In multicellular organisms, establishing the full body plane involves cell-cell signaling where protein associations are important for the diverse cellular functions within the cells. For the study of protein-protein interactions (PPI), bimolecular fluorescence complementation (BiFC) and luciferase complementation assays (LCA) have proven to be reliable tools that can be used to confirm the physical association of two proteins in a semi-in vivo environment. This chapter provides a detailed description of these two techniques using Nicotiana benthamiana as a semi-in vivo transient expression system. As an example, we will use the interaction of the two well-described transcription factors SHORT-ROOT (SHR) and SCARECROW (SCR), which are known as regulators of asymmetric cell division and stem cell specification in the root meristem of the model plant Arabidopsis thaliana. While the BiFC assay provides subcellular information by displaying a fluorescence signal, nuclear in this case, resulting from the reconstituted fluorophore, the LCA generates a quantitative readout of the SCR-SHR interaction. The combination of both assays provides information on the localization and strength of the PPI.
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http://dx.doi.org/10.1007/978-1-0716-3327-4_12 | DOI Listing |
Sex Med
December 2024
Department of Urology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou 730030, Gansu, China.
Background: Currently, the treatment and prevention of erectile dysfunction (ED) remain highly challenging.
Aim: This study conducted a systematic druggable genome-wide Mendelian randomization (MR) analysis to identify potential therapeutic targets for ED.
Methods: A proteome-wide MR approach was employed to investigate the causal effects of plasma proteins on ED.
EXCLI J
November 2024
Department of Herbal Pharmacology, College of Korean Medicine, Gachon University, 1342 Seongnamdae-ro, Sujeong-gu, Seongnam-si, 13120, Korea.
Hepatocellular carcinoma (HCC) is the fifth leading cause of cancer related deaths globally. Despite advancements in treatment, drug resistance and adverse side effects have spurred the search for novel therapeutic strategies. This study aimed to investigate how the can inhibit key targets involved in HCC progression.
View Article and Find Full Text PDFJ Cancer Prev
December 2024
Research Institute of Pharmaceutical Sciences, College of Pharmacy, Seoul National University, Seoul, Korea.
Prolyl hydroxylase domain 2 (PHD2) is the primary oxygen sensing enzyme involved in hydroxylation of hypoxia-inducible factor (HIF). Under normoxic conditions, PHD2 hydroxylates specific proline residues in HIF-1α and HIF-2α, promoting their ubiquitination and subsequent proteasomal degradation. Although PHD2 activity decreases in hypoxia, notable residual activity persists, but its function in these conditions remains unclear Peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (Pin1) targets proteins with phosphorylated serine/threonine-proline (pSer/Thr-Pro) motifs.
View Article and Find Full Text PDFMed Res Rev
January 2025
Wuya College of Innovation, Key Laboratory of Structure-Based Drug Design & Discovery, Ministry of Education, Shenyang Pharmaceutical University, Shenyang, China.
Proteins hold pivotal importance since many diseases manifest changes in protein activity. Proteomics techniques provide a comprehensive exploration of protein structure, abundance, and function in biological samples, enabling the holistic characterization of overall changes in organisms. Nowadays, the breadth of emerging methodologies in proteomics is unprecedentedly vast, with constant optimization of technologies in sample processing, data collection, data analysis, and its scope of application is steadily transitioning from the bench to the clinic.
View Article and Find Full Text PDFExpert Rev Proteomics
January 2025
Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA.
Introduction: Molecular recognition features (MoRFs) are regions in protein sequences that undergo induced folding upon binding partner molecules. MoRFs are common in nature and can be predicted from sequences based on their distinctive sequence signatures.
Areas Covered: We overview twenty years of progress in the sequence-based prediction of MoRFs which resulted in the development of 25 predictors of MoRFs that interact with proteins, peptides and lipids.
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