Summary: Herein we present COCOMAPS, a novel tool for analyzing, visualizing and comparing the interface in protein–protein and protein–nucleic acids complexes. COCOMAPS combines traditional analyses and 3D visualization of the interface with the effectiveness of intermolecular contact maps. Availability: COCOMAPS is accessible as a public web tool at http://www.molnac.unisa.it/BioTools/cocomaps Contact:romina.oliva@uniparthenope.it; lcavallo@unisa.it

We present the results for CAPRI Round 30, the first joint CASP‐CAPRI experiment, which brought together experts from the protein structure prediction and protein–protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact‐sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology‐built subunit models and the smaller pair‐wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323–348. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Tertiary interactions are crucial in maintaining the tRNA structure and functionality. We used a combined sequence analysis and quantum mechanics approach to calculate accurate energies of the most frequent tRNA tertiary base pairing interactions. Our analysis indicates that six out of the nine classical tertiary interactions are held in place mainly by H-bonds between the bases. In the remaining three cases other effects have to be considered. Tertiary base pairing interaction energies range from −8 to −38 kcal/mol in yeast tRNA^Phe and are estimated to contribute roughly 25% of the overall tRNA base pairing interaction energy. Six analyzed posttranslational chemical modifications were shown to have minor effect on the geometry of the tertiary interactions. Modifications that introduce a positive charge strongly stabilize the corresponding tertiary interactions. Non-additive effects contribute to the stability of base triplets.

The G15–C48 Levitt base pair, located at a crucial position in the core of canonical tRNAs, assumes a reverse Watson–Crick (RWC) geometry. By means of bioinformatics analysis and quantum mechanics calculations we show here that such a geometry is moderately more stable than an alternative bifurcated trans geometry, involving the guanine Watson–Crick face and the cytosine keto group, which we have also found in known RNA structures. However we also demonstrate that the RWC geometry can take advantage of additional stabilizing effects such as metal binding or post-transcriptional chemical modification. One of the few strong metal binding sites characterized for cytosolic tRNAs is localized on G15, and a domain-specific complex modification known as archaeosine is widespread at position 15 in archaeal tRNAs. We have found that both the bound Mg²⁺ ion and the archaeosine modification induce an analogous electron density redistribution, which results in an effective stabilization of the RWC geometry. Metal binding and chemical modification thus play an interchangeable role in stabilizing the G15–C48 correct geometry. Interestingly, these different but convergent strategies are selectively adopted in the different life domains.