Francesco Tabaro

The Database of Protein Disorder (DisProt, URL: www.disprot.org) has been significantly updated and upgraded since its last major renewal in 2007. The current release holds information on more than 800 entries of IDPs/IDRs, i.e. intrinsically disordered proteins or regions that exist and function without a well-defined three-dimensional structure. We have re-curated previous entries to purge DisProt from conflicting cases, and also upgraded the functional classification scheme to reflect continuous advance in the field in the past 10 years or so. We define IDPs as proteins that are disordered along their entire sequence, i.e. entirely lack structural elements, and IDRs as regions that are at least five consecutive residues without well-defined structure. We base our assessment of disorder strictly on experimental evidence, such as X-ray crystallography and nuclear magnetic resonance (primary techniques) and a broad range of other experimental approaches (secondary techniques). Confident and ambiguous annotations are highlighted separately. DisProt 7.0 presents classified knowledge regarding the experimental characterization and functional annotations of IDPs/IDRs, and is intended to provide an invaluable resource for the research community for a better understanding structural disorder and for developing better computational tools for studying disordered proteins.

The MobiDB (URL: mobidb.bio.unipd.it) database of protein disorder and mobility annotations has been significantly updated and upgraded since its last major renewal in 2014. Several curated datasets for intrinsic disorder and folding upon binding have been integrated from specialized databases. The indirect evidence has also been expanded to better capture information available in the PDB, such as high temperature residues in X-ray structures and overall conformational diversity. Novel nuclear magnetic resonance chemical shift data provides an additional experimental information layer on conformational dynamics. Predictions have been expanded to provide new types of annotation on backbone rigidity, secondary structure preference and disordered binding regions. MobiDB 3.0 contains information for the complete UniProt protein set and synchronization has been improved by covering all UniParc sequences. An advanced search function allows the creation of a wide array of custom-made datasets for download and further analysis. A large amount of information and cross-links to more specialized databases are intended to make MobiDB the central resource for the scientific community working on protein intrinsic disorder and mobility.

MOTIVATION: Eukaryotic cells contain different membrane-delimited compartments, which are crucial for the biochemical reactions necessary to sustain cell life. Recent studies showed that cells can also trigger the formation of membraneless organelles composed by phase-separated proteins to respond to various stimuli. These condensates provide new ways to control the reactions and phase-separation proteins (PSPs) are thus revolutionizing how cellular organization is conceived. The small number of experimentally validated proteins, and the difficulty in discovering them, remain bottlenecks in PSPs research. RESULTS: Here we present PSPer, the first in-silico screening tool for prion-like RNA-binding PSPs. We show that it can prioritize PSPs among proteins containing similar RNA-binding domains, intrinsically disordered regions and prions. PSPer is thus suitable to screen proteomes, identifying the most likely PSPs for further experimental investigation. Moreover, its predictions are fully interpretable in the sense that it assigns specific functional regions to the predicted proteins, providing valuable information for experimental investigation of targeted mutations on these regions. Finally, we show that it can estimate the ability of artificially designed proteins to form condensates (r=-0.87), thus providing an in-silico screening tool for protein design experiments. AVAILABILITY AND IMPLEMENTATION: PSPer is available at bio2byte.com/psp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

iCn3D was initially developed as a web-based 3D molecular viewer. It then evolved from visualization into a full-featured interactive structural analysis software. It became a collaborative research instrument through the sharing of permanent, shortened URLs that encapsulate not only annotated visual molecular scenes, but also all underlying data and analysis scripts in a FAIR manner. More recently, with the growth of structural databases, the need to analyze large structural datasets systematically led us to use Python scripts and convert the code to be used in Node. js scripts. We showed a few examples of Python scripts at https://github.com/ncbi/icn3d/tree/master/icn3dpython to export secondary structures or PNG images from iCn3D. Users just need to replace the URL in the Python scripts to export other annotations from iCn3D. Furthermore, any interactive iCn3D feature can be converted into a Node. js script to be run in batch mode, enabling an interactive analysis performed on one or a handful of protein complexes to be scaled up to analysis features of large ensembles of structures. Currently available Node. js analysis scripts examples are available at https://github.com/ncbi/icn3d/tree/master/icn3dnode . This development will enable ensemble analyses on growing structural databases such as AlphaFold or RoseTTAFold on one hand and Electron Microscopy on the other. In this paper, we also review new features such as DelPhi electrostatic potential, 3D view of mutations, alignment of multiple chains, assembly of multiple structures by realignment, dynamic symmetry calculation, 2D cartoons at different levels, interactive contact maps, and use of iCn3D in Jupyter Notebook as described at https://pypi.org/project/icn3dpy .