MCDB: A comprehensive curated mitotic catastrophe database for retrieval, protein sequence alignment, and target prediction.
10.1016/j.apsb.2021.05.032
- Author:
Le ZHANG
1
;
Lei ZHANG
1
;
Yue GUO
1
;
Ming XIAO
1
;
Lu FENG
1
;
Chengcan YANG
1
;
Guan WANG
1
;
Liang OUYANG
1
Author Information
1. Innovation Center of Nursing Research, West China Biomedical Big Data Center, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, College of Computer Science, and Collaborative Innovation Center of Biotherapy, Sichuan University, Chengdu 610065, China.
- Publication Type:Journal Article
- Keywords:
Data mining;
Database;
GO, Gene Ontology;
IUPAC, International Union of Pure and Applied Chemistry;
InChI Key, International Chemical Identifier hash;
InChI, International Chemical Identifier;
MC, Mitotic Catastrophe;
MCDB, Mitotic Catastrophe Database;
Mitotic catastrophe;
PDB, Protein Data Bank;
PMID, PubMed identifier;
Protein sequence analysis;
PubChem, Public Chemistry;
PubMed, Public Medicine;
SMILES, Simplified Molecular Input Line Entry Specification;
Target prediction;
UniProt, Universal Protein Resource
- From:
Acta Pharmaceutica Sinica B
2021;11(10):3092-3104
- CountryChina
- Language:English
-
Abstract:
Mitotic catastrophe (MC) is a form of programmed cell death induced by mitotic process disorders, which is very important in tumor prevention, development, and drug resistance. Because rapidly increased data for MC is vigorously promoting the tumor-related biomedical and clinical study, it is urgent for us to develop a professional and comprehensive database to curate MC-related data. Mitotic Catastrophe Database (MCDB) consists of 1214 genes/proteins and 5014 compounds collected and organized from more than 8000 research articles. Also, MCDB defines the confidence level, classification criteria, and uniform naming rules for MC-related data, which greatly improves data reliability and retrieval convenience. Moreover, MCDB develops protein sequence alignment and target prediction functions. The former can be used to predict new potential MC-related genes and proteins, and the latter can facilitate the identification of potential target proteins of unknown MC-related compounds. In short, MCDB is such a proprietary, standard, and comprehensive database for MC-relate data that will facilitate the exploration of MC from chemists to biologists in the fields of medicinal chemistry, molecular biology, bioinformatics, oncology and so on. The MCDB is distributed on http://www.combio-lezhang.online/MCDB/index_html/.
