Abstract:
:The disruption of large protein-protein (PP) interfaces remains a challenge in targeted therapy. Designing drugs that compete with binding partners is daunting, especially when the structure of the protein complex is unknown. To address the problem we propose a deep protein databank (PDB) learning platform to discover targetable epitopes for complex-disruptive leads.
journal_name
Trends Pharmacol Scijournal_title
Trends in pharmacological sciencesauthors
Fernández Adoi
10.1016/j.tips.2019.04.009subject
Has Abstractpub_date
2019-08-01 00:00:00pages
551-554issue
8eissn
0165-6147issn
1873-3735pii
S0165-6147(19)30086-0journal_volume
40pub_type
杂志文章abstract::Progress in understanding the genetic changes that drive tumorigenesis has enabled the development of molecularly targeted anticancer therapy. The first small molecule targeted to a specific protein was imatinib mesylate (Gleevec, STI571), which is used to treat chronic myeloid leukemia (CML). A recent article present...
journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
pub_type: 杂志文章,评审
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journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
pub_type: 杂志文章,评审
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journal_title:Trends in pharmacological sciences
pub_type: 杂志文章,评审
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journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
pub_type: 杂志文章,评审
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journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
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journal_title:Trends in pharmacological sciences
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