Abstract
Secondary structures (SS) of proteins are of great importance to structural, molecular, and computational biology and chemistry. Accurate and reliable method for automatic SS assignment when only c...
Highlights
There are many important purposes (Cabaleiro-Lago, Szczepankiewicz, & Linse, 2012; Cino, Choy, & Karttunen, 2012; Emr & Silhavy, 1983; Ji & Li, 2010; Konvalinová et al, 2015; Myers & Oas, 2001) for which structural, molecular, and computational biologists (SMCB) need SS of proteins even when only coarse-grained (CG) information of the protein is available
It is shown in this paper that RaFoSA requires only coordinates of alpha carbon (CAC) and achieves 96% agreements with DSSP—the acclaimed gold-standard for automatic SS assignment—it is important to mention that other SS assignment methods based on CAC exist in the literature
RaFoSA achieves an agreement of 96.2% with DSSP that require all-atom and hydrogen-bonding information, which are not always available
Summary
There are many important purposes (Cabaleiro-Lago, Szczepankiewicz, & Linse, 2012; Cino, Choy, & Karttunen, 2012; Emr & Silhavy, 1983; Ji & Li, 2010; Konvalinová et al, 2015; Myers & Oas, 2001) for which structural, molecular, and computational biologists (SMCB) need SS of proteins even when only coarse-grained (CG) information of the protein is available. RaFoSA (which is freely available at http://bioinformatics.center/RaFoSA) requires only the coordinates of alpha carbon atoms (CAC). It works for both CG and all-atom protein systems (i.e. regardless of whether all-atom information is available or not). Rather than manually looking for “human rules” (i.e. manual deterministic approach) that could guide SS assignment, the computer was allowed to learn the SS classification of proteins based on random forests algorithm (Breiman, 2001). It is shown in this paper that RaFoSA requires only CAC and achieves 96% (and 94%) agreements with DSSP (and STRIDE)—the acclaimed gold-standard for automatic SS assignment—it is important to mention that other SS assignment methods based on CAC exist in the literature. A review of the SS assignment algorithms for these methods has been published elsewhere (Andersen & Rost, 2009)
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