Amyloid fibrils are formed when soluble proteins misfold into highly ordered insoluble fibrillar aggregates and affect various organs and tissues. The deposition of amyloid fibrils is the main hallmark of a group of disorders, called amyloidoses. Curiously, fibril deposition has been also recorded as a complication in a number of other pathological conditions, including well-known neurodegenerative or endocrine diseases. To date, amyloidoses are roughly classified, owing to their tremendous heterogeneity. In this work, we introduce AmyCo, a freely available collection of amyloidoses and clinical disorders related to amyloid deposition. AmyCo classifies 75 diseases associated with amyloid deposition into two distinct categories, namely 1) amyloidosis and 2) clinical conditions associated with amyloidosis. Each database entry is annotated with the major protein component (causative protein), other components of amyloid deposits and affected tissues or organs. Database entries are also supplemented with appropriate detailed annotation and are referenced to ICD-10, MeSH, OMIM, PubMed, AmyPro and UniProtKB databases. To our knowledge, AmyCo is the first attempt towards the creation of a complete and an up-to-date repository, containing information about amyloidoses and diseases related to amyloid deposition. The AmyCo web interface is available at http://bioinformatics.biol.uoa.gr/amyco.

Receptor tyrosine kinases (RTKs) form a highly important group of protein receptors of the eukaryotic cell membrane. They control many vital cellular functions and are involved in the regulation of complex signaling networks. Mutations in RTKs have been associated with different types of cancers and other diseases. Although they are very important for proper cell function, they have been experimentally studied in a limited range of eukaryotic species. Currently, there is no available database for RTKs providing information about their function, expression, and interactions. Therefore, the identification of RTKs in multiple organisms, the documentation of their characteristics, and the collection of related information would be very useful. In this paper, we present a novel RTK detection pipeline (RTK-PRED) and the Receptor Tyrosine Kinases Database (TyReK-DB). RTK-PRED combines profile HMMs with transmembrane topology prediction to identify and classify potential RTKs. Proteins of all eukaryotic reference proteomes of the UniProt database were used as input in RTK-PRED leading to a filtered dataset of 20,478 RTKs. Based on the information collected for these RTKs from multiple databases, the relational TyReK database was created.

The nuclear envelope (NE) is a double-membrane system surrounding the nucleus of eukaryotic cells. A large number of proteins are localized in the NE, performing a wide variety of functions, from the bidirectional exchange of molecules between the cytoplasm and the nucleus to chromatin tethering, genome organization, regulation of signaling cascades, and many others. Despite its importance, several aspects of the NE, including its protein–protein interactions, remain understudied. In this work, we present NucEnvDB, a publicly available database of NE proteins and their interactions. Each database entry contains useful annotation including a description of its position in the NE, its interactions with other proteins, and cross-references to major biological repositories. In addition, the database provides users with a number of visualization and analysis tools, including the ability to construct and visualize protein–protein interaction networks and perform functional enrichment analysis for clusters of NE proteins and their interaction partners. The capabilities of NucEnvDB and its analysis tools are showcased by two informative case studies, exploring protein–protein interactions in Hutchinson–Gilford progeria and during SARS-CoV-2 infection at the level of the nuclear envelope.

Alzheimer’s disease (AD) affects an increasing number of people as the human population ages. The main pathological feature of AD, amyloid plaques, consists of the key protein amyloid-β and other co-deposited proteins. These co-deposited proteins and their protein interactors could hold some additional functional insights into AD pathophysiology. For this work, proteins found on amyloid plaques were collected from the AmyCo database. A protein–protein and protein–drug interaction network was constructed with data from the IntAct and DrugBank databases, respectively. In total, there were 12 proteins co-deposited on amyloid plaques that reportedly interact with 513 other proteins and are targets of 72 drugs. These drugs were shown to be almost entirely distinct from the panel of drugs currently approved by the FDA for AD and their corresponding protein targets. In conclusion, this work demonstrates the potential for drug repurposing of drugs that target proteins found in amyloid plaques.

Background: Exosomes are a group of extracellular vesicles that are released by almost all mammalian cell types and engage in intracellular communication. Studies conducted in recent years have shown that exosomes are involved in a variety of diseases, where they may act as “vehicles” for the transmission of biomolecules and biomolecular information. Amyloidoses constitute a critical subgroup of these diseases, caused by extracellular deposition or intracellular inclusions of insoluble protein fibrils in cells and tissues. However, how exosomes are involved in these diseases remains largely unexplored. Methods: To detect possible links between amyloid proteins and exosomes, protein data from amyloidosis-isolated exosomes were collected and visualized using biological networks. Results: This biomedical informatics approach for the analysis of interaction networks, in combination with the existing literature, highlighted the involvement of exosomes in amyloidosis while strengthening existing hypotheses regarding their mechanism of action. Conclusion: This work is focused on exosomes from patients with Alzheimer’s disease and identifies important amyloidogenic proteins found in exosomes. These proteins can be used for future research in the field of exosome-based biomarkers of amyloidosis and potential prognostic or preventive approaches.