Over the past few decades, the number of available structural bioinformatics pipelines, libraries, plugins, web resources and software has increased exponentially and become accessible to the broad realm of life scientists. This expansion has shaped the field as a tangled network of methods, algorithms and user interfaces. In recent years PyMOL, widely used software for biomolecules visualization and analysis, has started to play a key role in providing an open platform for the successful implementation of expert knowledge into an easy-to-use molecular graphics tool. This review outlines the plugins and features that make PyMOL an eligible environment for supporting structural bioinformatics analyses.
Motivation The primary strategy for predicting the binding mode of small molecules to their receptors and for performing receptor-based virtual screening studies is protein-ligand docking, which is undoubtedly the most popular and successful approach in computer-aided drug discovery. The increased popularity of docking has resulted in the development of different docking algorithms and scoring functions. Nonetheless, it is unlikely that a single approach outperforms the others in terms of reproducibility and precision. In this ground, consensus docking techniques are taking hold. Results We have developed DockingPie, an open source PyMOL plugin for individual, as well as consensus docking analyses. Smina, AutoDock Vina, ADFR, and RxDock are the four docking engines that DockingPie currently supports in an easy and extremely intuitive way, thanks to its integrated docking environment and its GUI, fully integrated within PyMOL. Availability https://github.com/paiardin/DockingPie Supplementary information Supplementary data are available at Bioinformatics online.
Protein–peptide interactions (PpIs) are a subset of the overall protein–protein interaction (PPI) network in the living cell and are pivotal for the majority of cell processes and functions. High-throughput methods to detect PpIs and PPIs usually require time and costs that are not always affordable. Therefore, reliable in silico predictions represent a valid and effective alternative. In this work, a new algorithm is described, implemented in a freely available tool, i.e., “PepThreader”, to carry out PPIs and PpIs prediction and analysis. PepThreader threads multiple fragments derived from a full-length protein sequence (or from a peptide library) onto a second template peptide, in complex with a protein target, “spotting” the potential binding peptides and ranking them according to a sequence-based and structure-based threading score. The threading algorithm first makes use of a scoring function that is based on peptides sequence similarity. Then, a rerank of the initial hits is performed, according to structure-based scoring functions. PepThreader has been benchmarked on a dataset of 292 protein–peptide complexes that were collected from existing databases of experimentally determined protein–peptide interactions. An accuracy of 80%, when considering the top predicted 25 hits, was achieved, which performs in a comparable way with the other state-of-art tools in PPIs and PpIs modeling. Nonetheless, PepThreader is unique in that it is able at the same time to spot a binding peptide within a full-length sequence involved in PPI and model its structure within the receptor. Therefore, PepThreader adds to the already-available tools supporting the experimental PPIs and PpIs identification and characterization.
The translation factor IF6 is a protein of about 25 kDa shared by the Archaea and the Eukarya but absent in Bacteria. It acts as a ribosome anti-association factor that binds to the large subunit preventing the joining to the small subunit. It must be released from the large ribosomal subunit to permit its entry to the translation cycle. In Eukarya, this process occurs by the coordinated action of the GTPase Efl1 and the docking protein SBDS. Archaea do not possess a homolog of the former factor while they have a homolog of SBDS. In the past, we have determined the function and ribosomal localization of the archaeal (Sulfolobus solfataricus) IF6 homolog (aIF6) highlighting its similarity to the eukaryotic counterpart. Here, we analyzed the mechanism of aIF6 release from the large ribosomal subunit. We found that, similarly to the Eukarya, the detachment of aIF6 from the 50S subunit requires a GTPase activity which involves the archaeal elongation factor 2 (aEF-2). However, the release of aIF6 from the 50S subunits does not require the archaeal homolog of SBDS, being on the contrary inhibited by its presence. Molecular modeling, using published structural data of closely related homologous proteins, elucidated the mechanistic interplay between the aIF6, aSBDS, and aEF2 on the ribosome surface. The results suggest that a conformational rearrangement of aEF2, upon GTP hydrolysis, promotes aIF6 ejection. On the other hand, aSBDS and aEF2 share the same binding site, whose occupation by SBDS prevents aEF2 binding, thereby inhibiting aIF6 release.
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