MCDB

MCDB curates and organizes experimentally reported genes, proteins, and compounds related to mitotic catastrophe (MC) to support research into tumor development, prevention, and drug resistance.

Key Features:

• Curated content: Contains 1,214 genes/proteins and 5,014 compounds manually gathered from over 8,000 research articles.
• Confidence and annotation schema: Defines confidence levels, classification criteria, and uniform naming rules for MC-related data to enhance consistency and reliability.
• Protein sequence alignment: Provides protein sequence alignment functions for predicting new potential genes and proteins associated with MC.
• Target prediction: Implements target prediction functionalities to identify potential target proteins for unknown MC-related compounds.

Scientific Applications:

• Tumor biology: Supports investigation of mitotic catastrophe mechanisms in tumor development and prevention.
• Drug resistance studies: Aids research into roles of MC in drug resistance and related molecular pathways.
• Medicinal chemistry: Facilitates identification of potential therapeutic targets and analysis of compound–protein interactions.
• Molecular biology: Enables exploration of novel genetic components involved in mitotic catastrophe via sequence-based prediction.
• Bioinformatics: Serves as a dataset for computational analyses leveraging sequence alignment and target prediction data.

Methodology:

Data were manually curated from over 8,000 research articles to compile 1,214 genes/proteins and 5,014 compounds; confidence levels, classification criteria, and uniform naming rules were defined; protein sequence alignment functions were developed; and target prediction functionalities were implemented.