机构:
Univ Washington, Dept Biochem, Seattle, WA 98195 USA
Univ Washington, Inst Prot Design, Seattle, WA 98195 USA
Univ Washington, Howard Hughes Med Inst, Seattle, WA 98195 USA
Stanford Univ, Dept Bioengn, Stanford, CA 94305 USAUniv Washington, Dept Biochem, Seattle, WA 98195 USA
Huang, Po-Ssu
[1
,2
,3
,4
]
Boyken, Scott E.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Washington, Dept Biochem, Seattle, WA 98195 USA
Univ Washington, Inst Prot Design, Seattle, WA 98195 USA
Univ Washington, Howard Hughes Med Inst, Seattle, WA 98195 USAUniv Washington, Dept Biochem, Seattle, WA 98195 USA
Boyken, Scott E.
[1
,2
,3
]
Baker, David
论文数: 0引用数: 0
h-index: 0
机构:
Univ Washington, Dept Biochem, Seattle, WA 98195 USA
Univ Washington, Inst Prot Design, Seattle, WA 98195 USA
Univ Washington, Howard Hughes Med Inst, Seattle, WA 98195 USAUniv Washington, Dept Biochem, Seattle, WA 98195 USA
Baker, David
[1
,2
,3
]
机构:
[1] Univ Washington, Dept Biochem, Seattle, WA 98195 USA
[2] Univ Washington, Inst Prot Design, Seattle, WA 98195 USA
[3] Univ Washington, Howard Hughes Med Inst, Seattle, WA 98195 USA
[4] Stanford Univ, Dept Bioengn, Stanford, CA 94305 USA
There are 20(200) possible amino-acid sequences for a 200-residue protein, of which the natural evolutionary process has sampled only an infinitesimal subset. De novo protein design explores the full sequence space, guided by the physical principles that underlie protein folding. Computational methodology has advanced to the point that a wide range of structures can be designed from scratch with atomic-level accuracy. Almost all protein engineering so far has involved the modification of naturally occurring proteins; it should now be possible to design new functional proteins from the ground up to tackle current challenges in biomedicine and nanotechnology.