal·mol^-1·K^-1). The concentrations (mol/L) of each strand are denoted C₁ and C₂. It is assumed that C₁ is greater or equal to C₂. If the strand is selfcomplementary, there is no second strand and C₂ is set to zero. The enthalpy (ΔH^o) and entropy (ΔS^o) of duplex annealing are predicted from the nearest-neighbor model and various thermodynamic parameters^1-5. These parameters are summed for each nearest neighbor doublet (stack). End (initiation) interactions are included.

where N_ij is the number of times the particular nearest-neighbor stack (i, j = A, T, G, C) appears in the duplex sequence.

Free energy at 37 ^oC is obtained from the standard relationship,

Are melting temperatures, entropies and free energies adjusted for salt concentrations?
The algorithm accounts for dependence of T_m, ΔS^o and ΔG^o values on cation concentrations. ΔH^o values are assumed to be independent of salt or temperature. Linear salt corrections of melting temperatures were previously used to model the effects of cations on duplex stability. IDT scientists measured stability of many DNA duplexes in various sodium, potassium, and magnesium buffers and developed more accurate models. Software employs the improved algorithm to take into account effects of divalent (Mg²⁺) ions⁶ and monovalent (Na⁺) ions⁷,

The f_GC is the fraction of GC base pairs. Thermodynamic parameters for Watson-Crick basepairs^1-5, internal single mismatches⁸, and 2 x 2 internal mismatches (internal loops) are implemented. Entropic correction similar to Mathews et al.⁹ is used for large symmetrical internal loops.

How is hybridization profile predicted?
The extent of oligo-target hybridization is calculated according to Owczarzy et al.¹⁰ (see Table 3). The two-state melting transition is assumed,

where θ is the fraction of melted base pairs, K_a is the association equilibrium constant obtained from predicted thermodynamic parameters,

By solving the quadratic equation for θ one can obtain the theoretical hybridization profile (θ versus temperature). Nievergelt reported the method that is numerically stable¹¹.

Is stabilizing effect of locked nucleic acid considered?
The sequence-dependent effects of LNA modifications are taken into account. We have determined nearest-neighbor parameters for duplexes containing consecutive LNA-DNA base pairs¹. These parameters are combined with published parameters⁵ for isolated LNAs to obtain accurate predictions for LNA-modified oligonucleotides.

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REFERENCES

1. Owczarzy R, You Y, Groth CL, and Tataurov AV (2011) Stability and mismatch discrimination of locked nucleic acid-DNA duplexes. Biochemistry, 50:9352-9367.
2. SantaLucia J. Jr. (1998) A unified view of polymer, dumbbell, and oligonucleotide DNA nearest-neighbor thermodynamics, Proc. Natl. Acad. Sci. USA 95, 1460-1465.
3. Xia T., SantaLucia J. Jr., Burkard M.E., Kierzek R., Schroeder S.J., Jiao X., Cox C., and Turner D.H. (1998) Thermodynamic parameters for an expanded nearest-neighbor model for formation of RNA duplexes with Watson-Crick base pairs, Biochemistry 37, 14719-14735.
4. Sugimoto N., Nakano S., Katoh M., Matsumura A., Nakamuta H., Ohmichi T., Yoneyama M., and Sasak M. (1995) Thermodynamic parameters to predict stability of RNA/DNA hybrid duplexes, Biochemistry 34, 11211-11216.
5. McTigue P.M., Peterson R.J., and Kahn J.D. (2004) Sequence-dependent thermodynamic parameters for locked nucleic acid (LNA)-DNA duplex formation, Biochemistry 43, 5388-5405.
6. Owczarzy R., Moreira B.G., You Y., Behlke M.A., and Walder J.A. (2008) Predicting stability of DNA duplexes in solutions containing magnesium and monovalent cations, Biochemistry 47, 5336-5353.
7. Owczarzy R., You Y., Moreira B.G., Manthey J.A., Huang L., Behlke M.A., and Walder J.A. (2004) Effects of sodium ions on DNA duplex oligomers: Improved predictions of melting temperatures, Biochemistry 43, 3537-3554.
8. SantaLucia J. Jr. and Hicks D. (2004) The thermodynamics of DNA structural motifs, Annu. Rev. Biophys. Biomol. Struct. 33, 415-440.
9. Mathews D.H., Sabina J., Zuker M., and Turner D.H. (1999) Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure, J. Mol. Biol. 288, 911-940.
10. Owczarzy R. (2005) Melting temperatures of nucleic acids: Discrepancies in analysis. Biophys. Chem., 117, 207-215.
11. Nievergelt, Y. (2003) How (Not) to Solve Quadratic Equations. The College Mathematics Journal 34, 90-104.