ZWINT antibody
- Known as:
- ZWINT (anti-)
- Catalog number:
- orb100450
- Product Quantity:
- EUR
- Category:
- -
- Supplier:
- Biorbyt biorb
- Gene target:
- ZWINT antibody
Related genes to: ZWINT antibody
- Gene:
- ZWINT NIH gene
- Name:
- ZW10 interacting kinetochore protein
- Previous symbol:
- -
- Synonyms:
- KNTC2AP, SIP30, Zwint1
- Chromosome:
- 10q21.1
- Locus Type:
- gene with protein product
- Date approved:
- 2001-06-22
- Date modifiied:
- 2018-04-13
Related products to: ZWINT antibody
Related articles to: ZWINT antibody
- Protein-protein interactions (PPIs) underpin most cellular processes, and disruptions to these interactions can lead to cellular dysfunction and disease. Understanding PPIs is essential for studying disease mechanisms, yet traditional experimental approaches are time- and labor-intensive. Recent advances in AI-based structural prediction tools, including AlphaFold2 and RoseTTAFold2, now enable efficient exploration of potential PPIs. To develop an integrated and practical multi-tool system for PPI investigation, we present a dual-arm computational pipeline centered on the ZWINT (SIP30) kinetochore protein, which we identified as a key gene in neuropathic signaling. The first arm of the workflow generates PPI models using AlphaFold2 and RoseTTAFold2 and evaluates model consistency using TM-Align. The second arm assesses binding affinity by identifying interface residues with PyMOL and calculating docking scores with HADDOCK. Together, these methods provide both quantitative and qualitative evaluations of candidate PPIs. Using this framework, we examined three established interactors (SNAP25, CAMK2A, UBC) and four exploratory proteins (STX1A, VCP, BLOC1S2, ARC) in combination with ZWINT. This study demonstrates that AI-supported analysis can streamline PPI discovery by prioritizing biologically plausible interactors and guiding downstream experimental validation. - Source: PubMed
Publication date: 2026/04/30
Abdelfattah NoraBroncales BridgetAlbert IvanaKohan JaimeeYu Lei - Subcellular RNA localization is a fundamental layer of gene regulation, yet its heterogeneity across individual cells remains poorly understood. Here, we introduce the RNA Localization Profiler (RLP), a proximity-based RNA-editing strategy that maps compartment-specific RNAs in living cells. Across the cytoplasm, endoplasmic reticulum (ER), and plasma membrane, RLP identifies robust and highly specific RNA localization programs linked to translation and membrane organization. Single-cell RLP (scRLP) reveals that individual cells harbor roughly 5,000-7,000 cytoplasmic RNAs, with <10% associated with the ER. These measurements uncover pervasive subcellular heterogeneity in RNA localization that is undetectable by bulk assays. Spatial RNA patterns define an orthogonal axis of cell-state identity that is independent of gene expression. For example, ZWINT mRNA relocalizes to the cytoplasm in a cell cycle-dependent manner. These findings establish heterogeneous levels of subcellular RNA localization as a variable dimension of intracellular organization and cell identity. - Source: PubMed
Publication date: 2026/02/06
Fan XiaojuanHafner Markus - Immune dysfunction in the tumor microenvironment contributes to the progression of non-small cell lung cancer (NSCLC) in patients with chronic obstructive pulmonary disease (COPD). This study aimed to elucidate the roles of the RNA-binding protein Aly/REF export factor (ALYREF) and its target, ZW10 interacting protein (ZWINT), in mediating CD4 T cell dysfunction in this context. - Source: PubMed
Publication date: 2026/03/23
Li ShiMinSong QiDong FuShiLiu HaiYangMeng ShanShanHu Xin - Bladder cancer (BCa) is characterized by substantial molecular and clinical heterogeneity, hindering accurate prognostic assessment and treatment stratification. This study aimed to develop a machine learning-based prognostic model based on DNA repair-related genes and to investigate the functional relevance of representative genes in BCa. - Source: PubMed
Publication date: 2026/02/11
Liang ShijieLiu HaodongSu QishengLi XiaohongYang ZhengMo Wuning - Oral cancer, a significant global health concern, remains a challenging disease with high mortality rates. Despite advancements in treatment, late diagnosis and lack of effective biomarkers hinder patient outcomes. To address this, our study investigates the potential of specific genes ( and ) and microRNAs (hsa-mir-607, hsa-mir-556-5p, hsa-mir-1225-3p, hsa-mir-361-3p) as prognostic markers and therapeutic targets for oral cancer. We hypothesize that these genes and miRNAs play crucial roles in regulating cell cycle progression, DNA damage repair, and apoptosis in oral cancer cells. By analyzing their expression patterns in oral cancer tissues and adjacent normal tissues, we aim to identify potential biomarkers for early diagnosis and prognosis. Additionally, we explore the potential of targeting these molecules to enhance the efficacy of radiation therapy and improve patient outcomes. Our study contributes to the comprehension of the molecular processes underlying oral cancer and provides insights into the development of novel therapeutic strategies based on personalized medicine. - Source: PubMed
Publication date: 2025/11/25
Khoushab SaloomehHobabi Aghmiuni MinaBizhanpour AnahitaRaei BehnazNemati Anaraki SaeidEntezari MalihehTaheriazam AfshinHashemi Mehrdad