Crystal structure of Thermus thermophilus methylenetetrahydrofolate dehydrogenase and determinants of thermostability

Targeting allosteric binding site in methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) to identify natural product inhibitors via structure-based computational approach

Cancer has been viewed as one of the deadliest diseases worldwide. Among various types of cancer, breast cancer is the most common type of cancer in women. Methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) is a promising druggable target and is overexpressed in cancerous cells, like, breast cancer. We conducted structure-based modeling on the allosteric site of the enzyme. Targeting the allosteric site avoids the problem of drug resistance. Pharmacophore modeling, molecular docking, HYDE assessment, drug-likeness, ADMET predictions, simulations, and free-energy calculations were performed. The RMSD, RMSF, RoG, SASA, and Hydrogen-bonding studies showed that seven candidates displayed stable behaviour. As per the literature, average superimposed simulated structures revealed a similar protein conformational change in the αE'-βf' loop, causing its displacement away from the allosteric site. The MM-PBSA showed tight binding of six compounds with the allosteric pocket. The effect of inhibitors interacting in the allosteric site causes a decrease in the binding energy of J49 (active-site inhibitor), suggesting the effect of allosteric binding. The PCA and FEL analysis revealed the significance of the docked compounds in the stable behaviour of the complexes. The outcome can contribute to the development of potential natural products with drug-like properties that can inhibit the MTHFD2 enzyme.

Computer-aided design of novel cellobiose 2-epimerase for efficient synthesis of lactulose using lactose

Cellobiose 2-epimerase (CE) is ideally suited to synthesize lactulose from lactose, but the poor thermostability and catalytic efficiency restrict enzymatic application. Herein, a non-characterized CE originating from Caldicellulosiruptor morganii (CmCE) was discovered in the NCBI database. Then, a smart mutation library was constructed based on FoldX ΔΔG calculation and modeling structure analysis, from which a positive mutant D226G located within the α₈/α₉ loop exhibited longer half-lives at 65-75 °C as well as lower K_m and higher k_cat/K_m values compared with CmCE. Molecular modeling demonstrated that the improvement of D226G was largely attributed to the rigidification of the flexible loop, the compactness of the catalysis pocket and the increment of substrate-binding capability. Finally, the yield of synthesizing lactulose catalyzed by D226G reached 45.5%, higher than the 35.9% achieved with CmCE. The disclosed effect of the flexible loop on enzymatic stability and catalysis provides insight to redesign efficient CEs to biosynthesize lactulose.

Modeling the role of charged residues in thermophilic proteins by rotamer and dynamic cross correlation analysis

Discerning the determinants of protein thermostability is very important both from the theoretical and applied perspective. Different lines of evidence seem to indicate that a dynamical network of salt bridges/charged residues plays a fundamental role in the thermostability of enzymes. In this work, we applied measures of dynamic variance, like the Gini coefficients, Kullback-Leibler (KL) divergence and dynamic cross correlation (DCC) coefficients to compare the behavior of 3 pairs of homologous proteins from the thermophilic bacterium Thermus thermophilus and mesophilic Escherichia coli. Molecular dynamic (MD) simulations of these proteins were performed at 303 K and 363 K. In the characterization of their side chain rotamer distributions, the corresponding Gini coefficients and KL-divergence both revealed significant correlations with temperature. Similarly, a DCC analysis revealed a higher trend to de-correlate the movement of charged residues at higher temperatures in the thermophilic proteins, when compared with their mesophilic homologues. These results highlight the importance of dynamic electrostatic network interactions for the thermostability of enzymes.

A proteomics-MM/PBSA dual approach for the analysis of SARS-CoV-2 main protease substrate peptide specificity

The main protease M^pro of SARS-CoV-2 is a well-studied major drug target. Additionally, it has been linked to this virus' pathogenicity, possibly through off-target effects. It is also an interesting diagnostic target. To obtain more data on possible substrates as well as to assess the enzyme's primary specificity a two-step approach was introduced. First, Terminal Amine Isobaric Labeling of Substrates (TAILS) was employed to identify novel M^pro cleavage sites in a mouse lung proteome library. In a second step, using a structural homology model, the MM/PBSA variant MM/GBSA (Molecular Mechanics Poisson-Boltzmann/Generalized Born Surface Area) free binding energy calculations were carried out to determine relevant interacting amino acids. As a result, 58 unique cleavage sites were detected, including six that displayed glutamine at the P1 position. Furthermore, modeling results indicated that M^pro has a far higher potential promiscuity towards substrates than expected. The combination of proteomics and MM/PBSA modeling analysis can thus be useful for elucidating the specificity of M^pro, and thus open novel perspectives for the development of future peptidomimetic drugs against COVID-19, as well as diagnostic tools.

Development of thermostable sucrose phosphorylase by semi-rational design for efficient biosynthesis of alpha-D-glucosylglycerol

Abstract

Sucrose phosphorylase (SPase) can specifically catalyze transglycosylation reactions and can be used to enzymatically synthesize α-D-glycosides. However, the low thermostability of SPase has been a bottleneck for its industrial application. In this study, a SPase gene from Leuconostoc mesenteroides ATCC 12,291 (LmSPase) was synthesized with optimized codons and overexpressed successfully in Escherichia coli. A semi-rational design strategy that combined the FireProt (a web server designing thermostable proteins), structure–function analysis, and molecular dynamic simulations was used to improve the thermostability of LmSPase. Finally, one single-point mutation T219L and a combination mutation I31F/T219L/T263L/S360A (Mut4) with improved thermostability were obtained. The half-lives at 50 °C of T219L and Mut4 both increased approximately two-fold compared to that of wild-type LmSPase (WT). Furthermore, the two variants T219L and Mut4 were used to produce α-D-glucosylglycerol (αGG) from sucrose and glycerol by incubating with 40 U/mL crude extracts at 37 °C for 60 h and achieved the product concentration of 193.2 ± 12.9 g/L and 195.8 ± 13.1 g/L, respectively, which were approximately 1.3-fold higher than that of WT (150.4 ± 10.0 g/L). This study provides an effective strategy for improving the thermostability of an industrial enzyme.

Key points

• Predicted potential hotspot residues directing the thermostability of LmSPase by semi-rational design

• Screened two positive variants with higher thermostability and higher activity

• Synthesized α-D-glucosylglycerol to a high level by two screened positive variants

Supplementary Information

The online version contains supplementary material available at 10.1007/s00253-021-11551-0.

From Enzyme Stability to Enzymatic Bioelectrode Stabilization Processes

Bioelectrocatalysis using redox enzymes appears as a sustainable way for biosensing, electricity production, or biosynthesis of fine products. Despite advances in the knowledge of parameters that drive the efficiency of enzymatic electrocatalysis, the weak stability of bioelectrodes prevents large scale development of bioelectrocatalysis. In this review, starting from the understanding of the parameters that drive protein instability, we will discuss the main strategies available to improve all enzyme stability, including use of chemicals, protein engineering and immobilization. Considering in a second step the additional requirements for use of redox enzymes, we will evaluate how far these general strategies can be applied to bioelectrocatalysis.

Dynamic cross correlation analysis of Thermus thermophilus alkaline phosphatase and determinants of thermostability

BACKGROUND

Understanding the determinants of protein thermostability is very important both from the theoretical and applied perspective. One emerging view in thermostable enzymes seems to indicate that a salt bridge/charged residue network plays a fundamental role in their thermostability.

METHODS

The structure of alkaline phosphatase (AP) from Thermus thermophilus HB8 was solved by X-ray crystallography at 2.1 Å resolution. The obtained structure was further analyzed by molecular dynamics studies at different temperatures (303 K, 333 K and 363 K) and compared to homologous proteins from the cold-adapted organisms Shewanella sp. and Vibrio strain G15-21. To analyze differences in measures of dynamic variation, several data reduction techniques like principal component analysis (PCA), residue interaction network (RIN) analysis and rotamer analysis were used. Using hierarchical clustering, the obtained results were combined to determine residues showing high degree dynamical variations due to temperature jumps. Furthermore, dynamic cross correlation (DCC) analysis was carried out to characterize networks of charged residues.

RESULTS

Top clustered residues showed a higher propensity for thermostabilizing mutations, indicating evolutionary pressure acting on thermophilic organisms. The description of rotamer distributions by Gini coefficients and Kullback-Leibler (KL) divergence both revealed significant correlations with temperature. DCC analysis revealed a significant trend to de-correlation of the movement of charged residues at higher temperatures.

SIGNIFICANCE

The de-correlation of charged residues detected in Thermus thermophilus AP, highlights the importance of dynamic electrostatic network interactions for the thermostability of this enzyme.