Here we present version 2.0 of HADDOCK, which incorporates considerable improvements and new features. HADDOCK is now able to model not only protein–protein complexes but also other kinds of biomolecular complexes and multi‐component (N > 2) systems. In the absence of any experimental and/or predicted information to drive the docking, HADDOCK now offers two additional ab initio docking modes based on either random patch definition or center‐of‐mass restraints. The docking protocol has been considerably improved, supporting among other solvated docking, automatic definition of semi‐flexible regions, and inclusion of a desolvation energy term in the scoring scheme. The performance of HADDOCK2.0 is evaluated on the targets of rounds 4‐11, run in a semi‐automated mode using the original information we used in our CAPRI submissions. This enables a direct assessment of the progress made since the previous versions. Although HADDOCK performed very well in CAPRI (65% and 71% success rates, overall and for unbound targets only, respectively), a substantial improvement was achieved with HADDOCK2.0. Proteins 2007. © 2007 Wiley‐Liss, Inc.

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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.

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The CAPRI and CASP 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 there may be important physical chemistry missing in the energy calculations. 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 non-polar 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 non-binder.

NMR characteristics of a model left-handed 3(1)-helical peptide are reported in this study. With temperature and sequence corrections on the predicted random coil (15)N chemical shifts, a significant (15)N chemical shift deviation is observed for the model 3(1) peptide. The (15)N chemical shift differences also correlate well with the molar ellipticities (at 220 nm) of the CD spectra at different temperatures, indicating that the (15)N chemical shift is a sensitive probe for 3(1)-helices. The average (3)J(HNalpha) and (1)J(CalphaHalpha) values of the model peptide are determined to be 6.5 and 142.6 Hz, respectively, which are consistent with the values calculated from the geometry of 3(1)-helices. With careful measurements of amide (15)N chemical shifts and incorporating temperature and sequence effect corrections, the (15)N chemical shifts can be used together with (3)J(HNalpha) and (1)J(CalphaHalpha) to differentiate 3(1)-helices from random coils with high confidence. Based on the observed NMR characteristics, a strategy is developed for probing left-handed 3(1)-helical structures from other secondary structures.

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The poly-proline type II extended left-handed helical structure is well represented in proteins. In an effort to determine the helix's role in nucleic acid recognition and binding, a survey of 258 nucleic acid-binding protein structures from the Protein Data Bank was conducted. Results indicate that left-handed helices are commonly found at the nucleic acid interfacial regions. Three examples are used to illustrate the utility of this structural element as a recognition motif. The third K homology domain of NOVA-2, the Epstein-Barr nuclear antigen-1, and the Drosophila paired protein homeodomain all contain left-handed helices involved in nucleic acid interactions. In each structure, these helices were previously unidentified as left-handed helices by secondary structure algorithms but, rather, were identified as either having small amounts of hydrogen bond patterns to the rest of the protein or as being "unstructured." Proposed mechanisms for nucleic acid interactions by the extended left-handed helix include both nonspecific and specific recognition. The observed interactions indicate that this secondary structure utilizes an increase in protein backbone exposure for nucleic acid recognition. Both main-chain and side-chain atoms are involved in specific and nonspecific hydrogen bonding to nucleobases or sugar-phosphates, respectively. Our results emphasize the need to classify the left-handed helix as a viable nucleic acid recognition and binding motif, similar to previously identified motifs such as the helix-turn-helix, zinc fingers, leucine zippers, and others.