Dynamic combinatorial chemistry.
作者： Sijbren Otto , Ricardo L.E Furlan , Jeremy K.M Sanders
DOI: 10.1016/S1359-6446(01)02086-4
关键词: Dynamic combinatorial chemistry 、 Self-replication 、 Set (abstract data type) 、 Ideal (set theory) 、 Combinatorial biology 、 Molecular network 、 Chemistry 、 Nanotechnology 、 Chemical biology 、 Drug discovery 、 Theoretical computer science
摘要: A combinatorial library that responds to its target by increasing the concentration of strong binders at expense weak sounds ideal. Dynamic chemistry has potential achieve exactly this. In this review, we will highlight unique features distinguish dynamic from traditional chemistry, and could make a useful addition set techniques used in drug discovery.
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