Carlos J. Camacho

ClusPro: an automated docking and discrimination method for the prediction of protein complexes

MOTIVATION Predicting protein interactions is one of the most challenging problems in functional genomics. Given two proteins known to interact, current docking methods evaluate billions of docked conformations by simple scoring functions, and in addition to near-native structures yield many false positives, i.e. structures with good surface complementarity but far from the native. RESULTS We have developed a fast algorithm for filtering docked conformations with good surface complementarity, and ranking them based on their clustering properties. The free energy filters select complexes with lowest desolvation and electrostatic energies. Clustering is then used to smooth the local minima and to select the ones with the broadest energy wells-a property associated with the free energy at the binding site. The robustness of the method was tested on sets of 2000 docked conformations generated for 48 pairs of interacting proteins. In 31 of these cases, the top 10 predictions include at least one near-native complex, with an average RMSD of 5 A from the native structure. The docking and discrimination method also provides good results for a number of complexes that were used as targets in the Critical Assessment of PRedictions of Interactions experiment. AVAILABILITY The fully automated docking and discrimination server ClusPro can be found at http://structure.bu.edu

ClusPro: A fully automated algorithm for protein-protein docking

ClusPro (http://nrc.bu.edu/cluster) represents the first fully automated, web-based program for the computational docking of protein structures. Users may upload the coordinate files of two protein structures through ClusPros web interface, or enter the PDB codes of the respective structures, which ClusPro will then download from the PDB server (http://www.rcsb.org/pdb/). The docking algorithms evaluate billions of putative complexes, retaining a preset number with favorable surface complementarities. A filtering method is then applied to this set of structures, selecting those with good electrostatic and desolvation free energies for further clustering. The program output is a short list of putative complexes ranked according to their clustering properties, which is automatically sent back to the user via email.

Free energy landscapes of encounter complexes in protein-protein association.

We report the computer generation of a high-density map of the thermodynamic properties of the diffusion-accessible encounter conformations of four receptor-ligand protein pairs, and use it to study the electrostatic and desolvation components of the free energy of association. Encounter complex conformations are generated by sampling the translational/rotational space of the ligand around the receptor, both at 5-A and zero surface-to-surface separations. We find that partial desolvation is always an important effect, and it becomes dominant for complexes in which one of the reactants is neutral or weakly charged. The interaction provides a slowly varying attractive force over a small but significant region of the molecular surface. In complexes with no strong charge complementarity this region surrounds the binding site, and the orientation of the ligand in the encounter conformation with the lowest desolvation free energy is similar to the one observed in the fully formed complex. Complexes with strong opposite charges exhibit two types of behavior. In the first group, represented by barnase/barstar, electrostatics exerts strong orientational steering toward the binding site, and desolvation provides some added adhesion within the local region of low electrostatic energy. In the second group, represented by the complex of kallikrein and pancreatic trypsin inhibitor, the overall stability results from the rather nonspecific electrostatic attraction, whereas the affinity toward the binding region is determined by desolvation interactions.

Kinetics of Desolvation-Mediated Protein–Protein Binding

The role of desolvation in protein binding kinetics is investigated using Brownian dynamics simulations in complexes in which the electrostatic interactions are relatively weak. We find that partial desolvation, modeled by a short-range atomic contact potential, is not only a major contributor to the binding free energy but also substantially increases the diffusion-limited rate for complexes in which long-range electrostatics is weak. This rate enhancement is mostly due to weakly specific pathways leading to a low free-energy attractor, i.e., a precursor state before docking. For alpha-chymotrypsin and human leukocyte elastase, both interacting with turkey ovomucoid third domain, we find that the forward rate constant associated with a collision within a solid angle phi around their corresponding attractor approaches 10(7) and 10(6) M(-1)s(-1), respectively, in the limit phi approximately 2 degrees. Because these estimates agree well with experiments, we conclude that the final bound conformation must be preceded by a small set of well-defined diffusion-accessible precursor states. The inclusion of the otherwise repulsive desolvation interaction also explains the lack of aggregation in proteins by restricting nonspecific association times to approximately 4 ns. Under the same reaction conditions but without short range forces, the association rate would be only approximately 10(3) M(-1)s(-1). Although desolvation increases these rates by three orders of magnitude, desolvation-mediated association is still at least 100-fold slower than the electrostatically assisted binding in complexes such as barnase and barstar.

Protein docking along smooth association pathways

We propose a docking method that mimics the way proteins bind. The method accounts for the dominant driving forces at the different length scales of the protein binding process, allowing for an efficient selection of a downhill path on the evolving receptor-ligand-free energy landscape. Starting from encounter complexes with as much as 10 Å rms deviation from the native conformation, the method locally samples the six dimensional space of rigid-body receptor-ligand structures subject to a van der Waals constraint. The sampling is initially biased only by the desolvation and electrostatic components of the free energy, which capture the partial affinity of unbound structures that are more than 4 Å away from the native state. Below this threshold, improved discrimination is attained by adding an increasing fraction of the van der Waals energy to the force field. The method, with no free parameters, was tested in eight different sets of independently crystallized receptor-ligand structures consistently predicting bound conformations with the lowest free energies and appropriate stability gap around 2 Å from the native complex. This multistage approach is consistent with the underlying kinetics and internal structure of the free energy funnel to the bound state. Implications for the nature of the protein binding pathways are also discussed.

Scoring docked conformations generated by rigid-body protein-protein docking.

Rigid‐body methods, particularly Fourier correlation techniques, are very efficient for docking bound (co‐crystallized) protein conformations using measures of surface complementarity as the target function. However, when docking unbound (separately crystallized) conformations, the method generally yields hundreds of false positive structures with good scores but high root mean square deviations (RMSDs). This paper describes a two‐step scoring algorithm that can discriminate near‐native conformations (with less than 5 Å RMSD) from other structures. The first step includes two rigid‐body filters that use the desolvation free energy and the electrostatic energy to select a manageable number of conformations for further processing, but are unable to eliminate all false positives. Complete discrimination is achieved in the second step that minimizes the molecular mechanics energy of the retained structures, and re‐ranks them with a combined free‐energy function which includes electrostatic, solvation, and van der Waals energy terms. After minimization, the improved fit in near‐native complex conformations provides the free‐energy gap required for discrimination. The algorithm has been developed and tested using docking decoys, i.e., docked conformations generated by Fourier correlation techniques. The decoy sets are available on the web for testing other discrimination procedures. Proteins 2000;40:525–537.

Community-wide assessment of protein-interface modeling suggests improvements to design methodology

The CAPRI (Critical Assessment of Predicted Interactions) and CASP (Critical Assessment of protein Structure Prediction) experiments have demonstrated the power of community-wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community-wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting that there may be important physical chemistry missing in the energy calculations. A total of 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the nonpolar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were, on average, structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a nonbinder.

FastContact: rapid estimate of contact and binding free energies

UNLABELLED Interaction free energies are crucial for analyzing binding propensities in proteins. Although the problem of computing binding free energies remains open, approximate estimates have become very useful for filtering potential binding complexes. We report on the implementation of a fast computational estimate of the binding free energy based on a statistically determined desolvation contact potential and Coulomb electrostatics with a distance-dependent dielectric constant, and validated in the Critical Assessment of PRotein Interactions experiment. The application also reports residue contact free energies that rapidly highlight the hotspots of the interaction. AVAILABILITY The program was written in Fortran. The executable and full documentation is freely available at http://structure.pitt.edu/software/FastContact

Protein-protein association kinetics and protein docking.

Rigid body protein docking methods frequently yield false positive structures that have good surface complementarity, but are far from the native complex. The main reason for this is the uncertainty of the protein structures to be docked, including the positions of solvent-exposed sidechains. Substantial efforts have been devoted to finding near-native structures by rescoring the docked conformations and employing various filters. An alternative approach emulates the process of protein-protein association, that is, first finding the region in which binding is likely to occur and then refining the complex while allowing for flexibility.

ZINCPharmer: pharmacophore search of the ZINC database

ZINCPharmer (http://zincpharmer.csb.pitt.edu) is an online interface for searching the purchasable compounds of the ZINC database using the Pharmer pharmacophore search technology. A pharmacophore describes the spatial arrangement of the essential features of an interaction. Compounds that match a well-defined pharmacophore serve as potential lead compounds for drug discovery. ZINCPharmer provides tools for constructing and refining pharmacophore hypotheses directly from molecular structure. A search of 176 million conformers of 18.3 million compounds typically takes less than a minute. The results can be immediately viewed, or the aligned structures may be downloaded for off-line analysis. ZINCPharmer enables the rapid and interactive search of purchasable chemical space.