NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability

Cu2+ -Chelatable and ROS-Scavenging MXenzyme as NIR-II-Triggered Blood-Brain Barrier-Crossing Nanocatalyst against Alzheimer's Disease

Transition-metal dyshomeostasis has been identified as a critical pathogenic factor for the aggregates of amyloid-beta (Aβ) peptide, which is associated with the onset and progression of Alzheimer's disease (AD). Excessive transition-metal ions, especially copper ion (Cu²⁺ ), catalyze the formation of reactive oxygen species (ROS), triggering neuroinflammation and neuronal cell apoptosis. Therefore, developing a robust chelating agent can not only efficiently bind toxic Cu²⁺ , but also simultaneously scavenge the over-generated ROS that is urgently needed for AD treatment. In this work, a 2D niobium carbide (Nb₂ C) MXene-based nano-chelator is constructed and its performance in suppressing Cu²⁺ -induced accumulation of aggregated Aβ peptide and acting as a nanozyme (MXenzyme) with powerful antioxidant property to scavenge excess cellular ROS is explored, and the intrinsic mechanism is revealed by computational simulation. Importantly, the benign photothermal effect of Nb₂ C MXenzyme demonstrates the facilitated permeability of the blood-brain barrier under near-infrared laser irradiation, conquering limitations of the most conventional anti-AD therapeutic agents. This work not only demonstrates a favorable strategy for combating AD by engineering Nb₂ C MXenzyme-based neuroprotective nano-chelator, but also paves a distinct insight for extending the biomedical applications of MXenes in treating transition-metal dyshomeostasis-and ROS-mediated central nervous system diseases.

NetControl4BioMed: A web-based platform for controllability analysis of protein-protein interaction networks

MOTIVATION

There is an increasing amount of data coming from genome-wide studies identifying disease-specific survivability-essential proteins and host factors critical to a cell becoming infected. Targeting such proteins has a strong potential for targeted, precision therapies. Typically however, too few of them are drug targetable. An alternative approach is to influence them through drug targetable proteins upstream of them. Structural target network controllability is a suitable solution to this problem. It aims to discover suitable source nodes (e.g., drug targetable proteins) in a directed interaction network that can control (through a suitable set of input functions) a desired set of targets.

RESULTS

We introduce NetControl4BioMed, a free open-source web-based application that allows users to generate or upload directed protein-protein interaction networks and to perform target structural network controllability analyses on them. The analyses can be customized to focus the search on drug targetable source nodes, thus providing drug therapeutic suggestions. The application integrates protein data from HGNC, Ensemble, UniProt, NCBI, and InnateDB, directed interaction data from InnateDB, Omnipath, and SIGNOR, cell-line data from COLT and DepMap, and drug-target data from DrugBank.

AVAILABILITY

The application and data are available online at https://netcontrol.combio.org/. The source code is available at https://github.com/Vilksar/NetControl4BioMed under an MIT license.