Dataset Information

Enhancing the thermostability and activity of glycosyltransferase UGT76G1 via computational design.

ABSTRACT: The diterpene glycosyltransferase UGT76G1, derived from Stevia rebaudiana, plays a pivotal role in the biosynthesis of rebaudioside A, a natural sugar substitute. Nevertheless, its potential for industrial application is limited by certain enzymatic characteristics, notably thermostability. To enhance the thermostability and enzymatic activity, we employed a computational design strategy, merging stabilizing mutation scanning with a Rosetta-based protein design protocol. Compared to UGT76G1, the designed variant 76_4 exhibited a 9 °C increase in apparent T_m, a 2.55-fold increase rebaudioside A production capacity, and a substantial 11% reduction in the undesirable byproduct rebaudioside I. Variant 76_7 also showed a 1.91-fold enhancement rebaudioside A production capacity, which was maintained up to 55 °C, while the wild-type lost most of its activity. These results underscore the efficacy of structure-based design in introducing multiple mutations simultaneously, which significantly improves the enzymatic properties of UGT76G1. This strategy provides a method for the development of efficient, thermostable enzymes for industrial applications.

SUBMITTER: Go SR

PROVIDER: S-EPMC10700650 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Enhancing the thermostability and activity of glycosyltransferase UGT76G1 via computational design.

Go Seong-Ryeong SR Lee Su-Jin SJ Ahn Woo-Chan WC Park Kwang-Hyun KH Woo Eui-Jeon EJ

Communications chemistry 20231206 1

The diterpene glycosyltransferase UGT76G1, derived from Stevia rebaudiana, plays a pivotal role in the biosynthesis of rebaudioside A, a natural sugar substitute. Nevertheless, its potential for industrial application is limited by certain enzymatic characteristics, notably thermostability. To enhance the thermostability and enzymatic activity, we employed a computational design strategy, merging stabilizing mutation scanning with a Rosetta-based protein design protocol. Compared to UGT76G1, the ...[more]

PMID: 38057441

Similar Datasets

Project description:The good thermostability of enzymes is an important basis for their wide application in industry. In this study, the phytase APPA from Yersinia intermedia was designed by evolution-guided design. Through the collection of homologous sequences in the NCBI database, we obtained a sequence set composed of 5,569 sequences, counted the number and locations of motif N-X-T/S, and selected the sites with high frequency in evolution as candidate sites for experiments. Based on the principle that N-glycosylation modification sites are located on the protein surface, 13 mutants were designed to optimize the number and location of N-glycosylation sites. Through experimental verification, 7 single mutants with improved thermostability were obtained. The best mutant, M14, with equal catalytic efficiency as the wild-type was obtained through combined mutation. The half-life (t1/2) value of mutant M14 was improved from 3.32 min at 65°C to 25 min of at 100°C, allowing it to withstand boiling water treatment, retaining approximately 75% initial activity after a 10-min incubation at 100°C. Differential scanning calorimetry analysis revealed that while the mutants' thermodynamic stability was nearly unchanged, their kinetic stability was greatly improved, and the combined mutant exhibited strong refolding ability. The results of a in vitro digestibility test indicated that the application effect of mutant M14 was about 4.5 times that of wild-type APPA, laying a foundation for its industrial application. IMPORTANCE Due to the harsh reaction conditions of industrial production, the relative instability of enzymes limits their application in industrial production, such as for food, pharmaceuticals, and feed. For example, the pelleting process of feed includes a brief high temperature (80 to 85°C), which requires the enzyme to have excellent thermostability. Therefore, a simple and effective method to improve the thermostability of enzymes has important practical value. In this study, we make full use of the existing homologous sequences (5,569) in the database to statistically analyze the existence frequency of N-X-T/S motifs in this large sequence space to design the phytase APPA with improved thermostability and a high hit rate (~50%). We obtained the best combination mutant, M14, that can tolerate boiling water treatment and greatly improved its kinetic stability without damaging its specific activity. Simultaneously, we proved that its performance improvement is due to its enhanced refolding ability, which comes from N-glycan modification rather than amino acid replacement. Our results provide a feasible and effective method for the modification of enzyme thermostability.

Project description:Over the past two decades, therapeutic antibodies have emerged as a rapidly expanding domain within the field of biologics. In silico tools that can streamline the process of antibody discovery and optimization are critical to support a pipeline that is growing more numerous and complex every year. High-quality structural information remains critical for the antibody optimization process, but antibody-antigen complex structures are often unavailable and in silico antibody docking methods are still unreliable. In this study, DeepAb, a deep learning model for predicting antibody Fv structure directly from sequence, was used in conjunction with single-point experimental deep mutational scanning (DMS) enrichment data to design 200 potentially optimized variants of an anti-hen egg lysozyme (HEL) antibody. We sought to determine whether DeepAb-designed variants containing combinations of beneficial mutations from the DMS exhibit enhanced thermostability and whether this optimization affected their developability profile. The 200 variants were produced through a robust high-throughput method and tested for thermal and colloidal stability (Tonset, Tm, Tagg), affinity (KD) relative to the parental antibody, and for developability parameters (nonspecific binding, aggregation propensity, self-association). Of the designed clones, 91% and 94% exhibited increased thermal and colloidal stability and affinity, respectively. Of these, 10% showed a significantly increased affinity for HEL (5- to 21-fold increase) and thermostability (>2.5C increase in Tm1), with most clones retaining the favorable developability profile of the parental antibody. Additional in silico tests suggest that these methods would enrich for binding affinity even without first collecting experimental DMS measurements. These data open the possibility of in silico antibody optimization without the need to predict the antibody-antigen interface, which is notoriously difficult in the absence of crystal structures.

Dataset Information

Enhancing the thermostability and activity of glycosyltransferase UGT76G1 via computational design.

Publications

Enhancing the thermostability and activity of glycosyltransferase UGT76G1 via computational design.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets