ATLAS: protein flexibility description from atomistic molecular dynamics simulations.

Dynamical behaviour is one of the most crucial protein characteristics. Despite the advances in the field of protein structure resolution and prediction, analysis and prediction of protein dynamic properties remains a major challenge, mostly due to the low accessibility of data and its diversity and heterogeneity. To address this issue, we present ATLAS, a database of standardised all-atom molecular dynamics simulations, accompanied by their analysis in the form of interactive diagrams and trajectory visualisation. ATLAS offers a large-scale view and valuable insights on protein dynamics for a large and representative set of proteins, by combining data obtained through molecular dynamics simulations with information extracted from experimental structures. Users can easily analyse dynamic properties of functional protein regions, such as domain limits (hinge positions) and residues involved in interaction with other biological molecules. Additionally, the database enables exploration of proteins with uncommon dynamic properties conditioned by their environment such as chameleon subsequences and Dual Personality Fragments. The ATLAS database is freely available at https://www.dsimb.inserm.fr/ATLAS.

DIONYSUS: a database of protein-carbohydrate interfaces.

Protein-carbohydrate interactions govern a wide variety of biological processes and play an essential role in the development of different diseases. Here, we present DIONYSUS, the first database of protein-carbohydrate interfaces annotated according to structural, chemical and functional properties of both proteins and carbohydrates. We provide exhaustive information on the nature of interactions, binding site composition, biological function and specific additional information retrieved from existing databases. The user can easily search the database using protein sequence and structure information or by carbohydrate binding site properties. Moreover, for a given interaction site, the user can perform its comparison with a representative subset of non-covalent protein-carbohydrate interactions to retrieve information on its potential function or specificity. Therefore, DIONYSUS is a source of valuable information both for a deeper understanding of general protein-carbohydrate interaction patterns, for annotation of the previously unannotated proteins and for such applications as carbohydrate-based drug design. DIONYSUS is freely available at www.dsimb.inserm.fr/DIONYSUS/.

Poincaré maps for visualization of large protein families.

In the era of constantly increasing amounts of the available protein data, a relevant and interpretable visualization becomes crucial, especially for tasks requiring human expertise. Poincaré disk projection has previously demonstrated its important efficiency for visualization of biological data such as single-cell RNAseq data. Here, we develop a new method PoincaréMSA for visual representation of complex relationships between protein sequences based on Poincaré maps embedding. We demonstrate its efficiency and potential for visualization of protein family topology as well as evolutionary and functional annotation of uncharacterized sequences. PoincaréMSA is implemented in open source Python code with available interactive Google Colab notebooks as described at https://www.dsimb.inserm.fr/POINCARE_MSA.

SWORD2: hierarchical analysis of protein 3D structures.

Understanding the functions and origins of proteins requires splitting these macromolecules into fragments that could be independent in terms of folding, activity, or evolution. For that purpose, structural domains are the typical level of analysis, but shorter segments, such as subdomains and supersecondary structures, are insightful as well. Here, we propose SWORD2, a web server for exploring how an input protein structure may be decomposed into 'Protein Units' that can be hierarchically assembled to delimit structural domains. For each partitioning solution, the relevance of the identified substructures is estimated through different measures. This multilevel analysis is achieved by integrating our previous work on domain delineation, 'protein peeling' and model quality assessment. We hope that SWORD2 will be useful to biologists searching for key regions in their proteins of interest and to bioinformaticians building datasets of protein structures. The web server is freely available online: https://www.dsimb.inserm.fr/SWORD2.

MEDUSA: Prediction of Protein Flexibility from Sequence.

Information on the protein flexibility is essential to understand crucial molecular mechanisms such as protein stability, interactions with other molecules and protein functions in general. B-factor obtained in the X-ray crystallography experiments is the most common flexibility descriptor available for the majority of the resolved protein structures. Since the gap between the number of the resolved protein structures and available protein sequences is continuously growing, it is important to provide computational tools for protein flexibility prediction from amino acid sequence. In the current study, we report a Deep Learning based protein flexibility prediction tool MEDUSA (https://www.dsimb.inserm.fr/MEDUSA). MEDUSA uses evolutionary information extracted from protein homologous sequences and amino acid physico-chemical properties as input for a convolutional neural network to assign a flexibility class to each protein sequence position. Trained on a non-redundant dataset of X-ray structures, MEDUSA provides flexibility prediction in two, three and five classes. MEDUSA is freely available as a web-server providing a clear visualization of the prediction results as well as a standalone utility (https://github.com/DSIMB/medusa). Analysis of the MEDUSA output allows a user to identify the potentially highly deformable protein regions and general dynamic properties of the protein.