.png){kind=icon}
Return
FROST: A filter-based fold recognition method
.png){kind=icon}
PRE
AI
DOI：10.1002/prot.10231.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
To assess the reliability of fold assignments to protein sequences, we developed a fold recognition method called FROST (Fold Recognition-Oriented Search Tool) based on a series of filters and a database specifically designed as a benchmark for this new method under realistic conditions. This benchmark database consists of proteins for which there exists, at least, another protein with an extensively similar 3D structure in a database of representative 3D structures (i.e., more than 65% of the residues in both proteins can be structurally aligned). Because the testing of our method must be carried out under conditions similar to those of real fold recognition experiments, no protein pair with sequence similarity detectable using standard sequence comparison methods such as FASTA is included in the benchmark database. While using FROST, we achieved a coverage of 60% for a rate of error of 1%. To obtain a baseline for our method, we used PSI-BILAST and 3D-PSSM. Under the same conditions, for a 1% error rate, coverages for PSI-BLAST and 3D-PSSM were 33 and 56%, respectively. (C) 2002 Wiley-Liss, Inc.
Keywords:
threading
in silico functional analysis
genome sequencing projects
protein evolution
benchmark
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
P
IF:
2.8
Papers:
6.6K
Citations:
1.4W
Organization
No organization information available
Cited Papers
.png){kind=icon}
ShareSaveShareSave
ShareSaveShareSave
View more