View source for Halicin

{{short description|Drug and first antibiotic identified by a deep learning algorithm}}
{{distinguish|Allicin|Halcion|Helicina}}
{{Drugbox
| IUPAC_name = 5-[(5-Nitro-1,3-thiazol-2-yl)sulfanyl]-1,3,4-thiadiazol-2-amine
| image = Halicin.svg
<!--Clinical data-->
| tradename = Halicin
| legal_US = Investigational New Drug
| legal_status =

<!--Pharmacokinetic data-->
| bioavailability =
| metabolism =
| elimination_half-life =
| excretion =

<!--Identifiers-->
| CAS_number_Ref = {{cascite|correct|CAS}}
| CAS_number = 40045-50-9
| PubChem = 11837140
| UNII_Ref = {{fdacite|correct|FDA}}
| UNII = Y4KQC5P9B2
| ChemSpiderID = 10011699
| ChEBI = 146227
| ChEMBL = 510038

<!--Chemical data-->
| C=5 | H=3 | N=5 | O=2 | S=3
| SMILES = C1=C(SC(=N1)SC2=NN=C(S2)N)[N+](=O)[O-]
| StdInChI=1S/C5H3N5O2S3/c6-3-8-9-5(14-3)15-4-7-1-2(13-4)10(11)12/h1H,(H2,6,8)
| StdInChIKey = NQQBNZBOOHHVQP-UHFFFAOYSA-N
}}

'''Halicin''' ('''SU-3327''') is an [[experimental drug]] that acts as an [[enzyme inhibitor]] of [[c-Jun N-terminal kinase]] (JNK).<ref name="pmid24838066">{{cite journal | vauthors = Augustine C, Cepinskas G, Fraser DD | title = Traumatic injury elicits JNK-mediated human astrocyte retraction in vitro | journal = Neuroscience | volume = 274 | pages = 1–10 | date = August 2014 | pmid = 24838066 | doi = 10.1016/j.neuroscience.2014.05.009 | s2cid = 9498486 }}</ref><ref name="pmid25423094">{{cite journal | vauthors = Jang S, Javadov S | title = Inhibition of JNK aggravates the recovery of rat hearts after global ischemia: the role of mitochondrial JNK | journal = PLOS ONE | volume = 9 | issue = 11 | pages = e113526 | date = 2014 | pmid = 25423094 | pmc = 4244102 | doi = 10.1371/journal.pone.0113526 | bibcode = 2014PLoSO...9k3526J | doi-access = free }}</ref><ref name="pmid26491845">{{cite journal | vauthors = Jang S, Yu LR, Abdelmegeed MA, Gao Y, Banerjee A, Song BJ | title = Critical role of c-jun N-terminal protein kinase in promoting mitochondrial dysfunction and acute liver injury | journal = Redox Biology | volume = 6 | pages = 552–564 | date = December 2015 | pmid = 26491845 | pmc = 4625008 | doi = 10.1016/j.redox.2015.09.040 }}</ref> Originally, it was researched for the treatment of [[diabetes]],<ref name="pmid19271755">{{cite journal | vauthors = De SK, Stebbins JL, Chen LH, Riel-Mehan M, Machleidt T, Dahl R, Yuan H, Emdadi A, Barile E, Chen V, Murphy R, Pellecchia M | display-authors = 6 | title = Design, synthesis, and structure-activity relationship of substrate competitive, selective, and in vivo active triazole and thiadiazole inhibitors of the c-Jun N-terminal kinase | journal = Journal of Medicinal Chemistry | volume = 52 | issue = 7 | pages = 1943–52 | date = April 2009 | pmid = 19271755 | pmc = 2667321 | doi = 10.1021/jm801503n }}</ref> but development was discontinued for this application due to poor results in testing.{{citation needed|date=March 2023}} In 2019, this molecule was found by an [[artificial intelligence]] (AI) model to show [[antibiotic]] properties against a number of [[bacteria]].<ref name="MIT 2020"/>

==History==
Halicin was previously known as SU-3327,<ref>{{cite news |title=AI finds molecules that kill bacteria, but would they make good antibiotics? |url=https://cen.acs.org/physical-chemistry/computational-chemistry/AI-finds-molecules-kill-bacteria/98/web/2020/02 |access-date=22 March 2023 |publisher=Chemical and engineering news (C&EN) |date=26 February 2020 |archive-url=https://web.archive.org/web/20200229191605/https://cen.acs.org/physical-chemistry/computational-chemistry/AI-finds-molecules-kill-bacteria/98/web/2020/02 |archive-date=29 February 2020}}</ref> developed by a group of researchers from [[Burnham Institute for Medical Research]], United States in 2009 for investigations into diabetes treatment.<ref name="pmid19271755"/>
Researchers named the molecule after the fictional artificial intelligence system [[HAL 9000|Hal]] from ''2001: A Space Odyssey''.<ref name="MIT 2020"/>

===Antibiotic properties===
Halicin was identified by artificial intelligence researchers, including bioengineer [[James Collins (bioengineer)|James Collins]], at the [[MIT Jameel Clinic]] in 2019 using an ''[[in silico]]'' [[deep learning]] approach, as a likely [[broad-spectrum antibiotic]].<ref name="MIT 2020">{{Cite web|title=Artificial Intelligence Yields New Antibiotic|url=https://betterworld.mit.edu/artificial-intelligence-yields-new-antibiotic/|access-date=2020-11-13|website=The MIT Campaign for a Better World|language=en}}</ref><ref name=":0" /> The process took just three days.<ref>{{Cite journal |last=May |first=Mike |date=2023 |title=How to fight antibiotic resistance |url=http://dx.doi.org/10.1038/d41591-023-00043-5 |journal=Nature Medicine |volume=29 |issue=7 |pages=1583–1586 |doi=10.1038/d41591-023-00043-5 |pmid=37464030 |issn=1078-8956}}</ref> This likelihood was verified by ''[[in vitro]]'' cell culture testing, followed by ''[[in vivo]]'' tests in mice.<ref>{{cite web | last = Sample | first = Ian | name-list-style = vanc | url = https://www.theguardian.com/society/2020/feb/20/antibiotic-that-kills-drug-resistant-bacteria-discovered-through-ai | title = Powerful antibiotic discovered using machine learning for first time | work = The Guardian | date = February 20, 2020 }}</ref> It showed activity against drug-resistant strains of ''[[Clostridioides difficile (bacteria)|Clostridiodes difficile]]'', ''[[Acinetobacter baumannii]]'', and ''[[Mycobacterium tuberculosis]]'', with an unusual mechanism of action involving the sequestration of [[iron]] inside the bacterial cells, that thereby interferes with their ability to regulate the [[pH]] balance across the [[cell membrane]] properly. Since this is a different mode of action from most antibiotics, halicin retained activity against bacterial strains resistant to many commonly used drugs.<ref>{{cite journal | vauthors = Stokes JM, Yang K, Swanson K, Jin W, Cubillos-Ruiz A, Donghia NM, MacNair CR, French S, Carfrae LA, Bloom-Ackerman Z, Tran VM, Chiappino-Pepe A, Badran AH, Andrews IW, Chory EJ, Church GM, Brown ED, Jaakkola TS, Barzilay R, Collins JJ | display-authors = 6 | title = A Deep Learning Approach to Antibiotic Discovery | journal = Cell | volume = 180 | issue = 4 | pages = 688–702.e13 | date = February 2020 | pmid = 32084340 | doi = 10.1016/j.cell.2020.01.021 | pmc = 8349178 | doi-access = free }}</ref>

Preliminary studies suggest that halicin kills bacteria by disrupting their ability to maintain an [[electrochemical gradient]] across their cell membranes. This gradient is necessary, among other functions, to produce [[adenosine triphosphate]] (ATP, molecules that cells use to store and transfer energy), so if the gradient breaks down, the cells die. This type of killing mechanism could be difficult for bacteria to develop resistance to.<ref name=":0">{{cite web | title = Artificial intelligence yields new antibiotic | url = http://news.mit.edu/2020/artificial-intelligence-identifies-new-antibiotic-0220 | first = Anne | last = Trafton | name-list-style = vanc | work = MIT News Office | date = February 20, 2020}}</ref>

== References ==
{{Reflist}}

== External links ==
* [https://www.science.org/content/blog-post/machine-learning-antibiotics Machine Learning for Antibiotics]

[[Category:Enzyme inhibitors]]
[[Category:Antibiotics]]
[[Category:Nitrothiazoles]]
[[Category:Thiadiazoles]]