The alpha-fetoprotein third domain receptor binding fragment: in search of scavenger and associated receptor targets.

J Drug Target

Molecular Diagnostics Laboratory, Division of Translational Medicine, Wadsworth Center, New York State Department of Health , Empire State Plaza, Albany, NY , USA.

Published: April 2016

Recent studies have demonstrated that the carboxyterminal third domain of alpha-fetoprotein (AFP-CD) binds with various ligands and receptors. Reports within the last decade have established that AFP-CD contains a large fragment of amino acids that interact with several different receptor types. Using computer software specifically designed to identify protein-to-protein interaction at amino acid sequence docking sites, the computer searches identified several types of scavenger-associated receptors and their amino acid sequence locations on the AFP-CD polypeptide chain. The scavenger receptors (SRs) identified were CD36, CD163, Stabilin, SSC5D, SRB1 and SREC; the SR-associated receptors included the mannose, low-density lipoprotein receptors, the asialoglycoprotein receptor, and the receptor for advanced glycation endproducts (RAGE). Interestingly, some SR interaction sites were localized on the AFP-derived Growth Inhibitory Peptide (GIP) segment at amino acids #480-500. Following the detection studies, a structural subdomain analysis of both the receptor and the AFP-CD revealed the presence of epidermal growth factor (EGF) repeats, extracellular matrix-like protein regions, amino acid-rich motifs and dimerization subdomains. For the first time, it was reported that EGF-like sequence repeats were identified on each of the three domains of AFP. Thereafter, the localization of receptors on specific cell types were reviewed and their functions were discussed.

Download full-text PDF

Source
http://dx.doi.org/10.3109/1061186X.2015.1015538DOI Listing

Publication Analysis

Top Keywords

third domain
8
amino acids
8
amino acid
8
acid sequence
8
receptor
6
receptors
6
amino
5
alpha-fetoprotein third
4
domain receptor
4
receptor binding
4

Similar Publications

Introduction: Traditional Chinese medicine (TCM) is commonly used alongside Western medicine for stroke management in China. However, there is significant variation in TCM practice, and the utilisation of evidence-based clinical practice guidelines is inadequate. This study aims to evaluate the effectiveness of three popular frameworks-Consolidated Framework for Implementation Research (CFIR), Theoretical Domains Framework (TDF) and Normalization Process Theory (NPT)-in improving implementation outcomes for the integrated TCM and Western medicine clinical practice guideline for stroke management.

View Article and Find Full Text PDF

Background Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects about a third of adults worldwide and is projected soon to be the leading cause of cirrhosis. It occurs when fat accumulates in hepatocytes and can progress to metabolic dysfunction-associated steatohepatitis (MASH), liver cirrhosis, and hepatocellular carcinoma. MASLD pathogenesis is believed to involve a combination of genetic and environmental risk factors.

View Article and Find Full Text PDF

Patient expectations have been shown to influence postoperative outcomes across surgical specialties. However, the impact of expectations in breast reconstruction is not well understood. The purpose of this project is to perform the first large-scale analysis and classification of BREAST-Q Expectations responses in patients undergoing implant-based reconstruction.

View Article and Find Full Text PDF

Photon-counting computed tomography (PCCT) is superior in providing better CT image contrast than traditional CT technology. However, noticeable ring artifacts are more likely caused by the imperfect functioning of photon-counting detectors. This study proposes an efficient ring artifacts correction approach based on the unique characteristics of unwanted components in multi-domains.

View Article and Find Full Text PDF

Fast and interpretable mortality risk scores for critical care patients.

J Am Med Inform Assoc

January 2025

Department of Computer Science, Duke University, Durham, NC 27708, United States.

Objective: Prediction of mortality in intensive care unit (ICU) patients typically relies on black box models (that are unacceptable for use in hospitals) or hand-tuned interpretable models (that might lead to the loss in performance). We aim to bridge the gap between these 2 categories by building on modern interpretable machine learning (ML) techniques to design interpretable mortality risk scores that are as accurate as black boxes.

Material And Methods: We developed a new algorithm, GroupFasterRisk, which has several important benefits: it uses both hard and soft direct sparsity regularization, it incorporates group sparsity to allow more cohesive models, it allows for monotonicity constraint to include domain knowledge, and it produces many equally good models, which allows domain experts to choose among them.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!