Theory of evolutionary molecular engineering through simultaneous accumulation of advantageous mutations

Engineering of phenylacetaldehyde reductase for efficient substrate conversion in concentrated 2-propanol

Phenylacetaldehyde reductase (PAR) is suitable for the conversion of various aryl ketones and 2-alkanones to corresponding chiral alcohols. 2-Propanol acts as a substrate solvent and hydrogen donor of coupled cofactor regeneration during the conversion of substrates catalyzed by PAR. To improve the conversion efficiency in high concentrations of substrate and 2-propanol, selection of a PAR mutant library and the subsequent rearrangement of mutations were attempted. With only a single selection round and following the manual combination of advantageous mutations, PAR was successfully adapted for the conversion of high concentrations of substrate with concentrated 2-propanol. This method will be widely applicable for the engineering of enzymes potentially valuable for industry.

Biased mutation-assembling: an efficient method for rapid directed evolution through simultaneous mutation accumulation

We have developed an efficient optimization technique, 'biased mutation-assembling', for improving protein properties such as thermostability. In this strategy, a mutant library is constructed using the overlap extension polymerase chain reaction technique with DNA fragments from wild-type and phenotypically advantageous mutant genes, in which the number of mutations assembled in the wild-type gene is stochastically controlled by the mixing ratio of the mutant DNA fragments to wild-type fragments. A high mixing ratio results in a mutant composition biased to favor multiple-point mutants. We applied this strategy to improve the thermostability of prolyl endopeptidase from Flavobacterium meningosepticum as a case study and found that the proportion of thermostable mutants in a library increased as the mixing ratio was increased. If the proportion of thermostable mutants increases, the screening effort needed to find them should be reduced. Indeed, we isolated a mutant with a 1200-fold longer activity half-life at 60 degrees C than that of wild-type prolyl endopeptidase after screening only 2000 mutants from a library prepared with a high mixing ratio. Our results indicate that an aggressive accumulation of advantageous mutations leads to an increase in the quality of the mutant library and a reduction in the screening effort required to find superior mutants.

Modeling and Analysis of Protein Design under Resource Constraints

The potency, or fitness, of a protein-based drug can be enhanced by changing the sequence of its underlying protein. We present a novel stochastic model for the sequence-fitness relation, and estimate its four parameters from industrial data. Using this model, we formulate and analyze two variants of the protein design problem. In the single-period design problem, the designer needs to decide under capacity constraints which set of sequences to screen in order to maximize the expected fitness of the best sequence in the set. In the more general two-period design problem, the designer can afford two screening rounds and needs to allocate resources optimally across the two periods to maximize the same objective function. Analytical and simulation results allow us to assess the utility of the proposed design strategies for various parameter regimes.

An in silico exploration of the neutral network in protein sequence space

Designating amino-acid sequences that fold into a common main-chain structure as "neutral sequences" for the structure, regardless of their function or stability, we investigated the distribution of neutral sequences in protein sequence space. For four distinct target structures (alpha, beta,alpha/beta and alpha+beta types) with the same chain length of 108, we generated the respective neutral sequences by using the inverse folding technique with a knowledge-based potential function. We assumed that neutral sequences for a protein structure have Z scores higher than or equal to fixed thresholds, where thresholds are defined as the Z score for the corresponding native sequence (case 1) or much greater Z score (case 2). An exploring walk simulation suggested that the neutral sequences mapped into the sequence space were connected with each other through straight neutral paths and formed an inherent neutral network over the sequence space. Through another exploring walk simulation, we investigated contiguous regions between or among the neutral networks for the distinct protein structures and obtained the following results. The closest approach distance between the two neutral networks ranged from 5 to 29 on the Hamming distance scale, showing a linear increase against the threshold values. The sequences located at the "interchange" regions between the two neutral networks have intermediate sequence-profile-scores for both corresponding structures. Introducing a "ball" in the sequence space that contains at least one neutral sequence for each of the four structures, we found that the minimal radius of the ball that is centered at an arbitrary position ranged from 35 to 50, while the minimal radius of the ball that is centered at a certain special position ranged from 20 to 30, in the Hamming distance scale. The relatively small Hamming distances (5-30) may support an evolution mechanism by transferring from a network for a structure to another network for a more beneficial structure via the interchange regions.

Surveying a local fitness landscape of a protein with epistatic sites for the study of directed evolution

We present a method for analysis of a fitness landscape of a biopolymer with significantly epistatic sites. The analysis is based on a quasi-additive fitness model. The fitness model is constructed with additive terms conducted by "site-fitness" and epistatic terms conducted by "pair-fitness," where the site-fitness is a fitness contribution from an independent residue and the pair-fitness is a fitness contribution from a pair of epistatic residues. As a case study, we analyzed the sequence-fitness data for 45 clones of thermostable prolyl endopeptidase mutants. They were generated by a mutation scrambling method, which can accumulate advantageous mutations. The fitness contributions from 14 single-point mutations including E67Q and Q656R were identified by the analysis. As a result, we found that the fitness model with a significant epistatic term by a pair of the 67th site and 656th site was in good agreement with the experimental data and that the explored landscape in the binary 14-dimensional sequence space is still a mountainous landscape with twin peaks. The validity was supported by the analysis of mutant fitness distributions derived from another mutation scrambling experiment and by (3D) structural data.

De novo design of biocatalysts

The challenging field of de novo enzyme design is beginning to produce exciting results. The application of powerful computational methods to functional protein design has recently succeeded at engineering target activities. In addition, efforts in directed evolution continue to expand the transformations that can be accomplished by existing enzymes. The engineering of completely novel catalytic activity requires traversing inactive sequence space in a fitness landscape, a feat that is better suited to computational design. Optimizing activity, which can include subtle alterations in backbone conformation and protein motion, is better suited to directed evolution, which is highly effective at scaling fitness landscapes towards maxima. Improved rational design efforts coupled with directed evolution should dramatically improve the scope of de novo enzyme design.

A cross-section of the fitness landscape of dihydrofolate reductase

In vitro molecular evolution is regarded as a hill-climbing on a fitness landscape in sequence space, where the 'fitness' is a quantitative measure of a certain physicochemical property of a biopolymer. We analyzed a 'cross-section' of the enzymatic activity landscape of dihydrofolate reductase (DHFR) by using a method of analysis of a fitness landscape. We limited the sequence space of interest to the five-dimensional sequence space, where the coordinate corresponds to the 1st, 16th, 20th, 42nd and 92nd site in the DHFR sequence. Thirty six mutants mapped into the limited sequence space were taken in the analysis. As a result, the cross-section is of the rough Mt Fuji type based on the mutational additivity. The ratio of the mean slope to the roughness is 2.8 and the Z-score of the original ratio against a distribution of random references is 7.0, which indicates a large statistical significance. The existence of such a cross-section was discussed in terms of the occurrence probability of sets of five sites distantly separated from each other on the DHFR 3D structure. Our results support the effectiveness of the evolution strategy which exploits the accumulation of advantageous single point mutations in such a cross-section.