Bioinformatic Analyses to Uncover Genes Involved in Trehalose Metabolism in the Polyploid Sugarcane

Trehalose-6-phosphate (T6P) is an intermediate of trehalose biosynthesis that plays an essential role in plant metabolism and development. Here, we comprehensively analyzed sequences from enzymes of trehalose metabolism in sugarcane, one of the main crops used for bioenergy production. We identified protein domains, phylogeny, and in silico expression levels for all classes of enzymes. However, post-translational modifications and residues involved in catalysis and substrate binding were analyzed only in trehalose-6-phosphate synthase (TPS) sequences. We retrieved 71 putative full-length TPS, 93 trehalose-6-phosphate phosphatase (TPP), and 3 trehalase (TRE) of sugarcane, showing all their conserved domains, respectively. Putative TPS (Classes I and II) and TPP sugarcane sequences were categorized into well-known groups reported in the literature. We measured the expression levels of the sequences from one sugarcane leaf transcriptomic dataset. Furthermore, TPS Class I has specific N-glycosylation sites inserted in conserved motifs and carries catalytic and binding residues in its TPS domain. Some of these residues are mutated in TPS Class II members, which implies loss of enzyme activity. Our approach retrieved many homo(eo)logous sequences for genes involved in trehalose metabolism, paving the way to discover the role of T6P signaling in sugarcane.

The Bacteroidetes Aequorivita sp. and Kaistella jeonii Produce Promiscuous Esterases With PET-Hydrolyzing Activity

Certain members of the Actinobacteria and Proteobacteria are known to degrade polyethylene terephthalate (PET). Here, we describe the first functional PET-active enzymes from the Bacteroidetes phylum. Using a PETase-specific Hidden-Markov-Model- (HMM-) based search algorithm, we identified several PETase candidates from Flavobacteriaceae and Porphyromonadaceae. Among them, two promiscuous and cold-active esterases derived from Aequorivita sp. (PET27) and Kaistella jeonii (PET30) showed depolymerizing activity on polycaprolactone (PCL), amorphous PET foil and on the polyester polyurethane Impranil® DLN. PET27 is a 37.8 kDa enzyme that released an average of 174.4 nmol terephthalic acid (TPA) after 120 h at 30°C from a 7 mg PET foil platelet in a 200 μl reaction volume, 38-times more than PET30 (37.4 kDa) released under the same conditions. The crystal structure of PET30 without its C-terminal Por-domain (PET30ΔPorC) was solved at 2.1 Å and displays high structural similarity to the IsPETase. PET30 shows a Phe-Met-Tyr substrate binding motif, which seems to be a unique feature, as IsPETase, LCC and PET2 all contain Tyr-Met-Trp binding residues, while PET27 possesses a Phe-Met-Trp motif that is identical to Cut190. Microscopic analyses showed that K. jeonii cells are indeed able to bind on and colonize PET surfaces after a few days of incubation. Homologs of PET27 and PET30 were detected in metagenomes, predominantly aquatic habitats, encompassing a wide range of different global climate zones and suggesting a hitherto unknown influence of this bacterial phylum on man-made polymer degradation.

Recognition of Metal Ion Ligand-Binding Residues by Adding Correlation Features and Propensity Factors

The realization of many protein functions is inseparable from the interaction with ligands; in particular, the combination of protein and metal ion ligands performs an important biological function. Currently, it is a challenging work to identify the metal ion ligand-binding residues accurately by computational approaches. In this study, we proposed an improved method to predict the binding residues of 10 metal ion ligands (Zn2+, Cu2+, Fe2+, Fe3+, Co2+, Mn2+, Ca2+, Mg2+, Na+, and K+). Based on the basic feature parameters of amino acids, and physicochemical and predicted structural information, we added another two features of amino acid correlation information and binding residue propensity factors. With the optimized parameters, we used the GBM algorithm to predict metal ion ligand-binding residues. In the obtained results, the Sn and MCC values were over 10.17% and 0.297, respectively. Besides, the Sn and MCC values of transition metals were higher than 34.46% and 0.564, respectively. In order to test the validity of our model, another method (Random Forest) was also used in comparison. The better results of this work indicated that the proposed method would be a valuable tool to predict metal ion ligand-binding residues.

Fruit Bromelain-Derived Peptide Potentially Restrains the Attachment of SARS-CoV-2 Variants to hACE2: A Pharmacoinformatics Approach

Before entering the cell, the SARS-CoV-2 spike glycoprotein receptor-binding domain (RBD) binds to the human angiotensin-converting enzyme 2 (hACE2) receptor. Hence, this RBD is a critical target for the development of antiviral agents. Recent studies have discovered that SARS-CoV-2 variants with mutations in the RBD have spread globally. The purpose of this in silico study was to determine the potential of a fruit bromelain-derived peptide. DYGAVNEVK. to inhibit the entry of various SARS-CoV-2 variants into human cells by targeting the hACE binding site within the RBD. Molecular docking analysis revealed that DYGAVNEVK interacts with several critical RBD binding residues responsible for the adhesion of the RBD to hACE2. Moreover, 100 ns MD simulations revealed stable interactions between DYGAVNEVK and RBD variants derived from the trajectory of root-mean-square deviation (RMSD), radius of gyration (Rg), and root-mean-square fluctuation (RMSF) analysis, as well as free binding energy calculations. Overall, our computational results indicate that DYGAVNEVK warrants further investigation as a candidate for preventing SARS-CoV-2 due to its interaction with the RBD of SARS-CoV-2 variants.

Novel allosteric mechanism of dual p53/MDM2 and p53/MDM4 inhibition by a small molecule

Restoration of the p53 tumor suppressor for personalised cancer therapy is a promising strategy. However, high-affinity MDM2 inhibitors have shown substantial side effects in clinical trials. Thus, elucidation of the molecular mechanisms of action of p53 reactivating molecules with alternative functional principle is of the utmost importance. Here, we report a discovery of a novel allosteric mechanism of p53 reactivation through targeting the p53 N-terminus which blocks both p53/MDM2 and p53/MDM4 interactions. Using biochemical assays and molecular docking, we identified the binding site of two p53 reactivating molecules, RITA and protoporphyrin IX (PpIX). Ion-mobility mass spectrometry revealed that the binding of RITA to serine 33 and serine 37 is responsible for inducing the allosteric shift in p53, which shields the MDM2 binding residues of p53 and prevents its interactions with MDM2 and MDM4. Our results point to an alternative mechanism of blocking p53 interaction with MDM2 and MDM4 and may pave the way for the development of novel allosteric inhibitors of p53/MDM2 and p53/MDM4 interactions.

The optimal pH of AID is skewed from that of its catalytic pocket by DNA-binding residues and surface charge

Activation-induced cytidine deaminase (AID) is a member of the apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) family of cytidine deaminases. AID mutates immunoglobulin loci to initiate secondary antibody diversification. The APOBEC3 (A3) sub-branch mutates viral pathogens in the cytosol and acidic endosomal compartments. Accordingly, AID functions optimally near neutral pH, while most A3s are acid-adapted (optimal pH 5.5-6.5). To gain a structural understanding for this pH disparity, we constructed high-resolution maps of AID catalytic activity vs pH. We found AID’s optimal pH was 7.3 but it retained most (>70%) of the activity at pH 8. Probing of ssDNA-binding residues near the catalytic pocket, key for bending ssDNA into the pocket (e.g R25) yielded mutants with altered pH preference, corroborating previous findings that the equivalent residue in APOBEC3G (H216) underlies its acidic pH preference. AID from bony fish exhibited more basic optimal pH (pH 7.5-8.1) and several R25-equivalent mutants altered pH preference. Comparison of pH optima across the AID/APOBEC3 family revealed an inverse correlation between positive surface charge and overall catalysis. The paralogue with the most robust catalytic activity (APOBEC3A) has the lowest surface charge, most acidic pH preference, while the paralogue with the most lethargic catalytic rate (AID) has the most positive surface charge and highest optimal pH. We suggest one possible mechanism is through surface charge dictating an overall optimal pH that is different from the optimal pH of the catalytic pocket microenvironment. These findings illuminate an additional structural mechanism that regulates AID/APOBEC3 mutagenesis.

Nanoparticles and photochemistry for native-like transmembrane protein footprinting

Mass spectrometry-based footprinting can probe higher order structure of soluble proteins in their native states and serve as a complement to high-resolution approaches. Traditional footprinting approaches, however, are hampered for integral membrane proteins because their transmembrane regions are not accessible to solvent, and they contain hydrophobic residues that are generally unreactive with most chemical reagents. To address this limitation, we bond photocatalytic titanium dioxide (TiO2) nanoparticles to a lipid bilayer. Upon laser irradiation, the nanoparticles produce local concentrations of radicals that penetrate the lipid layer, which is made permeable by a simultaneous laser-initiated Paternò–Büchi reaction. This approach achieves footprinting for integral membrane proteins in liposomes, helps locate both ligand-binding residues in a transporter and ligand-induced conformational changes, and reveals structural aspects of proteins at the flexible unbound state. Overall, this approach proves effective in intramembrane footprinting and forges a connection between material science and biology.

Protein embeddings and deep learning predict binding residues for various ligand classes

One important aspect of protein function is the binding of proteins to ligands, including small molecules, metal ions, and macromolecules such as DNA or RNA. Despite decades of experimental progress many binding sites remain obscure. Here, we proposed bindEmbed21, a method predicting whether a protein residue binds to metal ions, nucleic acids, or small molecules. The Artificial Intelligence (AI)-based method exclusively uses embeddings from the Transformer-based protein Language Model (pLM) ProtT5 as input. Using only single sequences without creating multiple sequence alignments (MSAs), bindEmbed21DL outperformed MSA-based predictions. Combination with homology-based inference increased performance to F1 = 48 ± 3% (95% CI) and MCC = 0.46 ± 0.04 when merging all three ligand classes into one. All results were confirmed by three independent data sets. Focusing on very reliably predicted residues could complement experimental evidence: For the 25% most strongly predicted binding residues, at least 73% were correctly predicted even when ignoring the problem of missing experimental annotations. The new method bindEmbed21 is fast, simple, and broadly applicable—neither using structure nor MSAs. Thereby, it found binding residues in over 42% of all human proteins not otherwise implied in binding and predicted about 6% of all residues as binding to metal ions, nucleic acids, or small molecules.

An insight into new glycotherapeutic in glial inflammation: Understanding the role of glycosylation from acute to chronic phase of inflammation

Glycosylation plays a critical role during inflammation and glial scar formation upon spinal cord injury (SCI) disease progression. Astrocytes and microglia are involved in this cascade to modulate the inflammation and tissue remodelling from acute to chronic phases. Therefore, understating the glycan changes in these glial cells is paramount. Herein a lectin microarray was undertaken using a cytokine-driven inflammatory MGC model, revealing considerable differential glycosylation from the acute to the chronic phase in a cytokine-combination generated inflamed MGC model. It was found that several N- and O-linked glycans associated with glia during SCI were differentially regulated. Pearson's correlation hierarchical clustering showed that groups were separated into several clusters, illustrating the heterogenicity among the control, cytokine combination, and LPS treated groups and the day on which treatment was given. Control and LPS treatments were observed to be in dense clusters. This was further confirmed with lectin immunostaining in which GalNAc, GlcNAc, mannose, fucose and sialic acid-binding residues were detected in astrocytes and microglia. However, this modification (upregulation of sialic acid expression) was inhibited by the sialyltransferase inhibitor which indeed modulates the mitochondrial functions. The present study is the first functional investigation of glycosylation modulation in a MGC (MGC) model which elucidates the role of the glycome in neuroinflammation and identified potential therapeutic targets for future glycol- therapeutics in neuroinflammation

Structural and functional characterization of NEMO cleavage by SARS-CoV-2 3CLpro

In addition to its essential role in viral polyprotein processing, the SARS-CoV-2 3C-like (3CLpro) protease can cleave human immune signaling proteins, like NF-κB Essential Modulator (NEMO) and deregulate the host immune response. Here, in vitro assays show that SARS-CoV-2 3CLpro cleaves NEMO with fine-tuned efficiency. Analysis of the 2.14 Å resolution crystal structure of 3CLpro C145S bound to NEMO226-235 reveals subsites that tolerate a range of viral and host substrates through main chain hydrogen bonds while also enforcing specificity using side chain hydrogen bonds and hydrophobic contacts. Machine learning- and physics-based computational methods predict that variation in key binding residues of 3CLpro-NEMO helps explain the high fitness of SARS-CoV-2 in humans. We posit that cleavage of NEMO is an important piece of information to be accounted for in the pathology of COVID-19.