Amino acid contribution to protein solubility: Asp, Glu, and Ser contribute more favorably than the other hydrophilic amino acids in RNase Sa

Rational design approach to improve the solubility of the β-sandwich domain 1 of a thermophilic protein

The β-sandwich domain 1 (SD1) of islandisin is a stable thermophilic protein with surface loops that can be redesigned for specific target binding, architecturally comparable to the variable domain of immunoglobulin (IgG). SD1's propensity to aggregate due to incorrect folding and subsequent accumulation in Escherichia coli inclusion bodies limits its use in biotechnological applications. We rationally designed SD1 for improved variants that were expressed in soluble forms in E. coli while maintaining the intrinsic thermal stability of the protein (melting temperature (Tm) = 73). We used FoldX's ΔΔG predictions to find beneficial mutations and aggregation-prone regions (APRs) using Tango. The S26K substitution within protein core residues did not affect protein stability. Among the soluble mutants studied, the S26K/Q91P combination significantly improved the expression and solubility of SD1. We also examined the effects of the surface residue, pH, and concentration on the solubility of SD1. We showed that the surface polarity of proteins had little or no effect on solubility, whereas surface charges played a substantial role. The storage stability of several SD1 variants was impaired at pH values near their isoelectric point, and pH levels resulting in highly charged groups. We observed that mutations that create an uneven distribution of charged groups on the SD1 surface could enhance protein solubility by eliminating favorable protein-protein surface charge interactions. Our findings suggest that SD1 is mutationally tolerant to new functionalities, thus providing a novel perspective for the application of rational design to improve the solubility of targeted proteins.

Selective Chiral Interactions between Hydrophilic/Hydrophobic Amino Acids and Growing Gypsum Crystals

In nature, selective interactions between chiral amino acids and crystals are important for the formation of chiral biominerals and provide insight into the mysterious origin of homochirality. Here, we show that chiral amino acids with different hydrophilicities/hydrophobicities exhibit different chiral selectivity preferences in the dynamically growing gypsum [001] steps. Hydrophilic amino acids show a chiral selectivity preference for their d-isomers, whereas hydrophobic amino acids prefer their l-isomers. These differences in chiral recognition can be attributed to the different stereochemical matching between the hydrophilic and hydrophobic amino acids on the [001] steps of growing gypsum. These different chiral selectivities resulting from the amino acid hydrophilicity/hydrophobicity are confirmed by the experimental crystallization investigations from nano regulation on dynamic steps, to microscopic modification of gypsum morphology, and to macroscopic precipitation. Furthermore, as the hydrophilicity of amino acids increases, the disparity in chiral selection rises; conversely, the increase in the hydrophobicity of amino acids results in a decline in chiral selection. These insights improve our understanding of the interaction mechanism between amino acids and crystals and provide insights into the formation process of chiral biominerals and the origin of homochirality in nature.

Computational analysis to comprehend the structure-function properties of fibrinolytic enzymes from Bacillus spp for their efficient integration into industrial applications

Background

The fibrinolytic enzymes from Bacillus sp. are proposed as therapeutics in preventing thrombosis. Computational-based analyses of these enzymes' amino acid composition, basic physiological properties, presence of functional domain and motifs, and secondary and tertiary structure analyses can lead to developing a specific enzyme with improved catalytic activity and other properties that may increase their therapeutic potential.

Methods

The nucleotide sequences of fibrinolytic enzymes produced by the genus Bacillus and its corresponding protein sequences were retrieved from the NCBI database and aligned using the PRALINE programme. The varied physiochemical parameters and structural and functional analysis of the enzyme sequences were carried out with the ExPASy-ProtParam tool, MEME server, SOPMA, PDBsum tool, CYS-REC tool, SWISS-MODEL, SAVES servers, TMHMM program, GlobPlot, and peptide cutter software. The assessed in-silico data were compared with the published experimental results for validation.

Results

The alignment of sixty fibrinolytic serine protease enzymes (molecular mass 12-86 kDa) sequences showed 49 enzymes possess a conserved domain with a catalytic triad of Asp196, His242, and Ser569. The predicted instability and aliphatic indexes were 1.94-37.77, and 68.9-93.41, respectively, indicating high thermostability. The random coil means value suggested the predominance of this secondary structure in these proteases. A set of 50 amino acid residues representing motif 3 signifies the Peptidase S8/S53 domain that was invariably observed in 56 sequences. Additionally, 28 sequences have transmembrane helices, with two having the most disordered areas, and they pose 25 enzyme cleavage sites. A comparative analysis of the experimental work with the results of in-silico study put forward the characteristics of the enzyme sequences JF739176.1 and MF677779.1 to be considered when creating a potential mutant enzyme as these sequences are stable at high pH with thermostability and to exhibit αβ-fibrinogenase activity in both experimental and in-silico studies.

Leveraging the biotechnological promise of the hagfish variable lymphocyte receptors: tools for aquatic microbial diseases

The jawless vertebrates (agnathans/cyclostomes) are ancestral animals comprising lampreys and hagfishes as the only extant representatives. They possess an alternative adaptive immune system (AIS) that uses leucine-rich repeats (LRR)-based variable lymphocyte receptors (VLRs) instead of the immunoglobulin (Ig)-based antigen receptors of jawed vertebrates (gnathostomes). The different VLR types are expressed on agnathan lymphocytes and functionally resemble gnathostome antigen receptors. In particular, VLRB is functionally similar to the B cell receptor and is expressed and secreted by B-like lymphocytes as VLRB antibodies that bind antigens with high affinity and specificity. The potential repertoire scale of VLR-based antigen receptors is believed to be at least comparable to that of Ig-based systems. VLR proteins inherently possess characteristics that render them excellent candidates for biotechnological development, including tractability to recombinant approaches. In recent years, scientists have explored the biotechnological development and utility of VLRB proteins as alternatives to conventional mammalian antibodies. The VLRB antibody platform represents a non-traditional approach to generating a highly diverse repertoire of unique antibodies. In this review, we first describe some aspects of the biology of the AIS of the jawless vertebrates, which recognizes antigens by means of unique receptors. We then summarize reports on the development of VLRB-based antibodies and their applications, particularly those from the inshore hagfish (Eptatretus burgeri) and their potential uses to address microbial diseases in aquaculture. Hagfish VLRB antibodies (we call Ccombodies) are being developed and improved, while obstacles to the advancement of the VLRB platform are being addressed to utilize VLRBs effectively as tools in immunology. VLRB antibodies for novel antigen targets are expected to emerge to provide new opportunities to tackle various scientific questions. We anticipate a greater interest in the agnathan AIS in general and particularly in the hagfish AIS for greater elucidation of the evolution of adaptive immunity and its applications to address microbial pathogens in farmed aquatic animals and beyond.

Understanding the Specific Implications of Amino Acids in the Antibody Development

As the demand for immunotherapy to treat and manage cancers, infectious diseases and other disorders grows, a comprehensive understanding of amino acids and their intricate role in antibody engineering has become a prime requirement. Naturally produced antibodies may not have the most suitable amino acids at the complementarity determining regions (CDR) and framework regions, for therapeutic purposes. Therefore, to enhance the binding affinity and therapeutic properties of an antibody, the specific impact of certain amino acids on the antibody's architecture must be thoroughly studied. In antibody engineering, it is crucial to identify the key amino acid residues that significantly contribute to improving antibody properties. Therapeutic antibodies with higher binding affinity and improved functionality can be achieved through modifications or substitutions with highly suitable amino acid residues. Here, we have indicated the frequency of amino acids and their association with the binding free energy in CDRs. The review also analyzes the experimental outcome of two studies that reveal the frequency of amino acids in CDRs and provides their significant correlation between the outcomes. Additionally, it discusses the various bond interactions within the antibody structure and antigen binding. A detailed understanding of these amino acid properties should assist in the analysis of antibody sequences and structures needed for designing and enhancing the overall performance of therapeutic antibodies.

Enhancing Protein Solubility via Glycosylation: From Chemical Synthesis to Machine Learning Predictions

Glycosylation is a valuable tool for modulating protein solubility; however, the lack of reliable research strategies has impeded efficient progress in understanding and applying this modification. This study aimed to bridge this gap by investigating the solubility of a model glycoprotein molecule, the carbohydrate-binding module (CBM), through a two-stage process. In the first stage, an approach involving chemical synthesis, comparative analysis, and molecular dynamics simulations of a library of glycoforms was employed to elucidate the effect of different glycosylation patterns on solubility and the key factors responsible for the effect. In the second stage, a predictive mathematical formula, innovatively harnessing machine learning algorithms, was derived to relate solubility to the identified key factors and accurately predict the solubility of the newly designed glycoforms. Demonstrating feasibility and effectiveness, this two-stage approach offers a valuable strategy for advancing glycosylation research, especially for the discovery of glycoforms with increased solubility.

Targeting Efficient Features of Urate Oxidase to Increase Its Solubility

With the demand for mass production of protein drugs, solubility has become a serious issue. Extrinsic and intrinsic factors both affect this property. A homotetrameric cofactor-free urate oxidase (UOX) is not sufficiently soluble. To engineer UOX for optimum solubility, it is important to identify the most effective factor that influences solubility. The most effective feature to target for protein engineering was determined by measuring various solubility-related factors of UOX. A large library of homologous sequences was obtained from the databases. The data was reduced to six enzymes from different organisms. On the basis of various sequence- and structure-derived elements, the most and the least soluble enzymes were defined. To determine the best protein engineering target for modification, features of the most and least soluble enzymes were compared. Metabacillus fastidiosus UOX was the most soluble enzyme, while Agrobacterium globiformis UOX was the least soluble. According to the comparison-constant method, positive surface patches caused by arginine residue distribution are appropriate targets for modification. Two Arg to Ala mutations were introduced to the least soluble enzyme to test this hypothesis. These mutations significantly enhanced the mutant's solubility. While different algorithms produced conflicting results, it was difficult to determine which proteins were most and least soluble. Solubility prediction requires multiple algorithms based on these controversies. Protein surfaces should be investigated regionally rather than globally, and both sequence and structural data should be considered. Several other biotechnological products could be engineered using the data reduction and comparison-constant methods used in this study.

Modeling and Analysis of HIV-1 Pol Polyprotein as a Case Study for Predicting Large Polyprotein Structures

Acquired immunodeficiency syndrome (AIDS) is caused by human immunodeficiency virus (HIV). HIV protease, reverse transcriptase, and integrase are targets of current drugs to treat the disease. However, anti-viral drug-resistant strains have emerged quickly due to the high mutation rate of the virus, leading to the demand for the development of new drugs. One attractive target is Gag-Pol polyprotein, which plays a key role in the life cycle of HIV. Recently, we found that a combination of M50I and V151I mutations in HIV-1 integrase can suppress virus release and inhibit the initiation of Gag-Pol autoprocessing and maturation without interfering with the dimerization of Gag-Pol. Additional mutations in integrase or RNase H domain in reverse transcriptase can compensate for the defect. However, the molecular mechanism is unknown. There is no tertiary structure of the full-length HIV-1 Pol protein available for further study. Therefore, we developed a workflow to predict the tertiary structure of HIV-1 NL4.3 Pol polyprotein. The modeled structure has comparable quality compared with the recently published partial HIV-1 Pol structure (PDB ID: 7SJX). Our HIV-1 NL4.3 Pol dimer model is the first full-length Pol tertiary structure. It can provide a structural platform for studying the autoprocessing mechanism of HIV-1 Pol and for developing new potent drugs. Moreover, the workflow can be used to predict other large protein structures that cannot be resolved via conventional experimental methods.

Plant protein solubility: A challenge or insurmountable obstacle

Currently, there is an increasing focus on comprehending the solubility of plant-based proteins, driven by the rising demand for animal-free food formulations. The solubility of proteins plays a crucial role in impacting other functional properties of proteins and food processing. Consequently, understanding protein solubility in a deeper sense may allow a better usage of plant proteins. Herein, we discussed the definition of protein solubility from both thermodynamic and colloidal perspectives. A range of factors affecting solubility of plant proteins are generalized, including intrinsic factors (amino acids composition, hydrophobicity), and extrinsic factors (pH, ionic strength, extraction and drying methods). Current methods to enhance solubility are outlined, including microwave, high intensity ultrasound, hydrostatic pressure, glycation, pH-shifting, enzymatic hydrolysis, enzymatic cross-linking, complexation and modulation of amino acids. We base the discussion on diverse modified methods of nitrogen solubility index available to determine and analyze protein solubility followed by addressing how other indigenous components affect the solubility of plant proteins. Some nonproteinaceous constituents in proteins such as carbohydrates and polyphenols may exert positive or negative impact on protein solubility. Appropriate protein extraction and modification methods that meet consumer and manufacturers requirements concerning nutritious and eco-friendly foods with lower cost should be investigated and further explored.

Impact of dipeptide on ADC physicochemical properties and efficacy identifies Ala-Ala as the optimal dipeptide

Side chains of natural occurring amino acids vary greatly in terms of charge state, polarity, size and hydrophobicity. Using a linear synthetic route, two amino acids were sequentially coupled to a potent glucocorticoid receptor modulator (GRM) to afford a library of dipeptide-GRM linker payloads with a range of in silico properties. The linker payloads were conjugated to a mouse anti-TNF antibody through interchain disulfide Cys. Impact of various dipeptide linkers on ADC physical properties, including solubility, hydrophobicity, and aggregation were evaluated and the in silico properties pI, Log P and tPSA of the linker drugs used to correlate with these properties. ADCs were screened in a GRE luciferase reporter assay to compare their in vitro efficacy. Data identified Ala-Ala as a superior dipeptide linker that allowed a maximum drug load of 10 while affording ADCs with low aggregation.

Aggregation of E121K mutant D-amino acid oxidase and ubiquitination-mediated autophagy mechanisms leading to amyotrophic lateral sclerosis

Amyotrophic Lateral Sclerosis (ALS) is a terminal adult-onset neuromuscular disorder. Our group has been studying this illness and previously reported novel mutations and rare mutations in a study using next-generation sequencing of DNA samples from Indian ALS patients. In this paper, we focus on the E121K mutation in the DAO gene to understand how it leads to ALS. Our experiments in SH-SY5Y cells indicate that the E121K mutation results in the accumulation of mutant protein aggregates, a change in cell morphology, and the death of neuronal cells. These protein aggregates get ubiquitinated and cause an imbalance in autophagy regulation. We observed an increase in the cellular concentrations of p62, OPTN, and LC3II. Through confocal microscopy studies, we show that the binding of p62 with ubiquitinated aggregates and its recruitment to LC3II mediates autophagosome generation. These relative changes in the key partners in autophagy increase cell death in cells harboring the E121K mutation and is a probable mechanism leading to ALS.

Health-promoting germinated rice and value-added foods: a comprehensive and systematic review of germination effects on brown rice

Over the last 30 years, thousands of articles have appeared examining the effects of soaking and germinating brown rice (BR). Variable germination conditions and methods have been employed to measure different health-beneficial parameters in a diverse germplasm of BR. Research results may therefore appear inconsistent with occasional anomalies, and it may be difficult to reach consensus concerning expected trends. Herein, we amassed a comprehensive review on germinated brown rice (GBR), attempting to codify 133 peer-reviewed articles regarding the effects on 164 chemical parameters related to health and nutrition in BR and in value-added food products. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-2020) approach was used to direct the flow of the literature search. A pair-wise comparison t-test was performed to deliver an overall approach indicating when a given compound has been found to significantly increase or decrease through germination, which was grouped into GABA and polyamines, γ-Oryzanol and phytosterols, phenolic compounds, vitamins, proteins and amino acids, starchy carbohydrates, free sugars, lipids, minerals and phytic acid. This resource will stimulate interest in germinating rice and optimistically help increase both production and consumption of highly nutritious, health-beneficial rice with pigmented bran.

Characterization and Classification In Silico of Peptides with Dual Activity (Antimicrobial and Wound Healing)

The growing challenge of chronic wounds and antibiotic resistance has spotlighted the potential of dual-function peptides (antimicrobial and wound healing) as novel therapeutic strategies. The investigation aimed to characterize and correlate in silico the physicochemical attributes of these peptides with their biological activity. We sourced a dataset of 207 such peptides from various peptide databases, followed by a detailed analysis of their physicochemical properties using bioinformatic tools. Utilizing statistical tools like clustering, correlation, and principal component analysis (PCA), patterns and relationships were discerned among these properties. Furthermore, we analyzed the peptides' functional domains for insights into their potential mechanisms of action. Our findings spotlight peptides in Cluster 2 as efficacious in wound healing, whereas Cluster 1 peptides exhibited pronounced antimicrobial potential. In our study, we identified specific amino acid patterns and peptide families associated with their biological activities, such as the cecropin antimicrobial domain. Additionally, we found the presence of polar amino acids like arginine, cysteine, and lysine, as well as apolar amino acids like glycine, isoleucine, and leucine. These characteristics are crucial for interactions with bacterial membranes and receptors involved in migration, proliferation, angiogenesis, and immunomodulation. While this study provides a groundwork for therapeutic development, translating these findings into practical applications necessitates additional experimental and clinical research.

Isolation and Identification of Antioxidant Peptides Derived from Cricket (Gryllus bimaculatus) Protein Fractions

Crickets contain high protein content that can be used to improve nutrition but are less exploited. This study was conducted to isolate different Cricket Protein Fractions including albumin, globulin, glutelin, and prolamin. All fractions were characterized and hydrolyzed by commercial enzymes. The results showed that the glutelin fractions had the highest extraction yields with 53.9 ± 2.12% (p < 0.05). Moreover, glutelin hydrolysate fraction prepared by Alcalase with a 16.35 ±0.29% hydrolysis degree was selected for further purification because of their high antioxidant activities, including ABTS radical-scavenging activity (0.44-0.55 µmol Trolox eq./g) and metal chelating activity (1721.99-1751.71 µmol EDTA eq./g). Two active fractions, GA-1 (<3 kDa) and GA-2 (<3 kDa), were collected from the consecutive purification of glutelin hydrolysates, which included processes such as membrane ultrafiltration and gel filtration. The fractions were analyzed by LC-MS/MS to obtain 10 peptides with 3-13 amino acids identified as TEAPLNPK, EVGA, KLL, TGNLPGAAHPLLL, AHLLT, LSPLYE, AGVL, VAAV, VAGL, and QLL with a molecular weight range of 359.23-721.37 Da in the two fractions. The amino acid sequence shows a prevalence of hydrophobic amino acids (50-100%) such as valine and leucine in the peptide chains, accounting for its high antioxidant activity. In conclusion, cricket glutelin hydrolysate prepared by Alcalase can serve as an alternative source of potent edible bioactive peptides in functional food products.

Earth Worming-An Evaluation of Earthworm (Eisenia andrei) as an Alternative Food Source

Aside from their bioremediation roles, little is known about the food and feed value of earthworms. In this study, a comprehensive evaluation of the nutritional composition (proximate analysis and profiles of fatty acids and minerals) and techno-functional properties (foaming and emulsion stability and capacity) of earthworm (Eisenia andrei, sourced in New Zealand) powder (EAP) were investigated. Lipid nutritional indices, ω6/ω3, atherogenicity index, thrombogenicity index, hypocholesterolemic/hypercholesterolemic acid ratio, and health-promoting index of EAP lipids are also reported. The protein, fat, and carbohydrate contents of EAP were found to be 53.75%, 19.30%, and 23.26% DW, respectively. The mineral profile obtained for the EAP consisted of 11 essential minerals, 23 non-essential minerals, and 4 heavy metals. The most abundant essential minerals were potassium (8220 mg·kg-1 DW), phosphorus (8220 mg·kg-1 DW), magnesium (744.7 mg·kg-1 DW), calcium (2396.7 mg·kg-1 DW), iron (244.7 mg·kg-1 DW), and manganese (25.6 mg·kg-1 DW). Toxic metals such as vanadium (0.2 mg·kg-1 DW), lead (0.2 mg·kg-1 DW), cadmium (2.2 mg·kg-1 DW), and arsenic (2.3 mg·kg-1 DW) were found in EAP, which pose safety considerations. Lauric acid (20.3% FA), myristoleic acid (11.20% FA), and linoleic acid (7.96% FA) were the most abundant saturated, monounsaturated, and polyunsaturated fatty acids, respectively. The lipid nutritional indices, such as IT and ω-6/ω-3, of E. andrei were within limits considered to enhance human health. A protein extract derived from EAP (EAPPE), obtained by alkaline solubilisation and pH precipitation, exhibited an isoelectric pH of ~5. The total essential amino acid content and essential amino acid index of EAPPE were 373.3 mg·g-1 and 1.36 mg·g-1 protein, respectively. Techno-functional analysis of EAPPE indicated a high foaming capacity (83.3%) and emulsion stability (88.8% after 60 min). Heat coagulation of EAPPE was greater at pH 7.0 (12.6%) compared with pH 5.0 (4.83%), corroborating the pH-solubility profile and relatively high surface hydrophobicity (1061.0). These findings demonstrate the potential of EAP and EAPPE as nutrient-rich and functional ingredients suitable as alternative food and feed material. The presence of heavy metals, however, should be carefully considered.

Edible insect as an alternative protein source: a review on the chemistry and functionalities of proteins under different processing methods

The consumption of edible insects can be anadvantageous alternative to the conventional food supply chain, which involves global water waste, land deficit, undernutrition, and starvation. Besides the nutritional aspects, insect proteins have demonstrated a wide range of functional properties such as foamability, emulsifying and gelling abilities. The protein content and amino acid profile of some insects have revealed a good nutritional value and interesting functional properties. However, it is crucial to comprehend how the protein quality is affected by insect feeding, drying, and defatting. There is a knowledge gap about the impact of industrial treatment, such as pH, ionic strength, and heat treatment, on insect proteins' functional properties. In this review, we have aimed to highlight the potential application of insect proteins as a nutritional source and their promising technological applications. The study reported the principal insect protein characterization methodologies that have been investigated in the literature aiming to correlate the physicochemical parameters to possible protein functionalities. The research on the functional properties of insect proteins is at the exploratory level. Further detailed studies are needed to clarify the structure-function relation of insect proteins and how these functionalities and insect processing can increase consumer acceptance.

Molecular engineering of a minimal E-cadherin inhibitor protein derived from Clostridium botulinum hemagglutinin

Hemagglutinin (HA), a nontoxic component of the botulinum neurotoxin (BoNT) complex, binds to E-cadherin and inhibits E-cadherin-mediated cell-cell adhesion. HA is a 470 kDa protein complex comprising six HA1, three HA2, and three HA3 subcomponents. Thus, to prepare recombinant full-length HA in vitro, it is necessary to reconstitute the macromolecular complex from purified HA subcomponents, which involves multiple purification steps. In this study, we developed NanoHA, a minimal E-cadherin inhibitor protein derived from Clostridium botulinum HA with a simple purification strategy needed for production. NanoHA, containing HA2 and a truncated mutant of HA3 (amino acids 380-626; termed as HA3^mini), is a 47 kDa single polypeptide (one-tenth the molecular weight of full-length HA, 470 kDa) engineered with three types of modifications: (i) a short linker sequence between the C terminus of HA2 and N terminus of HA3; (ii) a chimeric complex composed of HA2 derived from the serotype C BoNT complex and HA3^mini from the serotype B BoNT complex; and (iii) three amino acid substitutions from hydrophobic to hydrophilic residues on the protein surface. We demonstrated that NanoHA inhibits E-cadherin-mediated cell-cell adhesion of epithelial cells (e.g., Caco-2 and Madin-Darby canine kidney cells) and disrupts their epithelial barrier. Finally, unlike full-length HA, NanoHA can be transported from the basolateral side to adherens junctions via passive diffusion. Overall, these results indicate that the rational design of NanoHA provides a minimal E-cadherin inhibitor with a wide variety of applications as a lead molecule and for further molecular engineering.

Physicochemical Characteristics, Techno-Functionalities, and Amino Acid Profile of Prionoplus reticularis (Huhu) Larvae and Pupae Protein Extracts

The amino acid profile, techno-functionalities (foaming stability/capacity, emulsion stability/capacity, solubility, and coagulation), and physicochemical characteristics (colour, particle size, surface hydrophobicity, Fourier-transform infrared spectroscopy, and differential scanning calorimetry) of protein extracts (PE) obtained from Prionoplus reticularis (Huhu grub) larvae (HLPE) and pupae (HPPE) were investigated. Total essential amino acid contents of 386.7 and 411.7 mg/g protein were observed in HLPE and HPPE, respectively. The essential amino acid index (EAAI) was 3.3 and 3.4 for HLPE and HPPE, respectively, demonstrating their nutritional equivalence. A unique nitrogen-to-protein conversion constant, k, and the corresponding protein content of the extracts were 6.1 and 6.4 and 72.1% and 76.5%, respectively. HLPE (37.1 J/g) had a lower enthalpy than HPPE (54.1 J/g). HPPE (1% w/v) exhibited a foaming capacity of 50.7%, which was higher than that of HLPE (41.7%) at 150 min. The foaming stability was 75.3% for HLPE and 73.1% for HPPE after 120 min. Both protein extracts (1% w/v) had emulsifying capacities that were 96.8% stable after 60 min. Therefore, protein extracts from Huhu larvae and pupae are of a good nutritional quality (based on their EAAI) and have techno-functional properties, such as foaming and emulsification, that afford them potential for certain food technology applications.

Total free energy analysis of fully hydrated proteins

The total free energy of a hydrated biomolecule and its corresponding decomposition of energy and entropy provides detailed information about regions of thermodynamic stability or instability. The free energies of four hydrated globular proteins with different net charges are calculated from a molecular dynamics simulation, with the energy coming from the system Hamiltonian and entropy using multiscale cell correlation. Water is found to be most stable around anionic residues, intermediate around cationic and polar residues, and least stable near hydrophobic residues, especially when more buried, with stability displaying moderate entropy-enthalpy compensation. Conversely, anionic residues in the proteins are energetically destabilized relative to singly solvated amino acids, while trends for other residues are less clear-cut. Almost all residues lose intraresidue entropy when in the protein, enthalpy changes are negative on average but may be positive or negative, and the resulting overall stability is moderate for some proteins and negligible for others. The free energy of water around single amino acids is found to closely match existing hydrophobicity scales. Regarding the effect of secondary structure, water is slightly more stable around loops, of intermediate stability around β strands and turns, and least stable around helices. An interesting asymmetry observed is that cationic residues stabilize a residue when bonded to its N-terminal side but destabilize it when on the C-terminal side, with a weaker reversed trend for anionic residues.

Peptides and protein hydrolysates exhibiting anti-inflammatory activity: sources, structural features and modulation mechanisms

Inflammation is the response of the immune system to harmful stimuli such as tissue injury, infection or toxic chemicals, which has the aim of eliminating irritants or pathogenic microorganisms and enhancing tissue repair. Uncontrolled long-lasting acute inflammation can gradually progress to chronic, causing a variety of chronic inflammatory diseases that are usually treated with anti-inflammatory drugs, but most of them are inadequate to control chronic responses and are also associated with adverse side effects. Thus, many efforts are being directed to develop alternative and more selective anti-inflammatory therapies from natural products. One main field of interest is the obtaining of bioactive peptides exhibiting anti-inflammatory activity from sustainable protein sources like edible insects or agroindustry and fishing by-products. This work highlighted the structure-activity relationship of anti-inflammatory peptides. Small peptides with molecular weight under 1 kDa and amino acid chain length between 2 to 20 residues are generally the most active because of the higher probability to be absorbed in the intestine and penetrate into cells when compared with the larger size peptides. The presence of hydrophobic (Val, Ile, Pro) and positively charged (His, Arg, Lys) amino acids is another common occurrence for anti-inflammatory peptides. Interestingly, a high percentage (77%) of these bioactive peptides can be found in alternative sustainable protein sources such as Tenebrio molitor or sunflower, apart from its original protein source. However, not all of these peptides with anti-inflammatory potential in vitro achieve good scores by the in silico bioactivity predictors studied. Therefore, it is essential to implement current bioinformatics tools, in order to complement in vitro experiments with prior prediction of potential bioactive peptides.

Sequence Context and Complex Hofmeister Salt Interactions Dictate Phase Separation Propensity of Resilin-like Polypeptides

Resilin is an elastic material found in insects with exceptional durability, resilience, and extensibility, making it a promising biomaterial for tissue engineering. The monomeric precursor, pro-resilin, undergoes thermo-responsive self-assembly through liquid-liquid phase separation (LLPS). Understanding the molecular details of this assembly process is critical to developing complex biomaterials. The present study investigates the interplay between the solvent, sequence syntax, structure, and dynamics in promoting LLPS of resilin-like-polypeptides (RLPs) derived from domains 1 and 3 of Drosophila melanogaster pro-resilin. NMR, UV-vis, and microscopy data demonstrate that while kosmotropic salts and low pH promote LLPS, the effects of chaotropic salts with increasing pH are more complex. Subtle variations between the repeating amino acid motifs of resilin domain 1 and domain 3 lead to significantly different salt and pH dependence of LLPS, with domain 3 sequence motifs more strongly favoring phase separation under most conditions. These findings provide new insight into the molecular drivers of RLP phase separation and the complex roles of both RLP sequence and solution composition in fine-tuning assembly conditions.

Biophysical studies of amorphous protein aggregation and in vivo immunogenicity

Amorphous protein aggregates are oligomers that lack specific, high-order structures. Soluble amorphous aggregates are smaller than ~1 µm. Despite their lack of high-order structure, amorphous protein aggregates exhibit specific biophysical properties such as reversibility of formation, density, conformation, and biochemical stability. Our mutational analysis using a Solubility Controlling Peptide (SCP) tag strongly suggests that amorphous aggregation of small globular proteins can significantly increase in vivo immune response and that the magnitude of enhanced immune responses depends on the aggregates' biophysical and biochemical properties. We propose that SCP tags might help develop subunit (protein) adjuvant-free (immunostimulant-free) vaccines by controlling the aggregation propensity of target proteins.

Advanced Formulations/Drug Delivery Systems for Subcutaneous Delivery of Protein-Based Biotherapeutics

Multiple advanced formulations and drug delivery systems (DDSs) have been developed to deliver protein-based biotherapeutics via the subcutaneous (SC) route. These formulations/DDSs include high-concentration solution, co-formulation of two or more proteins, large volume injection, protein cluster/complex, suspension, nanoparticle, microparticle, and hydrogel. These advanced systems provide clinical benefits related to efficacy and safety, but meanwhile, have more complicated formulations and manufacturing processes compared to conventional solution formulations. To develop a fit-for-purpose formulation/DDS for SC delivery, scientists need to consider multiple factors, such as the primary indication, targeted site, immunogenicity, compatibility, biopharmaceutics, patient compliance, etc. Next, they need to develop appropriate formulation (s) and manufacturing processes using the QbD principle and have a control strategy. This paper aims to provide a comprehensive review of advanced formulations/DDSs recently developed for SC delivery of proteins, as well as some knowledge gaps and potential strategies to narrow them through future research.

Immuno-dominant dengue NS1 peptides as antigens for production of monoclonal antibodies

Synthetic peptides have recently become common as antigens for antibody production. Peptides are short chains of amino acids that can be used to elicit an immune response. The immunogenicity of the peptide antigens varies depending on the length, charge, solubility, and amino acids contained in the peptide sequence. Dengue NS1 protein is an important target antigen in the early detection of dengue infection. In this study, peptides corresponding to a highly conserved region from the dengue NS1 region were designed and synthesized. Balb/C mice were immunized against each peptide and spleen cells extracted from the immunized mice were fused with NS0 murine myeloma cells. Hybridoma clones obtained from the fusions were tested against peptides using ELISA. Out of 1,830 growing clones, 28 clones produced antibodies reacting with dengue NS1 peptides. A purified monoclonal antibody reacting with all four peptides was tested for reactivity with dengue NS1 native protein using dengue-confirmed serum and urine samples. The monoclonal antibody shows significant reactivity with both serum and urine. The findings of the current research can be used to detect dengue infection using urine, which ultimately results in the prevention of dengue epidemics through painless diagnosis, following treatment, and patient management to safeguard human and economic wellness.

Chemical Conjugation to Less Targeted Proteinogenic Amino Acids

Protein bioconjugates are in high demand for applications in biomedicine, diagnostics, chemical biology and bionanotechnology. Proteins are large and sensitive molecules containing multiple different functional groups and in particular nucleophilic groups. In bioconjugation reactions it can therefore be challenging to obtain a homogeneous product in high yield. Numerous strategies for protein conjugation have been developed, of which a vast majority target lysine, cysteine and to a lesser extend tyrosine. Likewise, several methods that involve recombinantly engineered protein tags have been reported. In recent years a number of methods have emerged for chemical bioconjugation to other amino acids and in this review, we present the progress in this area.

Protein Design: From the Aspect of Water Solubility and Stability

Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.

Alternative CUG Codon Usage in the Halotolerant Yeast Debaryomyces hansenii: Gene Expression Profiles Provide New Insights into Ambiguous Translation

The halotolerant yeast Debaryomyces hansenii belongs to the CTG-Ser1 clade of fungal species that use the CUG codon to translate as leucine or serine. The ambiguous decoding of the CUG codon is relevant for expanding protein diversity, but little is known about the role of leucine–serine ambiguity in cellular adaptations to extreme environments. Here, we examine sequences and structures of tRNA_CAG from the CTG-Ser1 clade yeasts, finding that D. hansenii conserves the elements to translate ambiguously. Then, we show that D. hansenii has tolerance to conditions of salinity, acidity, alkalinity, and oxidative stress associated with phenotypic and ultrastructural changes. In these conditions, we found differential expression in both the logarithmic and stationary growth phases of tRNA^Ser, tRNA^Leu, tRNA_CAG, LeuRS, and SerRS genes that could be involved in the adaptive process of this yeast. Finally, we compare the proteomic isoelectric points and hydropathy profiles, detecting that the most important variations among the physicochemical characteristics of D. hansenii proteins are in their hydrophobic and hydrophilic interactions with the medium. We propose that the ambiguous translation, i.e., leucylation or serynation, on translation of the CUG-encoded residues, could be linked to adaptation processes in extreme environments.

A Statistical Analysis of the Sequence and Structure of Thermophilic and Non-Thermophilic Proteins

Thermophilic proteins have various practical applications in theoretical research and in industry. In recent years, the demand for thermophilic proteins on an industrial scale has been increasing; therefore, the engineering of thermophilic proteins has become a hot direction in the field of protein engineering. However, the exact mechanism of thermostability of proteins is not yet known, for engineering thermophilic proteins knowing the basis of thermostability is necessary. In order to understand the basis of the thermostability in proteins, we have made a statistical analysis of the sequences, secondary structures, hydrogen bonds, salt bridges, DHA (Donor-Hydrogen-Accepter) angles, and bond lengths of ten pairs of thermophilic proteins and their non-thermophilic orthologous. Our findings suggest that polar amino acids contribute to thermostability in proteins by forming hydrogen bonds and salt bridges which provide resistance against protein denaturation. Short bond length and a wider DHA angle provide greater bond stability in thermophilic proteins. Moreover, the increased frequency of aromatic amino acids in thermophilic proteins contributes to thermal stability by forming more aromatic interactions. Additionally, the coil, helix, and loop in the secondary structure also contribute to thermostability.

Enhancement of solubility of recombinant alcohol dehydrogenase from Rhodococcus ruber using predictive tool

Solubility is one of key factors influencing the heterologous production of recombinant proteins in biotechnology. Among many aggregation-prone proteins, alcohol dehydrogenase (ADH-A) from Rhodococcus ruber (in this work abbreviated RrADH) shows a great potential in processes involved in the biotransformation of natural compounds. As ADH-A is a potentially high value asset in industrial biotransformation processes, improvement of its solubility would be of major commercial benefit. Predictive tools and in silico analysis provide a fast means for improving protein properties, for selecting appropriate changes, and ultimately for saving costs. We have therefore focused on enhancement of the solubility of RrADH using an online accesible predictive tool Aggrescan 3D 2.0. Selected mutations were introduced into the protein amino acid sequence by using site-directed PCR. This led to a 17% increase in the protein solubility of RrADHmut1 and a 98% increase for RrADHmut2. Moreover, the basic kinetics of the enzyme reaction were positively affected, further optimizing the overall performance of the production process.

Changes in Carbon Partitioning and Pattern of Antioxidant Enzyme Activity Induced by Arginine Treatment in the Green Microalga Dunaliella salina Under Long-Term Salinity

In this work, the effects of arginine (Arg) on biochemical responses and antioxidant enzyme activity in the green microalga Dunaliella salina grown at different salt concentrations were investigated. Suspensions adapted with the concentrations of 1, 2, and 3 M NaCl were treated at the exponential growth phase with a concentration of 5 mM Arg. Salt stress was associated with a large decrease in the number of cells and non-reducing sugar levels but accumulated higher amounts of chlorophyll, β-carotene, reducing sugar, starch, total protein, free amino acid, and glycerol. Increased levels of protein carbonylation, lipid peroxidation, proteolysis, hydrogen peroxide, and antioxidant enzyme activity also occurred during salinity. Arg treatment changed the pattern of biochemical responses in the cells grown at high salinity by directing carbon flow to the biosynthesis of non-reducing sugars instead of starch, lowering levels of hydrogen peroxide, and downregulating antioxidant enzyme activity, but the levels of lipid peroxidation, glycerol, and β-carotene remained nearly unchanged. These results suggest that Arg treatment alleviates salinity-induced oxidative stress in D. salina cells by modifying carbon partitioning and inducing signaling molecules rather than antioxidant enzymes.

PERISCOPE-Opt: Machine learning-based prediction of optimal fermentation conditions and yields of recombinant periplasmic protein expressed in Escherichia coli

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The ensemble model considered both fermentation conditions and protein properties.

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Optimal fermentation conditions and periplasmic recombinant protein yield can be predicted.

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Predictor’s accuracy and Pearson correlation coefficient are 75% and 0.91, respectively.

Optimization of the fermentation process for recombinant protein production (RPP) is often resource-intensive. Machine learning (ML) approaches are helpful in minimizing the experimentations and find vast applications in RPP. However, these ML-based tools primarily focus on features with respect to amino-acid-sequence, ruling out the influence of fermentation process conditions. The present study combines the features derived from fermentation process conditions with that from amino acid-sequence to construct an ML-based model that predicts the maximal protein yields and the corresponding fermentation conditions for the expression of target recombinant protein in the Escherichia coli periplasm. Two sets of XGBoost classifiers were employed in the first stage to classify the expression levels of the target protein as high (>50 mg/L), medium (between 0.5 and 50 mg/L), or low (<0.5 mg/L). The second-stage framework consisted of three regression models involving support vector machines and random forest to predict the expression yields corresponding to each expression-level-class. Independent tests showed that the predictor achieved an overall average accuracy of 75% and a Pearson coefficient correlation of 0.91 for the correctly classified instances. Therefore, our model offers a reliable substitution of numerous trial-and-error experiments to identify the optimal fermentation conditions and yield for RPP. It is also implemented as an open-access webserver, PERISCOPE-Opt (http://periscope-opt.erc.monash.edu).

Synthetic pro-peptide design to enhance the secretion of heterologous proteins by Saccharomyces cerevisiae

Heterologous protein production in Saccharomyces cerevisiae is a useful and effective strategy with many advantages, including the secretion of proteins that require posttranslational processing. However, heterologous proteins in S. cerevisiae are often secreted at comparatively low levels. To improve the production of the heterologous protein, human granulocyte colony-stimulating factor (hG-CSF) in S. cerevisiae, a secretion-enhancing peptide cassette including an hIL-1β-derived pro-peptide, was added and used as a secretion enhancer to alleviate specific bottlenecks in the yeast secretory pathway. The effects of three key parameters-N-glycosylation, net negative charge balance, and glycine-rich flexible linker-were investigated in batch cultures of S. cerevisiae. Using a three-stage design involving screening, selection, and optimization, the production and secretion of hG-CSF by S. cerevisiae were significantly increased. The amount of extracellular mature hG-CSF produced by the optimized pro-peptide after the final stage increased by 190% compared to that of the original pro-peptide. Although hG-CSF was used as the model protein in the current study, this strategy is applicable to the enhanced production of other heterologous proteins, using S. cerevisiae as the host.

Two physics-based models for pH-dependent calculations of protein solubility

When engineering a protein for its biological function, many physicochemical properties are also optimized throughout the engineering process, and the protein's solubility is among the most important properties to consider. Here, we report two novel computational methods to calculate the pH-dependent protein solubility, and to rank the solubility of mutants. The first is an empirical method developed for fast ranking of the solubility of a large number of mutants of a protein. It takes into account electrostatic solvation energy term calculated using Generalized Born approximation, hydrophobic patches, protein charge, and charge asymmetry, as well as the changes of protein stability upon mutation. This method has been tested on over 100 mutations for 17 globular proteins, as well as on 44 variants of five different antibodies. The prediction rate is over 80%. The antibody tests showed a Pearson correlation coefficient, R, with experimental data from .83 to .91. The second method is based on a novel, completely force-field-based approach using CHARMm program modules to calculate the binding energy of the protein to a part of the crystal lattice, generated from X-ray structure. The method predicted with very high accuracy the solubility of Ribonuclease SA and its 3K and 5K mutants as a function of pH without any parameter adjustments of the existing BIOVIA Discovery Studio binding affinity model. Our methods can be used for rapid screening of large numbers of design candidates based on solubility, and to guide the design of solution conditions for antibody formulation.

Evolution and co-evolution: insights into the divergence of plant heat shock factor genes

The Heat Shock Factor (Hsf) genes are widely distributed across the plant kingdom regulating the plant response to various abiotic stresses. In addition to natural selection, breeding and accelerated selection changed the structure and function of Hsf genes. 1076 Hsf genes from 30 genera from primitive algae to the most advanced plant species and major crop plants were used for phylogenetic analysis. The interspecific divergence was studied with 11 members of genus Oryza while intraspecific divergence was studied with sesame pan-genome adapted to diverse ecological niches. B2 genes in eudicots and monocots originated separately while A1 gave rise to the recently evolved Class-C genes and land colonization happened with evolution of A1 genes. An increase in the number of lineages in the Oryza clade with the evolution of AA genome indicated independent domestication and positive selection was observed in > 53% of loci whereas the highly conserved homologues were under purifying selection. The paralogous genes under positive selection exhibited more domain changes for diversified function and increased fitness. A significant co-evolving cluster involving amino acids Phenylalanine, Lysine and Valine played crucial role in maintaining hydrophobic core along with highly conserved Tryptophan residues. A mutation of Glutamic acid to Glutamine was observed in A8 genes of Lamiales affecting protein solvency. Breeding resulted in accumulation of mutations reducing the hydrophobicity of proteins and a further reduction in protein aggregation. This study identify genome duplications, non-neutral selection and co-evolving residues as causing drastic changes in the conserved domain of Hsf proteins.

Supplementary information

The online version contains supplementary material available at 10.1007/s12298-022-01183-7.

Structure and activity of a thermally stable mutant of Acanthamoeba actophorin

Actophorin, which was recently tested for crystallization under microgravity on the International Space Station, was subjected to mutagenesis to identify a construct with improved biophysical properties that were expected to improve the extent of diffraction. First, 20 mutations, including one C-terminal deletion of three residues, were introduced individually into actophorin, resulting in modest increases in thermal stability of between +0.5°C and +2.2°C. All but two of the stabilizing mutants increased both the rates of severing F-actin filaments and of spontaneous polymerization of pyrenyl G-actin in vitro. When the individual mutations were combined into a single actophorin variant, Acto-2, the overall thermal stability was 22°C higher than that of wild-type actophorin. When an inactivating S2P mutation in Acto-2 was restored, Acto-2/P2S was more stable by 20°C but was notably more active than the wild-type protein. The inactivating S2P mutation reaffirms the importance that Ser2 plays in the F-actin-severing reaction. The crystal structure of Acto-2 was solved to 1.7 Å resolution in a monoclinic space group, a first for actophorin. Surprisingly, despite the increase in thermal stability, the extended β-turn region, which is intimately involved in interactions with F-actin, is disordered in one copy of Acto-2 in the asymmetric unit. These observations emphasize the complex interplay among protein thermal stability, function and dynamics.

Influence of non-thermal microwaveradiationon emulsifying properties of sunflower protein

Sunflower protein isolate obtained from industrially de-oiled press cake was treated with non-thermal microwave, aiming to investigate how structure and emulsifying properties were affected. Our results indicated that the content of polar amino acids was decreased and solubility and surface hydrophobicity were altered upon exposure to non-thermal microwave. Higher solubility and surface hydrophobicity of the samples treated with defrost mode and also 350 W were accompanied by a smaller size and lower uniformity of the oil droplets compared to the control and other samples. Non-thermal microwave treatment improved the emulsion stability by 1.43 times and defrost mode treated sample had the lowest stability index after 120 min. Interfacial dilatational rheology measurements revealed that 70 and 350 W treated samples created higher elastic, less stretchable solid-like layer at the O/W interface in comparison with defrost mode treated and control samples. Consequently, non-thermal microwave treatment could be considered as a promising simple, fast, and "green" protein modification technique.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

Characterization of Novel Selected Microalgae for Antioxidant Activity and Polyphenols, Amino Acids, and Carbohydrates

The biochemical composition of three novel selected microalgae strains (Chlorophyta) was evaluated to confirm their potential possibilities as new sustainably produced biomass with nutritional, functional, and/or biomedical properties. Extracts from cultured Pseudopediastrum boryanum, Chloromonas cf. reticulata, and Chloroidium saccharophilum exhibited higher radical scavenging activity of DPPH (1,1-diphenyl-2-picrylhydrazyl) when compared to butylated hydroxytoluene (BHT), but lower than butylated hydroxyanisole (BHA). Total phenolic compounds and amino acids were determined by newly developed RP-HPLC methods. Total phenolic contents, as µg g⁻¹ of dry biomass, reached 27.1 for C. cf. reticulata, 26.4 for P. boryanum, and 55.8 for C. saccharophilum. Percentages of total analysed amino acids were 24.3, 32.1, and 18.5% of dry biomass, respectively, presenting high values for essential amino acids reaching 54.1, 72.6, and 61.2%, respectively. Glutamic acid was the most abundant free amino acid in all microalgae samples, followed by proline and lysine in C. saccharophilum and P. boryanum, and methionine and lysine in C. reticulata. Soluble carbohydrates in aqueous extracts ranged from 39.6 for C. saccharophilum to 49.3% for C. reticulata, increasing values to 45.1 for C. saccharophilum and 52.7% for P. boryanum in acid hydrolysates of dried biomass. Results confirmed the potential possibilities of these microalgae strains.

Enabling biocatalysis in high-concentration organic cosolvent by enzyme gate engineering

Biocatalysis in high-concentration organic solvents (OSs) offers many advantages, but realizing this process remains a huge challenge. An R-selective ω-amine transaminase variant (AcATA_M2 ) exhibited high activity toward 50 g/L pro-sitagliptin ketone 1-[1-piperidinyl]-4-[2,4,5-trifluorophenyl]-1,3-butanedione (PTfpB). However, AcATA_M2 displayed unsatisfactory organic-cosolvent resistance against high-concentration dimethyl sulfoxide (DMSO), which is required to enhance the solubility of the hydrophobic substrate PTfpB. Located in the substrate-binding tunnel, enzyme gates are structural elements that undergo reversible conformational transitions, thus affecting the accessibility of the binding pocket to solvent molecules. Depending on the conformation of the enzyme gates, one can define an open or closed conformation on which the enzyme activity in OSs may depend. To enhance the DMSO resistance of AcATA_M2 , we identified the beneficial residues at the "enzyme gate" region via computational analysis, alanine scanning, and site-saturation mutagenesis. Two beneficial variants, namely, AcATA_M2 ^F56D and AcATA_M2 ^F56V , not only displayed improved enzyme activity but also exhibited enhanced DMSO resistance (the half-life value increased from 25.71 to 42.49 h under 60% DMSO). Molecular dynamic simulations revealed that the increase in DMSO resistance was mainly caused by the decrease in the number of DMSO molecules in the substrate-binding pocket. Moreover, in the kilogram-scale experiment, the conversion of 80 g/L substrate was increased from 50% (AcATA_M2 ) to 85% (M2^F56D in 40% DMSO) with a high e.e. of >99% within 24 h.

DSResSol: A Sequence-Based Solubility Predictor Created with Dilated Squeeze Excitation Residual Networks

Protein solubility is an important thermodynamic parameter that is critical for the characterization of a protein's function, and a key determinant for the production yield of a protein in both the research setting and within industrial (e.g., pharmaceutical) applications. Experimental approaches to predict protein solubility are costly, time-consuming, and frequently offer only low success rates. To reduce cost and expedite the development of therapeutic and industrially relevant proteins, a highly accurate computational tool for predicting protein solubility from protein sequence is sought. While a number of in silico prediction tools exist, they suffer from relatively low prediction accuracy, bias toward the soluble proteins, and limited applicability for various classes of proteins. In this study, we developed a novel deep learning sequence-based solubility predictor, DSResSol, that takes advantage of the integration of squeeze excitation residual networks with dilated convolutional neural networks and outperforms all existing protein solubility prediction models. This model captures the frequently occurring amino acid k-mers and their local and global interactions and highlights the importance of identifying long-range interaction information between amino acid k-mers to achieve improved accuracy, using only protein sequence as input. DSResSol outperforms all available sequence-based solubility predictors by at least 5% in terms of accuracy when evaluated by two different independent test sets. Compared to existing predictors, DSResSol not only reduces prediction bias for insoluble proteins but also predicts soluble proteins within the test sets with an accuracy that is at least 13% higher than existing models. We derive the key amino acids, dipeptides, and tripeptides contributing to protein solubility, identifying glutamic acid and serine as critical amino acids for protein solubility prediction. Overall, DSResSol can be used for the fast, reliable, and inexpensive prediction of a protein's solubility to guide experimental design.

Compositional Features and Nutritional Value of Pig Brain: Potential and Challenges as a Sustainable Source of Nutrients

The goal of this study was to establish the nutritional value and compositional properties of the brains of crossbred pigs (Landrace-Large white-Duroc (LLD)), in order to realize the zero-waste concept and increase the use of by-products in the sustainable meat industry. Fat (9.25% fresh weight (fw)) and protein (7.25% fw) were the principal dry matters of pig brain, followed by carbohydrate and ash. Phospholipid and cholesterol had a 3:1 ratio. Pig brain had a red tone (L* = 63.88, a* = 5.60, and b* = 15.43) and a high iron content (66 mg/kg) due to a total heme protein concentration of 1.31 g/100 g fw. The most prevalent macro-element was phosphorus (14 g/kg), followed by potassium, sodium, calcium, and magnesium. Zinc, copper, and manganese were among the other trace elements discovered. The most prevalent nitrogenous constituents were alkali-soluble protein, followed by water-soluble protein, stromal protein, salt-soluble protein, and non-protein nitrogen. Essential amino acids were abundant in pig brain (44% of total amino acids), particularly leucine (28.57 mg/g protein), threonine, valine, and lysine. The total lipid, neutral, and polar lipid fractions of the pig brain had different fatty acid compositions. The largest amount was observed in saturated fatty acids (SFA), followed by monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA). Stearic acid and palmitic acid were the most common SFA. Oleic acid was the most prevalent MUFA, while docosahexaenoic acid was the most common PUFA. Thus, the pig brain can be used in food formulations as a source of nutrients.