Improving the thermal stability of Proteus mirabilis lipase based on multiple computational design strategies / 生物工程学报

Proteus mirabilis lipase (PML) features tolerance to organic solvents and great potential for biodiesel synthesis. However, the thermal stability of the enzyme needs to be improved before it can be used industrially. Various computational design strategies are emerging methods for the modification of enzyme thermal stability. In this paper, the complementary algorithm-based ABACUS, PROSS, and FoldX were employed for positive selection of PML mutations, and their pairwise intersections were further subjected to negative selection by PSSM and GREMLIN to narrow the mutation library. Thereby, 18 potential single-point mutants were screened out. According to experimental verification, 7 mutants had melting temperature (Tm) improved, and the ΔTm of K208G and G206D was the highest, which was 3.75 ℃ and 3.21 ℃, respectively. Five mutants with activity higher than the wild type (WT) were selected for combination by greedy accumulation. Finally, the Tm of the five-point combination mutant M10 increased by 10.63 ℃, and the relative activity was 140% that of the WT. K208G and G206D exhibited certain epistasis during the combination, which made a major contribution to the improvement of the thermal stability of M10. Molecular dynamics simulation indicated that new forces were generated at and around the mutation sites, and the rearrangement of forces near G206D/K208G might stabilize the Ca2+ binding site which played a key role in the stabilization of PML. This study provides an efficient and user-friendly computational design scheme for the thermal stability modification of natural enzymes and lays a foundation for the modification of PML and the expansion of its industrial applications.

Structure-based optimization and design of CRISPR protein xCas9 / 生物工程学报

Streptococcus pyogenes Cas9 (SpCas9) has become a powerful genome editing tool, but has a limited range of recognizable protospacer adjacent motifs (PAMs) and shows off-target effects. To address these issues, we present a rational approach to optimize the xCas9 mutant derived from SpCas9 by directed evolution. Firstly, energy minimization with the Rosetta program was applied to optimize the three-dimensional structure of Cas9 to obtain the lowest energy conformation. Subsequently, combinatorial mutations were designed based on the mutations sites of xCas9 acquired during the directed evolution. Finally, optimal mutants were selected from the designed mutants by free energy ranking and subjected to experimental verification. A new mutant yCas9 (262A/324R/409N/480K/543D/694L/1219T) with multiple PAM recognition ability and low off-target effects was obtained and verified by DNA cleavage experiments. This mutant recognizes the NG, GAA and GAT PAMs and shows low off-target DNA cleavage activity guided by mismatched sgRNA, thus provides a gene editing tool with potential applications in biomedical field. Furthermore, we performed molecular dynamics simulations on the structures of SpCas9, xCas9 and yCas9 to reveal the mechanisms of their PAM recognition and off-target effects. These may provide theoretical guidance for further optimization and modification of CRISPR/Cas9 proteins.

Computation-aided design of the flexible region of zearalenone hydrolase improves its thermal stability / 生物工程学报

The zearalenone hydrolase (ZHD101) derived from Clonostachys rosea can effectively degrade the mycotoxin zearalenone (ZEN) present in grain by-products and feed. However, the low thermal stability of ZHD101 hampers its applications. High throughput screening of variants using spectrophotometer is challenging because the reaction of hydrolyzing ZEN does not change absorbance. In this study, we used ZHD101 as a model enzyme to perform computation-aided design followed by experimental verification. By comparing the molecular dynamics simulation trajectories of ZHD101 at different temperatures, 32 flexible sites were selected. 608 saturated mutations were introduced into the 32 flexible sites virtually, from which 12 virtual mutants were screened according to the position specific score and enzyme conformation free energy calculation. Three of the mutants N156F, S194T and T259F showed an increase in thermal melting temperature (ΔTm>4 °C), and their enzyme activities were similar to or even higher than that of the wild type (relative enzyme activity 95.8%, 131.6% and 169.0%, respectively). Molecular dynamics simulation analysis showed that the possible mechanisms leading to the improved thermal stability were NH-π force, salt bridge rearrangement, and hole filling on the molecular surface. The three mutants were combined iteratively, and the combination of N156F/S194T showed the highest thermal stability (ΔTm=6.7 °C). This work demonstrated the feasibility of engineering the flexible region to improve enzyme performance by combining virtual computational mutations with experimental verification.

Protein modeling and design based on deep learning / 生物工程学报

The accumulation of protein sequence and structure data allows researchers to obtain large amount of descriptive information, simultaneously it poses an urgent need for researchers to extract information from existing data efficiently and apply it to downstream tasks. Protein design enables the development of novel proteins that are no longer restricted by experimental conditions, which is of great significance for drug target prediction, drug discovery, and material design. As an efficient method for data feature extraction, deep learning can be used to model protein data, and further add a priori information to design novel proteins. Therefore, protein design based on deep learning has become a promising approach despite of many challenges. This review summarizes the deep learning-based modeling and design methods of protein sequence and structure data, highlighting the strategies, principle, scope of application and case studies, with the aim to provide a valuable reference for relevant researchers.

Improving the thermal stability of Bacillus subtilis lipase based on multiple computational design strategies / 生物工程学报

Improving the thermal stability of enzymes is a hot and difficult point in the field of biocatalysis. Compared with the traditional directed evolution, computational assisted rational design is more efficient, and is widely used in enzyme engineering. Using Bacillus subtilis LipA as the model protein, the structure cavity of the enzyme was analyzed by Rosetta-VIP design, the mutation which was beneficial to the filling of the structure cavity (ΔΔE<0) was selected, followed by the solvent accessible surface area and evolutionary conservation analysis. The thermal stabilities of six out of sixteen designed single-point mutants were improved, with a maximum ΔTm value of 3.18 °C. These six mutations were further used for iterative combination mutation, the maximum ΔTm of the two-point and three-point combination mutants were 4.04 °C and 5.13 °C, respectively. The Tm of the four-point combination mutant M11 (F17A/L114P/I135V/M137L) was increased by 7.30 °C. The Tm of the six-point combination mutant M10 (F17A/V74I/L114P/I135V/M137A/I157L) was increased by 7.43 °C. The thermal stability of mutation with lower energy value, reduced accessible surface area, while conformed to evolutionary conservatism, was more likely to be improved. Therefore, the multiple virtual screening strategy based on the enzyme structure cavity filling, solvent accessible surface area and amino acid sequence conservation analysis can effectively improve the thermal stability of enzyme.

Application of Protein Design Method Based on The HNP Model and Relative Entropy for Different Protein Systems / 生物化学与生物物理进展

The application of the protein design method based on the HNP model and the relative entropy theory is discussed for four structural classes of real proteins, and the results are compared with that of the HP model. Testing on 190 proteins shows that this method is generally effective for the different structural classes of proteins. Further studies show that the success rate of this method on regular secondary structures is higher than that on the random coil. Additionally, the success rate for different types of amino acids is also analyzed. It is found that the success rate on the hydrophilic residues is higher than those of the other two types. Furthermore, the success rate of this method on the conserved residues is higher than the non-conserved residues. The reasons resulting in the difference of the success rate on different systems were also analyzed. All analyses mentioned above make the foundation for the development and the application of this method in the future.