Raquel Norel

Electrostatic aspects of protein–protein interactions

Structural and mutational analyses reveal a central role for electrostatic interactions in protein-protein association. Experiment and theory both demonstrate that clusters of charged and polar residues that are located on protein-protein interfaces may enhance complex stability, although the total effect of electrostatics is generally net destabilizing. The past year also witnessed significant progress in our understanding of the effect of electrostatics on protein association kinetics, specifically in the characterization of a partially desolvated encounter complex.

Examination of Shape Complementarity in Docking of Unbound Proteins

Here we carry out an examination of shape complementarity as a criterion in protein‐protein docking and binding. Specifically, we examine the quality of shape complementarity as a critical determinant not only in the docking of 26 protein‐protein “bound” complexed cases, but in particular, of 19 “unbound” protein‐protein cases, where the structures have been determined separately. In all cases, entire molecular surfaces are utilized in the docking, with no consideration of the location of the active site, or of particular residues/atoms in either the receptor or the ligand that participate in the binding. To evaluate the goodness of the strictly geometry‐based shape complementarity in the docking process as compared to the main favorable and unfavorable energy components, we study systematically a potential correlation between each of these components and the root mean square deviation (RMSD) of the “unbound” protein‐protein cases. Specifically, we examine the non‐polar buried surface area, polar buried surface area, buried surface area relating to groups bearing unsatisfied buried charges, and the number of hydrogen bonds in all docked protein‐protein interfaces. For these cases, where the two proteins have been crystallized separately, and where entire molecular surfaces are considered without a predefinition of the binding site, no correlation is observed. None of these parameters appears to consistently improve on shape complementarity in the docking of unbound molecules. These findings argue that simplicity in the docking process, utilizing geometrical shape criteria may capture many of the essential features in protein‐protein docking. In particular, they further reinforce the long held notion of the importance of molecular surface shape complementarity in the binding, and hence in docking. This is particularly interesting in light of the fact that the structures of the docked pairs have been determined separately, allowing side chains on the surface of the proteins to move relatively freely.

Protein interface conservation across structure space

With the advent of Systems Biology, the prediction of whether two proteins form a complex has become a problem of increased importance. A variety of experimental techniques have been applied to the problem, but three-dimensional structural information has not been widely exploited. Here we explore the range of applicability of such information by analyzing the extent to which the location of binding sites on protein surfaces is conserved among structural neighbors. We find, as expected, that interface conservation is most significant among proteins that have a clear evolutionary relationship, but that there is a significant level of conservation even among remote structural neighbors. This finding is consistent with recent evidence that information available from structural neighbors, independent of classification, should be exploited in the search for functional insights. The value of such structural information is highlighted through the development of a new protein interface prediction method, PredUs, that identifies what residues on protein surfaces are likely to participate in complexes with other proteins. The performance of PredUs, as measured through comparisons with other methods, suggests that relationships across protein structure space can be successfully exploited in the prediction of protein-protein interactions.

Electrostatic contributions to protein-protein interactions: Fast energetic filters for docking and their physical basis

The methods of continuum electrostatics are used to calculate the binding free energies of a set of protein–protein complexes including experimentally determined structures as well as other orientations generated by a fast docking algorithm. In the native structures, charged groups that are deeply buried were often found to favor complex formation (relative to isosteric nonpolar groups), whereas in nonnative complexes generated by a geometric docking algorithm, they were equally likely to be stabilizing as destabilizing. These observations were used to design a new filter for screening docked conformations that was applied, in conjunction with a number of geometric filters that assess shape complementarity, to 15 antibody–antigen complexes and 14 enzyme‐inhibitor complexes. For the bound docking problem, which is the major focus of this paper, native and near‐native solutions were ranked first or second in all but two enzyme‐inhibitor complexes. Less success was encountered for antibody–antigen complexes, but in all cases studied, the more complete free energy evaluation was able to idey native and near‐native structures. A filter based on the enrichment of tyrosines and tryptophans in antibody binding sites was applied to the antibody–antigen complexes and resulted in a native and near‐native solution being ranked first and second in all cases. A clear improvement over previously reported results was obtained for the unbound antibody–antigen examples as well. The algorithm and various filters used in this work are quite efficient and are able to reduce the number of plausible docking orientations to a size small enough so that a final more complete free energy evaluation on the reduced set becomes computationally feasible.

Two distinct binding sites for globotriaosyl ceramide on verotoxins: identification by molecular modelling and confirmation using deoxy analogues and a new glycolipid receptor for all verotoxins

BACKGROUNDnThe Escherichia coli verotoxins (VTs) can initiate human vascular disease via the specific recognition of globotriaosyl-ceramide (Gb3) on target endothelial cells. To explore the structural basis for receptor recognition by different VTs we used molecular modelling based on the crystal structure of VT1, mutational data and binding data for deoxy galabiosyl receptors.nnnRESULTSnWe propose a model for the verotoxin cleft-site complex with Gb3. Energy minimizations of Gb3 within the cleft site of verotoxins VT1, VT2, VT2c and VT2e resulted in stable complexes with hydrogen-bonding systems that were in agreement with binding data obtained for mono-deoxy analogues of Gb3. N-deacetylated globoside (aminoGb4), which was found to be a new, efficient receptor for all verotoxins, can be favourably accommodated in the cleft site of the VTs by formation of a salt bridge between the galactosamine and a cluster of aspartates in the site. The model is further extended to explain the binding of globoside by VT2e. Docking data support the possibility of an additional binding site for Gb3 on VT1.nnnCONCLUSIONSnThe proposed models for the complexes of verotoxins with their globoglycolipid receptors are consistent with receptor analogue binding data and explain previously published mutational studies. The results provide a first approach to the design of specific inhibitors of VT-receptor binding.

3-D Docking of Protein Molecules

We present geometric algorithms which tackle the docking problem in Molecular Biology. This problem is a central research topic both for synthetic drug design and for biomolecular recognition and interaction of proteins in general. Our algorithms have been implemented and experimented on several ‘real world’ biological examples. The preliminary experimental results show an order of magnitude improvement in the actual run-time of the algorithms in comparison to previously published techniques. The matching part of our algorithm is based on the Geometric Hashing technique, originally developed for Computer Vision applications. The algorithmic similarity between the problems emphasizes the importance of interdisciplinary research in Computational Molecular Biology. Future research directions are outlined as well.

PUDGE: a flexible, interactive server for protein structure prediction

The construction of a homology model for a protein can involve a number of decisions requiring the integration of different sources of information and the application of different modeling tools depending on the particular problem. Functional information can be especially important in guiding the modeling process, but such information is not generally integrated into modeling pipelines. Pudge is a flexible, interactive protein structure prediction server, which is designed with these issues in mind. By dividing the modeling into five stages (template selection, alignment, model building, model refinement and model evaluation) and providing various tools to visualize, analyze and compare the results at each stage, we enable a flexible modeling strategy that can be tailored to the needs of a given problem. Pudge is freely available at http://wiki.c2b2.columbia.edu/honiglab_public/index.php/Software:PUDGE.