AI Article Synopsis

  • SynSysNet is an online platform designed to create a detailed 4D network of synaptic interactions, focusing on the proteins that facilitate communication between nerve cells in the brain.
  • The platform integrates data from around 1000 synapse-specific proteins, providing 3D structures, drug-target interactions, and validated protein-protein interactions to enhance our understanding of human behavior and disease.
  • Users can interactively explore approximately 200 pathways related to drug-target interactions and export the network data in a variety of formats for further analysis.

Article Abstract

We created SynSysNet, available online at http://bioinformatics.charite.de/synsysnet, to provide a platform that creates a comprehensive 4D network of synaptic interactions. Neuronal synapses are fundamental structures linking nerve cells in the brain and they are responsible for neuronal communication and information processing. These processes are dynamically regulated by a network of proteins. New developments in interaction proteomics and yeast two-hybrid methods allow unbiased detection of interactors. The consolidation of data from different resources and methods is important to understand the relation to human behaviour and disease and to identify new therapeutic approaches. To this end, we established SynSysNet from a set of ∼1000 synapse specific proteins, their structures and small-molecule interactions. For two-thirds of these, 3D structures are provided (from Protein Data Bank and homology modelling). Drug-target interactions for 750 approved drugs and 50 000 compounds, as well as 5000 experimentally validated protein-protein interactions, are included. The resulting interaction network and user-selected parts can be viewed interactively and exported in XGMML. Approximately 200 involved pathways can be explored regarding drug-target interactions. Homology-modelled structures are downloadable in Protein Data Bank format, and drugs are available as MOL-files. Protein-protein interactions and drug-target interactions can be viewed as networks; corresponding PubMed IDs or sources are given.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531074PMC
http://dx.doi.org/10.1093/nar/gks1040DOI Listing

Publication Analysis

Top Keywords

protein-protein interactions
12
drug-target interactions
12
interactions
8
interactions drug-target
8
protein data
8
data bank
8
synsysnet integration
4
integration experimental
4
data
4
experimental data
4

Similar Publications

Revealing mitochondrial architecture and functions with single molecule localization microscopy.

Biol Cell

January 2025

CNRS, Univ Rennes, IGDR [(Institut de Génétique et Développement de Rennes)]-UMR 6290, Rennes, France.

Understanding the spatiotemporal organization of components within living systems requires the highest resolution possible. Microscopy approaches that allow for a resolution below 250 nm include electron and super-resolution microscopy (SRM). The latter combines advanced imaging techniques and the optimization of image processing methods.

View Article and Find Full Text PDF

Deciphering cellular complexity: advances and future directions in single-cell protein analysis.

Front Bioeng Biotechnol

January 2025

Yunnan Key Laboratory of Cell Metabolism and Diseases, Yunnan University, Kunming, China.

Single-cell protein analysis has emerged as a powerful tool for understanding cellular heterogeneity and deciphering the complex mechanisms governing cellular function and fate. This review provides a comprehensive examination of the latest methodologies, including sophisticated cell isolation techniques (Fluorescence-Activated Cell Sorting (FACS), Magnetic-Activated Cell Sorting (MACS), Laser Capture Microdissection (LCM), manual cell picking, and microfluidics) and advanced approaches for protein profiling and protein-protein interaction analysis. The unique strengths, limitations, and opportunities of each method are discussed, along with their contributions to unraveling gene regulatory networks, cellular states, and disease mechanisms.

View Article and Find Full Text PDF

Introduction: Autophagy is necessary for the progression of psoriasis.

Aim: This study aimed to recognize possible autophagy-related genes in psoriasis via bioinformatics study to present a better standard for the clinical treatment and management of psoriasis.

Material And Methods: The GEO dataset was utilized to derive the mRNA expression profile of the database GSE78097.

View Article and Find Full Text PDF

Problem: Oxidative stress (OS) plays a key role in the pathogenesis of gestational diabetes mellitus (GDM), but it was not well understood. We aimed to investigate the biomarkers and underlying mechanisms of OS-related genes in GDM.

Method Of Study: The GSE103552 and GSE70493 datasets of GDM were acquired from the Gene Expression Omnibus (GEO) database.

View Article and Find Full Text PDF

Background: Polycystic ovary syndrome (PCOS) is an endocrine disease associated with reproductive and metabolic abnormalities. The aim of this study was to elucidate the effects of Schisandra rubriflora (S. rubriflora) on PCOS and its related mechanisms using network pharmacology, molecular docking and in vitro experiments.

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!