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Modeling and Virtual Screening of Antisense Peptides Targeting the Divergent Region of Tumor‐Associated MT1‐MMP Protein
Author(s) -
Tan Bowen,
Zhou Yijie,
Song Zhilei,
Peng Yinxuan,
Wu Fang,
Kang Yue,
Liu Xiaomin,
Zeng Li,
Huang Tingting,
Liu Zongying,
Xiong Lili,
Guo Zhiyun,
Cui Jian,
Mao Canquan
Publication year - 2015
Publication title -
bulletin of the korean chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.237
H-Index - 59
ISSN - 1229-5949
DOI - 10.1002/bkcs.10421
Subject(s) - matrix metalloproteinase , peptide , virtual screening , chemistry , homology modeling , peptide library , cancer research , biology , biochemistry , enzyme , computational biology , peptide sequence , drug discovery , gene
Membrane type‐1 matrix metalloproteinase ( MT1‐MMP ; also known as MMP14 ) is a key enzyme involved in tumor invasion and metastasis, and is a potential target for drug discovery for cancer therapy. However, till now there is no MT1‐MMP ‐ or MMP ‐based anticancer drugs in the market mainly because of the high conservation of the MMP family and also because there is no elucidated crystal structure for the mature MT1‐MMP . The modeling of the three‐dimensional structure of mature MT1‐MMP and the finding of MT1‐MMP targeted peptides by virtual screening are highly desired. In this study, the three‐dimensional structure of mature MT1‐MMP is constructed by homology and de novo modeling and later rationalized and optimized by molecular dynamics simulations. An antisense peptide library was constructed against the divergent sense peptide DEGTEEET in the specific region of MT1‐MMP , which was found by multiple alignment of the whole MMP family. The antisense peptide library was virtually screened against the constructed three‐dimensional model of MT1‐MMP . The top 20 novel peptides were further studied, which were found well docked with MT1‐MMP at the region of DEGTEEET , again confirming their specific binding to MT1‐MMP . Preliminary study of one of the top‐ranked peptide SFLLSPFV showed that it could inhibit the viabilities of MG63 and MDA‐MB ‐231 tumor cells. We thus not only successfully modeled the three‐dimensional structure of mature MT1‐MMP but also provided a new way for the finding of peptide candidates targeting MT1‐MMP based on antisense peptide library.