BROWSE

Related Scientist

lie,eunkyung's photo.

lie,eunkyung
시냅스뇌질환연구단
more info

ITEM VIEW & DOWNLOAD

SALM/Lrfn family synaptic adhesion molecules

Cited 9 time in webofscience Cited 8 time in scopus
1,227 Viewed 373 Downloaded
Title
SALM/Lrfn family synaptic adhesion molecules
Author(s)
Eunkyung Lie; Yan Li; Ryunhee Kim; Eunjoon Kim
Subject
Adhesion molecules, ; Lrfn, ; PSD-95, ; SALM, ; Synaptic
Publication Date
2018-04
Journal
FRONTIERS IN MOLECULAR NEUROSCIENCE, v.11, pp.105 - 105
Publisher
FRONTIERS MEDIA SA
Abstract
Synaptic adhesion-like molecules (SALMs) are a family of cell adhesion molecules involved in regulating neuronal and synapse development that have also been implicated in diverse brain dysfunctions, including autism spectrum disorders (ASDs). SALMs, also known as leucine-rich repeat (LRR) and fibronectin III domain-containing (LRFN) proteins, were originally identified as a group of novel adhesion-like molecules that contain LRRs in the extracellular region as well as a PDZ domain-binding tail that couples to PSD-95, an abundant excitatory postsynaptic scaffolding protein. While studies over the last decade have steadily explored the basic properties and synaptic and neuronal functions of SALMs, a number of recent studies have provided novel insights into molecular, structural, functional and clinical aspects of SALMs. Here we summarize these findings and discuss how SALMs act in concert with other synaptic proteins to regulate synapse development and function. © 2018 Lie, Li, Kim and Kim
URI
https://pr.ibs.re.kr/handle/8788114/4553
DOI
10.3389/fnmol.2018.00105
ISSN
1662-5099
Appears in Collections:
Center for Synaptic Brain Dysfunctions(시냅스 뇌질환 연구단) > 1. Journal Papers (저널논문)
Files in This Item:
2018_146.pdfDownload

qrcode

  • facebook

    twitter

  • Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
해당 아이템을 이메일로 공유하기 원하시면 인증을 거치시기 바랍니다.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse