The role of conformational entropy in molecular recognition by calmodulin

Johnson Research Foundation, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Nature Chemical Biology (Impact Factor: 13). 04/2010; 6(5):352-8. DOI: 10.1038/nchembio.347
Source: PubMed


The physical basis for high-affinity interactions involving proteins is complex and potentially involves a range of energetic contributions. Among these are changes in protein conformational entropy, which cannot yet be reliably computed from molecular structures. We have recently used changes in conformational dynamics as a proxy for changes in conformational entropy of calmodulin upon association with domains from regulated proteins. The apparent change in conformational entropy was linearly related to the overall binding entropy. This view warrants a more quantitative foundation. Here we calibrate an 'entropy meter' using an experimental dynamical proxy based on NMR relaxation and show that changes in the conformational entropy of calmodulin are a significant component of the energetics of binding. Furthermore, the distribution of motion at the interface between the target domain and calmodulin is surprisingly noncomplementary. These observations promote modification of our understanding of the energetics of protein-ligand interactions.

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    • "Such measures have recently been used in the design of experimentally validated RNA molecules [55] [15]. Motivated by the fact that calmodulin-ligand binding has been shown to depend on conformational entropy [35], in Section , we show an improvement in the correlation between hammerhead ribozyme cleavage activity and total change of energy [49], if conformational entropy is also taken into account. In Section , we compute the entropy of genomic portions of the HIV-1 genome and compare entropy Z-scores with known HIV-1 noncoding elements. "
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    ABSTRACT: Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV aborption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs). However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner'99 and Turner'04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. The software is available at
    Full-text · Article · Aug 2015 · PLoS ONE
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    • "For example, reorganization of the hydrogen bonding networks and solvent bridges of the interacting molecules upon mutation, which was accompanied only by subtle structural changes, leads to radically different binding free energy [3] [4]. A recent work [5] shows that the apparent change in the amino acid dynamics determined by NMR spectroscopy is linearly related to the change in the overall binding entropy and also that changes in side-chain dynamics determined from NMR data can be used as a quantitative estimate of changes in conformational entropy [6] [7]. Also, an analysis of crystallographic B-factors has revealed a significant decrease of flexibility of residues exposed to solvent compared to flexibility of residues interacting with another biomolecule and further compared to their flexibility in the protein core [8]. "
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    ABSTRACT: Combining computational and experimental tools, we present a new strategy for designing high affinity variants of a binding protein. The affinity is increased by mutating residues not at the interface, but at positions lining internal cavities of one of the interacting molecules. Filling the cavities lowers flexibility of the binding protein, possibly reducing entropic penalty of binding. The approach was tested using the interferon-γ receptor 1 (IFNγR1) complex with IFNγ as a model. Mutations were selected from 52 amino acid positions lining the IFNγR1 internal cavities by using a protocol based on FoldX prediction of free energy changes. The final four mutations filling the IFNγR1 cavities and potentially improving the affinity to IFNγ were expressed, purified, and refolded, and their affinity towards IFNγ was measured by SPR. While individual cavity mutations yielded receptor constructs exhibiting only slight increase of affinity compared to WT, combinations of these mutations with previously characterized variant N96W led to a significant sevenfold increase. The affinity increase in the high affinity receptor variant N96W+V35L is linked to the restriction of its molecular fluctuations in the unbound state. The results demonstrate that mutating cavity residues is a viable strategy for designing protein variants with increased affinity.
    Full-text · Article · Jun 2015 · BioMed Research International
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    • "During the last fifteen years, the importance of functional conformational changes in proteins has been highlighted in several cases [9] [10] [11] [12] [13] [14] [15] [16]. Although very important for protein function, these changes can be extremely difficult to characterize at atomic resolution, as the biophysical methods most used for protein structure determination most often require conformational stability. "
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