TY - JOUR
T1 - Optimal protein library design using recombination or point mutations based on sequence-based scoring functions
AU - Pantazes, Robert J.
AU - Saraf, Manish C.
AU - Maranas, Costas D.
N1 - Funding Information:
We gratefully acknowledge support from the National Science Foundation Grant BES–0331047 and also an REU in Biomolecular Engineering award to RJP (NSF Grant EEC–0353569).
PY - 2007/8
Y1 - 2007/8
N2 - In this paper, we introduce and test two new sequence-based protein scoring systems (i.e. S1, S2) for assessing the likelihood that a given protein hybrid will be functional. By binning together amino acids with similar properties (i.e. volume, hydrophobicity and charge) the scoring systems S1 and S2 allow for the quantification of the severity of mismatched interactions in the hybrids. The S2 scoring system is found to be able to significantly functionally enrich a cytochrome P450 library over other scoring methods. Given this scoring base, we subsequently constructed two separate optimization formulations (i.e. OPTCOMB and OPTOLIGO) for optimally designing protein combinatorial libraries involving recombination or mutations, respectively. Notably, two separate versions of OPTCOMB are generated (i.e. model M1, M2) with the latter allowing for position-dependent parental fragment skipping. Computational benchmarking results demonstrate the efficacy of models OPTCOMB and OPTOLIGO to generate high scoring libraries of a prespecified size.
AB - In this paper, we introduce and test two new sequence-based protein scoring systems (i.e. S1, S2) for assessing the likelihood that a given protein hybrid will be functional. By binning together amino acids with similar properties (i.e. volume, hydrophobicity and charge) the scoring systems S1 and S2 allow for the quantification of the severity of mismatched interactions in the hybrids. The S2 scoring system is found to be able to significantly functionally enrich a cytochrome P450 library over other scoring methods. Given this scoring base, we subsequently constructed two separate optimization formulations (i.e. OPTCOMB and OPTOLIGO) for optimally designing protein combinatorial libraries involving recombination or mutations, respectively. Notably, two separate versions of OPTCOMB are generated (i.e. model M1, M2) with the latter allowing for position-dependent parental fragment skipping. Computational benchmarking results demonstrate the efficacy of models OPTCOMB and OPTOLIGO to generate high scoring libraries of a prespecified size.
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U2 - 10.1093/protein/gzm030
DO - 10.1093/protein/gzm030
M3 - Article
C2 - 17686879
AN - SCOPUS:34548803632
SN - 1741-0126
VL - 20
SP - 361
EP - 373
JO - Protein Engineering, Design and Selection
JF - Protein Engineering, Design and Selection
IS - 8
ER -