Signaling pathways are responsible for transmitting information between cells and regulating cell growth, differentiation, and death. Proteins in cells form complexes by interacting with each other through specific structural domains, playing a crucial role in various biological functions and cell signaling pathways. Protein-protein interactions (PPIs) within cell signaling pathways are essential for signal transmission and regulation. The spatiotemporal features of PPIs in signaling pathways are crucial for comprehending the regulatory mechanisms of signal transduction. Bimolecular fluorescence complementation (BiFC) is one kind of imaging tool for the direct visualization of PPIs in living cells and has been widely utilized to uncover novel PPIs in various organisms. BiFC demonstrates significant potential for application in various areas of biological research, drug development, disease diagnosis and treatment, and other related fields. This review systematically summarizes and analyzes the technical advancement of BiFC and its utilization in elucidating PPIs within established cell signaling pathways, including TOR, PI3K/Akt, Wnt/β-catenin, NF-κB, and MAPK. Additionally, it explores the application of this technology in revealing PPIs within the plant hormone signaling pathways of ethylene, auxin, Gibberellin, and abscisic acid. Using BiFC in conjunction with CRISPR-Cas9, live-cell imaging, and ultra-high-resolution microscopy will enhance our comprehension of PPIs in cell signaling pathways.

Technological advances in high-throughput techniques have resulted in tremendous growth of complex biological datasets providing evidence regarding various biomolecular interactions. To cope with this data flood, computational approaches, web services, and databases have been implemented to deal with issues such as data integration, visualization, exploration, organization, scalability, and complexity. Nevertheless, as the number of such sets increases, it is becoming more and more difficult for an end user to know what the scope and focus of each repository is and how redundant the information between them is. Several repositories have a more general scope, while others focus on specialized aspects, such as specific organisms or biological systems. Unfortunately, many of these databases are self-contained or poorly documented and maintained. For a clearer view, in this article we provide a comprehensive categorization, comparison and evaluation of such repositories for different bioentity interaction types. We discuss most of the publicly available services based on their content, sources of information, data representation methods, user-friendliness, scope and interconnectivity, and we comment on their strengths and weaknesses. We aim for this review to reach a broad readership varying from biomedical beginners to experts and serve as a reference article in the field of Network Biology.

Chronic obstructive pulmonary disease (COPD) is a chronic respiratory disease characterized by incompletely reversible airflow limitation and seriously threatens the health of humans due to its high morbidity and mortality. Naringenin, as a natural flavanone, has shown various potential pharmacological activities against multiple pathological stages of COPD, but available studies are scattered and unsystematic. Thus, we combined literature review with network pharmacology analysis to evaluate the potential therapeutic effects of naringenin on COPD and predict its underlying mechanisms, expecting to provide a promising tactic for clinical treatment of COPD.

The human ether-à-go-go related gene (HERG) encodes the alpha subunit of Kv11.1, which is a voltage-gated K+ channel protein mainly expressed in heart and brain tissue. HERG plays critical role in cardiac repolarization, and mutations in HERG can cause long QT syndrome. More recently, evidence has emerged that HERG channels are aberrantly expressed in many kinds of cancer cells and play important roles in cancer progression. HERG could therefore be a potential biomarker for cancer and a possible molecular target for anticancer drug design. HERG affects a number of cellular processes, including cell proliferation, apoptosis, angiogenesis and migration, any of which could be affected by dysregulation of HERG. This review provides an overview of available information on HERG channel as it relates to cancer, with focus on the mechanism by which HERG influences cancer progression. Molecular docking attempts suggest two possible protein-protein interactions of HERG with the ß1-integrin receptor and the transcription factor STAT-1 as novel HERG-directed therapeutic targeting which avoids possible cardiotoxicity. The role of epigenetics in regulating HERG channel expression and activity in cancer will also be discussed. Finally, given its inherent extracellular accessibility as an ion channel, we discuss regulatory roles of this molecule in cancer physiology and therapeutic potential. Future research should be directed to explore the possibilities of therapeutic interventions targeting HERG channels while minding possible complications.

The paper focuses on intermolecular interactions, particularly interactions between proteins and natural intermediates (small molecules). Molecules with a molecular weight of up to 1000 Da are free in cytoplasmic solution and form a pool of intermediates. Methods of computer modeling for prediction of protein-proteinaceous, protein-ligand, protein - a small molecule of interactions are presented. The program for modeling predicted biological activity in silico is Prediction of Activity Spectrum for Substances (PASS). In the Search Tool for Interacting Chemicals (STITCH) system, it is possible to identify potential protein interaction partners for small molecules. A review of the literature presents modern data on small molecules - metabolic switches, such as α-glycerophosphatedihydroxyacetone phosphate, pyruvate-lactate, oxaloacetate-malate. The molecules we study have different and multiple effects on metabolism and on intercellular interaction systems. Natural intermediates are at the intersection of metabolic pathways of metabolism of proteins, carbohydrates, lipids; they are signal molecules, participate in regulation of protein function, gene expression, enzyme activity. An increasing interest in deciphering protein-small molecule/metabolite interactions at the systemic level will lay a conceptual foundation that provides insight into complex epigenetic regulation under various environmental influences. A complete interplay, including a protein-small molecule interaction, will be crucial to eventually unraveling the complex relationships between the genotype and phenotype and to provide a deeper understanding of health and disease.

Network medicine is a rapidly evolving new field of medical research, which combines principles and approaches of systems biology and network science, holding the promise to uncovering the causes and to revolutionize the diagnosis and treatments of human diseases. This new paradigm reflects the fact that human diseases are not caused by single molecular defects, but driven by complex interactions among a variety of molecular mediators. The complexity of these interactions embraces different types of information: from the cellular-molecular level of protein-protein interactions to correlational studies of gene expression and regulation, to metabolic and disease pathways up to drug-disease relationships. The analysis of these complex networks can reveal new disease genes and/or disease pathways and identify possible targets for new drug development, as well as new uses for existing drugs. In this review, we offer a comprehensive overview of network types and algorithms used in the framework of network medicine. This article is part of a Special Issue entitled: Transcriptional Profiles and Regulatory Gene Networks edited by Dr. Dr. Federico Manuel Giorgi and Dr. Shaun Mahony.

Computational analysis of biomolecular interaction networks is now gaining a lot of importance to understand the functions of novel genes/proteins. Gene interaction (GI) network analysis and protein-protein interaction (PPI) network analysis play a major role in predicting the functionality of interacting genes or proteins and gives an insight into the functional relationships and evolutionary conservation of interactions among the genes. An interaction network is a graphical representation of gene/protein interactome, where each gene/protein is a node, and interaction between gene/protein is an edge. In this review, we discuss the popular open source databases that serve as data repositories to search and collect protein/gene interaction data, and also tools available for the generation of interaction network, visualization and network analysis. Also, various network analysis approaches like topological approach and clustering approach to study the network properties and functional enrichment server which illustrates the functions and pathway of the genes and proteins has been discussed. Hence the distinctive attribute mentioned in this review is not only to provide an overview of tools and web servers for gene and protein-protein interaction (PPI) network analysis but also to extract useful and meaningful information from the interaction networks.

Hematopoietic progenitor kinase 1 (HPK1), also known as mitogen‑activated protein kinase kinase kinase kinase 1 is a serine/threonine protein kinase. It is involved in various cellular events, including mitogen‑activated protein kinase signaling, nuclear factor‑κB signaling, cytokine signaling, cellular proliferation and apoptosis, T cell receptor/B cell receptor signaling and T/B/dendritic cell‑mediated immune responses. Therefore, HPK1 has variety of roles in immunity, and is associated with the pathogenesis of autoimmune diseases, cancer, and the inflammatory response. In these cellular and immune events, HPK1 interacts with several adaptor proteins, including caspase recruitment domain family, member 11, hematopoietic cell‑specific protein 1, HPK1‑interacting protein of 55 kDa, the growth factor receptor‑bound protein 2 family, linker for activated T‑cells, the SH2 domain‑containing leukocyte protein of 76 kDa family, the v‑crk avian sarcoma virus CT10 oncogene homolog family, B‑cell adaptor molecule of 32 kDa and non‑catalytic region of tyrosine kinase adaptor protein. These adaptor proteins can couple HPK1 with various effector molecules, leading to the transmission of upstream signals to downstream targets. They are crucial in regulating the relocation, phosphorylation, activation and functions of HPK1. HPK1 can also phosphorylate certain proteins, consequently modulating their functions. This review aims to describe the adaptor proteins, which interact with HPK1, particularly focusing on their modes of interaction with HPK1, and the effects that these interactions cause.

Histone lysine-specific demethylase 1 (LSD1) is the first discovered and reported histone demethylase by Dr. Shi Yang\'s group in 2004. It is classified as a member of amine oxidase superfamily, the common feature of which is using the flavin adenine dinucleotide (FAD) as its cofactor. Since it is located in cell nucleus and acts as a histone methylation eraser, LSD1 specifically removes mono- or dimethylated histone H3 lysine 4 (H3K4) and H3 lysine 9 (H3K9) through formaldehyde-generating oxidation. It has been indicated that LSD1 and its downstream targets are involved in a wide range of biological courses, including embryonic development and tumor-cell growth and metastasis. LSD1 has been reported to be overexpressed in variety of tumors. Inactivating LSD1 or downregulating its expression inhibits cancer-cell development. LSD1 targeting inhibitors may represent a new insight in anticancer drug discovery. This review summarizes recent studies about LSD1 and mainly focuses on the basic physiological function of LSD1 and its involved mechanisms in pathophysiologic conditions, as well as the development of LSD1 inhibitors as potential anticancer therapeutic agents.

This review highlights discoveries made using phage display that impact the use of agricultural products. The contribution phage display made to our fundamental understanding of how various protective molecules serve to safeguard plants and seeds from herbivores and microbes is discussed. The utility of phage display for directed evolution of enzymes with enhanced capacities to degrade the complex polymers of the cell wall into molecules useful for biofuel production is surveyed. Food allergies are often directed against components of seeds; this review emphasizes how phage display has been employed to determine the seed component(s) contributing most to the allergenic reaction and how it has played a central role in novel approaches to mitigate patient response. Finally, an overview of the use of phage display in identifying the mature seed proteome protection and repair mechanisms is provided. The identification of specific classes of proteins preferentially bound by such protection and repair proteins leads to hypotheses concerning the importance of safeguarding the translational apparatus from damage during seed quiescence and environmental perturbations during germination. These examples, it is hoped, will spur the use of phage display in future plant science examining protein-ligand interactions.