Cell biology: brief encounters bolster contacts.
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Bacterial Proteins↗
Biomedical subjects
Juan Fernández-Recio
Publications and source records attributed to Juan Fernández-Recio.
Efficient restraints for protein-protein docking by comparison of observed amino acid substitution patterns with those predicted from local environment.
The discovery that the functions of most eukaryotic gene products are mediated through multi-protein complexes makes the prediction of protein interactions one of the most important current challenges in structural biology. Rigid-body docking methods can generate a large number of alternative candidates, but it is difficult to discriminate the near-native interactions from the large number of false positives. Many different scoring functions have been developed for this purpose, but in most cases, experimental and biological information is still required for accurate predictions. We explore here the use of evolutionary restraints in evaluating rigid-body docking geometries. In order to identify potential interface residues we identify functional residues based on the comparison of observed amino acid substitutions with those predicted from local environment. The interface residues identified by this method are correctly located in 85% of the cases. These predicted interface residues are used to define distance restraints that help to score rigid-body docking solutions. We have developed the pyDockRST software, which uses the percentage of satisfied distance restraints, together with the electrostatics and desolvation binding energy, to identify correct docking orientations. This methodology dramatically improves the docking results when compared to the use of energy criteria alone, and is able to find the correct orientation within the top 20 docking solutions in 80% of the cases.
Amino Acid Substitution↗
Improving CAPRI predictions: optimized desolvation for rigid-body docking.
The ICM Docking and Interface Side-Chain Optimization (ICM-DISCO) showed promising predictive results during the first CAPRI experiment by successfully finding medium- or high-accuracy models in 3 of the 7 targets. A key factor was the ability to recognize near-native rigid-body geometries in a relatively low number of alternative docking poses, together with the successful refinement of the rigid-body docking interfaces. Since then, we have focused on improving the scoring function to optimally discriminate the near-native rigid-body conformations. For that, we have defined a new desolvation descriptor for rigid-body docking, based on atomic solvation parameters (ASPs) derived from octanol-water transfer experiments. This and other new approaches have been gradually incorporated into our docking procedure during our participation on the second CAPRI experiment. Overall, we produced reasonable models for 8 of the 9 official targets. Especially encouraging were those cases in which a homology model of 1 of the subunits had to be used during the docking simulations. And not less gratifying has been the successful prediction of antibody-antigen targets in a completely automatic, unrestrained fashion. In summary, our success rate (89%) shows a consistent improvement over the previous CAPRI rounds, and suggests that a correct desolvation description is key for improved protein-protein docking predictions.
Algorithms↗
The long and short flavodoxins: II. The role of the differentiating loop in apoflavodoxin stability and folding mechanism.
Flavodoxins are classified in two groups according to the presence or absence of a approximately 20-residue loop of unknown function. In the accompanying paper (36), we have shown that the differentiating loop from the long-chain Anabaena PCC 7119 flavodoxin is a peripheral structural element that can be removed without preventing the proper folding of the apoprotein. Here we investigate the role played by the loop in the stability and folding mechanism of flavodoxin by comparing the equilibrium and kinetic behavior of the full-length protein with that of loop-lacking, shortened variants. We show that, when the loop is removed, the three-state equilibrium thermal unfolding of apoflavodoxin becomes two-state. Thus, the loop is responsible for the complexity shown by long-chain apoflavodoxins toward thermal denaturation. As for the folding reaction, both shortened and wild type apoflavodoxins display three-state behavior but their folding mechanisms clearly differ. Whereas the full-length protein populates an essentially off-pathway transient intermediate, the additional state observed in the folding of the shortened variant analyzed seems to be simply an alternative native conformation. This finding suggests that the long loop may also be responsible for the accumulation of the kinetic intermediate observed in the full-length protein. Most revealing, however, is that the influence of the loop on the overall conformational stability of apoflavodoxin is quite low and the natively folded shortened variant Delta(120-139) is almost as stable as the wild type protein. The fact that the loop, which is not required for a proper folding of the polypeptide, does not even play a significant role in increasing the conformational stability of the protein supports our proposal (36) that the differentiating loop of long-chain flavodoxins may be related to a recognition function, rather than serving a structural purpose.
Anabaena↗
Identification of protein-protein interaction sites from docking energy landscapes.
Protein recognition is one of the most challenging and intriguing problems in structural biology. Despite all the available structural, sequence and biophysical information about protein-protein complexes, the physico-chemical patterns, if any, that make a protein surface likely to be involved in protein-protein interactions, remain elusive. Here, we apply protein docking simulations and analysis of the interaction energy landscapes to identify protein-protein interaction sites. The new protocol for global docking based on multi-start global energy optimization of an all-atom model of the ligand, with detailed receptor potentials and atomic solvation parameters optimized in a training set of 24 complexes, explores the conformational space around the whole receptor without restrictions. The ensembles of the rigid-body docking solutions generated by the simulations were subsequently used to project the docking energy landscapes onto the protein surfaces. We found that highly populated low-energy regions consistently corresponded to actual binding sites. The procedure was validated on a test set of 21 known protein-protein complexes not used in the training set. As much as 81% of the predicted high-propensity patch residues were located correctly in the native interfaces. This approach can guide the design of mutations on the surfaces of proteins, provide geometrical details of a possible interaction, and help to annotate protein surfaces in structural proteomics.
Binding Sites↗
ICM-DISCO docking by global energy optimization with fully flexible side-chains.
The ICM-DISCO (Docking and Interface Side-Chain Optimization) protein-protein-docking method is a direct stochastic global energy optimization from multiple starting positions of the ligand. The first step is performed by docking of a rigid all-atom ligand molecule to a set of soft receptor potentials precalculated on a 0.5 A grid from realistic solvent-corrected force-field energies. This step finds the correct solution as the lowest energy conformation in almost 100% of the cases in which interfaces do not change on binding. The second step is needed to deal with the induced changes and includes the global optimization of the interface side-chains of up to 400 best solutions. The CAPRI predictions were performed fully automatically with this method. Available experimental information was included as a filtering step to favor expected docking surfaces. In three of the seven proposed targets, the ICM-DISCO method found a good solution (>50% of correct contacts) within the five submitted models. The procedure is global and fully automated. We demonstrate that the algorithm handles the induced changes of surface side-chains but is less successful if the backbone undergoes large-scale rearrangements.
Algorithms↗
The 'relevant' stability of proteins with equilibrium intermediates.
Proteins perform many useful molecular tasks, and their biotechnological use continues to increase. As protein activity requires a stable native conformation, protein stabilisation is a major scientific and practical issue. Towards that end, many successful protein stabilisation strategies have been devised in recent years. In most cases, model proteins with a two-state folding equilibrium have been used to study and demonstrate protein stabilisation. Many proteins, however, display more complex folding equilibria where stable intermediates accumulate. Stabilising these proteins requires specifically stabilising the native state relative to the intermediates, as these are expected to lack activity. Here we discuss how to investigate the 'relevant' stability of proteins with equilibrium intermediates and propose a way to dissect the contribution of side chain interactions to the overall stability into the 'relevant' and 'nonrelevant' terms. Examples of this analysis performed on apoflavodoxin and in a single-chain mini antibody are presented.
Computational Biology↗
Soft protein-protein docking in internal coordinates.
The association of two biological macromolecules is a fundamental biological phenomenon and an unsolved theoretical problem. Docking methods for ab initio prediction of association of two independently determined protein structures usually fail when they are applied to a large set of complexes, mostly because of inaccuracies in the scoring function and/or difficulties on simulating the rearrangement of the interface residues on binding. In this work we present an efficient pseudo-Brownian rigid-body docking procedure followed by Biased Probability Monte Carlo Minimization of the ligand interacting side-chains. The use of a soft interaction energy function precalculated on a grid, instead of the explicit energy, drastically increased the speed of the procedure. The method was tested on a benchmark of 24 protein-protein complexes in which the three-dimensional structures of their subunits (bound and free) were available. The rank of the near-native conformation in a list of candidate docking solutions was <20 in 85% of complexes with no major backbone motion on binding. Among them, as many as 7 out of 11 (64%) protease-inhibitor complexes can be successfully predicted as the highest rank conformations. The presented method can be further refined to include the binding site predictions and applied to the structures generated by the structural proteomics projects. All scripts are available on the Web.
Algorithms↗