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Article

Prediction of Novel Disease-Related Regions in SIGLEC-7 by In Silico and Biochemical Analyses.

International journal of molecular sciences - 17 Jun 2026

Morishita Sayo, Hane Masaya, Wu Di, Kitajima Ken, Ohno Shiho, Yamaguchi Yoshiki, Sato Chihiro

Abstract excerpt

SIGLECs are well-known receptors that distinguish self from non-self by binding to sialic acid-containing glycoconjugates, thereby regulating normal immune functions. They have also been associated with several diseases, including systemic sclerosis, leukemia, and Alzheimer's disease. To identify pathogenic regions related to ligand binding in SIGLECs using a novel approach, we employed the in silico Individual...

Topics

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Amino Acid Motifs
Amino Acid Substitution
Antigens, CD
Antigens, Differentiation, B-Lymphocyte
Antigens, Differentiation, Myelomonocytic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Computer Simulation

Sialic Acid Binding Ig-like Lectin 3

Source

Open in PubMed Open full text

Identifiers

PMID: 42353205
DOI: 10.3390/ijms27125489
PMCID: PMC13299484

Genes

CD33

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 1 Sept 2026.

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