Methods of artificial evolution such as SELEX and in vitro selection have made it possible to isolate RNA and DNA motifs with a wide range of functions from large random sequence libraries. Once the primary sequence of a functional motif is known, the sequence space around it can be comprehensively explored using a combination of random mutagenesis and selection. However, methods to explore the sequence space of a secondary structure are not as well characterized. Here we address this question by describing a method to construct libraries in a single synthesis which are enriched for sequences with the potential to form a specific secondary structure, such as that of an aptamer, ribozyme, or deoxyribozyme. Although interactions such as base pairs cannot be encoded in a library using conventional DNA synthesizers, it is possible to modulate the probability that two positions will have the potential to pair by biasing the nucleotide composition at these positions. Here we show how to maximize this probability for each of the possible ways to encode a pair (in this study defined as A-U or U-A or C-G or G-C or G.U or U.G). We then use these optimized coding schemes to calculate the number of different variants of model stems and secondary structures expected to occur in a library for a series of structures in which the number of pairs and the extent of conservation of unpaired positions is systematically varied. Our calculations reveal a tradeoff between maximizing the probability of forming a pair and maximizing the number of possible variants of a desired secondary structure that can occur in the library. They also indicate that the optimal coding strategy for a library depends on the complexity of the motif being characterized. Because this approach provides a simple way to generate libraries enriched for sequences with the potential to form a specific secondary structure, we anticipate that it should be useful for the optimization and structural characterization of functional nucleic acid motifs.

• MeSH
• Aptamers, Nucleotide genetics   MeSH
• DNA, Catalytic genetics   MeSH
• Gene Library * MeSH
• Nucleic Acid Conformation MeSH
• Mutagenesis MeSH
• Nucleotide Motifs genetics   MeSH
• Inverted Repeat Sequences genetics   MeSH
• Base Pairing MeSH
• Probability MeSH
• Directed Molecular Evolution methods   MeSH
• RNA, Catalytic genetics   MeSH
• Synthetic Biology methods   MeSH
• In Vitro Techniques MeSH
• Publication type
• Journal Article MeSH

Engineered small non-antibody protein scaffolds are a promising alternative to antibodies and are especially attractive for use in protein therapeutics and diagnostics. The advantages include smaller size and a more robust, single-domain structural framework with a defined binding surface amenable to mutation. This calls for a more systematic approach in designing new scaffolds suitable for use in one or more methods of directed evolution. We hereby describe a process based on an analysis of protein structures from the Protein Data Bank and their experimental examination. The candidate protein scaffolds were subjected to a thorough screening including computational evaluation of the mutability, and experimental determination of their expression yield in E. coli, solubility, and thermostability. In the next step, we examined several variants of the candidate scaffolds including their wild types and alanine mutants. We proved the applicability of this systematic procedure by selecting a monomeric single-domain human protein with a fold different from previously known scaffolds. The newly developed scaffold, called ProBi (Protein Binder), contains two independently mutable surface patches. We demonstrated its functionality by training it as a binder against human interleukin-10, a medically important cytokine. The procedure yielded scaffold-related variants with nanomolar affinity.

• MeSH
• Databases, Protein MeSH
• Interleukin-10 metabolism   MeSH
• Protein Conformation MeSH
• Computer Simulation MeSH
• Protein Engineering MeSH
• Proteins chemistry   genetics   metabolism   MeSH
• Recombinant Proteins chemistry   genetics   metabolism   MeSH
• Ribosomes metabolism   MeSH
• Directed Molecular Evolution methods   MeSH
• Amino Acid Sequence MeSH
• Protein Stability MeSH
• Protein Binding MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Protein engineering is the discipline of developing useful proteins for applications in research, therapeutic, and industrial processes by modification of naturally occurring proteins or by invention of de novo proteins. Modern protein engineering relies on the ability to rapidly generate and screen diverse libraries of mutant proteins. However, design of mutant libraries is typically hampered by scale and complexity, necessitating development of advanced automation and optimization tools that can improve efficiency and accuracy. At present, automated library design tools are functionally limited or not freely available. To address these issues, we developed Mutation Maker, an open source mutagenic oligo design software for large-scale protein engineering experiments. Mutation Maker is not only specifically tailored to multisite random and directed mutagenesis protocols, but also pioneers bespoke mutagenic oligo design for de novo gene synthesis workflows. Enabled by a novel bundle of orchestrated heuristics, optimization, constraint-satisfaction and backtracking algorithms, Mutation Maker offers a versatile toolbox for gene diversification design at industrial scale. Supported by in silico simulations and compelling experimental validation data, Mutation Maker oligos produce diverse gene libraries at high success rates irrespective of genes or vectors used. Finally, Mutation Maker was created as an extensible platform on the notion that directed evolution techniques will continue to evolve and revolutionize current and future-oriented applications.

• MeSH
• Algorithms MeSH
• Escherichia coli genetics   MeSH
• Gene Library MeSH
• Codon genetics   MeSH
• Mutation * MeSH
• Mutagenesis, Site-Directed methods   MeSH
• Mutagenesis * MeSH
• Mutant Proteins MeSH
• Oligonucleotides genetics   MeSH
• Computer Simulation MeSH
• Proteins genetics   MeSH
• Directed Molecular Evolution methods   MeSH
• Software * MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Here we present an optimized procedure to generate amino acid variations at specific site(s) of proteins, followed by a simple one-step screen for mutants with the desired β-glucosidase activity. The procedure was evaluated by introducing sequence variation into a codon specifying a non-functional variant of the catalytic nucleophile (E401) of the maize β-glucosidase Zm-p60.1. Observed and theoretically expected frequencies of the four possible variants of the codon and the two possible phenotypes (functional and non-functional) were investigated. Deviations in codon and phenotype frequencies were expressed as a coefficient. This coefficient was then used to estimate the extent of oversampling, of the mutant library, which would be necessary to compensate for the underrepresentation of some sequences. This evaluation of the overall performance of the method allows experimentally derived parameters to be incorporated into mutant library design. This method combines the application of a well-defined distribution of variability with a reliable screening process. Thus, it facilitates the production of novel functional variants of β-glucosidases for either fundamental studies or potential biotechnological applications.

• MeSH
• Amino Acids chemistry   genetics   MeSH
• Cellulases chemistry   genetics   isolation & purification   MeSH
• Escherichia coli genetics   MeSH
• Codon chemistry   genetics   MeSH
• Zea mays enzymology   MeSH
• Mutagenesis MeSH
• Directed Molecular Evolution methods   MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH