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Two distinct DNA sequences recognized by transcription factors represent enthalpy and entropy optima.

ABSTRACT: Most transcription factors (TFs) can bind to a population of sequences closely related to a single optimal site. However, some TFs can bind to two distinct sequences that represent two local optima in the Gibbs free energy of binding (?G). To determine the molecular mechanism behind this effect, we solved the structures of human HOXB13 and CDX2 bound to their two optimal DNA sequences, CAATAAA and TCGTAAA. Thermodynamic analyses by isothermal titration calorimetry revealed that both sites were bound with similar ?G. However, the interaction with the CAA sequence was driven by change in enthalpy (?H), whereas the TCG site was bound with similar affinity due to smaller loss of entropy (?S). This thermodynamic mechanism that leads to at least two local optima likely affects many macromolecular interactions, as ?G depends on two partially independent variables ?H and ?S according to the central equation of thermodynamics, ?G = ?H - T?S.

SUBMITTER: Morgunova E

PROVIDER: S-EPMC5896879 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Two distinct DNA sequences recognized by transcription factors represent enthalpy and entropy optima.

Morgunova Ekaterina E Yin Yimeng Y Das Pratyush K PK Jolma Arttu A Zhu Fangjie F Popov Alexander A Xu You Y Nilsson Lennart L Taipale Jussi J

eLife 20180411

Most transcription factors (TFs) can bind to a population of sequences closely related to a single optimal site. However, some TFs can bind to two distinct sequences that represent two local optima in the Gibbs free energy of binding (ΔG). To determine the molecular mechanism behind this effect, we solved the structures of human HOXB13 and CDX2 bound to their two optimal DNA sequences, CAATAAA and TCGTAAA. Thermodynamic analyses by isothermal titration calorimetry revealed that both sites were b ...[more]

PMID: 29638214

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Project description:Exploring the protein-folding problem has been a longstanding challenge in molecular biology and biophysics. Intramolecular hydrogen (H)-bonds play an extremely important role in stabilizing protein structures. To form these intramolecular H-bonds, nascent unfolded polypeptide chains need to escape from hydrogen bonding with surrounding polar water molecules under the solution conditions that require entropy-enthalpy compensations, according to the Gibbs free energy equation and the change in enthalpy. Here, by analyzing the spatial layout of the side-chains of amino acid residues in experimentally determined protein structures, we reveal a protein-folding mechanism based on the entropy-enthalpy compensations that initially driven by laterally hydrophobic collapse among the side-chains of adjacent residues in the sequences of unfolded protein chains. This hydrophobic collapse promotes the formation of the H-bonds within the polypeptide backbone structures through the entropy-enthalpy compensation mechanism, enabling secondary structures and tertiary structures to fold reproducibly following explicit physical folding codes and forces. The temperature dependence of protein folding is thus attributed to the environment dependence of the conformational Gibbs free energy equation. The folding codes and forces in the amino acid sequence that dictate the formation of β-strands and α-helices can be deciphered with great accuracy through evaluation of the hydrophobic interactions among neighboring side-chains of an unfolded polypeptide from a β-strand-like thermodynamic metastable state. The folding of protein quaternary structures is found to be guided by the entropy-enthalpy compensations in between the docking sites of protein subunits according to the Gibbs free energy equation that is verified by bioinformatics analyses of a dozen structures of dimers. Protein folding is therefore guided by multistage entropy-enthalpy compensations of the system of polypeptide chains and water molecules under the solution conditions.

Dataset Information

Two distinct DNA sequences recognized by transcription factors represent enthalpy and entropy optima.

Publications

Two distinct DNA sequences recognized by transcription factors represent enthalpy and entropy optima.

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