Enzyme-like proteins from an unselected library of designed amino acid sequences.
Combinatorial libraries of de novo amino acid sequences can provide a rich source of diversity for the discovery of novel proteins with interesting and important activities. However, since arbitrary sequences rarely fold into well ordered protein-like structures, randomly generated libraries will yield functional proteins only very rarely. To enhance the likelihood of finding functional de novo proteins, we use binary patterning of polar and non-polar amino acids to design focused libraries of sequences that are predisposed to fold into ordered structures. Proteins isolated from binary patterned libraries have been shown previously to fold into well ordered and native-like three-dimensional structures. To probe the potential of such libraries to also yield proteins with enzyme-like activity, we measured the esterase activity of S-824, a de novo binary patterned protein whose alpha-helical three-dimensional structure was reported recently. Protein S-824 displayed a rate enhancement (k(cat)/k(uncat)) of 8700. The observed activity is similar to, or better than, that observed for several esterases designed previously using rational design or automated computational methods. Moreover, the observed activity rivals those of the first catalytic antibodies. To assess whether the activity of S-824 is representative of other proteins in binary patterned libraries, we measured the esterase activity of six additional proteins from two libraries. These libraries were 'naïve' in that they were neither designed to bind substrate, nor subjected to high throughput screens for activity. All six of the additional proteins displayed esterase activity significantly above background. These findings demonstrate that novel proteins with enzyme-like properties are surprisingly common in focused libraries designed by binary patterning. Moreover, the activity of these unselected proteins provides a reference state for the levels of activity that have been obtained by selection and/or computational design.
Wei
Yinan
Y
Department of Chemistry, Princeton University, Princeton, NJ 08544, USA.
Hecht
Michael H
MH
D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry*; D002384:Catalysis; D004798:Enzymes / Q000737:chemistry*; D004926:Escherichia coli / Q000378:metabolism; D004950:Esterases / Q000737:chemistry; D006863:Hydrogen-Ion Concentration; D006868:Hydrolysis; D007700:Kinetics; D009682:Magnetic Resonance Spectroscopy; D008956:Models, Chemical; D008958:Models, Molecular; D008969:Molecular Sequence Data; D019151:Peptide Library; D011487:Protein Conformation; D015202:Protein Engineering / Q000379:methods*; D011506:Proteins / Q000737:chemistry*; D017386:Sequence Homology, Amino Acid; D012984:Software; D013379:Substrate Specificity; D013997:Time Factors
D000596:Amino Acids; D004798:Enzymes; D019151:Peptide Library; D011506:Proteins; D004950:Esterases