4.7 Article

Improved Descriptors for the Quantitative Structure-Activity Relationship Modeling of Peptides and Proteins

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AMER CHEMICAL SOC
DOI: 10.1021/acs.jcim.7b00488

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  1. Biotechnology and Biological Sciences Research Council (BBSRC)
  2. Glaxo-SmithKline (GSK) under the Strategic Longer and Larger (sLoLa) grant initiative [BB/K00199X/1]
  3. BBSRC [BB/K00199X/1, BB/M017702/1] Funding Source: UKRI
  4. Biotechnology and Biological Sciences Research Council [BB/M017702/1, BB/K00199X/1] Funding Source: researchfish

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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.

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