Evgeny Krissinel

The assumption that crystal contacts reflect natural macromolecular interactions makes a basis for many studies in structural biology. However, the crystal state may correspond to a global minimum of free energy where biologically relevant interactions are sacrificed in favor to unspecific contacts. A large-scale docking experiment was performed to assess the extent of misrepresentation of natural (in-solvent) protein dimers by crystal packing. As found, the failure rate of docking may be quantitatively interpreted if both calculation errors and misrepresentation effects are taken into account. The failure rate analysis is based on the assumption that crystal structures reflect thermodynamic equilibrium between different dimeric configurations. The analysis gives an estimate of misrepresentation probability, which suggests that weakly bound complexes with K(D) > or = 100 microM (some 20% of all dimers in the PDB) have higher than 50% chances to be misrepresented by crystals. The developed theoretical framework is applicable in other studies, where experimental results may be viewed as snapshots of systems in thermodynamic equilibrium.

The main structure aligner in the CCP4 Software Suite, SSM (Secondary Structure Matching) has a limited applicability on the intermediate stages of the structure solution process, when the secondary structure cannot be reliably computed due to structural incompleteness or a fragmented mainchain. In this study, we describe a new algorithm for the alignment and comparison of protein structures in CCP4, which was designed to overcome SSM's limitations but retain its quality and speed. The new algorithm, named GESAMT (General Efficient Structural Alignment of Macromolecular Targets), employs the old idea of deriving the global structure similarity from a promising set of locally similar short fragments, but uses a few technical solutions that make it considerably faster. A comparative sensitivity and selectivity analysis revealed an unexpected significant improvement in the fold recognition properties of the new algorithm, which also makes it useful for applications in the structural bioinformatics domain. The new tool is included in the CCP4 Software Suite starting from version 6.3.

MOTIVATION: The underlying assumption of many sequence-based comparative studies in proteomics is that different aspects of protein structure and therefore functionality may be linked to particular sequence motifs. This holds true if sequence similarity is sufficiently high, but in general the relationship between protein sequence and structure appears complex and is not well understood. RESULTS: Statistical analysis of multiple and pairwise structural alignments of protein structures within SCOP folds is performed. The results indicate that multiple conservation of residue identity is not common and that relationship between sequence and structure may be explained by a model based on the assumption that protein structure is tolerant to residue substitutions preserving hydropathic profile of the sequence. This model also explains the origin and specific value of the sequence similarity threshold, noticed in many previous studies, below which structural resemblance is not statistically expected.