We present the results for CAPRI Round 46, the third joint CASP‐CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo‐oligomers and 6 heterocomplexes. Eight of the homo‐oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher‐order assemblies. These were more difficult to model, as their prediction mainly involved “ab‐initio” docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance “gap” was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template‐based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.

We propose an analytical substitute to the geometrical construction that is commonly used in calculating the protein surface area that is accessible to the solvent. A statistical approach leads to an expression of accessible surface areas as a function of distances between pairs of atoms or of residues in the protein structure, assuming only that these atoms or residues are randomly distributed in space but not penetrating each other. This function gives good estimates of the accessible surface area and of the area buried in subunit contacts for a number of proteins. Its evaluation is very fast, and the function can be differentiated, which opens the way to new applications of accessibility measurements in the study of proteins. As an example, we show that the presence of domains is easily detected by an automatic procedure based on surface areas only. The concept of accessible surface area, first proposed by Lee and Richards (1), has found many applications in the study of proteins (2). The accessible surface area of a protein atom is defined as the area of the surface over which a water molecule can be placed while making van der Waals contact with this atom and not penetrating any other protein atom. A geometrical construction (Fig. 1) leads to algorithms that calculate accessible surface areas from atomic coordinates derived from x-ray studies (1, 3, 4). These areas are linearly correlated to the free energies of transfer from polar to nonpolar solvents, or hydrophobic free energies, of hydrocarbons (5-8). Measurements of accessible surface areas and of area changes occurring in various biochemical processes may therefore give insights into the role of the solvent and of hydrophobicity in these processes. For instance, the evaluation of the surface area change when proteins fold (9) or associate (10) shows that hydrophobicity is the major driving factor in folding and in polymerization.Because of the complexity of protein structures and of the many atoms present, the geometrical algorithms used in measuring accessible surface areas are costly in computer time.Moreover, it would be desirable to represent the surface area as an analytical function of the atomic coordinates because the function and its derivatives could be used in minimization procedures. An increase in computing efficiency can be achieved by simplifying the protein structure and representing each amino acid residue rather than each atom of the structure by a sphere (11). We have shown that good estimates of accessible surface areas are obtained in this way, and a systematic analysis of the trypsin-pancreatic trypsin inhibitor complex was made possible by the quickness of the calculation (12), even with the algorithm of Lee and Richards.We develop here an analytical approximation to the accessible surface area, expressed as a function of interatomic distances only. The approximation is based on a statistical approach assuming that atoms or amino acid residues are randomly distributed. Measurements of accessible surface areas and of are...

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Our knowledge of metabolism can be represented as a network comprising several thousands of nodes (compounds and reactions). Several groups applied graph theory to analyse the topological properties of this network and to infer metabolic pathways by path finding. This is, however, not straightforward, with a major problem caused by traversing irrelevant shortcuts through highly connected nodes, which correspond to pool metabolites and co-factors (e.g. H2O, NADP and H+). In this study, we present a web server implementing two simple approaches, which circumvent this problem, thereby improving the relevance of the inferred pathways. In the simplest approach, the shortest path is computed, while filtering out the selection of highly connected compounds. In the second approach, the shortest path is computed on the weighted metabolic graph where each compound is assigned a weight equal to its connectivity in the network. This approach significantly increases the accuracy of the inferred pathways, enabling the correct inference of relatively long pathways (e.g. with as many as eight intermediate reactions). Available options include the calculation of the k-shortest paths between two specified seed nodes (either compounds or reactions). Multiple requests can be submitted in a queue. Results are returned by email, in textual as well as graphical formats (available in ).

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We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were