An analysis of the human chromosome 22 genomic sequence shows that both Z-DNA forming regions (ZDRs) and promoter sites for nuclear factor-I (NFI) are correlated with the locations of known and predicted genes across the chromosome and accumulate around the transcriptional start sites of the known genes. Thus, the occurrence of Z-DNA across human genomic sequences mirrors that of a known eukaryotic transcription factor. In addition, 43 of the 383 fully annotated chromosomal genes have ZDRs within 2 nucleosomes upstream of strong NFIs. This suggests a distinct class of human genes that may potentially be transcriptionally regulated by a mechanism that couples Z-DNA with NFI activation, similar to the mechanism previously elucidated for the human colony stimulation factor-I promoter [Liu et al. (2001) Cell, 106, 309-318]. The results from this study will facilitate the design of experimental studies to test the generality of this mechanism for other genes in the cell.

The use of TLS (translation/libration/screw) models to describe anisotropic displacement of atoms within a protein crystal structure has become increasingly common. These models may be used purely as an improved methodology for crystallographic refinement or as the basis for analyzing inter-domain and other large-scale motions implied by the crystal structure. In either case it is desirable to validate that the crystallographic model, including the TLS description of anisotropy, conforms to our best understanding of protein structures and their modes of flexibility. A set of validation tests has been implemented that can be integrated into ongoing crystallographic refinement or run afterwards to evaluate a previously refined structure. In either case validation can serve to increase confidence that the model is correct, to highlight aspects of the model that may be improved or to strengthen the evidence supporting specific modes of flexibility inferred from the refined TLS model. Automated validation checks have been added to the PARVATI and TLSMD web servers and incorporated into the CCP4i user interface.

‘FastContact’ is a server that estimates the direct electrostatic and desolvation interaction free energy between two proteins in units of kcal/mol. Users submit two proteins in PDB format, and the output is emailed back to the user in three files: one output file, and the two processed proteins. Besides the electrostatic and desolvation free energy, the server reports residue contact free energies that rapidly highlight the hotspots of the interaction and evaluates the van der Waals interaction using CHARMm. Response time is ∼1 min. The server has been successfully tested and validated, scoring refined complex structures and blind sets of docking decoys, as well as proven useful predicting protein interactions. ‘FastContact’ offers unique capabilities from biophysical insights to scoring and identifying important contacts.

Predicting protein-protein interactions involves sampling and scoring docked conformations. Barring some large structural rearrangement, rapidly sampling the space of docked conformations is now a real possibility, and the limiting step for the successful prediction of protein interactions is the scoring function used to reduce the space of conformations from billions to a few, and eventually one high affinity complex. An atomic level free-energy scoring function that estimates in units of kcal/mol both electrostatic and desolvation interactions (plus van der Waals if appropriate) of protein-protein docked conformations is used to rerank the blind predictions (860 in total) submitted for six targets to the community-wide Critical Assessment of PRediction of Interactions (CAPRI; http://capri.ebi.ac.uk). We found that native-like models often have varying intermolecular contacts and atom clashes, making unlikely that one can construct a universal function that would rank all these models as native-like. Nevertheless, our scoring function is able to consistently identify the native-like complexes as those with the lowest free energy for the individual models of 16 (out of 17) human predictors for five of the targets, while at the same time the modelers failed to do so in more than half of the cases. The scoring of high-quality models developed by a wide variety of methods and force fields confirms that electrostatic and desolvation forces are the dominant interactions determining the bound structure. The CAPRI experiment has shown that modelers can predict valuable models of protein-protein complexes, and improvements in scoring functions should soon solve the docking problem for complexes whose backbones do not change much upon binding. A scoring server and programs are available at http://structure.pitt.edu.

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