Mathematical expressions useful in the construction, description and evaluation of protein libraries

Bosley, Allen D.; Ostermeier, Marc

doi:10.1016/j.bioeng.2004.11.002

Cited by 117 publications

(82 citation statements)

References 8 publications

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“…Much of the existing probabilistic literature on saturation mutagenesis highlights the probability of full coverage as a criterion (1,5,11). Indeed, this criterion is used in practice (7).…”

Section: Discussionmentioning

confidence: 99%

“…The probabilistic literature on saturation mutagenesis (1,5,8,11) focuses mainly on two mathematical quantities: the first is the expected percentage of variant space that is represented in the library, and the second is the probability of "full coverage," i.e., the probability that the library contains all of variant space. Which quantity is more meaningful to the practitioner?…”

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confidence: 99%

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When Second Best Is Good Enough: Another Probabilistic Look at Saturation Mutagenesis

Nov

2012

Appl Environ Microbiol

103

107

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We developed new criteria for determining the library size in a saturation mutagenesis experiment. When the number of all possible distinct variants is large, any of the top-performing variants (e.g., any of the top three) is likely to meet the design requirements, so the probability that the library contains at least one of them is a sensible criterion for determining the library size. By using a criterion of this type, one may significantly reduce the library size and thus save costs and labor while minimally compromising the quality of the best variant discovered. We present the probabilistic tools underlying these criteria and use them to compare the efficiencies of four randomization schemes: NNN, which uses all 64 codons; NNB, which uses 48 codons; NNK, which uses 32 codons; and MAX, which assigns equal probabilities to each of the 20 amino acids. MAX was found to be the most efficient randomization scheme and NNN the least efficient. TopLib, a computer program for carrying out the related calculations, is available through a user-friendly Web server. Saturation mutagenesis (also called oligonucleotide-directed randomization) is a protein-engineering technique that has been used widely and successfully to improve protein properties such as catalytic activity, enantioselectivity, thermostability, and binding affinity (3,12,14,16). We use the term "activity" for the protein's property under optimization, but the methodology developed below is aimed at any desirable protein feature that may be influenced by mutation.In saturation mutagenesis, one or more positions along the protein sequence are identified as likely to accommodate beneficial mutations and are then randomized, i.e., the amino acids at these positions are replaced by random ones. The randomization originates at the DNA level, typically via degenerate primers containing a mixture of sequences at the chosen codons. To decrease the chances of introducing a premature stop codon, reduced codon sets are often used: NNB, NNS, and NNK codons (where N ϭ A/C/G/T, B ϭ C/G/T, S ϭ C/G, and K ϭ G/T) are popular choices that still encode all 20 amino acids, but the use of codon sets encoding fewer amino acids has been also advocated (9, 15). More sophisticated randomization schemes, such as MAX (6, 7), result in equal probabilities for all 20 amino acids (or for some predetermined subset thereof) without encoding stop codons. Either way, a large number of random variants, which together constitute a library, are produced and then screened in an attempt to discover a highly active variant among them. Clearly, the larger the library, the higher the probability of exploring more distinct variants. We shall use the term "variant space" to denote the set of all possible distinct variants in a given experiment; this space is determined by the number of positions randomized and the randomization scheme.The probabilistic literature on saturation mutagenesis (1, 5, 8, 11) focuses mainly on two mathematical quantities: the first is the expected percentage of variant spa...

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

When Second Best Is Good Enough: Another Probabilistic Look at Saturation Mutagenesis

Nov

2012

Appl Environ Microbiol

103

107

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“…The constructed library contained 1.5 ϫ 10 8 independent transformants. Thus, this library is expected to include all possible 5-mer and 4-mer substrate sequences with Ͼ95% and 99% confidence limits, respectively, assuming a random distribution (19). Using the whole-cell activity assay, a screening methodology was devised to isolate library members displaying substrates cleaved by a given protease and, thereby, identify optimal substrates.…”

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confidence: 99%

Protease specificity determination by using cellular libraries of peptide substrates (CLiPS)

Boulware¹,

Daugherty

2006

Proc. Natl. Acad. Sci. U.S.A.

111

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We report a general combinatorial approach to identify optimal substrates of a given protease by using quantitative kinetic screening of cellular libraries of peptide substrates (CLiPS). A whole-cell protease activity assay was developed by displaying fluorescent reporter substrates on the surface of Escherichia coli as N-terminal fusions. This approach enabled generation of substrate libraries of arbitrary amino acid composition and length that are self-renewing. Substrate hydrolysis by a target protease was measured quantitatively via changes in whole-cell fluorescence by using FACS. FACS enabled efficient screening to identify optimal substrates for a given protease and characterize their cleavage kinetics. The utility of CLiPS was demonstrated by determining the substrate specificity of two unrelated proteases, caspase-3 and enteropeptidase (or enterokinase). CLiPS unambiguously identified the caspase-3 consensus cleavage sequence DXVDG. Enteropeptidase was unexpectedly promiscuous, but exhibited a preference for substrates with the motif D ͞ERM, which were cleaved substantially faster than the canonical DDDDK recognition sequence, widely used for protein purification. CLiPS provides a straightforward and versatile approach to determine protease specificity and discover optimal substrates on the basis of cleavage kinetics.caspase-3 ͉ enteropeptidase ͉ FACS ͉ peptidase P roteolytic enzymes play central roles in most biological processes. At the same time, proteases are implicated in the pathogenesis of diverse diseases ranging from viral and bacterial infections (1) to cancer and neurodegenerative diseases (2, 3). The biological functions of proteases, or peptidases, are largely determined by the spectrum of biologically occurring substrates. Frequently, substrate specificity has been inferred by comparison and alignment of known, physiological substrates (4). Given this information, individually synthesized fluorogenic peptide substrates have been used extensively to measure protease activity (5). More recently, the substrate specificity of a small group of proteases has been characterized in greater detail by using combinatorial peptide libraries (6, 7). Library-based approaches to characterize specificity have contributed substantially to our understanding of protease function (6, 7). Nevertheless, quantitative characterization of protease specificity and substrate cleavage kinetics remains a bottleneck in basic and applied biological research (6,8).Among combinatorial methods, the ''substrate phage'' approach has been used to define the substrate specificities of Ϸ30 proteases and has been recently reviewed (6). In this approach, a library of peptide substrates is displayed on the surface of filamentous bacteriophage (9) as fusions between a surface-anchoring affinity domain and the display scaffold protein, typically the phage minor coat protein GPIII. The substrate library then is allowed to bind to a solid surface via the affinity domain. Phage liberated from the surface by proteolytic cleavage are rec...

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“…The ester (rac)-1 was used as screening substrate for the spectrophotometric activity assay. We assayed 2,400 transformants, which corresponds to a sequence coverage of 90% (46). Of all the screened variants, only a small group displayed good activity toward substrate 1.…”

Section: Resultsmentioning

confidence: 99%

Combinatorial reshaping of the Candida antarctica lipase A substrate pocket for enantioselectivity using an extremely condensed library

Sandström

Wikmark

Engström

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

125

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A highly combinatorial structure-based protein engineering method for obtaining enantioselectivity is reported that results in a thorough modification of the substrate binding pocket of Candida antarctica lipase A (CALA). Nine amino acid residues surrounding the entire pocket were simultaneously mutated, contributing to a reshaping of the substrate pocket to give increased enantioselectivity and activity for a sterically demanding substrate. This approach seems to be powerful for developing enantioselectivity when a complete reshaping of the active site is required. Screening toward ibuprofen ester 1, a substrate for which previously used methods had failed, gave variants with a significantly increased enantioselectivity and activity. Wild-type CALA has a moderate activity with an E value of only 3.4 toward this substrate. The best variant had an E value of 100 and it also displayed a high activity. The variation at each mutated position was highly reduced, comprising only the wild type and an alternative residue, preferably a smaller one with similar properties. These minimal binary variations allow for an extremely condensed protein library. With this highly combinatorial method synergistic effects are accounted for and the protein fitness landscape is explored efficiently.kinetic resolution | library design | protein design | enzyme catalysis

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Mathematical expressions useful in the construction, description and evaluation of protein libraries

Cited by 117 publications

References 8 publications

When Second Best Is Good Enough: Another Probabilistic Look at Saturation Mutagenesis

When Second Best Is Good Enough: Another Probabilistic Look at Saturation Mutagenesis

Protease specificity determination by using cellular libraries of peptide substrates (CLiPS)

Combinatorial reshaping of the Candida antarctica lipase A substrate pocket for enantioselectivity using an extremely condensed library

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