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Biomedical research benefits from the rapid growth and diversity of experimentally detected protein–protein interactions (PPIs) by gaining important biological insights. However, increasingly dense PPI networks can be challenging to interpret and apply. The 2025 update of the Integrated Interactions Database (IID) enhances accessibility and utility through several new features. We identify and incorporate network structural components from co-purified protein sets, as well as curated and predicted complexes, enabling users to explore network organization Show less

Claudin (CLDN) proteins are extensively studied due to their critical role in maintaining tissue barriers and cell polarity. However, significant gaps remain in understanding the functional mechanisms of their sequence motifs and the molecular mechanisms of their interactions with other tight junction proteins. This review systematically examines the multifunctional properties of the CLDN protein family from the perspectives of sequence and structure. During evolution, CLDN family members have developed highly conserved structural features, particularly key conserved sites within the first Show less

Deep learning, a cornerstone of artificial intelligence, is driving rapid advancements in computational biology. Protein-protein interactions (PPIs) are fundamental regulators of biological functions. With the inclusion of deep learning in PPI research, the field is undergoing transformative changes. Therefore, there is an urgent need for a comprehensive review and assessment of recent developments to improve analytical methods and open up a wider range of biomedical applications. This review meticulously assesses deep learning progress in PPI prediction from 2021 Show less

The versatility of cellular response arises from the communication, or crosstalk, of signaling pathways in a complex network of signaling and transcriptional regulatory interactions. Understanding the various mechanisms underlying crosstalk on a global scale requires untargeted computational approaches. We present a network-based statistical approach, MuXTalk, that uses high-dimensional edges called multilinks to model the unique ways in which signaling and regulatory interactions can interface. We demonstrate that the signaling-regulatory interface is located Show less

The Nrf2 transcription factor governs the expression of hundreds genes involved in cell defense against oxidative stress, the hallmark of numerous diseases such as neurodegenerative, cardiovascular, some viral pathologies, diabetes and others. The main route for Nrf2 activity regulation is via interactions with the Keap1 protein. Under the normoxia the Keap1 binds the Nrf2 and targets it to the proteasomal degradation, while the Keap1 is regenerated. Upon oxidative stress the interactions between Nrf2 and Keap1 are interrupted and the Nrf2 activates the transcription of the protective genes. Currently, the Nrf2 system activation is considered as a powerful cytoprotective strategy for treatment of different pathologies, which pathogenesis relies on oxidative stress including viral diseases of pivotal importance such as COVID-19. The implementation of this strategy is accomplished mainly through the inactivation of the Keap1 "guardian" function. Two approaches are now developing: the Keap1 modification via electrophilic agents, which leads to the Nrf2 release, and direct interruption of the Nrf2:Keap1 protein-protein interactions (PPI). Because of theirs chemical structure, the Nrf2 electrophilic inducers could non-specifically interact with others cellular proteins leading to undesired effects. Whereas the non-electrophilic inhibitors of the Nrf2:Keap1 PPI could be more specific, thereby widening the therapeutic window. Show less

IID (Integrated Interactions Database) is the first database providing tissue-specific protein–protein interactions (PPIs) for model organisms and human. IID covers six species (S. cerevisiae (yeast), C. elegans (worm), D. melonogaster (fly), R. norvegicus (rat), M. musculus (mouse) and H. sapiens (human)) and up to 30 tissues per species. Users query IID by providing a set of proteins or PPIs from any of these organisms, and specifying species and tissues where IID should search for interactions. If query proteins are not from the selected species, IID enables Show less