Methods for protein modeling and design advanced rapidly in recent years. At the heart of these computational methods is an energy function that calculates the free energy of the system. Many of these functions were also developed to estimate the consequence of mutation on protein stability or binding affinity. In the current study, we chose six different methods that were previously reported as being able to predict the change in protein stability (DeltaDeltaG) upon mutation: CC/PBSA, EGAD, FoldX, I-Mutant2.0, Rosetta and Hunter. We evaluated their performance on a large set of 2156 single mutations, avoiding for each program the mutations used for training. The correlation coefficients between experimental and predicted DeltaDeltaG values were in the range of 0.59 for the best and 0.26 for the worst performing method. All the tested computational methods showed a correct trend in their predictions, but failed in providing the precise values. This is not due to lack in precision of the experimental data, which showed a correlation coefficient of 0.86 between different measurements. Combining the methods did not significantly improve prediction accuracy compared to a single method. These results suggest that there is still room for improvement, which is crucial if we want forcefields to perform better in their various tasks.
The folding dynamics of small proteins are often described in terms of a simple two-state kinetic model. Within this notion, the behavior of individual molecules is expected to be stochastic, with a protein molecule residing in either the unfolded or the folded state for extended periods of time, with intermittent rapid jumps across the free energy barrier. However, a direct observation of this bistable behavior has not been made to date. Rather, previous reports of folding trajectories of individual proteins have shown an unexpected degree of complexity. This raises the question whether the simple kinetic properties derived from classical experiments on large ensembles of molecules are reflected in the folding paths taken by individual proteins. Here we report single-molecule folding/unfolding trajectories observed by fluorescence resonance energy transfer for a protein that meets all criteria of a two state-system. The trajectories, measured on molecules immobilized in lipid vesicles, demonstrate the anticipated bistable behavior, with steplike transitions between folded and unfolded conformations. They further allow us to put an upper bound on the barrier crossing time.
Chemokines orchestrate cell migration for development, immune surveillance, and disease by binding to cell surface heterotrimeric guanine nucleotide–binding protein (G protein)–coupled receptors (GPCRs). The array of interactions between the nearly 50 chemokines and their 20 GPCR targets generates an extensive signaling network to which promiscuity and biased agonism add further complexity. The receptor CXCR4 recognizes both monomeric and dimeric forms of the chemokine CXCL12, which is a distinct example of ligand bias in the chemokine family. We demonstrated that a constitutively monomeric CXCL12 variant reproduced the G protein–dependent and β-arrestin–dependent responses that are associated with normal CXCR4 signaling and lead to cell migration. In addition, monomeric CXCL12 made specific contacts with CXCR4 that are not present in the structure of the receptor in complex with a dimeric form of CXCL12, a biased agonist that stimulates only G protein–dependent signaling. We produced an experimentally validated model of an agonist-bound chemokine receptor that merged a nuclear magnetic resonance–based structure of monomeric CXCL12 bound to the amino terminus of CXCR4 with a crystal structure of the transmembrane domains of CXCR4. The large CXCL12:CXCR4 protein-protein interface revealed by this structure identified previously uncharacterized functional interactions that fall outside of the classical “two-site model” for chemokine-receptor recognition. Our model suggests a mechanistic hypothesis for how interactions on the extracellular face of the receptor may stimulate the conformational changes required for chemokine receptor-mediated signal transduction.
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