The ZINC database (recursive acronym: ZINC is not commercial) is a curated collection of commercially available chemical compounds prepared especially for virtual screening. ZINC is used by investigators (generally people with training as biologists or chemists) in pharmaceutical companies, biotechnology companies, and research universities.[1][2][3]

Scope and access

ZINC is different from other chemical databases because it aims to represent the biologically relevant, three dimensional form of the molecule.

Curation and updates

ZINC is updated regularly and may be downloaded and used free of charge. It is developed by John Irwin in the Shoichet Laboratory in the Department of Pharmaceutical Chemistry at the University of California, San Francisco.

Version

The latest release of the website interface is "ZINC-22". The database is continuously updated and as of 2023 is claimed to contain over 37 billion commercially available molecules.[4]

Uses

The database is typically used for molecule mining, a process in which Quantitative structure–activity relationships are used to find new compounds with improved biological activity, given a known starting point found, for example, by high-throughput screening.[5][6]

See also

  • PubChem a database of small molecules from the chemical and biological literature, hosted by NCBI
  • ChEMBL, a database of information about medicinal chemistry and biological activities of small molecules.
  • Ultra-large-scale docking

References

  1. ^ Koes, DR; Camacho, CJ (2012). „ZINCPharmer: Pharmakophorsuche in der ZINC-Datenbank“ . Nucleic Acids Research . 40 : W409– W414. doi : 10.1093/nar/gks378 . PMID 22553363 . 
  2. ^ Doytchinova, Irini; Atanasova, Mariyana; Valkova, Iva; et al. (2018). „Neue Treffer für die Acetylcholinesterase-Hemmung durch Docking-basiertes Screening der ZINC-Datenbank“ . Journal of Enzyme Inhibition and Medicinal Chemistry . 33 (1): 768–776 . doi : 10.1080/14756366.2018.1458031 . PMC 6010092. PMID 29651876 .  
  3. ^ Olawale, Femi; Iwaloye, Opeyemi; Folorunso, Ibukun Mary; Shityakov, Sergey (2023). „ In silico High-Throughput Screening der ZINC-Datenbank natürlicher Verbindungen zur Identifizierung neuartiger Histon-Deacetylase-Inhibitoren“. Journal of Computational Biophysics and Chemistry . 22 (1): 11–30 . Bibcode : 2023JCBC...22...11O . doi : 10.1142/S2737416522500466 .
  4. ^ Tingle, Benjamin I.; Tang, Khanh G.; Castanon, Mar; Gutierrez, John J.; Khurelbaatar, Munkhzul; Dandarchuluun, Chinzorig; Moroz, Yurii S.; Irwin, John J. (2023). „ZINC-22 – Eine kostenlose, milliardenschwere Datenbank mit greifbaren Verbindungen zur Ligandenfindung“ . Journal of Chemical Information and Modeling . 63 (4): 1166–1176 . doi : 10.1021/acs.jcim.2c01253 . PMC 9976280. PMID 36790087 .  
  5. ^ Awale, Mahendra; Jin, Xian; Reymond, Jean-Louis (2015). „Stereoselektive virtuelle Screening der ZINC - Datenbank mittels 3D-Fingerabdrücken von Atompaaren“ . Journal of Cheminformatics . 7. doi : 10.1186/s13321-014-0051-5 . PMC 4352573. PMID 25750664 .  
  6. ^ Panagiotopoulos, Athanasios A.; Konstantinou, Evangelia; Pirintsos, Stergios A.; et al. (2023). „Durchsuchen der ZINC-Datenbank von Naturprodukten nach spezifischen, testosteronähnlichen OXER1-Antagonisten“. Steroide . 199 . doi : 10.1016/j.steroids.2023.109309 . PMID 37696380 .