The ability to model the activity of a protein using quantitative structure activity relationships (QSAR) requires descriptors for the 20 naturally coded amino acids. In this work we show that by modifying some established descriptors we were able to model the activity data of 140 mutants of the enzyme epoxide hydrolase with improved accuracy. These new descriptors (referred to as physical descriptors) also gave very good results when tested against a series of four dipeptide data sets. The physical descriptors encode the amino acids using only two orthogonal scales: the first is strongly linked to hydrophilicity/hydrophobicity, and the second, to the volume of the amino acid residue. The use of these new amino acid descriptors should result in simpler and more readily interpretable models for the enzyme activity (and potentially other functions of interest, e.g., secondary and tertiary structure) of peptides and proteins.
机构:
Univ N Carolina, Sch Pharm, Div Med Chem & Nat Prod, Lab Mol Modeling, Chapel Hill, NC 27599 USAUniv N Carolina, Sch Pharm, Div Med Chem & Nat Prod, Lab Mol Modeling, Chapel Hill, NC 27599 USA
Golbraikh, A
Tropsha, A
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Univ N Carolina, Sch Pharm, Div Med Chem & Nat Prod, Lab Mol Modeling, Chapel Hill, NC 27599 USAUniv N Carolina, Sch Pharm, Div Med Chem & Nat Prod, Lab Mol Modeling, Chapel Hill, NC 27599 USA
机构:
Univ N Carolina, Sch Pharm, Div Med Chem & Nat Prod, Lab Mol Modeling, Chapel Hill, NC 27599 USAUniv N Carolina, Sch Pharm, Div Med Chem & Nat Prod, Lab Mol Modeling, Chapel Hill, NC 27599 USA
Golbraikh, A
Tropsha, A
论文数: 0引用数: 0
h-index: 0
机构:
Univ N Carolina, Sch Pharm, Div Med Chem & Nat Prod, Lab Mol Modeling, Chapel Hill, NC 27599 USAUniv N Carolina, Sch Pharm, Div Med Chem & Nat Prod, Lab Mol Modeling, Chapel Hill, NC 27599 USA