Complex-type-dependent scoring functions in protein-protein docking

A major challenge in the field of protein-protein docking is to discriminate between the many wrong and few near-native conformations, i.e. scoring. Here, we introduce combinatorial complex-type-dependent scoring functions for different types of protein-protein complexes, protease/inhibitor, antibody/antigen, enzyme/inhibitor and others. The scoring functions incorporate both physical and knowledge-based potentials, i.e. atomic contact energy (ACE), the residue pair potential (RP), electrostatic and van der Waals' interactions. For different type complexes, the weights of the scoring functions were optimized by the multiple linear regression method, in which only top 300 structures with ligand root mean square deviation (L_RMSD) less than 20 A from the bound (co-crystallized) docking of 57 complexes were used to construct a training set. We employed the bound docking studies to examine the quality of the scoring function, and also extend to the unbound (separately crystallized) docking studies and extra 8 protein-protein complexes. In bound docking of the 57 cases, the first hits of protease/inhibitor cases are all ranked in the top 5. For the cases of antibody/antigen, enzyme/inhibitor and others, there are 17/19, 5/6 and 13/15 cases with the first hits ranked in the top 10, respectively. In unbound docking studies, the first hits of 9/17 protease/inhibitor, 6/19 antibody/antigen, 1/6 enzyme/inhibitor and 6/15 others' complexes are ranked in the top 10. Additionally, for the extra 8 cases, the first hits of the two protease/inhibitor cases are ranked in the top for the bound and unbound test. For the two enzyme/inhibitor cases, the first hits are ranked 1st for bound test, and the 119th and 17th for the unbound test. For the others, the ranks of the first hits are the 1st for the bound test and the 12th for the 1WQ1 unbound test. To some extent, the results validated our divide-and-conquer strategy in the docking study, which might hopefully shed light on the prediction of protein-protein interactions.     

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.     

Information-driven protein-DNA docking using HADDOCK: it is a matter of flexibility

Intrinsic flexibility of DNA has hampered the development of efficient protein−DNA docking methods. In this study we extend HADDOCK (High Ambiguity Driven DOCKing) [C. Dominguez, R. Boelens and A. M. J. J. Bonvin (2003) J. Am. Chem. Soc. 125, 1731–1737] to explicitly deal with DNA flexibility. HADDOCK uses non-structural experimental data to drive the docking during a rigid-body energy minimization, and semi-flexible and water refinement stages. The latter allow for flexibility of all DNA nucleotides and the residues of the protein at the predicted interface. We evaluated our approach on the monomeric repressor−DNA complexes formed by bacteriophage 434 Cro, the Escherichia coli Lac headpiece and bacteriophage P22 Arc. Starting from unbound proteins and canonical B-DNA we correctly predict the correct spatial disposition of the complexes and the specific conformation of the DNA in the published complexes. This information is subsequently used to generate a library of pre-bent and twisted DNA structures that served as input for a second docking round. The resulting top ranking solutions exhibit high similarity to the published complexes in terms of root mean square deviations, intermolecular contacts and DNA conformation. Our two-stage docking method is thus able to successfully predict protein−DNA complexes from unbound constituents using non-structural experimental data to drive the docking.     

Prediction and scoring of docking poses with pyDock

The two previous CAPRI experiments showed the success of our rigid-body and refinement approach. For this third edition of CAPRI, we have used a new faster protocol called pyDock, which uses electrostatics and desolvation energy to score docking poses generated with FFT-based algorithms. In target T24 (unbound/model), our best prediction had the highest value of fraction of native contacts (40%) among all participants, although it was not considered as acceptable by the CAPRI criteria. In target T25 (unbound/bound), we submitted a model with medium quality. In target T26 (unbound/unbound), we did not submit any acceptable model (but we would have submitted acceptable predictions if we had included available mutational information about the binding site). For targets T27 (unbound/unbound) and T28 (homo-dimer using model), nobody (including us) submitted any acceptable model. Intriguingly, the crystal structure of target T27 shows an alternative interface that correlates with available biological data (we would have submitted acceptable predictions if we had included this). We also participated in all targets of the SCORERS experiment, with at least acceptable accuracy in all valid cases. We submitted two medium and four acceptable scoring models of T25. Using additional distance restraints (from mutational data), we had two medium and two acceptable scoring models of T26. For target T27, we submitted two acceptable scoring models of the alternative interface in the crystal structure. In summary, CAPRI showed the excellent capabilities of pyDock in identifying near-native docking poses.     

Amino acid network and its scoring application in protein-protein docking

Protein-protein complex, composed of hydrophobic and hydrophilic residues, can be divided into hydrophobic and hydrophilic amino acid network structures respectively. In this paper, we are interested in analyzing these two different types of networks and find that these networks are of small-world properties. Due to the characteristic complementarity of the complex interfaces, protein-protein docking can be viewed as a particular network rewiring. These networks of correct docked complex conformations have much more increase of the degree values and decay of the clustering coefficients than those of the incorrect ones. Therefore, two scoring terms based on the network parameters are proposed, in which the geometric complementarity, hydrophobic-hydrophobic and polar-polar interactions are taken into account. Compared with a two-term energy function, a simple scoring function HPNet which includes the two network-based scoring terms shows advantages in two aspects, not relying on energy considerations and better discrimination. Furthermore, combing the network-based scoring terms with some other energy terms, a new multi-term scoring function HPNet-combine can also make some improvements to the scoring function of RosettaDock.     

Evaluating scoring functions for docking and designing beta-secretase inhibitors

Several simple scoring methods were examined for 2 series of beta-secretase (BACE-1) inhibitors to identify a docking/scoring protocol which could be used to design BACE-1 inhibitors in a drug discovery program. Both the PLP1 score and MMFFs interaction energy (E(inter)) performed as well or better than more computationally intensive methods for a set of substrate-based inhibitors, while the latter performed well for both sets of inhibitors.     

High-specific-activity probes and a high-resolution in-gel photo cross-linking assay for protein-DNA complexes

Photochemical cross-linking has been widely employed to identify proteins interacting with specific sites on DNA. Identification of bound proteins usually relies on transfer of a radiolabel from the DNA to the protein by cross-linking. We set out to fine-map a small viral replication preinitiation complex composed of two protein dimers bound to DNA, the bovine papillomavirus E1E2-ori complex. Here we describe a simple method for generating high-specific-activity probes with a phenyl-azide photoactivatible cross-linking group positioned immediately adjacent to a labeled nucleotide. The method is based on the selective destruction of one 5'-phosphorylated strand of a polymerase chain reaction product with lambda exonuclease and reconstitution of the probe with a phosphorothioate-substituted oligonucleotide, an [alpha-(32)P]dNTP, and thermophilic enzymes. We also developed a high-resolution in-gel cross-linking assay to probe defined protein-DNA complexes. With these methods we have obtained structural information for the papillomavirus E1E2-ori preinitiation complex that would otherwise have been hard to obtain. These approaches should be widely applicable to the study of protein-DNA complexes.     

Visualization of DNA and RNA molecules, and protein-DNA complexes for electron microscopy

This article provides step-by step instructions for the preparation of double- and single-stranded DNA and RNA molecules and protein-DNA complexes for electron microscopy (EM). Absorption, spreading, staining, dark-field imaging, and metal shadowing techniques are described in detail. A number of examples are illustrated on analysis of DNA replication, DNA repair and DNA recombination to demonstrate the usefulness of the technique for EM visualisation. Application of immunogold labeling of specific protein in DNA-protein complexes is also covered.     

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.     

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.     

Immunofluorescent study of non-histone protein-DNA complexes in cultured cells and lymphocytes

Antibody against non-histone chromosomal protein-DNA complex of C-6 cells derived from human lymphoblastoid cells were prepared. By immunofluorescent studies using the antibody, nuclear fluorescence, which was speckled or clumped in appearance, was observed in cultured human lymphoblastoid cell lines, cultured human epithelial cell lines and human peripheral lymphocytes. In the human peripheral lymphocytes, there was a distinct variation in intensity of the nuclear fluorescence among the cell population. On the contrary, no nuclear fluorescence was observed in cultured animal cell lines.     

Structural study of homeodomain protein-DNA complexes using a homology modeling approach

The homeodomain is a conserved protein motif that binds to DNA and plays a central role in gene regulation. We use homeodomain as a model system to study the specific interactions between protein and DNA in a complex. Following the fundamental concept of homology modeling, we have developed an algorithm for predicting structures of both protein and DNA using the known structure of a similar complex as the template. The accuracies of the algorithm in predicting the complex structures are evaluated when two of the homeodomain protein-DNA complexes with known structures (antennapedia and MATalpha2) are selected as test systems. This algorithm allows structural studies of homeodomain binds to DNA with different sequences.     

Recent advances in FRET: distance determination in protein-DNA complexes

Fluorescence resonance energy transfer (FRET) provides information on the distance between a donor and an acceptor dye in the range 10 to 100 A. Knowledge of the exact positions of some dyes with respect to nucleic acids now enables us to translate these data into precise structural information using molecular modeling. Advances in the preparation of dye-labeled nucleic acid molecules and in new techniques, such as the measurement of FRET in polyacrylamide gels or in vivo, will lead to an increasingly important role of FRET in structural and molecular biology.     

Bi-functional cross-linking reagents efficiently capture protein-DNA complexes in Drosophila embryos

Chromatin immunoprecipitation (ChIP) is widely used for mapping DNA-protein interactions across eukaryotic genomes in cells, tissues or even whole organisms. Critical to this procedure is the efficient cross-linking of chromatin-associated proteins to DNA sequences that are in close proximity. Since the mid-nineties formaldehyde fixation has been the method of choice. However, some protein-DNA complexes cannot be successfully captured for ChIP using formaldehyde. One such formaldehyde refractory complex is the developmentally regulated insulator factor, Elba. Here we describe a new embryo fixation procedure using the bi-functional cross-linking reagents DSG (disuccinimidyl glutarate) and DSP (dithiobis[succinimidyl propionate). We show that unlike standard formaldehyde fixation protocols, it is possible to capture Elba association with insulator elements in 2–5 h embryos using this new cross-linking procedure. We show that this new cross-linking procedure can also be applied to localize nuclear proteins that are amenable to ChIP using standard formaldehyde cross-linking protocols, and that in the cases tested the enrichment was generally superior to that achieved using formaldehyde cross-linking.     

Association of protein-DNA recognition complexes: electrostatic and nonelectrostatic effects

In this study the electrostatic and nonelectrostatic contributions to the binding free energy of a number of different protein-DNA recognition complexes are investigated. To determine the electrostatic effects in the protein-DNA association the Poisson-Boltzmann approach was applied. Overall the salt-dependent electrostatic free energy opposed binding in all protein-DNA complexes except one, and the salt-independent electrostatic contribution favored binding in more than half of the complexes. Further the salt-dependent electrostatic free energy increased with higher ionic concentrations and therefore complex association is stronger opposed at higher ionic concentrations. The hydrophobic effect in the protein-DNA complexes was determined from the buried accessible surface area and the surface tension. A majority of the complexes showed more polar than nonpolar buried accessible surface area. Interestingly the buried DNA-accessible surface area was preferentially hydrophilic, only in one complex a slightly more hydrophobic buried accessible surface area was observed. A quite sophisticated balance between several different free energy components seems to be responsible for determining the free energy of binding in protein-DNA systems.     

Hydrogen bonds in protein-DNA complexes: where geometry meets plasticity

Recognition of a DNA sequence by a protein is achieved by interface-coupled chemical and shape complementation. This complementation between the two molecules is clearly directional and is determined by the specific chemical contacts including mainly hydrogen bonds. Directionality is an instrumental property of hydrogen bonding as it influences molecular conformations, which also affects DNA-protein recognition. The prominent elements in the recognition of a particular DNA sequence by a protein are the hydrogen-bond donors and acceptors of the base pairs into the grooves of the DNA that must interact with complementary moieties of the protein partner. Protein side chains make most of the crucial contacts through bidentate and complex hydrogen-bonding interactions with DNA base edges hence conferring remarkable specificity.     

A model binding site for testing scoring functions in molecular docking

Prediction of interaction energies between ligands and their receptors remains a major challenge for structure-based inhibitor discovery. Much effort has been devoted to developing scoring schemes that can successfully rank the affinities of a diverse set of possible ligands to a binding site for which the structure is known. To test these scoring functions, well-characterized experimental systems can be very useful. Here, mutation-created binding sites in T4 lysozyme were used to investigate how the quality of atomic charges and solvation energies affects molecular docking. Atomic charges and solvation energies were calculated for 172,118 molecules in the Available Chemicals Directory using a semi-empirical quantum mechanical approach by the program AMSOL. The database was first screened against the apolar cavity site created by the mutation Leu99Ala (L99A). Compared to the electronegativity-based charges that are widely used, the new charges and desolvation energies improved ranking of known apolar ligands, and better distinguished them from more polar isosteres that are not observed to bind. To investigate whether the new charges had predictive value, the non-polar residue Met102, which forms part of the binding site, was changed to the polar residue glutamine. The structure of the resulting Leu99Ala and Met102Gln double mutant of T4 lysozyme (L99A/M102Q) was determined and the docking calculation was repeated for the new site. Seven representative polar molecules that preferentially docked to the polar versus the apolar binding site were tested experimentally. All seven bind to the polar cavity (L99A/M102Q) but do not detectably bind to the apolar cavity (L99A). Five ligand-bound structures of L99A/M102Q were determined by X-ray crystallography. Docking predictions corresponded to the crystallographic results to within 0.4A RMSD. Improved treatment of partial atomic charges and desolvation energies in database docking appears feasible and leads to better distinction of true ligands. Simple model binding sites, such as L99A and its more polar variants, may find broad use in the development and testing of docking algorithms.     

Bi-functional cross-linking reagents efficiently capture protein-DNA complexes in Drosophila embryos

Chromatin immunoprecipitation (ChIP) is widely used for mapping DNA-protein interactions across eukaryotic genomes in cells, tissues or even whole organisms. Critical to this procedure is the efficient cross-linking of chromatin-associated proteins to DNA sequences that are in close proximity. Since the mid-nineties formaldehyde fixation has been the method of choice. However, some protein-DNA complexes cannot be successfully captured for ChIP using formaldehyde. One such formaldehyde refractory complex is the developmentally regulated insulator factor, Elba. Here we describe a new embryo fixation procedure using the bi-functional cross-linking reagents DSG (disuccinimidyl glutarate) and DSP (dithiobis[succinimidyl propionate). We show that unlike standard formaldehyde fixation protocols, it is possible to capture Elba association with insulator elements in 2–5 h embryos using this new cross-linking procedure. We show that this new cross-linking procedure can also be applied to localize nuclear proteins that are amenable to ChIP using standard formaldehyde cross-linking protocols, and that in the cases tested the enrichment was generally superior to that achieved using formaldehyde cross-linking.