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Thermodynamic coupling of protonation and conformational equilibria in proteins: theory and simulation.

ABSTRACT: Ionization-coupled conformational phenomena are ubiquitous in biology. However, quantitative characterization of the underlying thermodynamic cycle comprised of protonation and conformational equilibria has remained an elusive goal. Here we use theory and continuous constant pH molecular dynamics (CpHMD) simulations to provide a thermodynamic description for the coupling of proton titration and conformational exchange between two distinct states of a protein. CpHMD simulations with a hybrid-solvent scheme and the pH-based replica-exchange (REX) protocol are applied to obtain the equilibrium constants and atomic details of the ionization-coupled conformational exchange between open and closed states of an engineered mutant of staphylococcal nuclease. Although the coupling of protonation and conformational equilibria is not exact in the simulation, the results are encouraging. They demonstrate that REX-CpHMD simulations can be used to study thermodynamics of ionization-coupled conformational processes--which has not possible using present experimental techniques or traditional simulations based on fixed protonation states.

SUBMITTER: Shi C

PROVIDER: S-EPMC3318114 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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Thermodynamic coupling of protonation and conformational equilibria in proteins: theory and simulation.

Shi Chuanyin C Wallace Jason A JA Shen Jana K JK

Biophysical journal 20120403 7

Ionization-coupled conformational phenomena are ubiquitous in biology. However, quantitative characterization of the underlying thermodynamic cycle comprised of protonation and conformational equilibria has remained an elusive goal. Here we use theory and continuous constant pH molecular dynamics (CpHMD) simulations to provide a thermodynamic description for the coupling of proton titration and conformational exchange between two distinct states of a protein. CpHMD simulations with a hybrid-solv ...[more]

PMID: 22500759

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Project description:We present a hybrid computational methodology to predict multiple energetically accessible conformations for G protein-coupled receptors (GPCRs) that might play a role in binding to ligands and different signaling partners. To our knowledge, this method, termed ActiveGEnSeMBLE, enables the first quantitative energy profile for GPCR activation that is consistent with the qualitative profile deduced from experiments. ActiveGEnSeMBLE starts with a systematic coarse grid sampling of helix tilts/rotations (∼13 trillion transmembrane-domain conformations) and selects the conformational landscape based on energy. This profile identifies multiple potential active-state energy wells, with the TM3-TM6 intracellular distance as an approximate activation coordinate. These energy wells are then sampled locally using a finer grid to find locally minimized conformation in each energy well. We validate this strategy using the inactive and active experimental structures of β2 adrenergic receptor (hβ2AR) and M2 muscarinic acetylcholine receptor. Structures of membrane-embedded hβ2AR along its activation coordinate are subjected to molecular-dynamics simulations for relaxation and interaction energy analysis to generate a quantitative energy landscape for hβ2AR activation. This landscape reveals several metastable states along this coordinate, indicating that for hβ2AR, the agonist alone is not enough to stabilize the active state and that the G protein is necessary, consistent with experimental observations. The method's application to somatostatin receptor SSTR5 (no experimental structure available) shows that to predict an active conformation it is better to start from an inactive structure template based on a close homolog than to start from an active template based on a distant homolog. The energy landscape for hSSTR5 activation is consistent with hβ2AR in the role of the G protein. These results demonstrate the utility of the ActiveGEnSeMBLE method for predicting multiple conformations along the pathways for activating GPCRs and the corresponding energy landscapes, thereby providing detailed structural insights into the initial molecular events of GPCR function that are not easily accessible by experiments.

Project description:The binding of aminoglycoside antibiotics to a broad range of macromolecular targets is coupled to protonation of one or more of the amino groups that typify this class of drugs. Determining how and to what extent this linkage influences the energetics of the aminoglycoside-macromolecule binding reaction requires a detailed understanding of the thermodynamics associated with the protonation equilibria of the aminoglycoside amino groups. In recognition of this need, a calorimetric- and NMR-based approach for obtaining the requisite thermodynamic information is presented using paromomycin as the model aminoglycoside. Temperature- and pH-dependent 15N NMR studies provide pK(a) values for the five paromomycin amino groups, as well as the temperature dependence of these pK(a) values. These studies also indicate that the observed pK(a) values associated with the free base form of paromomycin are lower in magnitude than the corresponding values associated with the sulfate salt form of the drug. This difference in pK(a) is due to drug interactions with the sulfate counterions at the high drug concentrations (> or = 812 mM) used in the 15N NMR studies. Isothermal titration calorimetry studies conducted at drug concentrations < or = 45 microM reveal that the extent of paromomycin protonation linked to the binding of the drug to its pharmacologically relevant target, the 16 S rRNA A-site, is consistent with the pK(a) values of the free base and not the sulfate salt form of the drug. Temperature- and pH-dependent isothermal titration calorimetry studies yield exothermic enthalpy changes (deltaH) for protonation of the five paromomycin amino groups, as well as positive heat capacity changes (deltaC(p)) for three of the five amino groups. Regarded as a whole, the results presented here represent an important first step toward establishing a thermodynamic database that can be used to predict how aminoglycoside-macromolecule binding energetics will be influenced by conditions such as temperature, pH, and ionic strength. Such a predictive capability is a critical component of any drug design strategy.

Dataset Information

Thermodynamic coupling of protonation and conformational equilibria in proteins: theory and simulation.

Publications

Thermodynamic coupling of protonation and conformational equilibria in proteins: theory and simulation.

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