期刊
JOURNAL OF MOLECULAR BIOLOGY
卷 307, 期 1, 页码 429-445出版社
ACADEMIC PRESS LTD
DOI: 10.1006/jmbi.2000.4424
关键词
dead-end elimination; protein design; structural genomics; homology modeling
资金
- NIGMS NIH HHS [R01GM49871] Funding Source: Medline
- PHS HHS [5T32-GN08487] Funding Source: Medline
The dead-end elimination (DEE) theorems are powerful tools for the combinatorial optimization of protein side-chain placement in protein design and homology modeling. In order to reach their full potential, the theorems must be extended to handle very hard problems. We present a suite of new algorithms within the DEE paradigm that significantly extend its range of convergence and reduce run time. As a demonstration, we show that a total protein design problem of 10(115) combinations, a hydrophobic core design problem of 10(244) combinations, and a side-chain placement problem of 10(1044) combinations are solved in less than two weeks, a day and a half, and an hour of CPU time, respectively. This extends the range of the method by approximately 53, 144 and 851 log-units, respectively, using modest computational resources. Small to average-sized protein domains can now be designed automatically, and side-chain placement calculations can be solved for nearly all sizes of proteins and protein complexes in the growing field of structural genomics. (C) 2001 Academic Press.
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