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 A 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.     

Flexible relaxation of rigid-body docking solutions

Molecular Dynamics (MD) simulations have been performed on a set of rigid-body docking poses, carried out over 25 protein-protein complexes. The results show that fully flexible relaxation increases the fraction of native contacts (NC) by up to 70% for certain docking poses. The largest increase in the fraction of NC is observed for docking poses where anchor residues are able to sample their bound conformation. For each MD simulation, structural snap-shots were clustered and the centre of each cluster used as the MD-relaxed docking pose. A comparison between two energy-based scoring schemes, the first calculated for the MD-relaxed poses, the second for energy minimized poses, shows that the former are better in ranking complexes with large hydrophobic interfaces. Furthermore, complexes with large interfaces are generally ranked well, regardless of the type of relaxation method chosen, whereas complexes with small hydrophobic interfaces remain difficult to rank. In general, the results indicate that current force-fields are able to correctly describe direct intermolecular interactions between receptor and ligand molecules. However, these force-fields still fail in cases where protein-protein complexes are stabilized by subtle energy contributions.     

RDOCK: refinement of rigid-body protein docking predictions

We present a simple and effective algorithm RDOCK for refining unbound predictions generated by a rigid-body docking algorithm ZDOCK, which has been developed earlier by our group. The main component of RDOCK is a three-stage energy minimization scheme, followed by the evaluation of electrostatic and desolvation energies. Ionic side chains are kept neutral in the first two stages of minimization, and reverted to their full charge states in the last stage of brief minimization. Without side chain conformational search or filtering/clustering of resulting structures, RDOCK represents the simplest approach toward refining unbound docking predictions. Despite its simplicity, RDOCK makes substantial improvement upon the top predictions by ZDOCK with all three scoring functions and the improvement is observed across all three categories of test cases in a large benchmark of 49 non-redundant unbound test cases. RDOCK makes the most powerful combination with ZDOCK2.1, which uses pairwise shape complementarity as the scoring function. Collectively, they rank a near-native structure as the number-one prediction for 18 test cases (37% of the benchmark), and within the top 4 predictions for 24 test cases (49% of the benchmark). To various degrees, funnel-like energy landscapes are observed for these 24 test cases. To the best of our knowledge, this is the first report of binding funnels starting from global searches for a broad range of test cases. These results are particularly exciting, given that we have not used any biological information that is specific to individual test cases and the whole process is entirely automated. Among three categories of test cases, the best results are seen for enzyme/inhibitor, with a near-native structure ranked as the number-one prediction for 48% test cases, and within the top 10 predictions for 78% test cases. RDOCK is freely available to academic users at http://zlab.bu.edu/ approximately rong/dock.     

Divergence of interdomain geometry in two-domain proteins

For homologous protein chains composed of two domains, we have determined the extent to which they conserve (1) their interdomain geometry and (2) the molecular structure of the domain interface. This work was carried out on 128 unique two-domain architectures. Of the 128, we find 75 conserve their interdomain geometry and the structure of their domain interface; 5 conserve their interdomain geometry but not the structure of their interface; and 48 have variable geometries and divergent interface structure. We describe how different types of interface changes or the absence of an interface is responsible for these differences in geometry. Variable interdomain geometries can be found in homologous structures with high sequence identities (70%).     

Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations

Protein-protein docking algorithms provide a means to elucidate structural details for presently unknown complexes. Here, we present and evaluate a new method to predict protein-protein complexes from the coordinates of the unbound monomer components. The method employs a low-resolution, rigid-body, Monte Carlo search followed by simultaneous optimization of backbone displacement and side-chain conformations using Monte Carlo minimization. Up to 10(5) independent simulations are carried out, and the resulting "decoys" are ranked using an energy function dominated by van der Waals interactions, an implicit solvation model, and an orientation-dependent hydrogen bonding potential. Top-ranking decoys are clustered to select the final predictions. Small-perturbation studies reveal the formation of binding funnels in 42 of 54 cases using coordinates derived from the bound complexes and in 32 of 54 cases using independently determined coordinates of one or both monomers. Experimental binding affinities correlate with the calculated score function and explain the predictive success or failure of many targets. Global searches using one or both unbound components predict at least 25% of the native residue-residue contacts in 28 of the 32 cases where binding funnels exist. The results suggest that the method may soon be useful for generating models of biologically important complexes from the structures of the isolated components, but they also highlight the challenges that must be met to achieve consistent and accurate prediction of protein-protein interactions.     

pyDock: electrostatics and desolvation for effective scoring of rigid-body protein-protein docking

The accurate scoring of rigid-body docking orientations represents one of the major difficulties in protein-protein docking prediction. Other challenges are the development of faster and more efficient sampling methods and the introduction of receptor and ligand flexibility during simulations. Overall, good discrimination of near-native docking poses from the very early stages of rigid-body protein docking is essential step before applying more costly interface refinement to the correct docking solutions. Here we explore a simple approach to scoring of rigid-body docking poses, which has been implemented in a program called pyDock. The scheme is based on Coulombic electrostatics with distance dependent dielectric constant, and implicit desolvation energy with atomic solvation parameters previously adjusted for rigid-body protein-protein docking. This scoring function is not highly dependent on specific geometry of the docking poses and therefore can be used in rigid-body docking sets generated by a variety of methods. We have tested the procedure in a large benchmark set of 80 unbound docking cases. The method is able to detect a near-native solution from 12,000 docking poses and place it within the 100 lowest-energy docking solutions in 56% of the cases, in a completely unrestricted manner and without any other additional information. More specifically, a near-native solution will lie within the top 20 solutions in 37% of the cases. The simplicity of the approach allows for a better understanding of the physical principles behind protein-protein association, and provides a fast tool for the evaluation of large sets of rigid-body docking poses in search of the near-native orientation.     

Effect of local shape modifications of molecular surfaces on rigid-body protein-protein docking

Geometric complementarity is the most dominant term in protein-protein docking and therefore, a good geometric representation of the molecules, which takes into account the flexibility of surface residues, is desirable. We present a modified geometric representation of the molecular surface that down-weighs the contribution of specified parts of the surface to the complementarity score. We apply it to the mobile ends of the most flexible side chains: lysines, glutamines and arginines (trimming). The new representation systematically reduces the complementarity scores of the false-positive solutions, often more than the scores of the correct solutions, thereby improving significantly our ability to identify nearly correct solutions in rigid-body docking of unbound structures. The effect of trimming lysine residues is larger than trimming of glutamine or arginine residues. It appears to be independent of the conformations of the trimmed residues but depends on the relative abundance of such residues at the interface and on the non-interacting surface. Combining the modified geometric representation with electrostatic complementarity further improves the docking results.     

On docking, scoring and assessing protein-DNA complexes in a rigid-body framework

We consider the identification of interacting protein-nucleic acid partners using the rigid body docking method FTdock, which is systematic and exhaustive in the exploration of docking conformations. The accuracy of rigid body docking methods is tested using known protein-DNA complexes for which the docked and undocked structures are both available. Additional tests with large decoy sets probe the efficacy of two published statistically derived scoring functions that contain a huge number of parameters. In contrast, we demonstrate that state-of-the-art machine learning techniques can enormously reduce the number of parameters required, thereby identifying the relevant docking features using a miniscule fraction of the number of parameters in the prior works. The present machine learning study considers a 300 dimensional vector (dependent on only 15 parameters), termed the Chemical Context Profile (CCP), where each dimension reflects a specific type of protein amino acid-nucleic acid base interaction. The CCP is designed to capture the chemical complementarities of the interface and is well suited for machine learning techniques. Our objective function is the Chemical Context Discrepancy (CCD), which is defined as the angle between the native system's CCP vector and the decoy's vector and which serves as a substitute for the more commonly used root mean squared deviation (RMSD). We demonstrate that the CCP provides a useful scoring function when certain dimensions are properly weighted. Finally, we explore how the amino acids on a protein's surface can help guide DNA binding, first through long-range interactions, followed by direct contacts, according to specific preferences for either the major or minor grooves of the DNA.     

Monte Carlo refinement of rigid-body protein docking structures with backbone displacement and side-chain optimization

Structures of hitherto unknown protein complexes can be predicted by docking the solved protein monomers. Here, we present a method to refine initial docking estimates of protein complex structures by a Monte Carlo approach including rigid-body moves and side-chain optimization. The energy function used is comprised of van der Waals, Coulomb, and atomic contact energy terms. During the simulation, we gradually shift from a novel smoothed van der Waals potential, which prevents trapping in local energy minima, to the standard Lennard-Jones potential. Following the simulation, the conformations are clustered to obtain the final predictions. Using only the first 100 decoys generated by a fast Fourier transform (FFT)-based rigid-body docking method, our refinement procedure is able to generate near-native structures (interface RMSD <2.5 A) as first model in 14 of 59 cases in a benchmark set. In most cases, clear binding funnels around the native structure can be observed. The results show the potential of Monte Carlo refinement methods and emphasize their applicability for protein-protein docking.     

Automated docking of substrates to proteins by simulated annealing

The Metropolis technique of conformation searching is combined with rapid energy evaluation using molecular affinity potentials to give an efficient procedure for docking substrates to macromolecules of known structure. The procedure works well on a number of crystallographic test systems, functionally reproducing the observed binding modes of several substrates.     

Structural requirements for membrane assembly of proteins spanning the membrane several times

We have investigated the structural requirements for the biogenesis of proteins spanning the membrane several times. Proteins containing various combinations of topological signals (signal anchor and stop transfer sequences) were synthesized in a cell-free translation system and their membrane topology was determined. Proteins spanning the membrane twice were obtained when a signal anchor sequence was followed by either a stop transfer sequence or a second signal anchor sequence. Thus, a signal anchor sequence in the second position can function as a stop transfer sequence, spanning the membrane in the opposite orientation to that of the first signal anchor sequence. A signal anchor sequence in the third position was able to insert amino acid sequences located COOH terminal to it. We conclude that proteins spanning the membrane several times can be generated by stringing together signal anchor and stop transfer sequences. However, not all proteins with three topological signals were found to span the membrane three times. A certain segment located between the first and second topological signal could prevent stable membrane integration of a third signal anchor segment.     

Narrowing the conformational space sampled by two-domain proteins with paramagnetic probes in both domains

Calmodulin is a two-domain protein which in solution can adopt a variety of conformations upon reorientation of its domains. The maximum occurrence (MO) of a set of calmodulin conformations that are representative of the overall conformational space possibly sampled by the protein, has been calculated from the paramagnetism-based restraints. These restraints were measured after inclusion of a lanthanide binding tag in the C-terminal domain to supplement the data obtained by substitution of three paramagnetic lanthanide ions to the calcium ion in the second calcium binding loop of the N-terminal domain. The analysis shows that the availability of paramagnetic restraints arising from metal ions placed on both domains, reduces the MO of the conformations to different extents, thereby helping to identify those conformations that can be mostly sampled by the protein.     

Incorporation of flexibility into rigid-body docking: applications in rounds 3-5 of CAPRI

We have submitted models for all 9 targets in Rounds 3-5 of CAPRI and have predicted at least 30% of the correct contacts for 4 of the targets and at least 10% of the correct contacts for another 4 targets. We have employed a variety of techniques but have had the greatest success by combining established rigid-body docking with a variety of initial conformations generated by molecular dynamics.     

Structural studies of a two-domain chitinase from Streptomyces griseus HUT6037

Chitinase C (ChiC) from Streptomyces griseus HUT6037 was the first glycoside hydrolase family 19 chitinase that was found in an organism other than higher plants. An N-terminal chitin-binding domain and a C-terminal catalytic domain connected by a linker peptide constitute ChiC. We determined the crystal structure of full-length ChiC, which is the only representative of the two-domain chitinases in the family. The catalytic domain has an alpha-helix-rich fold with a deep cleft containing a catalytic site, and lacks three loops on the domain surface compared with the catalytic domain of plant chitinases. The chitin-binding domain is an all-beta protein with two tryptophan residues (Trp59 and Trp60) aligned on the surface. We suggest the binding mechanism of tri-N-acetylchitotriose onto the chitin-binding domain on the basis of molecular dynamics (MD) simulations. In this mechanism, the ligand molecule binds well on the surface-exposed binding site through two stacking interactions and two hydrogen bonds and only Trp59 and Trp60 are involved in the binding. Furthermore, the flexibility of the Trp60 side-chain, which may be involved in adjusting the binding surface to fit the surface of crystalline chitin by the rotation of chi2 angle, is shown.     

The affinity-enhancing roles of flexible linkers in two-domain DNA-binding proteins.

Recently many attempts have been made to design high-affinity DNA-binding proteins by linking two domains. Here a theory for guiding these designs is presented. Flexible linkers may play three types of roles: (a) linking domains which by themselves are unfolded and bind to DNA only as a folded dimer (as in a designed single-chain Arc repressor), (b) connecting domains which can separately bind to DNA (as in the Oct-1 POU domain), and (c) linking a DNA-binding domain with a dimerization domain (as in the lambda repressor). In (a), the linker keeps the protein as a folded dimer so that it is always DNA-binding-competent. In (b), the linker is predicted to enhance DNA-binding affinity over those of the individual domains (with dissociation constants K(A) and K(B)) by p(d(0))/K(B) or p(d(0))/K(A), where p(d(0)) = (3/4pil(p)bL)(3/2) exp(-3d(0)(2)/4l(p)bL)(1 - 5l(p)/4bL +...) is the probability density for the end-to-end vector of the linker with L residues to have a distance d(0). In (c), the linker is predicted to enhance the binding affinity by K(d)(C)/p(d(0)), where K(d)(C) is the dimer dissociation constant for the dimerization domain. The predicted affinity enhancements are found to be actually reached by the Oct-1 POU domain and lambda repressor. However, there is room for improvement in many of the recently designed proteins. The theoretical limits presented should provide a useful guide for current efforts of designing DNA-binding proteins.     

Structural relationships between clathrin assembly proteins from the Golgi and the plasma membrane

We have established by peptide mapping and immunochemical analysis of purified clathrin assembly protein preparations from bovine brain, that the cluster of components of mol. wt 100-120 kd fall into four classes, which we term alpha, beta, beta' and gamma. The beta and beta' proteins are immunologically related and generate a series of common tryptic peptides. The same criteria reveal no such homologies between the alpha, beta(beta') and gamma polypeptides. The so-called HA-II assembly protein group contains equimolar amounts of alpha and beta class polypeptides, which are shown to interact with each other. In the HA-I group assembly protein complex gamma and beta' class polypeptides form a stoichiometric complex. Immunofluorescence microscopy reveals that the HA-I complex is specifically associated with clathrin-coated membranes in the Golgi region of cultured cells, whereas the HA-II complex appears to be restricted to coated pits on the plasma membrane. The data lead to the tentative conclusion that the clathrin assembly proteins are involved in the recognition of the intracellular targets by uncoated vesicles.     

Comparison of Segger and other methods for segmentation and rigid-body docking of molecular components in cryo-EM density maps

Segmentation and docking are useful methods for the discovery of molecular components in electron cryo-microscopy (cryo-EM) density maps of macromolecular complexes. In this article, we describe the segmentation and docking methods implemented in Segger. For 11 targets posted in the 2010 cryo-EM challenge, we segmented the regions corresponding to individual molecular components using Segger. We then used the segmented regions to guide rigid-body docking of individual components. Docking results were evaluated by comparing the docked components with published structures, and by calculation of several scores, such as atom inclusion, density occupancy, and geometry clash. The accuracy of the component segmentation using Segger and other methods was assessed by comparing segmented regions with docked components.     

Structural templates for comparative protein docking

Structural characterization of protein‐protein interactions is important for understanding life processes. Because of the inherent limitations of experimental techniques, such characterization requires computational approaches. Along with the traditional protein‐protein docking (free search for a match between two proteins), comparative (template‐based) modeling of protein‐protein complexes has been gaining popularity. Its development puts an emphasis on full and partial structural similarity between the target protein monomers and the protein‐protein complexes previously determined by experimental techniques (templates). The template‐based docking relies on the quality and diversity of the template set. We present a carefully curated, nonredundant library of templates containing 4950 full structures of binary complexes and 5936 protein‐protein interfaces extracted from the full structures at 12 Å distance cut‐off. Redundancy in the libraries was removed by clustering the PDB structures based on structural similarity. The value of the clustering threshold was determined from the analysis of the clusters and the docking performance on a benchmark set. High structural quality of the interfaces in the template and validation sets was achieved by automated procedures and manual curation. The library is included in the Dockground resource for molecular recognition studies at http://dockground.bioinformatics.ku.edu . Proteins 2015; 83:1563–1570. © 2014 Wiley Periodicals, Inc.