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Cited 3 time in webofscience Cited 3 time in scopus
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Designing Tyrosinase siRNAs by Multiple Prediction Algorithms and Evaluation of Their Anti-Melanogenic Effects

Authors
Kwon, OS[Kwon, Ok-Seon]Kwon, SJ[Kwon, Soo-Jung]Kim, JS[Kim, Jin Sang]Lee, G[Lee, Gunbong]Maeng, HJ[Maeng, Han-Joo]Lee, J[Lee, Jeongmi]Hwang, GS[Hwang, Gwi Seo]Cha, HJ[Cha, Hyuk-Jin]Chun, KH[Chun, Kwang-Hoon]
Issue Date
May-2018
Publisher
KOREAN SOC APPLIED PHARMACOLOGY
Keywords
Tyrosinase; Melanin; siRNA; Melanocytes; Whitening
Citation
BIOMOLECULES & THERAPEUTICS, v.26, no.3, pp.282 - 289
Indexed
SCIE
SCOPUS
KCI
Journal Title
BIOMOLECULES & THERAPEUTICS
Volume
26
Number
3
Start Page
282
End Page
289
URI
https://scholarworks.bwise.kr/skku/handle/2021.sw.skku/20211
DOI
10.4062/biomolther.2017.115
ISSN
1976-9148
Abstract
Melanin is a pigment produced from tyrosine in melanocytes. Although melanin has a protective role against UVB radiation-induced damage, it is also associated with the development of melanoma and darker skin tone. Tyrosinase is a key enzyme in melanin synthesis, which regulates the rate-limiting step during conversion of tyrosine into DOPA and dopaquinone. To develop effective RNA interference therapeutics, we designed a melanin siRNA pool by applying multiple prediction programs to reduce human tyrosinase levels. First, 272 siRNAs passed the target accessibility evaluation using the RNAxs program. Then we selected 34 siRNA sequences with Delta G >=-34.6 kcal/mol, i-Score value >= 65, and siRNA scales score <= 30. siRNAs were designed as 19-bp RNA duplexes with an asymmetric 3' overhang at the 3' end of the antisense strand. We tested if these siRNAs effectively reduced tyrosinase gene expression using qRT-PCR and found that 17 siRNA sequences were more effective than commercially available siRNA. Three siRNAs further tested showed an effective visual color change in MNT-1 human cells without cytotoxic effects, indicating these sequences are anti-melanogenic. Our study revealed that human tyrosinase siRNAs could be efficiently designed using multiple prediction algorithms.
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