Computer-Aided Saturation Mutagenesis of Arabidopsis thaliana Ent-Copalyl Diphosphate Synthase

From in-silico screening to in-vitro evaluation: Enhancing the detection of Microcystins with engineered PP1 mutant variants

Cyanotoxins produced during harmful algal blooms (CyanoHABs) have become a worldwide issue of concern. Microcystins (MC) are the most ubiquitous group of cyanotoxins and have known carcinogenic and hepatotoxic effects. The protein phosphatase inhibition assays (PPIAs), based on the inhibition of Protein Phosphatase 1/2A (PP1/PP2A) by MC, are one of the most cost-effective options for detecting MC. In this work, we aimed to design in-silico and evaluate in-vitro mutant variants of the PP1 protein, in order to enhance their capabilities as a MC biosensor. To this end, we performed an in-silico active site-saturated mutagenesis screening, followed by stability and docking affinity calculation with the MCLR cyanotoxin. Candidates with improved both affinity and stability were further tested in a fully flexible active-site docking. The best-scored mutations (19) were individually analysed regarding their locations and interactions. Four of them (p.D197F; p.Q249Y; p.S129W; p.D220Q) were selected for in-vitro expression and evaluation. Mutant p.D197F, exhibited a significant increment in inhibition by MCLR with respect to the WT, while showing a non-significant difference in stability nor activity. This successful PP1 inhibition enhancement suggests the potential of the p.D197F variant for practical MC detection applications.

RosettaSurf—A surface-centric computational design approach

Proteins are typically represented by discrete atomic coordinates providing an accessible framework to describe different conformations. However, in some fields proteins are more accurately represented as near-continuous surfaces, as these are imprinted with geometric (shape) and chemical (electrostatics) features of the underlying protein structure. Protein surfaces are dependent on their chemical composition and, ultimately determine protein function, acting as the interface that engages in interactions with other molecules. In the past, such representations were utilized to compare protein structures on global and local scales and have shed light on functional properties of proteins. Here we describe RosettaSurf, a surface-centric computational design protocol, that focuses on the molecular surface shape and electrostatic properties as means for protein engineering, offering a unique approach for the design of proteins and their functions. The RosettaSurf protocol combines the explicit optimization of molecular surface features with a global scoring function during the sequence design process, diverging from the typical design approaches that rely solely on an energy scoring function. With this computational approach, we attempt to address a fundamental problem in protein design related to the design of functional sites in proteins, even when structurally similar templates are absent in the characterized structural repertoire. Surface-centric design exploits the premise that molecular surfaces are, to a certain extent, independent of the underlying sequence and backbone configuration, meaning that different sequences in different proteins may present similar surfaces. We benchmarked RosettaSurf on various sequence recovery datasets and showcased its design capabilities by generating epitope mimics that were biochemically validated. Overall, our results indicate that the explicit optimization of surface features may lead to new routes for the design of functional proteins.

Finely orchestrated protein-protein interactions are at the heart of virtually all fundamental cellular processes. Altering these processes or encoding new functions in proteins has been a long-standing goal in computational protein design. Protein design methods commonly rely on scoring functions that seek to identify amino acid sequences that optimize structural configurations of atoms while minimizing a variety of physics-based and statistical terms. The objectives of the large majority of computational design protocols have been focused on obtaining a predefined structural conformation. However, routinely introducing a functional aspect on designer proteins has been more challenging. Our results suggest that the molecular surface features can be a useful optimization parameter to guide the design process towards functional surfaces that mimic known protein binding sites and interact with their intended targets. Specifically, we demonstrate that our design method can optimize experimental libraries through computational screening, creating a basis for highly specific protein binders, as well as design a potent immunogen that engages with site-specific antibodies. The ability to create proteins with novel functions will be transformative for biomedical applications, providing many opportunities for the design of novel immunogens, protein components for synthetic biology, and other protein-based biotechnologies.

Mining methods and typical structural mechanisms of terpene cyclases

Terpenoids, formed by cyclization and/or permutation of isoprenes, are the most diverse and abundant class of natural products with a broad range of significant functions. One family of the critical enzymes involved in terpenoid biosynthesis is terpene cyclases (TCs), also known as terpene synthases (TSs), which are responsible for forming the ring structure as a backbone of functionally diverse terpenoids. With the recent advances in biotechnology, the researches on terpene cyclases have gradually shifted from the genomic mining of novel enzyme resources to the analysis of their structures and mechanisms. In this review, we summarize both the new methods for genomic mining and the structural mechanisms of some typical terpene cyclases, which are helpful for the discovery, engineering and application of more and new TCs.

Dynamic Analyses of Transcriptome and Metabolic Profiling: Revealing Molecular Insight of Aroma Synthesis of Mango (Mangifera indica L. Var. Tainong)

This study aimed to evaluate the changes in aromatic components and other chemical properties of Tainong mango during fruit development, ripening, and storage. As the volatiles of Tainong mango and their related molecular mechanisms remain unclear, volatile profile, metabonomics, and transcriptome analyses were applied to investigate the molecular determinants of the synthesis of aroma components in mango during fruit development and storage. Total acids, total sugar, total carotenoids, enzyme activities of the mango pulp samples were also determined. Volatile components of the mango pulp samples were identified using a gas chromatography-mass spectrometric method. Ribonucleic acid (RNA) sequences of the samples were analyzed by real-time polymerase chain reaction. The results showed that 181 volatiles were isolated and identified in the fruit at seven stages. Compared to the other stages, mango collected on day 8 and day 12 had higher concentrations of 17 volatile components, especially (E,Z)-2,6-nonadienal, 53384 transcripts were also detected through RNA sequencing. The differentially expressed genes analyses included catalytic activity, transferase activity, adenosine diphosphate binding, transcription factor activity, and oxidoreductase activity. α-Pinene content and expression of the differentially expressed genes involved in terpenoid metabolism and enzyme activities in the terpenoid metabolic pathways gradually increased during the maturity of the fruit, and had maximum values at day 8 of storage. Moreover, the integrative analyses revealed potential molecular insights of mango development and aroma formation in the fruit.

A Major Locus on Wheat Chromosome 7B Associated With Late-Maturity α-Amylase Encodes a Putative ent-Copalyl Diphosphate Synthase

Many wheat varieties have the potential to develop unacceptably high levels of α-amylase in the grains if exposed to a cool temperature shock or simply cool temperature during the early to middle stages of grain filling. This phenomenon is referred to as late maturity α-amylase (LMA). The enzyme persists in the grain until harvest and may result in wheat with a low Falling Number that does not meet receival and export specifications. Resistance to LMA is therefore a valuable target for wheat breeders and wheat industries in general. Genetic evidence implicating a locus on the long arm of chromosome 7B in variation in LMA phenotype was confirmed in this investigation. Through intensive fine-mapping an ent-copalyl diphosphate synthase (CPS), hitherto named LMA-1, was identified as the likely candidate gene associated with variation in LMA phenotype. Single Nucleotide Polymorphisms (SNPs) within the LMA-1 coding sequence of Chinese Spring, Maringa and Halberd result in either prematurely terminated or functionally altered proteins that are associated with useful levels of resistance to LMA. LMA-1 transcripts detected in de-embryonated grain tissue from around 15 days after anthesis, several days before the synthesis of α-amylase, were low in the resistant varieties Chinese Spring and Maringa compared with LMA susceptible genotype Spica. This was associated with a dramatic reduction in the concentrations of intermediates in the gibberellin biosynthesis pathway such as GA₁₉, evidence that LMA-1 was functioning as CPS in the gibberellin biosynthesis pathway. A survey of a large collection of Australian and international wheat varieties distinguished 9 major haplotypes at the LMA-1 locus. Generally, within classes, there was notable variation for LMA phenotype and evidence for genotypes whose resistance is presumed to be due to genetic loci located elsewhere on the wheat genome. Further investigation is required to characterize the sequence of steps between LMA-1 and α-amylase synthesis as well as to gain a better understanding of the role and potential impact of other genetic loci. Diagnostic markers for sources of resistance and SNP variation reported in this study should assist breeders to deploy resistance associated with LMA-1 variants in breeding programs.

Transcriptomic analysis of tea plant (Camellia sinensis) revealed the co-expression network of 4111 paralogous genes and biosynthesis of quality-related key metabolites under multiple stresses

The tea plant is an essential economic plant in many countries. However, its growing season renders them vulnerable to stresses. To understand the transcriptomic influences of these stresses on tea plants, we sequenced and analyzed the transcriptomes under drought, high-temperature, and pest. Paralogs were identified by comparing 14 evolutionarily close genomes. The differentially expressed paralog (DEPs) genes were analyzed regarding single or multiple stresses, and 1075 of the 4111 DEPs were commonly found in all the stresses. The co-expression network of the DEPs and TFs indicated that genes of catechin biosynthesis were associated with most transcription factors specific to each stress. The genes playing a significant role in the late response to drought and pest stress mainly functioned in the early response to high-temperature. This study revealed the relationship between stress and regulation of QRM synthesis and the role of QRMs in response to these (a)biotic stresses.

Improving enzyme activity of glucosamine-6-phosphate synthase by semi-rational design strategy and computer analysis

OBJECTIVE

To improve enzyme activity of Glucosamine-6-phosphate synthase (Glms) of Bacillus subtilis by site saturation mutagenesis at Leu₅₉₃, Ala₅₉₄, Lys₅₉₅, Ser₅₉₆ and Val₅₉₇ based on computer-aided semi-rational design.

RESULTS

The results indicated that L₅₉₃S had the greatest effect on the activity of BsGlms and the enzyme activity increased from 5 to 48 U/mL. The mutation of L₅₉₃S increased the yield of glucosamine by 1.6 times that of the original strain. The binding energy of the mutant with substrate was reduced from - 743.864 to - 768.246 kcal/mol. Molecular dynamics simulation results showed that Ser₅₉₃ enhanced the flexibility of the protein, which ultimately led to increased enzyme activity.

CONCLUSION

We successfully improved BsGlms activity through computer simulation and site saturation mutagenesis. This combination of methodologies may fit into an efficient workflow for improving Glms and other proteins activity.