Protein structure modelling and evaluation based on a 4-distance description of side-chain interactions.

BACKGROUND: Accurate evaluation and modelling of residue-residue interactions within and between proteins is a key aspect of computational structure prediction including homology modelling, protein-protein docking, refinement of low-resolution structures, and computational protein design. RESULTS: Here we introduce a method for accurate protein structure modelling and evaluation based on a novel 4-distance description of residue-residue interaction geometry. Statistical 4-distance preferences were extracted from high-resolution protein structures and were used as a basis for a knowledge-based potential, called Hunter. We demonstrate that 4-distance description of side chain interactions can be used reliably to discriminate the native structure from a set of decoys. Hunter ranked the native structure as the top one in 217 out of 220 high-resolution decoy sets, in 25 out of 28 "Decoys 'R' Us" decoy sets and in 24 out of 27 high-resolution CASP7/8 decoy sets. The same concept was applied to side chain modelling in protein structures. On a set of very high-resolution protein structures the average RMSD was 1.47 A for all residues and 0.73 A for buried residues, which is in the range of attainable accuracy for a model. Finally, we show that Hunter performs as good or better than other top methods in homology modelling based on results from the CASP7 experiment. The supporting web site http://bioinfo.weizmann.ac.il/hunter/ was developed to enable the use of Hunter and for visualization and interactive exploration of 4-distance distributions. CONCLUSIONS: Our results suggest that Hunter can be used as a tool for evaluation and for accurate modelling of residue-residue interactions in protein structures. The same methodology is applicable to other areas involving high-resolution modelling of biomolecules.

Four distances between pairs of amino acids provide a precise description of their interaction.

The three-dimensional structures of proteins are stabilized by the interactions between amino acid residues. Here we report a method where four distances are calculated between any two side chains to provide an exact spatial definition of their bonds. The data were binned into a four-dimensional grid and compared to a random model, from which the preference for specific four-distances was calculated. A clear relation between the quality of the experimental data and the tightness of the distance distribution was observed, with crystal structure data providing far tighter distance distributions than NMR data. Since the four-distance data have higher information content than classical bond descriptions, we were able to identify many unique inter-residue features not found previously in proteins. For example, we found that the side chains of Arg, Glu, Val and Leu are not symmetrical in respect to the interactions of their head groups. The described method may be developed into a function, which computationally models accurately protein structures.

Assessing computational methods for predicting protein stability upon mutation: good on average but not in the details.

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.

Similar chemistry, but different bond preferences in inter versus intra-protein interactions.

Proteins fold into a well-defined structure as a result of the collapse of the polypeptide chain, while transient protein-complex formation mainly is a result of binding of two folded individual monomers. Therefore, a protein-protein interface does not resemble the core of monomeric proteins, but has a more polar nature. Here, we address the question of whether the physico-chemical characteristics of intraprotein versus interprotein bonds differ, or whether interfaces are different from folded monomers only in the preference for certain types of interactions. To address this question we assembled a high resolution, nonredundant, protein-protein interaction database consisting of 1374 homodimer and 572 heterodimer complexes, and compared the physico-chemical properties of these interactions between protein interfaces and monomers. We performed extensive statistical analysis of geometrical properties of interatomic interactions of different types: hydrogen bonds, electrostatic interactions, and aromatic interactions. Our study clearly shows that there is no significant difference in the chemistry, geometry, or packing density of individual interactions between interfaces and monomeric structures. However, the distribution of different bonds differs. For example, side-chain-side-chain interactions constitute over 62% of all interprotein interactions, while they make up only 36% of the bonds stabilizing a protein structure. As on average, properties of backbone interactions are different from those of side chains, a quantitative difference is observed. Our findings clearly show that the same knowledge-based potential can be used for protein-binding sites as for protein structures. However, one has to keep in mind the different architecture of the interfaces and their unique bond preference.

Noncovalent, site-specific biotinylation of histidine-tagged proteins.

Site-specific conjugation of proteins to surfaces, spectroscopic probes, or other functional units is a key task for implementing biochemical assays. The streptavidin-biotin interaction has proven a highly versatile tool for detection, quantification, and functional analysis of proteins. We have developed an approach for site-specific reversible biotinylation of recombinant proteins through their histidine tag using biotin conjugated to the multivalent chelator trisnitrilotriacetic acid (BTtris-NTA). Stable binding of BTtris-NTA to His-tagged proteins was demonstrated, which is readily reversed by addition of imidazole, enabling versatile conjugation schemes in solution as well as at interfaces. Gel filtration experiments revealed that His-tagged proteins bind to streptavidin doped with BTtris-NTA in a 2:1 stoichiometry. Furthermore, an increased binding affinity toward His-tagged proteins was observed for BTtris-NTA linked to streptavidin compared to tris-NTA in solution and on surfaces. These results indicate an efficient cooperative interaction of two adjacent tris-NTA moieties with a single His-tag, yielding an extremely tight complex with a lifetime of several days. We demonstrate several applications of BTtris-NTA including multiplexed capturing of proteins to biosensor surfaces, cell surface labeling, and Western blot detection. The remarkable selectivity of the His-tag-specific biotinylation, as well as the highly stable, yet reversible complex provides the basis for numerous further applications for functional protein analysis.

On the dynamic nature of the transition state for protein-protein association as determined by double-mutant cycle analysis and simulation.

The process of protein-protein association starts with their random collision, which may develop into an encounter complex followed by a transition state and final complex formation. Here we aim to experimentally characterize the nature of the transition state of protein-protein association for three different protein-protein interactions; Barnase-Barstar, TEM1-BLIP and IFNalpha2-IFNAR2, and use the data to model the transition state structures. To model the transition state, we determined inter-protein distance-constraints of the activated complex by using double mutant cycles (DMC) assuming that interacting residues are spatially close. Significant DeltaDeltaG(double dagger)(int) values were obtained only between residues on Barnase and Barstar. However, introducing specific mutations that optimize the charge complementarity between BLIP and TEM1 resulted in the introduction of significant DeltaDeltaG(double dagger)(int) values also between residues of these two proteins. While electrostatic interactions make major contributions towards stabilizing the transition state, we show two examples where steric hindrance exerts an effect on the transition state as well. To model the transition-state structures from the experimental DeltaDeltaG(double dagger)(int) values, we introduced a method for structure perturbation, searching for those inter-protein orientations that best support the experimental DeltaDeltaG(double dagger)(int) values. Two types of transition states were found, specific as observed for Barnase-Barstar and the electrostatically optimized TEM1-BLIP mutants, and diffusive as shown for wild-type TEM1-BLIP and IFNalpha2-IFNAR2. The specific transition states are characterized by defined inter-protein orientations, which cannot be modeled for the diffusive transition states. Mutations introduced through rational design can change the transition state from diffusive to specific. Together, these data provide a structural view of the mechanism allowing rates of association to differ by five orders of magnitude between different protein complexes.

The molecular architecture of protein-protein binding sites.

The formation of specific protein interactions plays a crucial role in most, if not all, biological processes, including signal transduction, cell regulation, the immune response and others. Recent advances in our understanding of the molecular architecture of protein-protein binding sites, which facilitates such diversity in binding affinity and specificity, are enabling us to address key questions. What is the amino acid composition of binding sites? What are interface hotspots? How are binding sites organized? What are the differences between tight and weak interacting complexes? How does water contribute to binding? Can the knowledge gained be translated into protein design? And does a universal code for binding exist, or is it the architecture and chemistry of the interface that enable diverse but specific binding solutions?

Two-state folding observed in individual protein molecules.

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.