Utility of B-Factors in Protein Science: Interpreting Rigidity, Flexibility, and Internal Motion and Engineering Thermostability

Prediction of Ca2+ Binding Site in Proteins With a Fast and Accurate Method Based on Statistical Mechanics and Analysis of Crystal Structures

Predicting the precise locations of metal binding sites within metalloproteins is a crucial challenge in biophysics. A fast, accurate, and interpretable computational prediction method can complement the experimental studies. In the current work, we have developed a method to predict the location of Ca2+ ions in calcium-binding proteins using a physics-based method with an all-atom description of the proteins, which is substantially faster than the molecular dynamics simulation-based methods with accuracy as good as data-driven approaches. Our methodology uses the three-dimensional reference interaction site model (3D-RISM), a statistical mechanical theory, to calculate Ca2+ ion density around protein structures, and the locations of the Ca2+ ions are obtained from the density. We have taken previously used datasets to assess the efficacy of our method as compared to previous works. Our accuracy is 88%, comparable with the FEATURE program, one of the well-known data-driven methods. Moreover, our method is physical, and the reasons for failures can be ascertained in most cases. We have thoroughly examined the failed cases using different structural and crystallographic measures, such as B-factor, R-factor, electron density map, and geometry at the binding site. It has been found that x-ray structures have issues in many of the failed cases, such as geometric irregularities and dubious assignment of ion positions. Our algorithm, along with the checks for structural accuracy, is a major step in predicting calcium ion positions in metalloproteins.

A homo-FRET assay for patatin-specific proteolytic activity

The potato protein patatin embeds bioactive peptides that require targeted hydrolysis to be released as promising food additives. This study presents a patatin-specific protease assay for assessing a wide range of protease activities in high-throughput format. Conjugating patatin to the amine reactive fluorogenic BODIPY FL dye provided a stable protease substrate with efficient homo-FRET quenching at a low degree (7-8) of labeling. Compared to commercial BODIPY-casein, BODIPY-patatin provided higher fluorescence enhancement (by de-quenching) at high protease concentrations, while the sensitivity was generally comparable for both highly specific (e.g. Trypsin) and industrial relevant proteases (e.g. Alcalase and Neutrase) at low doses. For Chymotrypsin, BODIPY-patatin provided a 39 % response improvement at 5 ng dose. A peptide-centric analysis of mass spectrometry-based bottom-up proteomics data identified several BODIPY-labeling sites with varying occupancies in patatin, indicating heterogenous labeling under the applied conjugation conditions. BODIPY-labeled patatin complements commercial BODIPY-labeled casein as a globular, plant-based alternative for screening of proteolytic activity.

Crystal structure of the alternative complex III from the phototrophic bacterium Chloroflexus aurantiacus

Alternative complex III (ACIII) is a multi-subunit quinol:electron acceptor oxidoreductase that couples quinol oxidation with transmembrane proton translocation in bacterial respiratory and photosynthetic electron transport chains. Four ACIII cryoelectron microscopy (cryo-EM) structures are known. However, the effects of cryo-EM versus X-ray crystallography structure determination on ACIII structure are unclear. Here, we report a 3.25 Å crystal structure of photosynthetic ACIII from Chloroflexus aurantiacus (CaACIIIp), revealing eight subunits (ActA-G and I) with four iron-sulfur clusters and six c-type hemes, a menaquinol-binding site, and two proton translocation passages. Structural comparisons with the previously reported cryo-EM structures reveal slight local conformational changes in the solvent-exposed regions of ActB, ActD, ActG, and the transmembrane (TM) helix of subunit I. The regions conferring structural flexibility possess low sequence conservation across species. However, the core functional modules containing the menaquinol-binding pocket, redox centers, and proton translocation passages remain unchanged, preserving the enzyme's activity.

Surface engineering of amine transaminases to control their region-selective immobilization

The industrial use of enzymes often requires their immobilization to facilitate downstream processing and enable reuse. However, controlling enzyme orientation during immobilization is challenging and typically restricted to the N- and C-terminal regions. In this work, we propose a strategy to immobilize more active and stable amine transaminases (ATAs) by combining protein engineering with immobilization techniques. Our approach involves the structure-guided insertion of histidine clusters (His-clusters) at flexible regions of ATA subunit interfaces, enabling immobilization on cobalt-chelated carriers. By screening multiple ATAs from various microbial sources and testing different His-clusters for each, we identified the most active and stable heterogeneous biocatalysts. Notably, the immobilized H2A variant of Chromobacterium violaceum ATA (CvATA-2HA) exhibited the highest activity per mass of biocatalyst (4 U g-1). Meanwhile, the H3 variant of Pseudomonas fluorescens ATA (PfATA-H3) showed enhanced thermostability and DMSO resistance, being approximately 2.5 times more stable than its free counterpart. Overall, our findings highlight the impact of enzyme surface engineering on immobilization efficiency. The strategic placement of His-clusters enabled region-directed immobilization, improving both the activity and stability of specific ATA variants.

Structural insights into temperature-dependent dynamics of METPsc1, a miniaturized electron-transfer protein

The design of protein-metal complexes is rapidly advancing, with applications spanning catalysis, sensing, and bioremediation. We report a comprehensive investigation of METPsc1, a Miniaturized Electron Transfer Protein, in complex with cadmium. This study elucidates the impact of metal coordination on protein folding and structural dynamics across temperatures from 100 K to 300 K. Our findings reveal that METPsc1, composed of two similar halves stabilized by intramolecular hydrogen bonds, exhibits a unique "clothespin-like" recoil mechanism. This allows it to adapt to metal ions of varying radii, mirroring the flexibility observed in natural rubredoxins. High-resolution crystallography and molecular dynamics simulations unveil concerted backbone motions and subtle temperature-dependent shifts in side-chain conformations, particularly for residues involved in crystal packing. Notably, CdS bond lengths increase with temperature, correlating with anisotropic motions of the sulfur atoms involved in second-shell hydrogen bonding. This suggests a dynamic role of protein matrix upon redox cycling. These insights into METPsc1 highlight its potential for catalysis and contribute to the designing of artificial metalloproteins with functional plasticity.

Improving the anti-autolytic ability of alkaline protease from Bacillus alcalophilus by a rationally combined strategy

Detergent enzymes have been extensively developed as eco-friendly alternatives to harmful chemicals, with alkaline protease representing a significant portion of detergent enzyme sales. However, the self-cleavage function of alkaline protease impacts its activity and overall application. Therefore, a new rational combinatorial strategy is proposed based on self-molecular docking (Self-ZDOCK) and molecular dynamics (MD) simulations. Self-ZDOCK is a computational method for predicting the binding mode of proteins to themselves, which is crucial for understanding the self-cleavage mechanism of proteases. On the other hand, MD simulation is a powerful tool to gain insight into the dynamic behaviour of proteins over time, and thus to analyse the structural stability and flexibility of BpAP under various conditions. Experiments verified this strategy is an effective way to improve the anti-autolytic ability of BpAP. Among the 28 mutants of BpAP, 5 mutants showed increases in thermal stability, pH stability, and storage stability in detergent, indicating a significant enhancement in their anti-autolytic capacity. Structural analysis and MD simulations confirmed that the enhanced stability characteristic of BpAP is attributed to improved anti-autolytic ability rather than increased structural stability. The three points combined mutant (MT5) showed the best increases in autolytic ability, as well as advanced catalytic efficiency. The low rate of inactive mutants and the high rate of positive mutants indicated that newly introduced screening factors (distance from catalytic residues, Gibbs free energy term, molecular simulation, and visual inspections) greatly enhance the design of anti-autolytic alkaline protease. Additionally, these findings enhance the industrial use of alkaline protease in detergents and similar applications.

The activity regulation of lipase from Aspergillus fumigatus by ligand through allosteric exploration

Lipase activity from Aspergillus fumigatus (AFL) were modulated by an effector (HMD) that was discovered for an allosteric site on the bioactive macromolecule. Experimental evaluation and computational modeling of allosteric effects revealed alterations in the structure of AFL. It was found that AFL's activity in HMD solution increased by approximately 46 % due to mainly enhanced lid mobility. HMD-AFL interaction was driven by enthalpy and entropy. However, when AFL was coupled to HMD-modified microspheres (PS-HMD-p), its hydrolysis activity decreased by ~14.3 % due to reduced lid mobility. After immobilization, AFL's ester-synthesis activity also decreased, due to changes in the conformational dynamics and the geometric characteristics of active site. Investigating the structural dynamics of allosteric regulation of the lipase not only reveals its structural changes underlying the functional variation but also enhances the understanding of the allosteric property that is underappreciated in exoenzymes.

Artificial trimerization of β-glucosidase for enhanced thermostability and activity via computational redesign

The improvement of enzyme thermostability is of great significance in the biotechnology industry. Herein, we modified the C-terminus of β-glucosidase via the computer-aided rational design and successfully obtained six variants that exhibit improved optimal temperatures and thermal inactivation half-lives at 65 °C. Among these variants, the thermal inactivation half-life and hydrolytic activity of TrCel1b-H13 at 65 °C were increased by 416 and 3223 folds, respectively, compared to those of the wild type. The optimal catalytic temperature and melting temperature (Tm) of TrCel1b-H13 were elevated by 55 °C and 20 °C respectively, compared to those of the wild type. The Kcat/Km value of TrCel1b-H13 was improved by 13.3-fold, compared to that of the wild type. Furthermore, we found that the modified β-glucosidase, TrCel1b-H13, self-assembles into a trimeric structure, which was confirmed by X-ray crystallography and blue native polyacrylamide gel electrophoresis. The amino acid residues, including E28, H60, E99, K106, and K471, located at the trimeric interface of the adjacent subunits, were found to play an important role in maintaining the crystal structure of the protein trimer. Thus, protein multimerization via the computer-aided rational design method provides a cost-effective tool for simultaneously improving the thermostability and activity of enzymes.

Application of immunoinformatics to develop a novel and effective multiepitope chimeric vaccine against Variovorax durovernensis

Bloodstream infections pose a significant public health challenge caused by resistant bacteria such as Variovorax durovernensis, a recently reported Gram-negative bacterium, worsening the burden on healthcare systems. The design of a vaccine using chimeric peptides derived from a representative V. durovernensis strain holds significant promise for preventing disease onset. The current study aimed to employ reverse vaccinology (RV) approaches such as the retrieval of V. durovernensis proteomics data, removal of redundant proteins by CD-HIT, filtering of non-homologous proteins to humans and essential proteins, identification of outer membrane (OM) proteins by CELLO and PSORTb. Following these steps immunoinformatic approaches were applied, such as epitope prediction by IEDB, vaccine design using linkers and adjuvant and analysis of antigenicity, allergenicity, safety and stability. Among the 4208 nonredundant proteins, an OmpA family protein (A0A940EKP4) was designated a potential candidate for the development of a multiepitope vaccine construct. Upon analysis of OM protein, six immunodominant (B cell) epitopes were found on the basis of the chimeric construct following the prediction of CTL stands cytotoxic T lymphocyte and HTL stands helper T lymphocyte epitopes. To ensure comprehensive population coverage globally, the CTL and HTL coverage rates were 58.18 % and 46.56 %, respectively, and 77.23 % overall. By utilizing EAAAK, GPGPG, and AAY linkers, Cholera toxin B subunit adjuvants, and appropriate epitopes were smoothly incorporated into a chimeric vaccine effectively triggering both adaptive and innate immune responses. For example, the administered antigen showed a peak in counts on the fifthday post injection and then gradually declined until the fifteenth day. Elevated levels of several antibodies (IgG + IgM > 700,000; IgM > 600,000; IgG1 + IgG2; IgG1 > 500,000) were observed as decreased in the antigen concentration. Molecular dynamics simulations carried out via iMODS revealed strong correlations between residue pairs, highlighting the stability of the docked complex. The designed vaccine has promising potential in eliciting specific immunogenic responses, thereby facilitating future research for vaccine development against V. durovernensis.

Semi-rational design in simultaneous improvement of thermostability and activity of β-1,3-glucanase from Alkalihalobacillus clausii KSMK16

Endo-β-1,3-glucanase (β-1,3-GA) is a key enzyme capable of acting on the β-1,3-glycosidic bond of β-1,3-glucan, resulting in the production of β-1,3-gluco-oligosaccharides with higher water solubility. Higher temperatures are beneficial for curdlan hydrolysis; however, low enzymatic activity and thermal stability limit their applicability. In this study, a mutant library of Endo-β-1,3-glucanase (AC-GA) derived from Alkalihalobacillus clausii KSM-K16 was constructed by a semi-rational design using amino-acid-based multiple sequence alignment and protein structure-based computer-aided engineering. The best combination mutant (S52T/M120L) was screened through ordered recombination mutations, which showed a 24.88 % increase in specific enzyme activity over the wild-type. The melting temperature (Tm) value, an enzyme protein denaturation temperature, was raised to 82.99 °C from 78.60 of the wild type. In comparison, the Km for hydrolysis of curdlan by S52T/M120L was reduced by 12.1 %, while the kcat was increased by 59.39 %, thus leading to a higher catalytic efficiency (kcat/Km, 227.73 vs 125.46 mL·s-1·mg-1). Molecular dynamics (MD) simulations showed that mutations resulted in a reduction in the overall flexibility of the enzyme, an increase in rigidity, and a more stable structure. An increase in the hydrophobic network at the entrance of the substrate increases the accessibility of the substrate to the enzyme, resulting in increased enzyme activity. High-efficiency mutants have potential industrial applications in the enzymatic preparation of β-1,3-gluco-oligosaccharides.

Computational design of α-amylase from Bacillus licheniformis to increase its activity and stability at high temperatures

The thermostable α-amylase derived from Bacillus licheniformis (BLA) has multiple advantages, including enhancing the mass transfer rate and by reducing microbial contamination in starch hydrolysis. Nonetheless, the application of BLA is constrained by the accessibility and stability of enzymes capable of achieving high conversion rates at elevated temperatures. Moreover, the thermotolerance of BLA requires further enhancement. Here, we developed a computational strategy for constructing small and smart mutant libraries to identify variants with enhanced thermostability. Initially, molecular dynamics (MD) simulations were employed to identify the regions with high flexibility. Subsequently, FoldX, a computational design predictor, was used to design mutants by rigidifying highly flexible residues, whereas the simultaneous decrease in folding free energy assisted in improving thermostability. Through the utilization of MD and FoldX, residues K251, T277, N278, K319, and E336, situated at a distance of 5 Å from the catalytic triad, were chosen for mutation. Seventeen mutants were identified and characterized by evaluating enzymatic characteristics and kinetic parameters. The catalytic efficiency of the E271L/N278K mutant reached 184.1 g L-1 s-1, which is 1.88-fold larger than the corresponding value determined for the WT. Furthermore, the most thermostable mutant, E336S, exhibited a 1.43-fold improvement in half-life at 95 ℃, compared with that of the WT. This study, by combining computational simulation with experimental verification, establishes that potential sites can be computationally predicted to increase the activity and stability of BLA and thus provide a possible strategy by which to guide protein design.

A general temperature-guided language model to design proteins of enhanced stability and activity

Designing protein mutants with both high stability and activity is a critical yet challenging task in protein engineering. Here, we introduce PRIME, a deep learning model, which can suggest protein mutants with improved stability and activity without any prior experimental mutagenesis data for the specified protein. Leveraging temperature-aware language modeling, PRIME demonstrated superior predictive ability compared to current state-of-the-art models on the public mutagenesis dataset across 283 protein assays. Furthermore, we validated PRIME's predictions on five proteins, examining the impact of the top 30 to 45 single-site mutations on various protein properties, including thermal stability, antigen-antibody binding affinity, and the ability to polymerize nonnatural nucleic acid or resilience to extreme alkaline conditions. More than 30% of PRIME-recommended mutants exhibited superior performance compared to their premutation counterparts across all proteins and desired properties. We developed an efficient and effective method based on PRIME to rapidly obtain multisite mutants with enhanced activity and stability. Hence, PRIME demonstrates broad applicability in protein engineering.

Differential Responses in the Core, Active Site and Peripheral Regions of Cytochrome c Peroxidase to Extreme Pressure and Temperature

In consideration of life in extreme environments, the effects of hydrostatic pressure on proteins at the atomic level have drawn substantial interest. Large deviations of temperature and pressure from ambient conditions can shift the free energy landscape of proteins to reveal otherwise lowly populated structural states and even promote unfolding. We report the crystal structure of the heme-containing peroxidase, cytochrome c peroxidase (CcP) at 1.5 and 3.0 kbar and make comparisons to structures determined at 1.0 bar and cryo-temperatures (100 K). Pressure produces anisotropic changes in CcP, but compressibility plateaus after 1.5 kbar. CcP responds to pressure with volume declines at the periphery of the protein where B-factors are relatively high but maintains nearly intransient core structure, hydrogen bonding interactions and active site channels. Changes in active-site solvation and heme ligation reveal pressure sensitivity to protein-ligand interactions and a potential docking site for the substrate peroxide. Compression at the surface affects neither alternate side-chain conformers nor B-factors. Thus, packing in the core, which resembles a crystalline solid, limits motion and protects the active site, whereas looser packing at the surface preserves side-chain dynamics. These data demonstrate that conformational dynamics and packing densities are not fully correlated in proteins and that encapsulation of cofactors by the polypeptide can provide a precisely structured environment resistant to change across a wide range of physical conditions.

Structural analysis of the TPI-Manchester, a thermolabile variant of human triosephosphate isomerase

Human triosephosphate isomerase G122R, also known as TPI-Manchester, is a thermolabile variant detected in a screening of more than 3400 individuals from a population in Ann Arbor, Michigan. Here, the crystallographic structure of G122R was solved to determine the molecular basis of its thermal stability. Structural analysis revealed an increase in the flexibility of residues at the dimer interface, even though R122 is about 20 Å away, suggesting that long-range electrostatic interactions may play a key role in the mutation effect.

Improvement the thermostability and specific activity of acidic xylanase PjxA from Penicillium janthinellum via rigid flexible sites

Acidic xylanase PjxA from Penicillium janthinellum MA21601, with good eosinophilic and enzymatic activity, is an excellent candidate for xylan degradation to achieve effective utilization of biomass materials. However, the low thermal stability of PjxA has become a major bottleneck in its application. In this study, the flexible sites of PjxA were identified and rigidified through computational simulations of structure and sequence analysis combined with folding free energy calculations. Finally, a combined mutase PjxA-DS was constructed by rational integration of the two single mutants S82N and D45N. Compared to PjxA, PjxA-DS showed a 115.11-fold longer half-life at 50 °C and a 2.02-fold higher specific enzyme activity. Computer simulation analysis showed that S82N and D45N acted synergistically to improve the thermostability of PjxA. The stabilization of the N-terminus and the active center of PjxA, the increase in surface positive charge and hydrophilicity are the main reasons for the improved thermostability and catalytic activity of PjxA. Rigidification of the flexible site is an effective method for improving the thermostability of enzymes, S82N and D45N can be used as effective targets for the thermostability engineering modification of GH11 acidic xylanase.

Precise Immobilization Strategy Combined with Rational Design to Improve β-Agarase Stability

Recently, the orientational immobilization of enzymes has attracted extensive attention. In this study, we report the development of a strategy combined with rational design to achieve precise site-specific covalent immobilization of β-agarase. We first rationally screened six surface sites that can be mutated to cysteine by combining molecular dynamics simulation and energy calculation. Site-specific immobilization was successfully achieved by Michael addition reaction of mutant enzymes and maleimide-modified magnetic nanoparticles (MAL-MNPs). The enzyme activity retention rate of R66C-MAL-MNPs and K588C-MAL-MNPs was greater than 96%. The thermal deactivation kinetics study revealed that the site-specific immobilization strategy significantly improved the thermal stability of Aga50D, resulting in a substantial increase in its antidenaturation activity at elevated temperatures, and the highest t1/2 of the immobilized mutant enzymes was increased by an impressive 21.25-fold at 40 °C. The immobilized mutant enzymes also showed significantly enhanced tolerance to metal ions and organic reagents. For instance, all of the immobilized enzymes maintained over 90% of their enzymatic activity in the 50% (v/v) acetone/water solution. The present work may pave the way for the design of precisely immobilized enzymes, which can help promote green manufacturing.

Noncanonical Amino Acids: Bringing New-to-Nature Functionalities to Biocatalysis

Biocatalysis has become an important component of modern organic chemistry, presenting an efficient and environmentally friendly approach to synthetic transformations. Advances in molecular biology, computational modeling, and protein engineering have unlocked the full potential of enzymes in various industrial applications. However, the inherent limitations of the natural building blocks have sparked a revolutionary shift. In vivo genetic incorporation of noncanonical amino acids exceeds the conventional 20 amino acids, opening new avenues for innovation. This review provides a comprehensive overview of applications of noncanonical amino acids in biocatalysis. We aim to examine the field from multiple perspectives, ranging from their impact on enzymatic reactions to the creation of novel active sites, and subsequent catalysis of new-to-nature reactions. Finally, we discuss the challenges, limitations, and promising opportunities within this dynamic research domain.

Hydrogen/Deuterium Exchange Mass Spectrometry: Fundamentals, Limitations, and Opportunities

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) probes dynamic motions of proteins by monitoring the kinetics of backbone amide deuteration. Dynamic regions exhibit rapid HDX, while rigid segments are more protected. Current data readouts focus on qualitative comparative observations (such as "residues X to Y become more protected after protein exposure to ligand Z"). At present, it is not possible to decode HDX protection patterns in an atomistic fashion. In other words, the exact range of protein motions under a given set of conditions cannot be uncovered, leaving space for speculative interpretations. Amide back exchange is an under-appreciated problem, as the widely used (m-m0)/(m100-m0) correction method can distort HDX kinetic profiles. Future data analysis strategies require a better fundamental understanding of HDX events, going beyond the classical Linderstrøm-Lang model. Combined with experiments that offer enhanced spatial resolution and suppressed back exchange, it should become possible to uncover the exact range of motions exhibited by a protein under a given set of conditions. Such advances would provide a greatly improved understanding of protein behavior in health and disease.

Water-mediated active conformational transitions of lipase on organic solvent interfaces

When it comes to enzyme stability and their application in organic solvents, enzyme biocatalysis has emerged as a popular substitute for conventional chemical processes. However, the demand for enzymes exhibiting improved stability remains a persistent challenge. Organic solvents can significantly impacts enzyme properties, thereby limiting their practical application. This study focuses on Lipase Thermomyces lanuginose, through molecular dynamics simulations and experiments, we quantified the effect of different solvent-lipase interfaces on the interfacial activation of lipase. Revealed molecular views of the complex solvation processes through the minimum distance distribution function. Solvent-protein interactions were used to interpret the factors influencing changes in lipase conformation and enzyme activity. We found that water content is crucial for enzyme stability, and the optimum water content for lipase activity was 35 % in the presence of benzene-water interface, which is closely related to the increase of its interfacial activation angle from 78° to 102°. Methanol induces interfacial activation in addition to significant competitive inhibition and denaturation at low water content. Our findings shed light on the importance of understanding solvent effects on enzyme function and provide practical insights for enzyme engineering and optimization in various solvent-lipase interfaces.

A review of in vitro stochastic and non-stochastic affinity maturation strategies for phage display derived monoclonal antibodies

Monoclonal antibodies identified using display technologies like phage display occasionally suffers from a lack of affinity making it unsuitable for application. This drawback is circumvented with the application of affinity maturation. Affinity maturation is an essential step in the natural evolution of antibodies in the immune system. The evolution of molecular based methods has seen the development of various mutagenesis approaches. This allows for the natural evolutionary process during somatic hypermutation to be replicated in the laboratories for affinity maturation to fine-tune the affinity and selectivity of antibodies. In this review, we will discuss affinity maturation strategies for mAbs generated through phage display systems. The review will highlight various in vitro stochastic and non-stochastic affinity maturation approaches that includes but are not limited to random mutagenesis, site-directed mutagenesis, and gene synthesis.

Vanadium complex as a potential modulator of the autophagic mechanism through proteins PI3K and ULK1: development, validation and biological implications of a specific force field for [VO(bpy)2Cl]

The modulation of autophagy has been presented as a very useful strategy in anticancer treatments. In this sense, the vanadium complex (VC) bis(2,2'-bipyridine)chlorooxovanadium(IV), [VO(bpy)2Cl], is known for its ability to induce autophagy in triple-negative breast cancer cells (TNBC). An excellent resource to investigate the role of VC in the induction of autophagy is to make use of Molecular Dynamics (MD) simulations. However, until now, the scarcity of force field parameters for the VC prevented a reliable analysis. The autophagy signaling pathway starts with the PI3K protein and ends with ULK1. Therefore, in the first stage of this work, we developed a new AMBER force field for the VC (VCFF) from a quantum structure, obtained by DFT calculations. In the second stage, the VCFF was validated through structural analyses. From this, it was possible to investigate, through docking and MD (200 ns), the performance of the PI3K-VC and ULK1-VC systems (third stage). The analyses of this last stage involved RMSD, hydrogen bonds, RMSF and two pathways for the modulation of autophagy. In general, this work fills in the absence of force field parameters (FF) for VC by proposing an efficient and new FF, in addition to investigating, at the molecular level, how VC is able to induce autophagy in TNBC cells. This study encourages new parameterizations of metallic complexes and contributes to the understanding of the duality of autophagic processes.Communicated by Ramaswamy H. Sarma.

Identification and characterisation of 'No apical meristem; Arabidopsis transcription activation factor; Cup-shape cotyledon' (NAC) family transcription factors involved in sugar accumulation and abscisic acid signalling in grape (Vitis vinifera)

The 'No apical meristem; Arabidopsis transcription activation factor; Cup-shape cotyledon' (NAC) transcription factors are pivotal in plant development and stress response. Sucrose-non-fermenting-related protein kinase 1.2 (SnRK1) is a key enzyme in glucose metabolism and ABA signalling. In this study, we used grape (Vitis vinifera ) calli to explore NAC's roles in sugar and ABA pathways and its relationship with VvSnRK1.2 . We identified 19 VvNACs highly expressed at 90days after blooming, coinciding with grape maturity and high sugar accumulation, and 11 VvNACs randomly selected from 19 were demonstrated in response to sugar and ABA treatments. VvNAC26 showed significant response to sugar and ABA treatments, and its protein, as a nucleus protein, had transcriptional activation in yeast. We obtained the overexpression (OE-VvNAC26 ) and RNA-inhibition (RNAi-VvNAC26 ) of VvNAC26 in transgenic calli by Agrobacterium tumefaciens -mediated transformation. We found that VvNAC26 negatively influenced fructose content. Under sugar and ABA treatments, VvNAC26 negatively influenced the expression of most sugar-related genes, while positively influencing the expression of most ABA pathway-related genes. Dual-luciferase reporter experiments demonstrated that VvNAC26 significantly upregulates VvSnRK1.2 promoter expression in tobacco (Nicotiana benthamiana ) leaves, although this process in grape calli requires ABA. The levels of sugar content, sugar-related genes, and ABA-related genes fluctuated significantly in OE-VvNAC26 +RNAi-VvSnRK1.2 and OE-VvSnRK1.2 +RNAi-VvNAC26 transgenic calli. These findings indicated that VvNAC26 regulates sugar metabolism and ABA pathway, displaying synergistic interactions with VvSnRK1.2 .

Characterization and rational engineering of an alkaline-tolerant azoreductase derived from Roseibium sp. H3510 for enhanced decolorization of azo dyes

rAzoR2326, an azoreductase derived from Roseibium sp. H3510, functions as an FMN-dependent homodimer utilizing NADH as cofactor. It demonstrated maximum activity at 45 °C and retained moderate activity above 50 °C, exhibiting stability from pH 7-10. Evolution and structure guided rational design of wild-type rAzoR2326 (WT) efficiently yielded 6 single-point mutants with improved thermostability and activity from a 22-variant library. Further combinatorial mutation led to mutant M20 with substantially enhanced thermostability (15-fold longer half-life at 50 °C) and activity (3.24-fold higher kcat/Km). M20 exhibited superior catalytic properties for decolorizing Allura Red compared to WT. Specifically, its decolorization capacity at pH 10.0 was 4.26-fold higher than WT. Additionally, M20 demonstrated remarkable thermostability, retaining 76.83 % decolorization activity for Allura Red after 120 min at 50 °C, whereas WT nearly lost all catalytic activity under the same conditions. Molecular dynamics simulations revealed the structural changes in M20, such as improved hydrogen bonding and a new C-H···π interaction, led to a more compact and rigid enzyme structure. This resulted in a more stable FMN-binding pocket and substrate tunnel, thereby improving the catalytic stability and activity of M20. Given its enhanced dye decolorization ability and alkaline tolerance, M20 shows promise as a biocatalyst for treating azo dye effluents.

Rational enzyme design by reducing the number of hotspots and library size

Biocatalysts that are eco-friendly, sustainable, and highly specific have great potential for applications in the production of fine chemicals, food, detergents, biofuels, pharmaceuticals, and more. However, due to factors such as low activity, narrow substrate scope, poor thermostability, or incorrect selectivity, most natural enzymes cannot be directly used for large-scale production of the desired products. To overcome these obstacles, protein engineering methods have been developed over decades and have become powerful and versatile tools for adapting enzymes with improved catalytic properties or new functions. The vastness of the protein sequence space makes screening a bottleneck in obtaining advantageous mutated enzymes in traditional directed evolution. In the realm of mathematics, there are two major constraints in the protein sequence space: (1) the number of residue substitutions (M); and (2) the number of codons encoding amino acids as building blocks (N). This feature review highlights protein engineering strategies to reduce screening efforts from two dimensions by reducing the numbers M and N, and also discusses representative seminal studies of rationally engineered natural enzymes to deliver new catalytic functions.

An immunoinformatics approach for a potential NY-ESO-1 and WT1 based multi-epitope vaccine designing against triple-negative breast cancer

Breast cancer emerges as one of the most prevalent malignancies in women, its incidence showing a concerning upward trend. Among the diverse array of breast cancer subtypes, triple-negative breast cancer (TNBC) assumes notable significance, due to lack of estrogen, progesterone, and HER-2 receptors. More focus has to be placed on creating effective therapy due to the high prevalence and rising incidence of TNBC. Currently, conventional passive treatments have several drawbacks that have not yet been resolved. On the other hand, as innovative immunotherapy approaches, cancer vaccines have offered promising prospects in combatting advanced stages of TNBC. Therefore, the main objective of this study was to utilize WT1 and NY-ESO-1 antigenic proteins in designing a multiepitope vaccine against TNBC. Initially, to generate robust immune responses, we identified antigenic epitopes of both proteins and assessed their immunogenicity. In order to reduce junctional immunogenicity, promiscuous epitopes were joined using the suitable adjuvant (50S ribosomal L7/L12 protein) and incorporated appropriate linkers (GPGPG, AAY, and EAAAK). The best predicted 3D model was refined and validated to achieve an excellent 3D model. Molecular docking analysis and dynamic simulation were conducted to demonstrate the structural stability and integrity of the vaccine/TLR-4 complex. Finally, the vaccine was cloned into the vector pET28 (+). Thus, analysis of the constructed vaccine through immunoinformatics indicates its capability to elicit robust humoral and cellular immune responses in the targeted organism. As such, it holds promise as a therapeutic weapon against TNBC and may open doors for further research in the field.

Structural and biochemical investigation into stable FGF2 mutants with novel mutation sites and hydrophobic replacements for surface-exposed cysteines

Fibroblast growth factor 2 (FGF2) is an attractive biomaterial for pharmaceuticals and functional cosmetics. To improve the thermo-stability of FGF2, we designed two mutants harboring four-point mutations: FGF2-M1 (D28E/C78L/C96I/S137P) and FGF2-M2 (D28E/C78I/C96I/S137P) through bioinformatics, molecular thermodynamics, and molecular modeling. The D28E mutation reduced fragmentation of the FGF2 wild type during preparation, and the substitution of a whale-specific amino acid, S137P, enhanced the thermal stability of FGF2. Surface-exposed cysteines that participate in oligomerization through intermolecular disulfide bond formation were substituted with hydrophobic residues (C78L/C78I and C96I) using the in silico method. High-resolution crystal structures revealed at the atomic level that the introduction of mutations stabilizes each local region by forming more favorable interactions with neighboring residues. In particular, P137 forms CH-π interactions with the side chain indole ring of W123, which seems to stabilize a β-hairpin structure, containing a heparin-binding site of FGF2. Compared to the wild type, both FGF2-M1 and FGF2-M2 maintained greater solubility after a week at 45 °C, with their Tm values rising by ~ 5 °C. Furthermore, the duration for FGF2-M1 and FGF2-M2 to reach 50% residual activity at 45 °C extended to 8.8- and 8.2-fold longer, respectively, than that of the wild type. Interestingly, the hydrophobic substitution of surface-exposed cysteine in both FGF2 mutants makes them more resistant to proteolytic cleavage by trypsin, subtilisin, proteinase K, and actinase than the wild type and the Cys → Ser substitution. The hydrophobic replacements can influence protease resistance as well as oligomerization and thermal stability. It is notable that hydrophobic substitutions of surface-exposed cysteines, as well as D28E and S137P of the FGF2 mutants, were designed through various approaches with structural implications. Therefore, the engineering strategies and structural insights adopted in this study could be applied to improve the stability of other proteins.

Data-driven probabilistic definition of the low energy conformational states of protein residues

Protein dynamics and related conformational changes are essential for their function but difficult to characterise and interpret. Amino acids in a protein behave according to their local energy landscape, which is determined by their local structural context and environmental conditions. The lowest energy state for a given residue can correspond to sharply defined conformations, e.g. in a stable helix, or can cover a wide range of conformations, e.g. in intrinsically disordered regions. A good definition of such low energy states is therefore important to describe the behaviour of a residue and how it changes with its environment. We propose a data-driven probabilistic definition of six low energy conformational states typically accessible for amino acid residues in proteins. This definition is based on solution NMR information of 1322 proteins through a combined analysis of structure ensembles with interpreted chemical shifts. We further introduce a conformational state variability parameter that captures, based on an ensemble of protein structures from molecular dynamics or other methods, how often a residue moves between these conformational states. The approach enables a different perspective on the local conformational behaviour of proteins that is complementary to their static interpretation from single structure models.

The evolution of cutinase Est1 based on the clustering strategy and its application for commercial PET bottles degradation

The rapid increase in global plastic consumption, especially the worldwide use of polyethylene terephthalate (PET), has caused serious pollution problems. Due to the low recycling rate of PET, a substantial amount of waste accumulates in the environment, which prompts a growing focus on enzymatic degradation for its efficiency and environmentally friendliness. This study systematically designed and modified a cutinase, Est1 from Thermobifida alba AHK119, known for its potential of plastic-degradation at high temperatures. Additionally, the introduction of clustering algorithms provided the ability to understand and modify biomolecules, to accelerate the process of finding the optimal mutations. K-means was further proceeded based on the positive mutations. After comprehensive screening for thermostability and activity mutation sites, the dominant mutation Est1_5M (Est1 with the mutations of N213M, T215P, S115P, Q93A, and L91W) exhibited satisfying degradation ability for commercial PET bottles. The results showed that Est1_5M achieved a degradation rate of 90.84% in 72 h, 65-fold higher than the wild type. This study offers reliable theoretical and practical support for the development of efficient PET-degrading enzymes, providing a reference for plastic pollution management.

Machine-learned molecular mechanics force fields from large-scale quantum chemical data

The development of reliable and extensible molecular mechanics (MM) force fields-fast, empirical models characterizing the potential energy surface of molecular systems-is indispensable for biomolecular simulation and computer-aided drug design. Here, we introduce a generalized and extensible machine-learned MM force field, espaloma-0.3, and an end-to-end differentiable framework using graph neural networks to overcome the limitations of traditional rule-based methods. Trained in a single GPU-day to fit a large and diverse quantum chemical dataset of over 1.1 M energy and force calculations, espaloma-0.3 reproduces quantum chemical energetic properties of chemical domains highly relevant to drug discovery, including small molecules, peptides, and nucleic acids. Moreover, this force field maintains the quantum chemical energy-minimized geometries of small molecules and preserves the condensed phase properties of peptides and folded proteins, self-consistently parametrizing proteins and ligands to produce stable simulations leading to highly accurate predictions of binding free energies. This methodology demonstrates significant promise as a path forward for systematically building more accurate force fields that are easily extensible to new chemical domains of interest.

Structure-based characterization and compound identification of the wild-type THF class-II riboswitch

Riboswitches are conserved regulatory RNA elements participating in various metabolic pathways. Recently, a novel RNA motif known as the folE RNA motif was discovered upstream of folE genes. It specifically senses tetrahydrofolate (THF) and is therefore termed THF-II riboswitch. To unravel the ligand recognition mechanism of this newly discovered riboswitch and decipher the underlying principles governing its tertiary folding, we determined both the free-form and bound-form THF-II riboswitch in the wild-type sequences. Combining structural information and isothermal titration calorimetry (ITC) binding assays on structure-based mutants, we successfully elucidated the significant long-range interactions governing the function of THF-II riboswitch and identified additional compounds, including alternative natural metabolites and potential lead compounds for drug discovery, that interact with THF-II riboswitch. Our structural research on the ligand recognition mechanism of the THF-II riboswitch not only paves the way for identification of compounds targeting riboswitches, but also facilitates the exploration of THF analogs in diverse biological contexts or for therapeutic applications.

Design and Evolution of an Enzyme for the Asymmetric Michael Addition of Cyclic Ketones to Nitroolefins by Enamine Catalysis

Consistent introduction of novel enzymes is required for developing efficient biocatalysts for challenging biotransformations. Absorbing catalytic modes from organocatalysis may be fruitful for designing new-to-nature enzymes with novel functions. Herein we report a newly designed artificial enzyme harboring a catalytic pyrrolidine residue that catalyzes the asymmetric Michael addition of cyclic ketones to nitroolefins through enamine activation with high efficiency. Diverse chiral γ-nitro cyclic ketones with two stereocenters were efficiently prepared with excellent stereoselectivity (up to 97 % e.e., >20 : 1 d.r.) and good yield (up to 86 %). This work provides an efficient biocatalytic strategy for cyclic ketone functionalization, and highlights the usefulness of artificial enzymes for extending biocatalysis to further non-natural reactions.

Evolution of liquid phase during homogenous non-equilibrium melting of Ta at superheating temperature

Homogenous melting at superheating temperature is commonly described by classical nucleation theory (CNT), but the atomic mechanism of the formation and development of critical liquid nuclei is still unclear. Molecular dynamics simulations were conducted to analyze the melting process of Ta. It is found that the process of subcritical liquid clusters evolving into critical liquid nucleus occupies most of the melting time, and merging between neighboring liquid clusters is the main path for subcritical liquid clusters to grow in size. Total melting time is strongly affected by the distribution of formation sites of subcritical liquid clusters, which has been considered random in homogenous melting. This work depicts a clear picture of the formation and development of liquid phase during the homogeneous melting process at superheating temperature and suggests an internal factor of melting mechanism.

Quercetin and taxifolin inhibits TMPRSS2 activity and its interaction with EGFR in paclitaxel-resistant breast cancer cells: An in silico and in vitro study

Transmembrane protease/serine (TMPRSS2), a type II transmembrane serine protease, plays a crucial role in different stages of cancer. Recent studies have reported that the triggering epidermal growth factor receptor (EGFR) activation through protease action promotes metastasis. However, there are no reports on the interaction of TMPRSS2 with EGFR, especially in triple-negative triple negative (TNBC). The current study investigates the unexplored interaction between TMPRSS2 and EGFR, which are key partners mediating metastasis. This interaction is explored for potential targeting using quercetin (QUE) and taxifolin (TAX). TMPRSS2 expression patterns in breast cancer (BC) tissues and subtypes have been predicted, with the prognostic significance assessed using the GENT2.0 database. Validation of TMPRSS2 expression was performed in normal and TNBC tissues, including drug-resistant cell lines, utilizing GEO datasets. TMPRSS2 was further validated as a predictive biomarker for FDA-approved chemotherapeutics through transcriptomic data from BC patients. The study demonstrated the association of TMPRSS2 with EGFR through in silico analysis and validates the findings in TNBC cohorts using the TIMER2.0 web server and the TCGA dataset through C-Bioportal. Molecular docking and molecular dynamic simulation studies identified QUE and TAX as best leads targeting TMPRSS2. They inhibited cell-free TMPRSS2 activity like clinical inhibitor of TMPRSS2, Camostat mesylate. In cell-based assays focused on paclitaxel-resistant TNBC (TNBC/PR), QUE and TAX demonstrated potent inhibitory activity against extracellular and membrane-bound TMPRSS2, with low IC50 values. Furthermore, ELISA and cell-based AlphaLISA assays demonstrated that QUE and TAX inhibit the interaction of TMPRSS2 with EGFR. Additionally, QUE and TAX exhibited significant inhibition of proliferation and cell cycle accompanied by notable alterations in the morphology of TNBC/PR cells. This study provides valuable insights into potential of QUE and TAX targeting TMPRSS2 overexpressing TNBC.

Theory vs. experiment: The rise of the dynamic view of proteins

Over the past century, the scientific conception of the protein has evolved significantly. This paper focuses on the most recent stage of this evolution, namely, the origin of the dynamic view of proteins and the challenge it posed to the static view of classical molecular biology. Philosophers and scientists have offered two hypotheses to explain the origin of the dynamic view and its slow reception by structural biologists. Some have argued that the shift from the static to the dynamic view was a Kuhnian revolution, driven by the accumulation of dynamic anomalies, while others have argued that the shift was caused by new empirical findings made possible by technological advances. I analyze this scientific episode and ultimately reject both of these empiricist accounts. I argue that focusing primarily on technological advances and empirical discoveries overlooks the important role of theory in driving this scientific change. I show how the application of general thermodynamic principles to proteins gave rise to the dynamic view, and a commitment to these principles then led early adopters to seek out the empirical examples of protein dynamics, which would eventually convince their peers. My analysis of this historical case shows that empiricist accounts of modern scientific progress-at least those that aim to explain developments in the molecular life sciences-need to be tempered in order to capture the interplay between theory and experiment.

Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme engineering

The effective design of combinatorial libraries to balance fitness and diversity facilitates the engineering of useful enzyme functions, particularly those that are poorly characterized or unknown in biology. We introduce MODIFY, a machine learning (ML) algorithm that learns from natural protein sequences to infer evolutionarily plausible mutations and predict enzyme fitness. MODIFY co-optimizes predicted fitness and sequence diversity of starting libraries, prioritizing high-fitness variants while ensuring broad sequence coverage. In silico evaluation shows that MODIFY outperforms state-of-the-art unsupervised methods in zero-shot fitness prediction and enables ML-guided directed evolution with enhanced efficiency. Using MODIFY, we engineer generalist biocatalysts derived from a thermostable cytochrome c to achieve enantioselective C-B and C-Si bond formation via a new-to-nature carbene transfer mechanism, leading to biocatalysts six mutations away from previously developed enzymes while exhibiting superior or comparable activities. These results demonstrate MODIFY's potential in solving challenging enzyme engineering problems beyond the reach of classic directed evolution.

Structural Assessment of Chlamydia trachomatis Major Outer Membrane Protein (MOMP)-Derived Vaccine Antigens and Immunological Profiling in Mice with Different Genetic Backgrounds

Chlamydia trachomatis (Ct) is the most common cause of bacterial sexually transmitted infections (STIs) worldwide. Ct infections are often asymptomatic in women, leading to severe reproductive tract sequelae. Development of a vaccine against Chlamydia is crucial. The Chlamydia major outer membrane protein (MOMP) is a prime vaccine antigen candidate, and it can elicit both neutralizing antibodies and protective CD4+ T cell responses. We have previously designed chimeric antigens composed of immunogenic variable regions (VDs) and conserved regions (CDs) of MOMP from Chlamydia muridarum (Cm) expressed into a carrier protein (PorB), and we have shown that these were protective in a mouse model of Cm respiratory infection. Here, we generated corresponding constructs based on MOMP from Ct serovar F. Preliminary structure analysis of the three antigens, PorB/VD1-3, PorB/VD1-4 and PorB/VD1-2-4, showed that they retained structure features consistent with those of PorB. The antigens induced robust humoral and cellular responses in mice with different genetic backgrounds. The antibodies were cross-reactive against Ct, but only anti-PorB/VD1-4 and anti-PorB/VD1-2-4 IgG antibodies were neutralizing, likely due to the antigen specificity. The cellular responses included proliferation in vitro and production of IFN-γ by splenocytes following Ct re-stimulation. Our results support further investigation of the PorB/VD antigens as potential protective candidates for a Chlamydia subunit vaccine.

A dataset of alternately located segments in protein crystal structures

Protein Data Bank (PDB) files list the relative spatial location of atoms in a protein structure as the final output of the process of fitting and refining to experimentally determined electron density measurements. Where experimental evidence exists for multiple conformations, atoms are modelled in alternate locations. Programs reading PDB files commonly ignore these alternate conformations by default leaving users oblivious to the presence of alternate conformations in the structures they analyze. This has led to underappreciation of their prevalence, under characterisation of their features and limited the accessibility to this high-resolution data representing structural ensembles. We have trawled PDB files to extract structural features of residues with alternately located atoms. The output includes the distance between alternate conformations and identifies the location of these segments within the protein chain and in proximity of all other atoms within a defined radius. This dataset should be of use in efforts to predict multiple structures from a single sequence and support studies investigating protein flexibility and the association with protein function.

Multivariate Silicification-Assisted Single Enzyme Structure Augmentation for Improved Enzymatic Activity-Stability Trade-Off

The ability to finely tune/balance the structure and rigidity of enzymes to realize both high enzymatic activity and long-term stability is highly desired but highly challenging. Herein, we propose the concept of the "silicazyme", where solid inorganic silica undergoes controlled hybridization with the fragile enzyme under moderate conditions at the single-enzyme level, thus enabling simultaneous structure augmentation, long-term stability, and high enzymatic activity preservation. A multivariate silicification approach was utilized and occurred around individual enzymes to allow conformal coating. To realize a high activity-stability trade-off the structure flexibility/rigidity of the silicazyme was optimized by a component adjustment ternary (CAT) plot method. Moreover, the multivariate organosilica frameworks bring great advantages, including surface microenvironment adjustability, reversible modification capability, and functional extensibility through the rich chemistry of silica. Overall silicazymes represent a new class of enzymes with promise for catalysis, separations, and nanomedicine.

Engineering of a Baeyer-Villiger monooxygenase to Improve Substrate Scope, Stereoselectivity and Regioselectivity

Baeyer-Villiger monooxygenases belong to a family of flavin-binding proteins that catalyze the Baeyer-Villiger (BV) oxidation of ketones to produce lactones or esters, which are important intermediates in pharmaceuticals or sustainable materials. Phenylacetone monooxygenase (PAMO) from Thermobifida fusca with moderate thermostability catalyzes the oxidation of aryl ketone substrates, but is limited by high specificity and narrow substrate scope. In the present study, we applied loop optimization by loop swapping followed by focused saturation mutagenesis in order to evolve PAMO mutants capable of catalyzing the regioselective BV oxidation of cyclohexanone and cyclobutanone derivatives with formation of either normal or abnormal esters or lactones. We further modulated PAMO to increase enantioselectivity. Crystal structure studies indicate that rotation occurs in the NADP-binding domain and that the high B-factor region is predominantly distributed in the catalytic pocket residues. Computational analyses further revealed dynamic character in the catalytic pocket and reshaped hydrogen bond interaction networks, which is more favorable for substrate binding. Our study provides useful insights for studying enzyme-substrate adaptations.

Enhancing efficiency of protein language models with minimal wet-lab data through few-shot learning

Accurately modeling the protein fitness landscapes holds great importance for protein engineering. Pre-trained protein language models have achieved state-of-the-art performance in predicting protein fitness without wet-lab experimental data, but their accuracy and interpretability remain limited. On the other hand, traditional supervised deep learning models require abundant labeled training examples for performance improvements, posing a practical barrier. In this work, we introduce FSFP, a training strategy that can effectively optimize protein language models under extreme data scarcity for fitness prediction. By combining meta-transfer learning, learning to rank, and parameter-efficient fine-tuning, FSFP can significantly boost the performance of various protein language models using merely tens of labeled single-site mutants from the target protein. In silico benchmarks across 87 deep mutational scanning datasets demonstrate FSFP's superiority over both unsupervised and supervised baselines. Furthermore, we successfully apply FSFP to engineer the Phi29 DNA polymerase through wet-lab experiments, achieving a 25% increase in the positive rate. These results underscore the potential of our approach in aiding AI-guided protein engineering.

Enhanced Thermostability of Nattokinase by Computation-Based Rational Redesign of Flexible Regions

Nattokinase is a nutrient in healthy food natto that has the function of preventing and treating blood thrombus. However, its low thermostability and fibrinolytic activity limit its application in food and pharmaceuticals. In this study, we used bioinformatics analysis to identify two loops (loop10 and loop12) in the flexible region of nattokinase rAprY. Using this basis, we screened the G131S-S161T variant, which showed a 2.38-fold increase in half-life at 55 °C, and the M3 variant, which showed a 2.01-fold increase in activity, by using a thermostability prediction algorithm. Bioinformatics analysis revealed that the enhanced thermostability of the G131S-S161T variant was due to the increased rigidity and structural shrinkage of the overall structure. Additionally, the increased rigidity of the local region surrounding the active center and its mutated sites helps maintain its normal conformation in high-temperature environments. The increased catalytic activity of the M3 variant may be due to its more efficient substrate binding mechanism. We investigated strategies to improve the thermostability and fibrinolytic activity of nattokinase, and the resulting variants show promise for industrial production and application.

Immunoinformatics and Reverse Vaccinology Approach for the Identification of Potential Vaccine Candidates against Vandammella animalimors

Vandammella animalimorsus is a Gram-negative and non-motile bacterium typically transmitted to humans through direct contact with the saliva of infected animals, primarily through biting, scratches, or licks on fractured skin. The absence of a confirmed post-exposure treatment of V. animalimorsus bacterium highlights the imperative for developing an effective vaccine. We intended to determine potential vaccine candidates and paradigm a chimeric vaccine against V. animalimorsus by accessible public data analysis of the strain by utilizing reverse vaccinology. By subtractive genomics, five outer membranes were prioritized as potential vaccine candidates out of 2590 proteins. Based on the instability index and transmembrane helices, a multidrug transporter protein with locus ID A0A2A2AHJ4 was designated as a potential candidate for vaccine construct. Sixteen immunodominant epitopes were retrieved by utilizing the Immune Epitope Database. The epitope encodes the strong binding affinity, nonallergenic properties, non-toxicity, high antigenicity scores, and high solubility revealing the more appropriate vaccine construct. By utilizing appropriate linkers and adjuvants alongside a suitable adjuvant molecule, the epitopes were integrated into a chimeric vaccine to enhance immunogenicity, successfully eliciting both adaptive and innate immune responses. Moreover, the promising physicochemical features, the binding confirmation of the vaccine to the major innate immune receptor TLR-4, and molecular dynamics simulations of the designed vaccine have revealed the promising potential of the selected candidate. The integration of computational methods and omics data has demonstrated significant advantages in discovering novel vaccine targets and mitigating vaccine failure rates during clinical trials in recent years.

Engineering of Halide Methyltransferase BxHMT through Dynamic Cross-Correlation Network Analysis

Halide methyltransferases (HMTs) provide an effective way to regenerate S-adenosyl methionine (SAM) from S-adenosyl homocysteine and reactive electrophiles, such as methyl iodide (MeI) and methyl toluene sulfonate (MeOTs). As compared with MeI, the cost-effective unnatural substrate MeOTs can be accessed directly from cheap and abundant alcohols, but shows only limited reactivity in SAM production. In this study, we developed a dynamic cross-correlation network analysis (DCCNA) strategy for quickly identifying hot spots influencing the catalytic efficiency of the enzyme, and applied it to the evolution of HMT from Paraburkholderia xenovorans. Finally, the optimal mutant, M4 (V55T/C125S/L127T/L129P), exhibited remarkable improvement, with a specific activity of 4.08 U/mg towards MeOTs, representing an 82-fold increase as compared to the wild-type (WT) enzyme. Notably, M4 also demonstrated a positive impact on the catalytic ability with other methyl donors. The structural mechanism behind the enhanced enzyme activity was uncovered by molecular dynamics simulations. Our work not only contributes a promising biocatalyst for the regeneration of SAM, but also offers a strategy for efficient enzyme engineering.

Perspective on Agricultural Industrialization: Modification Strategies for Enhancing the Catalytic Capacity of Keratinase

Keratinases is a special hydrolytic enzyme produced by microorganisms, which has the ability to catalyze the degradation of keratin. Currently, keratinases show great potential for application in many agricultural and industrial fields, such as biofermented feed, leather tanning, hair removal, and fertilizer production. However, these potentials have not yet been fully unleashed on an industrial scale. This paper reviews the sources, properties, and catalytic mechanisms of keratinases. Strategies for the molecular modification of keratinases are summarized and discussed in terms of improving the substrate specificity, thermostability, and pH tolerance of keratinases. The modification strategies are also enriched by the introduction of immobilized enzymes and directed evolution. In addition, the selection of modification strategies when facing specific industrial applications is discussed and prospects are provided. We believe that this review serves as a reference for the future quest to extend the application of keratinases from the laboratory to industry.

Impact of single-residue mutations on protein thermal stability: The case of threonine 83 of BC2L-CN lectin

The thermal stability of trimeric lectin BC2L-CN was investigated and found to be considerably altered when mutating residue 83, originally a threonine, located at the fucose-binding loop. Mutants were analyzed using differential scanning calorimetry and isothermal microcalorimetry. Although most mutations decreased the affinity of the protein for oligosaccharide H type 1, six mutations increased the melting temperature (Tm) by >5 °C; one mutation, T83P, increased the Tm value by 18.2 °C(T83P, Tm = 96.3 °C). In molecular dynamic simulations, the investigated thermostable mutants, T83P, T83A, and T83S, had decreased fluctuations in the loop containing residue 83. In the T83S mutation, the side-chain hydroxyl group of serine formed a hydrogen bond with a nearby residue, suggesting that the restricted movement of the side-chain resulted in fewer fluctuations and enhanced thermal stability. Residue 83 is located at the interface and near the upstream end of the equivalent loop in a different protomer; therefore, fluctuations by this residue likely propagate throughout the loop. Our study of the dramatic change in thermal stability by a single amino acid mutation provides useful insights into the rational design of protein structures, especially the structures of oligomeric proteins.

Enhancing the stability of a novel D-allulose 3-epimerase from Ruminococcus sp. CAG55 by interface interaction engineering and terminally attached a self-assembling peptide

D-allulose, a highly desirable sugar substitute, is primarily produced using the D-allulose 3-epimerase (DAE). However, the availability of usable DAE enzymes is limited. In this study, we discovered and engineered a novel DAE Rum55, derived from a human gut bacterium Ruminococcus sp. CAG55. The activity of Rum55 was strictly dependent on the presence of Co2+, and it exhibited an equilibrium conversion rate of 30.6 % and a half-life of 4.5 h at 50 °C. To enhance its performance, we engineered the interface interaction of Rum55 to stabilize its tetramer structure, and the best variant E268R was then attached with a self-assembling peptide to form active enzyme aggregates as carrier-free immobilization. The half-life of the best variant E268R-EKL16 at 50 °C was dramatically increased 30-fold to 135.3 h, and it maintained 90 % of its activity after 13 consecutive reaction cycles. Additionally, we identified that metal ions played a key role in stabilizing the tetramer structure of Rum55, and the dependence on metal ions for E268R-EKL16 was significantly reduced. This study provides a useful route for improving the thermostability of DAEs, opening up new possibilities for the industrial production of D-allulose.

Engineering a Carotenoid Cleavage Oxygenase for Coenzyme-Free Synthesis of Vanillin from Ferulic Acid

One-pot biosynthesis of vanillin from ferulic acid without providing energy and cofactors adds significant value to lignin waste streams. However, naturally evolved carotenoid cleavage oxygenase (CCO) with extreme catalytic conditions greatly limited the above pathway for vanillin bioproduction. Herein, CCO from Thermothelomyces thermophilus (TtCCO) was rationally engineered for achieving high catalytic activity under neutral pH conditions and was further utilized for constructing a one-pot synthesis system of vanillin with Bacillus pumilus ferulic acid decarboxylase. TtCCO with the K192N-V310G-A311T-R404N-D407F-N556A mutation (TtCCOM3) was gradually obtained using substrate access channel engineering, catalytic pocket engineering, and pocket charge engineering. Molecular dynamics simulations revealed that reducing the site-blocking effect in the substrate access channel, enhancing affinity for substrates in the catalytic pocket, and eliminating the pocket's alkaline charge contributed to the high catalytic activity of TtCCOM3 under neutral pH conditions. Finally, the one-pot synthesis of vanillin in our study could achieve a maximum rate of up to 6.89 ± 0.3 mM h-1. Therefore, our study paves the way for a one-pot biosynthetic process of transforming renewable lignin-related aromatics into valuable chemicals.

Engineering the activity and thermostability of a carboxylic acid reductase in the conversion of vanillic acid to vanillin

Vanillin is a valuable natural product that can be used as a fragrance and additive. Recent research in the biosynthesis of vanillin has brought attention to a key enzyme, carboxylic acid reductase (CAR), which catalyzes the reduction of vanillic acid to vanillin. Nevertheless, the biosynthesis of vanillin is hampered by the low activity and stability of CAR. As such, a rational design campaign was conducted on a well-documented carboxylic acid reductase from Segniliparus rugosus (SrCAR), using vanillic acid as the model substrate. After combined active site saturation and iterative site-specific mutagenesis, the best quadruple mutant N292H/K524S/A627L/E1121W (M3) was successfully obtained. In comparison to the wildtype SrCAR, M3 demonstrated a 4.2-fold increase in catalytic efficiency (kcat/Km), and its half-life (t1/2) was enhanced by 3.8 times up to 385.08 minutes at 40 °C. In silico docking and molecular dynamics simulation provided insights into the improved activity and stability. In the subsequent preparative-scale reaction with 100 mM (16.8 g L-1) vanillic acid, the whole cell catalysis utilizing M3 produced 10.15 g·L-1 of vanillin and 1.11 g·L-1 of vanillyl alcohol, respectively. This work demonstrates a dual improvement in the activity and thermal stability of SrCAR, thereby potentially facilitating the application of carboxylic acid reductase in the biosynthesis of vanillin.

MISATO: machine learning dataset of protein-ligand complexes for structure-based drug discovery

Large language models have greatly enhanced our ability to understand biology and chemistry, yet robust methods for structure-based drug discovery, quantum chemistry and structural biology are still sparse. Precise biomolecule-ligand interaction datasets are urgently needed for large language models. To address this, we present MISATO, a dataset that combines quantum mechanical properties of small molecules and associated molecular dynamics simulations of ~20,000 experimental protein-ligand complexes with extensive validation of experimental data. Starting from the existing experimental structures, semi-empirical quantum mechanics was used to systematically refine these structures. A large collection of molecular dynamics traces of protein-ligand complexes in explicit water is included, accumulating over 170 μs. We give examples of machine learning (ML) baseline models proving an improvement of accuracy by employing our data. An easy entry point for ML experts is provided to enable the next generation of drug discovery artificial intelligence models.

Automated in vivo enzyme engineering accelerates biocatalyst optimization

Achieving cost-competitive bio-based processes requires development of stable and selective biocatalysts. Their realization through in vitro enzyme characterization and engineering is mostly low throughput and labor-intensive. Therefore, strategies for increasing throughput while diminishing manual labor are gaining momentum, such as in vivo screening and evolution campaigns. Computational tools like machine learning further support enzyme engineering efforts by widening the explorable design space. Here, we propose an integrated solution to enzyme engineering challenges whereby ML-guided, automated workflows (including library generation, implementation of hypermutation systems, adapted laboratory evolution, and in vivo growth-coupled selection) could be realized to accelerate pipelines towards superior biocatalysts.