IPC 2.0: prediction of isoelectric point and pKa dissociation constants

A Three-Dimensional Electrochemiluminescence Sensor Integrated with Peptide Hydrogel for Detection of H2O2 Released from Different Subtypes of Breast Cancer Cells

Breast cancer is a malignant tumor, with various subtypes showing different behaviors. Endogenous H2O2 is an important marker of tumor progression, which makes it important to study the relationship between breast cancer subtypes and H2O2 for pathogenesis and treatment strategies, but this has rarely been reported so far. In this work, we constructed a three-dimensional (3D) electrochemiluminescence (ECL) sensing platform for the detection of H2O2 released from two typical subtypes of breast cancer cells (MCF-7 cells for luminal A-type and MDA-MB-231 cells for three negative breast cancers, TNBCs). To adequately replicate the tumor microenvironment, the peptide hydrogel was introduced as a scaffold for 3D cell culture. The titanium foam (TF) was used as a 3D electrode to better match the 3D culture substrate. N-(4-Aminobutyl)-N-ethylisoluminol (ABEI) was selected as the ECL emitter and assembled into the peptide hydrogel by hydrogen bonding and π-stacking, which resulted in a stable and homogeneous distribution of ABEI along the hydrogel fibers. Furthermore, basic amino acids were introduced to provide alkaline microenvironment for ABEI. Therefore, ABEI exhibited high ECL efficiency, resulting in a high sensitivity with an ultralow detection limit of 0.023 nM (S/N = 3) for H2O2 of the proposed ECL biosensor. MCF-7 and MDA-MB-231 cells were cultured in a 3D peptide hydrogel/ABEI/TF electrode, respectively, and endogenous H2O2 was successfully monitored. A notably significant difference of H2O2 released between MDA-MB-231 cells and MCF-7 cells without stimulation but similar extra release with stimulation were observed. These findings may help understand the physiological mechanisms behind the various subtypes and reactive oxygen species (ROS)-related treatment for breast cancer.

Shotgun proteomics of detergent-solubilized proteins from Trypanosoma evansi

Trypanosoma evansi, the causative agent of surra, is the most prevalent pathogenic salivarian trypanosome and affects the majority of domesticated and wild animals in endemic regions. This work aimed to analyze detergent-solubilized T. evansi proteins and identify potential diagnostic biomarkers for surra. Triton X-114-extracted membrane-enriched proteins (MEP) of T. evansi bloodstream forms were analyzed using a gel-free technique (LC-ESI-MS/MS). 247 proteins were identified following the MS analysis of three biological and technical replicates. Two of these proteins were predicted to have a GPI-anchor, 100 (40%) were predicted to have transmembrane domains, and 166 (67%) were predicted to be membrane-bound based on at least one of six features: location (WolfPSORT, DeepLoc-2.0, Protcomp-9.0), transmembrane, GPI, and gene ontology. It was predicted that 76 (30%) of proteins had membrane evidence. Typical membrane proteins for each organelle were identified, among them ISG families (64, 65, and 75 kDa), flagellar calcium-binding protein, 24 kDa calflagin, syntaxins and oligosaccharyltransferase some of which had previously been studied in other trypanosomatids. T. evansi lacks singletons and exclusive orthologous groups, whereas three distinct epitopes have been identified. Data are available via ProteomeXchange with identifier PXD040594. SIGNIFICANCE: Trypanosoma evansi is a highly prevalent parasite that induces a pathological condition known as "surra" in various species of ungulates across five continents. The infection gives rise to symptoms that are not pathognomonic, thereby posing challenges in its diagnosis and leading to substantial economic losses in the livestock industry. A significant challenge arises from the absence of a diagnostic test capable of distinguishing between Trypanosoma equiperdum and T. evansi, both of which are implicated in equine diseases. Therefore, there is a pressing need to conduct research on the biochemistry of the parasite in order to identify proteins that could potentially serve as targets for differential diagnosis or therapeutic interventions.

PypKa server: online pKa predictions and biomolecular structure preparation with precomputed data from PDB and AlphaFold DB

When preparing biomolecular structures for molecular dynamics simulations, pKa calculations are required to provide at least a representative protonation state at a given pH value. Neglecting this step and adopting the reference protonation states of the amino acid residues in water, often leads to wrong electrostatics and nonphysical simulations. Fortunately, several methods have been developed to prepare structures considering the protonation preference of residues in their specific environments (pKa values), and some are even available for online usage. In this work, we present the PypKa server, which allows users to run physics-based, as well as ML-accelerated methods suitable for larger systems, to obtain pKa values, isoelectric points, titration curves, and structures with representative pH-dependent protonation states compatible with commonly used force fields (AMBER, CHARMM, GROMOS). The user may upload a custom structure or submit an identifier code from PBD or UniProtKB. The results for over 200k structures taken from the Protein Data Bank and the AlphaFold DB have been precomputed, and their data can be retrieved without extra calculations. All this information can also be obtained from an application programming interface (API) facilitating its usage and integration into existing pipelines as well as other web services. The web server is available at pypka.org.

Computer-driven Evolution of Myrosinase from the Cabbage Aphid for Efficient Production of (R)-Sulforaphane

Myrosinase (Myr) catalyzes the hydrolysis of glucosinolates, yielding biologically active metabolites. In this study, glucoraphanin (GRA) extracted from broccoli seeds was effectively hydrolyzed using a Myr-obtained cabbage aphid (Brevicoryne brassicae) (BbMyr) to produce (R)-sulforaphane (SFN). The gene encoding BbMyr was successfully heterologously expressed in Escherichia coli, resulting in the production of 1.6 g/L (R)-SFN, with a remarkable yield of 20.8 mg/gbroccoli seeds, achieved using recombination E. coli whole-cell catalysis under optimal conditions (pH 4.5, 45 °C). Subsequently, BbMyr underwent combinatorial simulation-driven mutagenesis, yielding a mutant, DE9 (N321D/Y426S), showing a remarkable 2.91-fold increase in the catalytic efficiency (kcat/KM) compared with the original enzyme. Molecular dynamics simulations demonstrated that the N321D mutation in loopA of mutant DE9 enhanced loopA stability by inducing favorable alterations in hydrogen bonds, while the Y426S mutation in loopB decreased spatial resistance. This research lays a foundation for the environmentally sustainable enzymatic (R)-SFN synthesis.

The Rapid Evolution of De Novo Proteins in Structure and Complex

Recent studies in the rice genome-wide have established that de novo genes, evolving from noncoding sequences, enhance protein diversity through a stepwise process. However, the pattern and rate of their evolution in protein structure over time remain unclear. Here, we addressed these issues within a surprisingly short evolutionary timescale (<1 million years for 97% of Oryza de novo genes) with comparative approaches to gene duplicates. We found that de novo genes evolve faster than gene duplicates in the intrinsically disordered regions (such as random coils), secondary structure elements (such as α helix and β strand), hydrophobicity, and molecular recognition features. In de novo proteins, specifically, we observed an 8% to 14% decay in random coils and intrinsically disordered region lengths and a 2.3% to 6.5% increase in structured elements, hydrophobicity, and molecular recognition features, per million years on average. These patterns of structural evolution align with changes in amino acid composition over time as well. We also revealed higher positive charges but smaller molecular weights for de novo proteins than duplicates. Tertiary structure predictions showed that most de novo proteins, though not typically well folded on their own, readily form low-energy and compact complexes with other proteins facilitated by extensive residue contacts and conformational flexibility, suggesting a faster-binding scenario in de novo proteins to promote interaction. These analyses illuminate a rapid evolution of protein structure in de novo genes in rice genomes, originating from noncoding sequences, highlighting their quick transformation into active, protein complex-forming components within a remarkably short evolutionary timeframe.

Membraneless channels sieve cations in ammonia-oxidizing marine archaea

Nitrosopumilus maritimus is an ammonia-oxidizing archaeon that is crucial to the global nitrogen cycle1,2. A critical step for nitrogen oxidation is the entrapment of ammonium ions from a dilute marine environment at the cell surface and their subsequent channelling to the cell membrane of N. maritimus. Here we elucidate the structure of the molecular machinery responsible for this process, comprising the surface layer (S-layer), using electron cryotomography and subtomogram averaging from cells. We supplemented our in situ structure of the ammonium-binding S-layer array with a single-particle electron cryomicroscopy structure, revealing detailed features of this immunoglobulin-rich and glycan-decorated S-layer. Biochemical analyses showed strong ammonium binding by the cell surface, which was lost after S-layer disassembly. Sensitive bioinformatic analyses identified similar S-layers in many ammonia-oxidizing archaea, with conserved sequence and structural characteristics. Moreover, molecular simulations and structure determination of ammonium-enriched specimens enabled us to examine the cation-binding properties of the S-layer, revealing how it concentrates ammonium ions on its cell-facing side, effectively acting as a multichannel sieve on the cell membrane. This in situ structural study illuminates the biogeochemically essential process of ammonium binding and channelling, common to many marine microorganisms that are fundamental to the nitrogen cycle.

Unveiling cytokine charge disparity as a potential mechanism for immune regulation

Cytokines are small signaling proteins that regulate the immune responses to infection and tissue damage. Surface charges of cytokines determine their in vivo fate in immune regulation, e.g., half-life and distribution. The overall negative charges in the extracellular microenvironment and the acidosis during inflammation and infection may differentially impact cytokines with different surface charges for fine-tuned immune regulation via controlling tissue residential properties. However, the trend and role of cytokine surface charges has yet to be elucidated in the literature. Interestingly, we have observed that most pro-inflammatory cytokines have a negative charge, while most anti-inflammatory cytokines and chemokines have a positive charge. In this review, we extensively examined the surface charges of all cytokines and chemokines, summarized the pharmacokinetics and tissue adhesion of major cytokines, and analyzed the link of surface charge with cytokine biodistribution, activation, and function in immune regulation. Additionally, we identified that the general trend of charge disparity between pro- and anti-inflammatory cytokines represents a unique opportunity to develop precise immune modulation approaches, which can be applied to many inflammation-associated diseases including solid tumors, chronic wounds, infection, and sepsis.

Immunoglobulin repertoire sequencing and de novo sequencing - Powerful tools for identifying free light chains from patients with light chain cast nephropathy

In patients with light chain cast nephropathy (LCCN), abundantly produced monoclonal immunoglobulin free light chains (FLCs) play a vital role in pathogenesis. Determining the precise sequences of patient-derived FLCs is therefore highly desirable. Although immunoglobulin repertoire sequencing (5' RACE-seq) has been proven to be sensitive enough to provide full-length V(D)J region (variable, diversity and joining genes) of FLCs using bone marrow samples, an invasive and bone marrow independent method is still in demand. Here a de novo sequencing workflow based on the bottom-up proteomics for patient-derived FLCs was established. PEAKS software was used for the de novo sequencing of peptides that were further assembled into full-length FLC sequences. This de novo protein sequencing method can obtain the full-length amino acid sequences of FLCs, and had been shown to be as reliable as 5' RACE-seq. The two LCCN sequences derived from above the two methods were identical, and they possessed more hydrophobic or nonpolar amino acids compared with the corresponding germline, which may be associated with the pathogenesis.

Dissolution of ribonucleoprotein condensates by the embryonic stem cell protein L1TD1

L1TD1 is a cytoplasmic RNA-binding protein specifically expressed in pluripotent stem cells and, unlike its mouse ortholog, is essential for the maintenance of stemness in human cells. Although L1TD1 is the only known protein-coding gene domesticated from a LINE-1 (L1) retroelement, the functional legacy of its ancestral protein, ORF1p of L1, and how it is manifested in L1TD1 are still unknown. Here, we determined RNAs associated with L1TD1 and found that, like ORF1p, L1TD1 binds L1 RNAs and localizes to high-density ribonucleoprotein (RNP) condensates. Unexpectedly, L1TD1 enhanced the translation of a subset of mRNAs enriched in the condensates. L1TD1 depletion promoted the formation of stress granules in embryonic stem cells. In HeLa cells, ectopically expressed L1TD1 facilitated the dissolution of stress granules and granules formed by pathological mutations of TDP-43 and FUS. The glutamate-rich domain and the ORF1-homology domain of L1TD1 facilitated dispersal of the RNPs and induced autophagy, respectively. These results provide insights into how L1TD1 regulates gene expression in pluripotent stem cells. We propose that the ability of L1TD1 to dissolve stress granules may provide novel opportunities for treatment of neurodegenerative diseases caused by disturbed stress granule dynamics.

Retention time prediction for post-translationally modified peptides: Ser, Thr, Tyr-phosphorylation

The development of a peptide retention prediction model for reversed-phase chromatography applications in proteomics is reported for peptides carrying phosphorylated Ser, Thr and Tyr-residues. The major retention features have been assessed using a collection of over 10,000 phosphorylated/non-phosphorylated peptide pairs identified in a series 1D and 2D LC-MS/MS acquisitions using formic acid as ion pairing modifier. Single modification event on average results in increased peptide retention for phosphorylation of Ser (+ 1.46), Thr (+1.33), Tyr (+0.93% acetonitrile, ACN) on gradient elution scale for Luna C18(2) stationary phase. We established several composition and sequence specific features, which drive deviations from these average values. Thus, single phosphorylation of serine results in retention shifts ranging from -2.4 to 5.5% ACN depending on position of the residue, nature of nearest neighbour residues, peptide length, hydrophobicity and pI value, and its propensity to form amphipathic helical structures. We established that the altered ion-pairing environment upon phosphorylation is detrimental for this variability. Hydrophobicity of ion-pairing modifier directly informs the magnitude of expected shifts: (most hydrophilic) 0.5 % acetic acid (larger positive shift upon phosphorylation) > 0.1 % formic acid (positive) > 0.1 % trifluoroacetic (negative) > 0.1 % heptafluorobutyric acid (larger negative shift). The effect of phosphorylation has been also evaluated for several separation conditions used in the first dimension of 2D LC applications: high pH reversed-phase (RP), hydrophilic interaction liquid chromatography (HILIC), strong cation- and strong anion exchange separations.

Fluorescent proteins generate a genetic color polymorphism and counteract oxidative stress in intertidal sea anemones

Fluorescent proteins (FPs) are ubiquitous tools in research, yet their endogenous functions in nature are poorly understood. In this work, we describe a combination of functions for FPs in a clade of intertidal sea anemones whose FPs control a genetic color polymorphism together with the ability to combat oxidative stress. Focusing on the underlying genetics of a fluorescent green "Neon" color morph, we show that allelic differences in a single FP gene generate its strong and vibrant color, by increasing both molecular brightness and FP gene expression level. Natural variation in FP sequences also produces differences in antioxidant capacity. We demonstrate that these FPs are strong antioxidants that can protect live cells against oxidative stress. Finally, based on structural modeling of the responsible amino acids, we propose a model for FP antioxidant function that is driven by molecular surface charge. Together, our findings shed light on the multifaceted functions that can co-occur within a single FP and provide a framework for studying the evolution of fluorescence as it balances spectral and physiological functions in nature.

Antimicrobial properties of tomato juice and peptides against typhoidal Salmonella

Tomatoes are readily available and affordable vegetables that offer a range of health benefits due to their bioactive molecules, such as antioxidants and antimicrobials. In contrast to the widely recognized antioxidant properties of tomatoes, their antimicrobial properties remain largely unexplored. Here, we present our findings on the antimicrobial properties of tomato juice and peptides, namely, tomato-derived antimicrobial peptides (tdAMPs), in relation to their effectiveness against typhoidal Salmonella. Our research has revealed that tomato juice demonstrates significant antimicrobial properties against Salmonella Typhi, a pathogen that specifically affects humans and is responsible for causing typhoid fever. By employing computational analysis of the tomato genome sequence, conducting molecular dynamics simulation, and performing functional analyses, we have successfully identified two tdAMPs, namely, tdAMP-1 and tdAMP-2. These tdAMPs have demonstrated potent antimicrobial properties by effectively disrupting bacterial membranes. The efficacy of tdAMP-2 is shown to be more effective than tdAMP-1. The efficacy of tdAMP-1 and tdAMP-2 has been demonstrated against drug-resistant S. Typhi, as well as hyper-capsular S. Typhi variants that possess hypervirulent characteristics, which are presently circulating in countries with endemicity. Tomato juice, along with the two tdAMPs, has demonstrated effectiveness against uropathogenic Escherichia coli as well. This underscores their potential as viable agents in combating certain Gram-negative pathogens. This study provides valuable insights into the development of effective and sustainable public health strategies that utilize tomato and its derivatives as lifestyle interventions.IMPORTANCEIn this study, we investigate the antimicrobial properties of tomato juice, the most widely consumed affordable vegetables, as well as tomato-derived antimicrobial peptides, in relation to their effectiveness against foodborne pathogens with an emphasis on Salmonella Typhi, a deadly human-specific pathogen.

MoDAFold: a strategy for predicting the structure of missense mutant protein based on AlphaFold2 and molecular dynamics

Protein structure prediction is a longstanding issue crucial for identifying new drug targets and providing a mechanistic understanding of protein functions. To enhance the progress in this field, a spectrum of computational methodologies has been cultivated. AlphaFold2 has exhibited exceptional precision in predicting wild-type protein structures, with performance exceeding that of other methods. However, predicting the structures of missense mutant proteins using AlphaFold2 remains challenging due to the intricate and substantial structural alterations caused by minor sequence variations in the mutant proteins. Molecular dynamics (MD) has been validated for precisely capturing changes in amino acid interactions attributed to protein mutations. Therefore, for the first time, a strategy entitled 'MoDAFold' was proposed to improve the accuracy and reliability of missense mutant protein structure prediction by combining AlphaFold2 with MD. Multiple case studies have confirmed the superior performance of MoDAFold compared to other methods, particularly AlphaFold2.

Structure-guided discovery of anti-CRISPR and anti-phage defense proteins

Bacteria use a variety of defense systems to protect themselves from phage infection. In turn, phages have evolved diverse counter-defense measures to overcome host defenses. Here, we use protein structural similarity and gene co-occurrence analyses to screen >66 million viral protein sequences and >330,000 metagenome-assembled genomes for the identification of anti-phage and counter-defense systems. We predict structures for ~300,000 proteins and perform large-scale, pairwise comparison to known anti-CRISPR (Acr) and anti-phage proteins to identify structural homologs that otherwise may not be uncovered using primary sequence search. This way, we identify a Bacteroidota phage Acr protein that inhibits Cas12a, and an Akkermansia muciniphila anti-phage defense protein, termed BxaP. Gene bxaP is found in loci encoding Bacteriophage Exclusion (BREX) and restriction-modification defense systems, but confers immunity independently. Our work highlights the advantage of combining protein structural features and gene co-localization information in studying host-phage interactions.

Molecular characterization of the PhiKo endolysin from Thermus thermophilus HB27 bacteriophage phiKo and its cryptic lytic peptide RAP-29

Introduction

In the era of increasing bacterial resistance to antibiotics, new bactericidal substances are sought, and lysins derived from extremophilic organisms have the undoubted advantage of being stable under harsh environmental conditions. The PhiKo endolysin is derived from the phiKo bacteriophage infecting Gram-negative extremophilic bacterium Thermus thermophilus HB27. This enzyme shows similarity to two previously investigated thermostable type-2 amidases, the Ts2631 and Ph2119 from Thermus scotoductus bacteriophages, that revealed high lytic activity not only against thermophiles but also against Gram-negative mesophilic bacteria. Therefore, antibacterial potential of the PhiKo endolysin was investigated in the study presented here.

Methods

Enzyme activity was assessed using turbidity reduction assays (TRAs) and antibacterial tests. Differential scanning calorimetry was applied to evaluate protein stability. The Collection of Anti-Microbial Peptides (CAMP) and Antimicrobial Peptide Calculator and Predictor (APD3) were used to predict regions with antimicrobial potential in the PhiKo primary sequence. The minimum inhibitory concentration (MIC) of the RAP-29 synthetic peptide was determined against Gram-positive and Gram-negative selected strains, and mechanism of action was investigated with use of membrane potential sensitive fluorescent dye 3,3'-Dipropylthiacarbocyanine iodide (DiSC3(5)).

Results and discussion

The PhiKo endolysin is highly thermostable with melting temperature of 91.70°C. However, despite its lytic effect against such extremophiles as: T. thermophilus, Thermus flavus, Thermus parvatiensis, Thermus scotoductus, and Deinococcus radiodurans, PhiKo showed moderate antibacterial activity against mesophiles. Consequently, its protein sequence was searched for regions with potential antibacterial activity. A highly positively charged region was identified and synthetized (PhiKo105-133). The novel RAP-29 peptide lysed mesophilic strains of staphylococci and Gram-negative bacteria, reducing the number of cells by 3.7-7.1 log units and reaching the minimum inhibitory concentration values in the range of 2-31 μM. This peptide is unstructured in an aqueous solution but forms an α-helix in the presence of detergents. Moreover, it binds lipoteichoic acid and lipopolysaccharide, and causes depolarization of bacterial membranes. The RAP-29 peptide is a promising candidate for combating bacterial pathogens. The existence of this cryptic peptide testifies to a much wider panel of antimicrobial peptides than thought previously.

Additional PfCRT mutations driven by selective pressure for improved fitness can result in the loss of piperaquine resistance and altered Plasmodium falciparum physiology

IMPORTANCE

Our study leverages gene editing techniques in Plasmodium falciparum asexual blood stage parasites to profile novel mutations in mutant PfCRT, an important mediator of piperaquine resistance, which developed in Southeast Asian field isolates or in parasites cultured for long periods of time. We provide evidence that increased parasite fitness of these lines is the primary driver for the emergence of these PfCRT variants. These mutations differentially impact parasite susceptibility to piperaquine and chloroquine, highlighting the multifaceted effects of single point mutations in this transporter. Molecular features of drug resistance and parasite physiology were examined in depth using proteoliposome-based drug uptake studies and peptidomics, respectively. Energy minimization calculations, showing how these novel mutations might impact the PfCRT structure, suggested a small but significant effect on drug interactions. This study reveals the subtle interplay between antimalarial resistance, parasite fitness, PfCRT structure, and intracellular peptide availability in PfCRT-mediated parasite responses to changing drug selective pressures.

Recent developments in capillary and microchip electroseparations of peptides (2021-mid-2023)

This review article brings a comprehensive survey of developments and applications of high-performance capillary and microchip electromigration methods (zone electrophoresis in a free solution or in sieving media, isotachophoresis, isoelectric focusing, affinity electrophoresis, electrokinetic chromatography, and electrochromatography) for analysis, micropreparation, and physicochemical characterization of peptides in the period from 2021 up to ca. the middle of 2023. Progress in the study of electromigration properties of peptides and various aspects of their analysis, such as sample preparation, adsorption suppression, electroosmotic flow regulation, and detection, are presented. New developments in the particular capillary electromigration methods are demonstrated, and several types of their applications are reported. They cover qualitative and quantitative analysis of synthetic or isolated peptides and determination of peptides in complex biomatrices, peptide profiling of biofluids and tissues, and monitoring of chemical and enzymatic reactions and physicochemical changes of peptides. They include also amino acid and sequence analysis of peptides, peptide mapping of proteins, separation of stereoisomers of peptides, and their chiral analyses. In addition, micropreparative separations and physicochemical characterization of peptides and their interactions with other (bio)molecules by the above CE methods are described.

Investigation of the mutated antimicrobial peptides to inhibit ACE2, TMPRSS2 and GRP78 receptors of SARS-CoV-2 and angiotensin II type 1 receptor (AT1R) as well as controlling COVID-19 disease

SARS-CoV-2 is a global problem nowadays. Based on studies, some human receptors are involved in binding to SARS-CoV-2. Thus, the inhibition of these receptors can be effective in the treatment of Covid-19. Because of the proven benefits of antimicrobial peptides (AMPs) and the side effects of chemical drugs, they can be known as an alternative to recent medicines. RCSB PDB to obtain PDB id, StraPep and PhytAMP to acquire Bio-AMPs information and 3-D structure, and AlgPred, Toxinpred, TargetAntiAngio, IL-4pred, IL-6pred, ACPred and Hemopred databases were used to find the best score peptide features. HADDOCK 2.2 was used for molecular docking analysis, and UCSF Chimera software version 1.15, SWISS-MODEL and BIOVIA Discovery Studio Visualizer4.5 were used for mutation and structure modeling. Furthermore, MD simulation results were achieved from GROMACS 4.6.5. Based on the obtained results, the Moricin peptide was found to have the best affinity for ACE2. Moreover, Bacteriocin leucocin-A had the highest affinity for GRP78, Cathelicidin-6 had the best affinity for AT1R, and Bacteriocin PlnK had the best binding affinity for TMPRSS2. Additionally, Bacteriocin glycocin F, Bacteriocin lactococcin-G subunit beta and Cathelicidin-6 peptides were the most common compounds among the four receptors. However, these peptides also have some side effects. Consequently, the mutation eliminated the side effects, and MD simulation results indicated that the mutation proved the result of the docking analysis. The effect of AMPs on ACE2, GRP78, TMPRSS2 and AT1R receptors can be a novel treatment for Covid-19.Communicated by Ramaswamy H. Sarma.

PepAnalyzer: predicting peptide properties using its sequence

Peptides are short linear molecules consisting of amino acids that play an essential role in most biological processes. They can treat diseases by working as a vaccine or antimicrobial agent and serves as a cancer molecule to deliver the drug to the target site for the treatment of cancer. They have the potential to solve the drawbacks of current medications and can be industrially produced in large quantities at low cost. However, poor chemical and physical stability, short circulating plasma half-life, and solubility are some issues that need solutions before they can be used as therapeutics. PepAnalyzer tool is a user-friendly tool that predicts 15 different properties such as binding potential, half-life, transmembrane patterns, test tube stability, charge, isoelectric point, molecular weights, and molar extinction coefficients only using the sequence. The tool is designed using BioPython utility and has even results with standard tools, such as Expasy, EBI, Genecorner, and Geneinfinity. The tool assists students, researchers, and the pharmaceutical sector. The PepAnalyzer tool's online platform is accessible at the link: http://www.iksmbrlabdu.in/peptool .

AmorProt: Amino Acid Molecular Fingerprints Repurposing-Based Protein Fingerprint

As protein therapeutics play an important role in almost all medical fields, numerous studies have been conducted on proteins using artificial intelligence. Artificial intelligence has enabled data-driven predictions without the need for expensive experiments. Nevertheless, unlike the various molecular fingerprint algorithms that have been developed, protein fingerprint algorithms have rarely been studied. In this study, we proposed the amino acid molecular fingerprints repurposing-based protein (AmorProt) fingerprint, a protein sequence representation method that effectively uses the molecular fingerprints corresponding to 20 amino acids. Subsequently, the performances of the tree-based machine learning and artificial neural network models were compared using (1) amyloid classification and (2) isoelectric point regression. Finally, the applicability and advantages of the developed platform were demonstrated through a case study and the following experiments: (3) comparison of dataset dependence with feature-based methods, (4) feature importance analysis, and (5) protein space analysis. Consequently, the significantly improved model performance and data-set-independent versatility of the AmorProt fingerprint were verified. The results revealed that the current protein representation method can be applied to various fields related to proteins, such as predicting their fundamental properties or interaction with ligands.

Facile Purification and Use of Tobamoviral Nanocarriers for Antibody-Mediated Display of a Two-Enzyme System

Immunosorbent turnip vein clearing virus (TVCV) particles displaying the IgG-binding domains D and E of Staphylococcus aureus protein A (PA) on every coat protein (CP) subunit (TVCVPA) were purified from plants via optimized and new protocols. The latter used polyethylene glycol (PEG) raw precipitates, from which virions were selectively re-solubilized in reverse PEG concentration gradients. This procedure improved the integrity of both TVCVPA and the wild-type subgroup 3 tobamovirus. TVCVPA could be loaded with more than 500 IgGs per virion, which mediated the immunocapture of fluorescent dyes, GFP, and active enzymes. Bi-enzyme ensembles of cooperating glucose oxidase and horseradish peroxidase were tethered together on the TVCVPA carriers via a single antibody type, with one enzyme conjugated chemically to its Fc region, and the other one bound as a target, yielding synthetic multi-enzyme complexes. In microtiter plates, the TVCVPA-displayed sugar-sensing system possessed a considerably increased reusability upon repeated testing, compared to the IgG-bound enzyme pair in the absence of the virus. A high coverage of the viral adapters was also achieved on Ta2O5 sensor chip surfaces coated with a polyelectrolyte interlayer, as a prerequisite for durable TVCVPA-assisted electrochemical biosensing via modularly IgG-assembled sensor enzymes.

Characterisation of the E. coli HMS174 and BLR host cell proteome to guide purification process development

Mass-spectrometry-based proteomics is increasingly employed to monitor purification processes or to detect critical host cell proteins in the final drug substance. This approach is inherently unbiased and can be used to identify individual host cell proteins without prior knowledge. In process development for the purification of new biopharmaceuticals, such as protein subunit vaccines, a broader knowledge of the host cell proteome could promote a more rational process design. Proteomics can establish qualitative and quantitative information on the complete host cell proteome before purification (i.e., protein abundances and physicochemical properties). Such information allows for a more rational design of the purification strategy and accelerates purification process development. In this study, we present an extensive proteomic characterisation of two E. coli host cell strains widely employed in academia and industry to produce therapeutic proteins, BLR and HMS174. The established database contains the observed abundance of each identified protein, information relating to their hydrophobicity, the isoelectric point, molecular weight, and toxicity. These physicochemical properties were plotted on proteome property maps to showcase the selection of suitable purification strategies. Furthermore, sequence alignment allowed integration of subunit information and occurrences of post-translational modifications from the well-studied E. coli K12 strain.

PKAD-2: New entries and expansion of functionalities of the database of experimentally measured pKa's of proteins

Almost all biological reactions are pH dependent and understanding the origin of pH dependence requires knowledge of the pKa's of ionizable groups. Here we report a new edition of PKAD, the PKAD-2, which is a database of experimentally measured pKa's of proteins, both wild type and mutant proteins. The new additions include 117 wild type and 54 mutant pKa values, resulting in total 1742 experimentally measured pKa's. The new edition of PKAD-2 includes 8 new wild type and 12 new mutant proteins, resulting in total of 220 proteins. This new edition incorporates a visual 3D image of the highlighted residue of interest within the corresponding protein or protein complex. Hydrogen bonds were identified, counted, and implemented as a search feature. Other new search features include the number of neighboring residues <4A from the heaviest atom of the side chain of a given amino acid. Here, we present PKAD-2 with the intention to continuously incorporate novel features and current data with the goal to be used as benchmark for computational methods.

Systematic analysis of the impact of phosphorylation and O-GlcNAcylation on protein subcellular localization

The subcellular localization of proteins is critical for their functions in eukaryotic cells and is tightly correlated with protein modifications. Here, we comprehensively investigate the nuclear-cytoplasmic distributions of the phosphorylated, O-GlcNAcylated, and non-modified forms of proteins to dissect the correlation between protein distribution and modifications. Phosphorylated and O-GlcNAcylated proteins have overall higher nuclear distributions than non-modified ones. Different distributions among the phosphorylated, O-GlcNAcylated, and non-modified forms of proteins are associated with protein size, structure, and function, as well as local environment and adjacent residues around modification sites. Moreover, we perform site-mutagenesis experiments using phosphomimetic and phospho-null mutants of two proteins to validate the proteomic results. Additionally, the effects of the OGT/OGA inhibition on glycoprotein distribution are systematically investigated, and the distribution changes of glycoproteins are related to their abundance changes under the inhibitions. Systematic investigation of the relationship between protein modification and localization advances our understanding of protein functions.

Cellulose metabolism in halo(natrono)archaea: a comparative genomics study

Extremely halophilic archaea are one of the principal microbial community components in hypersaline environments. The majority of cultivated haloarchaea are aerobic heterotrophs using peptides or simple sugars as carbon and energy sources. At the same time, a number of novel metabolic capacities of these extremophiles were discovered recently among which is a capability of growing on insoluble polysaccharides such as cellulose and chitin. Still, polysaccharidolytic strains are in minority among cultivated haloarchaea and their capacities of hydrolyzing recalcitrant polysaccharides are hardly investigated. This includes the mechanisms and enzymes involved in cellulose degradation, which are well studied for bacterial species, while almost unexplored in archaea and haloarchaea in particular. To fill this gap, a comparative genomic analysis of 155 cultivated representatives of halo(natrono)archaea, including seven cellulotrophic strains belonging to the genera Natronobiforma, Natronolimnobius, Natrarchaeobius, Halosimplex, Halomicrobium and Halococcoides was performed. The analysis revealed a number of cellulases, encoded in the genomes of cellulotrophic strains but also in several haloarchaea, for which the capacity to grow on cellulose was not shown. Surprisingly, the cellulases genes, especially of GH5, GH9 and GH12 families, were significantly overrepresented in the cellulotrophic haloarchaea genomes in comparison with other cellulotrophic archaea and even cellulotrophic bacteria. Besides cellulases, the genes for GH10 and GH51 families were also abundant in the genomes of cellulotrophic haloarchaea. These results allowed to propose the genomic patterns, determining the capability of haloarchaea to grow on cellulose. The patterns helped to predict cellulotrophic capacity for several halo(natrono)archaea, and for three of them it was experimentally confirmed. Further genomic search revealed that glucose and cellooligosaccharides import occurred by means of porters and ABC (ATP-binding cassette) transporters. Intracellular glucose oxidation occurred through glycolysis or the semi-phosphorylative Entner-Dudoroff pathway which occurrence was strain-specific. Comparative analysis of CAZymes toolbox and available cultivation-based information allowed proposing two possible strategies used by haloarchaea capable of growing on cellulose: so-called specialists are more effective in degradation of cellulose while generalists are more flexible in nutrient spectra. Besides CAZymes profiles the groups differed in genome sizes, as well as in variability of mechanisms of import and central metabolism of sugars.

Site Identification by Ligand Competitive Saturation-Biologics Approach for Structure-Based Protein Charge Prediction

Protein-based therapeutics typically require high concentrations of the active protein, which can lead to protein aggregation and high solution viscosity. Such solution behaviors can limit the stability, bioavailability, and manufacturability of protein-based therapeutics and are directly influenced by the charge of a protein. Protein charge is a system property affected by its environment, including the buffer composition, pH, and temperature. Thus, the charge calculated by summing the charges of each residue in a protein, as is commonly done in computational methods, may significantly differ from the effective charge of the protein as these calculations do not account for contributions from bound ions. Here, we present an extension of the structure-based approach termed site identification by ligand competitive saturation-biologics (SILCS-Biologics) to predict the effective charge of proteins. The SILCS-Biologics approach was applied on a range of protein targets in different salt environments for which membrane-confined electrophoresis-determined charges were previously reported. SILCS-Biologics maps the 3D distribution and predicted occupancy of ions, buffer molecules, and excipient molecules bound to the protein surface in a given salt environment. Using this information, the effective charge of the protein is predicted such that the concentrations of the ions and the presence of excipients or buffers are accounted for. Additionally, SILCS-Biologics also produces 3D structures of the binding sites of ions on the proteins, which enable further analyses such as the characterization of protein surface charge distribution and dipole moments in different environments. Notable is the capability of the method to account for competition between salts, excipients, and buffers on the calculated electrostatic properties in different protein formulations. Our study demonstrates the ability of the SILCS-Biologics approach to predict the effective charge of proteins and its applicability in uncovering protein-ion interactions and their contributions to protein solubility and function.

Unveiling the Impact of Gene Presence/Absence Variation in Driving Inter-Individual Sequence Diversity within the CRP-I Gene Family in Mytilus spp

Mussels (Mytilus spp.) tolerate infections much better than other species living in the same marine coastal environment thanks to a highly efficient innate immune system, which exploits a remarkable diversification of effector molecules involved in mucosal and humoral responses. Among these, antimicrobial peptides (AMPs) are subjected to massive gene presence/absence variation (PAV), endowing each individual with a potentially unique repertoire of defense molecules. The unavailability of a chromosome-scale assembly has so far prevented a comprehensive evaluation of the genomic arrangement of AMP-encoding loci, preventing an accurate ascertainment of the orthology/paralogy relationships among sequence variants. Here, we characterized the CRP-I gene cluster in the blue mussel Mytilus edulis, which includes about 50 paralogous genes and pseudogenes, mostly packed in a small genomic region within chromosome 5. We further reported the occurrence of widespread PAV within this family in the Mytilus species complex and provided evidence that CRP-I peptides likely adopt a knottin fold. We functionally characterized the synthetic peptide sCRP-I H1, assessing the presence of biological activities consistent with other knottins, revealing that mussel CRP-I peptides are unlikely to act as antimicrobial agents or protease inhibitors, even though they may be used as defense molecules against infections from eukaryotic parasites.

Peptide Models of the Cytoplasmic Tail of Influenza A/H1N1 Virus Hemagglutinin Expand Understanding its pH-Dependent Modes of Interaction with Matrix Protein M1

Influenza A virus hemagglutinin (HA) is a major virus antigen. No cryo-electron microscopy or X-ray data can be obtained for the HA intraviral (cytoplasmic) domain (CT) post-translationally modified with long fatty acid residues bound to three highly conserved cysteines. We recently proposed a model of HA CT of Influenza A/H1N1 virus possessing an antiparallel beta structure based on the experimental secondary structure analysis of four 14-15 amino acid long synthetic peptides, corresponding to the HA CT sequence, with free or acetaminomethylated cysteines. To dispel doubts about possible non-specific "amyloid-like" aggregation of those synthetic peptides in phosphate buffer solution, we have determined the order of oligomers based on blue native gel electrophoresis, membrane filtration, fluorescence spectroscopy and molecular modeling approaches. We have found that unmodified peptides form only low molecular weight oligomers, while modified peptides form both oligomers of low order similar to those found for unmodified peptides and high order conglomerates, which however are not of beta-amyloid-like fold. This study confirms that the beta structure previously detected by circular dichroism spectroscopy analysis is more likely the result of intrinsic propensity of the HA CT amino acid sequence than the consequence of aggregation. The structures of low order oligomers of the synthetic peptides were used for in silico experiments on modeling of HA CT interactions with matrix protein M1 at physiological and acidic pH levels and revealed two different areas of binding. Finally, tripeptides capable of blocking interactions between HA CT and M1 were proposed.

Sequence-based prediction of pH-dependent protein solubility using CamSol

Solubility is a property of central importance for the use of proteins in research in molecular and cell biology and in applications in biotechnology and medicine. Since experimental methods for measuring protein solubility are material intensive and time consuming, computational methods have recently emerged to enable the rapid and inexpensive screening of solubility for large libraries of proteins, as it is routinely required in development pipelines. Here, we describe the development of one such method to include in the predictions the effect of the pH on solubility. We illustrate the resulting pH-dependent predictions on a variety of antibodies and other proteins to demonstrate that these predictions achieve an accuracy comparable with that of experimental methods. We make this method publicly available at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolph, as the version 3.0 of CamSol.

Terahertz phase shift sensing and identification of a chiral amino acid based on a protein-modified metasurface through the isoelectric point and peptide bonding

The efficient sensing of amino acids, especially the distinction of their chiral enantiomers, is important for biological, chemical, and pharmaceutical research. In this work, a THz phase shift sensing method was performed for amino acid detection based on a polarization-dependent electromagnetically induced transparency (EIT) metasurface. More importantly, a method for binding the specific amino acids to the functional proteins modified on the metasurface was developed based on the isoelectric point theory so that the specific recognition for Arginine (Arg) was achieved among the four different amino acids. The results show that via high-Q phase shift, the detection precision for L-Arg is 2.5 × 10^-5g /ml, much higher than traditional sensing parameters. Due to the specific electrostatic adsorption by the functionalized metasurface to L-Arg, its detection sensitivity and precision are 22 times higher than the other amino acids. Furthermore, by comparing nonfunctionalized and functionalized metasurfaces, the D- and L-chiral enantiomers of Arg were distinguished due to their different binding abilities to the functionalized metasurface. Therefore, this EIT metasurface sensor and its specific binding method improve both detection precision and specificity in THz sensing for amino acids, and it will promote the development of THz highly sensitive detection of chiral enantiomers.

Bioinformatics and computational analyses of kidney stone modulatory proteins lead to solid experimental evidence and therapeutic potential

In recent biomedical research, bioinformatics and computational analyses have played essential roles for examining experimental findings and database information. Several bioinformatic tools have been developed and made publicly available for analyzing protein sequence, structure, functional motif/domain, and interactions network. Such properties are very helpful to define biochemical and functional roles of the protein(s) of interest. During the past few decades, bioinformatics and computational biotechnology have been widely applied to kidney stone research. This review summarizes commonly used tools and evidence of bioinformatics and computational biotechnology applied to kidney stone disease (KSD) with special emphasis on analyses of the stone modulatory proteins that play critical roles in kidney stone formation. Such analyses lead to solid experimental evidence to demonstrate mechanisms underlying their stone modulatory activities. The findings obtained from such analyses may also lead to better understanding of KSD pathogenesis and to further development of new therapeutic and preventive strategies.

GCmapCrys: Integrating graph attention network with predicted contact map for multi-stage protein crystallization propensity prediction

X-ray crystallography is the major approach for atomic-level protein structure determination. Since not all proteins can be easily crystallized, accurate prediction of protein crystallization propensity is critical to guiding the experimental design and improving the success rate of X-ray crystallography experiments. In this work, we proposed a new deep learning pipeline, GCmapCrys, for multi-stage crystallization propensity prediction through integrating graph attention network with predicted protein contact map. Experimental results on 1548 proteins with known crystallization records demonstrated that GCmapCrys increased the value of Matthew's correlation coefficient by 37.0% in average compared to state-of-the-art protein crystallization propensity predictors. Detailed analyses show that the major advantages of GCmapCrys lie in the efficiency of the graph attention network with predicted contact map, which effectively associates the residue-interaction knowledge with crystallization pattern. Meanwhile, the designed four sequence-based features can be complementary to further enhance crystallization propensity proprediction.

Tunable Surface Charge Enables the Electrostatic Adsorption-Controlled Release of Neuroprotective Peptides from a Hydrogel-Nanoparticle Drug Delivery System

We exploit the electrostatic interactions between the positively charged neuroprotective peptide, pituitary adenylate cyclase-activating polypeptide (PACAP), and negatively charged poly(lactic-co-glycolic acid) (PLGA) nanoparticles to control PACAP release from the surface of nanoparticles dispersed in a hyaluronan-methylcellulose (HAMC) hydrogel composite. PACAP is a promising therapeutic for the treatment of neurological disorders, yet it has been difficult to deliver in vivo. Herein, the PACAP release rate was tuned by manipulating peptide adsorption onto the surface of blank nanoparticles by modifying either nanoparticle loading in the hydrogel or nanoparticle surface charge. This peptide-nanoparticle interaction was controlled by the pH-responsive carboxylic acid end terminal groups of PLGA. We further validated this system with the controlled release of a novel stabilized PACAP analog: Ac-[Ala¹⁵, Ala²⁰]PACAP-propylamide, which masks its recognition to peptidases in circulation. Both wild-type and stabilized PACAP released from the vehicle increased the production of neuroprotective Interleukin-6 from cultured primary astrocytes. Using computational fluid dynamics methods, PACAP release from the composite was predicted based on experimentally derived adsorption isotherms, which exhibited similar release profiles to experimental data. This versatile adsorption-based system was used to deliver PACAP locally to the brains of stroke-injured mice over a 10 day period in vivo, highlighting its effectiveness for the controlled release of PACAP to the central nervous system.

pIChemiSt ─ Free Tool for the Calculation of Isoelectric Points of Modified Peptides

The isoelectric point (pI) is a fundamental physicochemical property of peptides and proteins. It is widely used to steer design away from low solubility and aggregation and guide peptide separation and purification. Experimental measurements of pI can be replaced by calculations knowing the ionizable groups of peptides and their corresponding pK_a values. Different pK_a sets are published in the literature for natural amino acids, however, they are insufficient to describe synthetically modified peptides, complex peptides of natural origin, and peptides conjugated with structures of other modalities. Noncanonical modifications (nCAAs) are ignored in the conventional sequence-based pI calculations, therefore producing large errors in their pI predictions. In this work, we describe a pI calculation method that uses the chemical structure as an input, automatically identifies ionizable groups of nCAAs and other fragments, and performs pK_a predictions for them. The method is validated on a curated set of experimental measures on 29 modified and 119093 natural peptides, providing an improvement of R² from 0.74 to 0.95 and 0.96 against the conventional sequence-based approach for modified peptides for the two studied pK_a prediction tools, ACDlabs and pKaMatcher, correspondingly. The method is available in the form of an open source Python library at https://github.com/AstraZeneca/peptide-tools, which can be integrated into other proprietary and free software packages. We anticipate that the pI calculation tool may facilitate optimization and purification activities across various application domains of peptides, including the development of biopharmaceuticals.

A software tool for data mining of physicochemical properties of peptides

Biologically active peptides (BAP) are increasingly in the focus of scientific research due to their widespread use in medicine, food and pharmaceutical industries. Researching and studying the properties of peptides is a laborious and expensive process. In recent years, in silico methods, including data mining or artificial intelligence, have been applied more and more to reveal biological, physicochemical and sensory properties of peptides. This significantly shortens the process of peptide sequences analysis. This article presents a software tool that uses a data mining approach to discover a number of physicochemical properties of a specific peptide. Working with it is extremely simple - it is only necessary to input the amino acid sequence of the peptide of interest. The software tool is designed to generate data in order to increase the classification and prediction accuracy, as well as to leverage the engineering of new amino acid sequences. This way, the proposed software greatly facilitates the work or scientific researchers. The software application is publicly available at www.pep-lab.info/dmpep.

qNABpredict: Quick, accurate, and taxonomy-aware sequence-based prediction of content of nucleic acid binding amino acids

Protein sequence-based predictors of nucleic acid (NA)-binding include methods that predict NA-binding proteins and NA-binding residues. The residue-level tools produce more details but suffer high computational cost since they must predict every amino acid in the input sequence and rely on multiple sequence alignments. We propose an alternative approach that predicts content (fraction) of the NA-binding residues, offering more information than the protein-level prediction and much shorter runtime than the residue-level tools. Our first-of-its-kind content predictor, qNABpredict, relies on a small, rationally designed and fast-to-compute feature set that represents relevant characteristics extracted from the input sequence and a well-parametrized support vector regression model. We provide two versions of qNABpredict, a taxonomy-agnostic model that can be used for proteins of unknown taxonomic origin and more accurate taxonomy-aware models that are tailored to specific taxonomic kingdoms: archaea, bacteria, eukaryota, and viruses. Empirical tests on a low-similarity test dataset show that qNABpredict is 100 times faster and generates statistically more accurate content predictions when compared to the content extracted from results produced by the residue-level predictors. We also show that qNABpredict's content predictions can be used to improve results generated by the residue-level predictors. We release qNABpredict as a convenient webserver and source code at http://biomine.cs.vcu.edu/servers/qNABpredict/. This new tool should be particularly useful to predict details of protein-NA interactions for large protein families and proteomes.

Fitness Landscape-Guided Engineering of Locally Supercharged Virus-like Particles with Enhanced Cell Uptake Properties

Protein-based nanoparticles are useful models for the study of self-assembly and attractive candidates for drug delivery. Virus-like particles (VLPs) are especially promising platforms for expanding the repertoire of therapeutics that can be delivered effectively as they can deliver many copies of a molecule per particle for each delivery event. However, their use is often limited due to poor uptake of VLPs into mammalian cells. In this study, we use the fitness landscape of the bacteriophage MS2 VLP as a guide to engineer capsid variants with positively charged surface residues to enhance their uptake into mammalian cells. By combining mutations with positive fitness scores that were likely to produce assembled capsids, we identified two key double mutants with internalization efficiencies as much as 67-fold higher than that of wtMS2. Internalization of these variants with positively charged surface residues depends on interactions with cell surface sulfated proteoglycans, and yet, they are biophysically similar to wtMS2 with low cytotoxicity and an overall negative charge. Additionally, the best-performing engineered MS2 capsids can deliver a potent anticancer small-molecule therapeutic with efficacy levels similar to antibody-drug conjugates. Through this work, we were able to establish fitness landscape-based engineering as a successful method for designing VLPs with improved cell penetration. These findings suggest that VLPs with positive surface charge could be useful in improving the delivery of small-molecule- and nucleic acid-based therapeutics.

Prediction of polyreactive and nonspecific single-chain fragment variables through structural biochemical features and protein language-based descriptors

BACKGROUND

Monoclonal antibodies (mAbs) have been used as therapeutic agents, which must overcome many developability issues after the discovery from in vitro display libraries. Especially, polyreactive mAbs can strongly bind to a specific target and weakly bind to off-target proteins, which leads to poor antibody pharmacokinetics in clinical development. Although early assessment of polyreactive mAbs is important in the early discovery stage, experimental assessments are usually time-consuming and expensive. Therefore, computational approaches for predicting the polyreactivity of single-chain fragment variables (scFvs) in the early discovery stage would be promising for reducing experimental efforts.

RESULTS

Here, we made prediction models for the polyreactivity of scFvs with the known polyreactive antibody features and natural language model descriptors. We predicted 19,426 protein structures of scFvs with trRosetta to calculate the polyreactive antibody features and investigated the classifying performance of each factor for polyreactivity. In the known polyreactive features, the net charge of the CDR2 loop, the tryptophan and glycine residues in CDR-H3, and the lengths of the CDR1 and CDR2 loops, importantly contributed to the performance of the models. Additionally, the hydrodynamic features, such as partial specific volume, gyration radius, and isoelectric points of CDR loops and scFvs, were newly added to improve model performance. Finally, we made the prediction model with a robust performance ([Formula: see text]) with an ensemble learning of the top 3 best models.

CONCLUSION

The prediction models for polyreactivity would help assess polyreactive scFvs in the early discovery stage and our approaches would be promising to develop machine learning models with quantitative data from high throughput assays for antibody screening.

Identification and Expression Analysis of the C-TERMINALLY ENCODED PEPTIDE Family in Pisum sativum L

The C-TERMINALLY ENCODED PEPTIDE(CEP) peptides play crucial roles in plant growth and response to environmental factors. These peptides were characterized as positive regulators of symbiotic nodule development in legume plants. However, little is known about the CEP peptide family in pea. Here, we discovered in pea genome 21 CEP genes (PsCEPs), among which three genes contained additional conserved motifs corresponding to the PIP (PAMP-induced secreted peptides) consensus sequences. We characterized the expression patterns of pea PsCEP genes based on transcriptomic data, and for six PsCEP genes with high expression levels in the root and symbiotic nodules the detailed expression analysis at different stages of symbiosis and in response to nitrate treatment was performed. We suggest that at least three PsCEP genes, PsCEP1, PsCEP7 and PsCEP2, could play a role in symbiotic nodule development, whereas the PsCEP1 and PsCEP13 genes, downregulated by nitrate addition, could be involved in regulation of nitrate-dependent processes in pea. Further functional studies are required to elucidate the functions of these PsCEP genes.

Analysis of the Compositional Features and Codon Usage Pattern of Genes Involved in Human Autophagy

Autophagy plays an intricate role in paradigmatic human pathologies such as cancer, and neurodegenerative, cardiovascular, and autoimmune disorders. Autophagy regulation is performed by a set of autophagy-related (ATG) genes, first recognized in yeast genome and subsequently identified in other species, including humans. Several other genes have been identified to be involved in the process of autophagy either directly or indirectly. Studying the codon usage bias (CUB) of genes is crucial for understanding their genome biology and molecular evolution. Here, we examined the usage pattern of nucleotide and synonymous codons and the influence of evolutionary forces in genes involved in human autophagy. The coding sequences (CDS) of the protein coding human autophagy genes were retrieved from the NCBI nucleotide database and analyzed using various web tools and software to understand their nucleotide composition and codon usage pattern. The effective number of codons (ENC) in all genes involved in human autophagy ranges between 33.26 and 54.6 with a mean value of 45.05, indicating an overall low CUB. The nucleotide composition analysis of the autophagy genes revealed that the genes were marginally rich in GC content that significantly influenced the codon usage pattern. The relative synonymous codon usage (RSCU) revealed 3 over-represented and 10 under-represented codons. Both natural selection and mutational pressure were the key forces influencing the codon usage pattern of the genes involved in human autophagy.

Molecular characterization of the genome-wide BOR transporter family and their responses to boron conditions in common wheat (Triticum aestivum L.)

Boron (B) deficiency is an agricultural problem that causes significant yield losses in many countries. B transporters (BORs) are responsible for B uptake and distribution and play important roles in yield formation. A comprehensive analysis of the BOR family members in common wheat is still lacking. In the present study, to clarify the molecular characterization and response to B status, genome-wide TaBOR genes and expression patterns were investigated. Fourteen TaBOR genes were identified in common wheat by a homology search. The corresponding phylogenetic tree indicated that 14 TaBOR genes were separately classified into subfamilies of TaBOR1, TaBOR3, and TaBOR4. All TaBOR genes had 12-14 extrons and 11-13 introns. Most TaBOR proteins contained 10 conserved motifs, and motifs 1, 2, 3, 4, and 6 constituted the conserved bicarbonate (HCO₃ ^-) domain. Fourteen TaBOR genes were mapped on 13 chromosomes mainly distributed in the first, third, fifth, and seventh homologous groups. The promoters of TaBOR genes consisted of phytohormones, light responses, and stress-related cis-elements. GO analysis indicated that TaBOR genes were enriched in terms of transmembrane transport and ion homeostasis. TaBOR genes showed diverse expression profiles in different tissues. The members of the TaBOR1 subfamily showed high expression in grains, leaves, roots, stems, and spikes, but members of the TaBOR4 subfamily were highly expressed only in spikes and grains. RT-qPCR indicated that TaBOR1-5A, TaBOR1-5B, and TaBOR1-5D were induced by low B concentrations and had much higher expression in roots than in shoots. TaBOR3-3A, TaBOR3-3B, TaBOR3-3D, TaBOR4-1A, TaBOR4-1B, TaBOR4-1D, and TaBOR3-4B were induced by low and high B concentrations and had high expression in roots and shoots. TaBOR3-4D and TaBOR3-7B were upregulated by low and high B concentrations, respectively, but had expression only in roots. Our results provide basic information on the TaBOR family, which is beneficial for elucidating the functions of TaBOR genes to overcome the problem of B deficiency.

Piperaquine-resistant PfCRT mutations differentially impact drug transport, hemoglobin catabolism and parasite physiology in Plasmodium falciparum asexual blood stages

The emergence of Plasmodium falciparum parasite resistance to dihydroartemisinin + piperaquine (PPQ) in Southeast Asia threatens plans to increase the global use of this first-line antimalarial combination. High-level PPQ resistance appears to be mediated primarily by novel mutations in the P. falciparum chloroquine resistance transporter (PfCRT), which enhance parasite survival at high PPQ concentrations in vitro and increase the risk of dihydroartemisinin + PPQ treatment failure in patients. Using isogenic Dd2 parasites expressing contemporary pfcrt alleles with differential in vitro PPQ susceptibilities, we herein characterize the molecular and physiological adaptations that define PPQ resistance in vitro. Using drug uptake and cellular heme fractionation assays we report that the F145I, M343L, and G353V PfCRT mutations differentially impact PPQ and chloroquine efflux. These mutations also modulate proteolytic degradation of host hemoglobin and the chemical inactivation of reactive heme species. Peptidomic analyses reveal significantly higher accumulation of putative hemoglobin-derived peptides in the PPQ-resistant mutant PfCRT isoforms compared to parental PPQ-sensitive Dd2. Joint transcriptomic and metabolomic profiling of late trophozoites from PPQ-resistant or -sensitive isogenic lines reveals differential expression of genes involved in protein translation and cellular metabolism. PPQ-resistant parasites also show increased susceptibility to an inhibitor of the P. falciparum M17 aminopeptidase that operates on short globin-derived peptides. These results reveal unique physiological changes caused by the gain of PPQ resistance and highlight the potential therapeutic value of targeting peptide metabolism in P. falciparum.

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.

A variable gene family encoding nodule-specific cysteine-rich peptides in pea (Pisum sativum L.)

Various legume plants form root nodules in which symbiotic bacteria (rhizobia) fix atmospheric nitrogen after differentiation into a symbiotic form named bacteroids. In some legume species, bacteroid differentiation is promoted by defensin-like nodule-specific cysteine-rich (NCR) peptides. NCR peptides have best been studied in the model legume Medicago truncatula Gaertn., while in many other legumes relevant information is still fragmentary. Here, we characterize the NCR gene family in pea (Pisum sativum L.) using genomic and transcriptomic data. We found 360 genes encoding NCR peptides that are expressed in nodules. The sequences of pea NCR genes and putative peptides are highly variable and differ significantly from NCR sequences of M. truncatula. Indeed, only one pair of orthologs (PsNCR47-MtNCR312) has been identified. The NCR genes in the pea genome are located in clusters, and the expression patterns of NCR genes from one cluster tend to be similar. These data support the idea of independent evolution of NCR genes by duplication and diversification in related legume species. We also described spatiotemporal expression profiles of NCRs and identified specific transcription factor (TF) binding sites in promoters of "early" and "late" NCR genes. Further, we studied the expression of NCR genes in nodules of Fix^- mutants and predicted potential regulators of NCR gene expression, one among them being the TF ERN1 involved in the early steps of nodule organogenesis. In general, this study contributes to understanding the functions of NCRs in legume nodules and contributes to understanding the diversity and potential antibiotic properties of pea nodule-specific antimicrobial molecules.

An Arabidopsis thaliana arabinogalactan-protein (AGP31) and several cationic AGP fragments catalyse the boron bridging of rhamnogalacturonan-II

Rhamnogalacturonan-II (RG-II) is a complex pectic domain in plant primary cell walls. In vivo, most RG-II domains are covalently dimerised via borate diester bridges, essential for correct cell-wall assembly, but the dimerisation of pure RG-II monomers by boric acid in vitro is extremely slow. Cationic ‘chaperones’ can promote dimerisation, probably by overcoming the mutual repulsion between neighbouring anionic RG-II molecules. Highly effective artificial chaperones include Pb²⁺ and polyhistidine, but the proposed natural chaperones remained elusive. We have now tested cationic peptide fragments of several Arabidopsis thaliana arabinogalactan-proteins (AGPs) as candidates. Fragments of AGP17, 18, 19 and 31 were effective, typically at ∼25 µg/ml (9–19 µM), promoting the boron bridging of 16–20 µM monomeric RG-II at pH 4.8 in vitro. Native AGP31 glycoprotein was also effective, and hexahistidine was moderately so. All chaperones tested interacted reversibly with RG-II and were not consumed during the reaction; thus they acted catalytically, and may constitute the first reported boron-acting enzyme activity, an RG-II borate diesterase. Many of the peptide chaperones became less effective catalysts at higher concentration, which we interpret as due to the formation of RG-II–peptide complexes with a net positive charge, as mutually repulsive as negatively charged pure RG-II molecules. The four unique AGPs studied here may serve an enzymic role in the living plant cell, acting on RG-II within Golgi cisternae and/or in the apoplast after secretion. In this way, RG-II and specific AGPs may contribute to cell-wall assembly and hence plant cell expansion and development.

Adsorption of flexible proteins in the 'wrong side' of the isoelectric point: Casein macropeptide as a model system

We analyze the conditions of the adsorption of a flexible peptide onto a charged substrate in the 'wrong side' of the isoelectric point (WSIP), i.e. when surface and peptide charges have the same sign. As a model system, we focus on the casein macropeptide (CMP), both in the aglycosylated (aCMP) and fully glycosydated (gCMP) forms. We model the substrate as a uniformly charged plane while CMP is treated as a bead-and-spring model including electrostatic interactions, excluded volume effects and acid/base equilibria. Adsorption coverage, aminoacid charges and concentration profiles are computed by means of Monte Carlo simulations at fixed pH and salt concentration. We conclude that for different reasons the CMP can be adsorbed to both positively and negatively charged surfaces in the WSIP. For negatively charged surfaces, WSIP adsorption is due to the patchy distribution of charges: the peptide is attached to the surface by the positively charged end of the chain, while the repulsion of the surface for the negatively charged tail is screened by the small ions of the added salt. This effect increases with salt concentration. Conversely, a positively charged substrate induces strong charge regulation of the peptide: the acidic groups are deprotonated, and the peptide becomes negatively charged. This effect is stronger at low salt concentrations and it is more intense for gCMP than for aCMP, due to the presence of the additional sialic groups in gCMP.

The Knock-Down of the Chloroquine Resistance Transporter PfCRT Is Linked to Oligopeptide Handling in Plasmodium falciparum

The chloroquine resistance transporter, PfCRT, is an essential factor during intraerythrocytic development of the human malaria parasite Plasmodium falciparum. PfCRT resides at the digestive vacuole of the parasite, where hemoglobin taken up by the parasite from its host cell is degraded. PfCRT can acquire several mutations that render PfCRT a drug transporting system expelling compounds targeting hemoglobin degradation from the digestive vacuole. The non-drug related function of PfCRT is less clear, although a recent study has suggested a role in oligopeptide transport based on studies conducted in a heterologous expression system. The uncertainty about the natural function of PfCRT is partly due to a lack of a null mutant and a dearth of functional assays in the parasite. Here, we report on the generation of a conditional PfCRT knock-down mutant in P. falciparum. The mutant accumulated oligopeptides 2 to at least 8 residues in length under knock-down conditions, as shown by comparative global metabolomics. The accumulated oligopeptides were structurally diverse, had an isoelectric point between 4.0 and 5.4 and were electrically neutral or carried a single charge at the digestive vacuolar pH of 5.2. Fluorescently labeled dipeptides and live cell imaging identified the digestive vacuole as the compartment where oligopeptides accumulated. Our findings suggest a function of PfCRT in oligopeptide transport across the digestive vacuolar membrane in P. falciparum and associated with it a role in nutrient acquisition and the maintenance of the colloid osmotic balance. IMPORTANCE The chloroquine resistance transporter, PfCRT, is important for the survival of the human malaria parasite Plasmodium falciparum. It increases the tolerance to many antimalarial drugs, and it is essential for the development of the parasite within red blood cells. While we understand the role of PfCRT in drug resistance in ever increasing detail, the non-drug resistance functions are still debated. Identifying the natural substrate of PfCRT has been hampered by a paucity of functional assays to test putative substrates in the parasite system and the absence of a parasite mutant deficient for the PfCRT encoding gene. By generating a conditional PfCRT knock-down mutant, together with comparative metabolomics and uptake studies using fluorescently labeled oligopeptides, we could show that PfCRT is an oligopeptide transporter. The oligopeptides were structurally diverse and were electrically neutral or carried a single charge. Our data support a function of PfCRT in oligopeptide transport.

Molecular Characterization of a DNA Polymerase from Thermus thermophilus MAT72 Phage vB_Tt72: A Novel Type-A Family Enzyme with Strong Proofreading Activity

We present a structural and functional analysis of the DNA polymerase of thermophilic Thermus thermophilus MAT72 phage vB_Tt72. The enzyme shows low sequence identity (<30%) to the members of the type-A family of DNA polymerases, except for two yet uncharacterized DNA polymerases of T. thermophilus phages: φYS40 (91%) and φTMA (90%). The Tt72 polA gene does not complement the Escherichia colipolA− mutant in replicating polA-dependent plasmid replicons. It encodes a 703-aa protein with a predicted molecular weight of 80,490 and an isoelectric point of 5.49. The enzyme contains a nucleotidyltransferase domain and a 3′-5′ exonuclease domain that is engaged in proofreading. Recombinant enzyme with His-tag at the N-terminus was overproduced in E. coli, subsequently purified by immobilized metal affinity chromatography, and biochemically characterized. The enzyme exists in solution in monomeric form and shows optimum activity at pH 8.5, 25 mM KCl, and 0.5 mM Mg2+. Site-directed analysis proved that highly-conserved residues D15, E17, D78, D180, and D184 in 3′-5′ exonuclease and D384 and D615 in the nucleotidyltransferase domain are critical for the enzyme’s activity. Despite the source of origin, the Tt72 DNA polymerase has not proven to be highly thermoresistant, with a temperature optimum at 55 °C. Above 60 °C, the rapid loss of function follows with no activity > 75 °C. However, during heat treatment (10 min at 75 °C), trehalose, trimethylamine N-oxide, and betaine protected the enzyme against thermal inactivation. A midpoint of thermal denaturation at Tm = 74.6 °C (ΔHcal = 2.05 × 104 cal mol−1) and circular dichroism spectra > 60 °C indicate the enzyme’s moderate thermal stability.

The C-terminal head domain of Burkholderia pseudomallei BpaC has a striking hydrophilic core with an extensive solvent network

Gram‐negative pathogens like Burkholderia pseudomallei use trimeric autotransporter adhesins such as BpaC as key molecules in their pathogenicity. Our 1.4 Å crystal structure of the membrane‐proximal part of the BpaC head domain shows that the domain is exclusively made of left‐handed parallel β‐roll repeats. This, the largest such structure solved, has two unique features. First, the core, rather than being composed of the canonical hydrophobic Ile and Val, is made up primarily of the hydrophilic Thr and Asn, with two different solvent channels. Second, comparing BpaC to all other left‐handed parallel β‐roll structures showed that the position of the head domain in the protein correlates with the number and type of charged residues. In BpaC, only negatively charged residues face the solvent—in stark contrast to the primarily positive surface charge of the left‐handed parallel β‐roll “type” protein, YadA. We propose extending the definitions of these head domains to include the BpaC‐like head domain as a separate subtype, based on its unusual sequence, position, and charge. We speculate that the function of left‐handed parallel β‐roll structures may differ depending on their position in the structure.

Expanding the Database of Signal-Anchor-Release Domain Endolysins Through Metagenomics

Endolysins are bacteriophage-derived lytic enzymes with antimicrobial activity. The action of endolysins against Gram-negative bacteria remains a challenge due to the physical protection of the outer membrane. However, recent research has demonstrated that signal-anchor-release (SAR) endolysins permeate the outer membrane of Gram-negative bacteria. This study investigates 2628 putative endolysin genes identified in 183,298 bacteriophage genomes. Previously, bioinformatic approaches resulted in a database of 66 SAR endolysins. This manuscript almost doubles the list with 53 additional SAR endolysin candidates. Forty-eight of the putative SAR endolysins described in this study contained one muramidase catalytic domain, and five included additional cell wall-binding domains at the C-terminus. For the moment, SAR domains are found in four protein families: glycoside hydrolase family 19 (GH19), glycoside hydrolase family 24 (GH24), glycoside hydrolase family 25 (GH25), and glycoside hydrolase family 108 (GH108). These SAR lysis are clustered in eight groups based on biochemical properties and domain presence/absence. Therefore, in this study, we expand the arsenal of endolysin candidates that might act against Gram-negative bacteria and develop a consult database for antimicrobial proteins derived from bacteriophages.