The Protein Journal最新文献

Dihydrofolate reductase (DHFR) is ubiquitously present in all living organisms and plays a crucial role in the growth of the fungal pathogen R.solani. Sequence alignment confirmed the evolutionary conservation of the essential lid domain, with the amino acid ‘P’ within the PEKN lid domain appearing with a frequency of 89.5% in higher organisms and 11.8% in lower organisms. Consequently, a K65P variant was introduced into R.solani DHFR (rDHFR). Subsequent enzymatic kinetics assays were conducted for human DHFR (hDHFR), rDHFR, E. coli DHFR (eDHFR), and the K65P variant. hDHFR exhibited the highest k_cat of 0.95 s⁻¹, followed by rDHFR with 0.14 s⁻¹, while eDHFR displayed the lowest k_cat of 0.09 s⁻¹. Remarkably, the K65P variant induced a significant reduction in K_m, resulting in a 1.8-fold enhancement in catalytic efficiency (k_cat/K_m) relative to the wild type. Differential scanning fluorimetry and binding free energy calculations confirmed the enhanced substrate affinity for both folate and NADPH in the K65P variant. These results suggest that the K65P mutation enhances substrate affinity and catalytic efficiency in DHFR, highlighting the evolutionary and functional importance of the K65 residue.

Glucuronoyl esterases (GEs) are carbohydrate active enzymes in carbohydrate esterase family 15 which are involved in the hydrolysis of lignin-carbohydrate complexes. They are encoded by a wide range of aerobic and anaerobic fungi and bacteria inhabiting diverse environments. The rumen microbiome is a complex microbial community with a wide array of enzymes that specialize in deconstructing plant cell wall carbohydrates. Enzymes from the rumen tend to show low similarity to homologues found in other environments, making the rumen microbiome a promising source for the discovery of novel enzymes. Using a combination of phylogenetic and structural analysis, we investigated the structure-function relationship of GEs from the rumen bacteria Fibrobacter succinogenes and Ruminococcus flavefaciens, and from the rumen fungus, Piromyces rhizinflata. All adopt a canonical α/β hydrolase fold and possess a structurally conserved Ser-His-Glu/Asp catalytic triad. Structural variations in the enzymes are localized to loops surrounding the active site. Analysis of the active site structures in these enzymes emphasized the importance of structural plasticity in GEs with non-canonical active site conformations. We hypothesize that interkingdom HGT events may have contributed to the diversity of GEs in the rumen, and this is demonstrated by the phylogenetic and structural similarity observed between rumen bacterial and fungal GEs. This study advances our understanding of the structure-function relationship in glucuronoyl esterases and illuminates the evolutionary dynamics that contribute to enzyme diversity in the rumen microbiome.

Polyphenol oxidase (PPO) is an industrially important enzyme associated with browning reactions. In the present study, a set of ten new dihydropyridine [2,3-d] pyrimidines (TD-Hid-1-10) were synthesized and was found to be proven characteristically by ¹H NMR, ¹³C NMR, IR, elemental analysis, and assessed as possible PPO inhibitors. PPO was purified from banana using three-phase partitioning, achieving an 18.65-fold purification and 136.47% activity recovery. Enzyme kinetics revealed that the compounds TD-Hid-6 and TD-Hid-7 are to be the most potent inhibitors, exhibiting mixed-type inhibition profile with IC₅₀ values of 1.14 µM, 5.29 µM respectively against purified PPO enzyme. Electronic structure calculations at the B3LYP/PBE0 level of theories using def-2 SVP, def2-TZVP basis sets with various molecular descriptors characterized the electronic behavior of studied derivatives TD-Hid-1-10. Molecular electrostatic potential (MEP) and reduced density gradient analyses of RDG-NCI provided insights into charge distributions and weak intermolecular interactions. Docking study simulations predicted binding poses within crucial amino acid sequence in the 2y9x enzyme’s active site, which is typically similar in sequence to the PPO form is not allowed. Ligands were analysed in terms of binding energies, inhibitor concentrations (mM) and various molecular interactions such as H-bonds, H-carbon, π-carbon, π-sigma, π-sigma, π-π T-shaped, π-π stacked, π-alkyl, Van der Waals and Cu interactions. The lowest binding energy (-7.83 kcal/mol) and the highest inhibitory effect (1.83 mM) were shown by the ligand Td-Hid-6, which forms H-bonds with Met280 and Asn260, exhibits π-sigma interactions with His61 and π-alkyl interactions with Val283. Other ligands also showed different interactions with various amino acids; for example, the Td-Hid-1 ligand formed H-bonds with His244 and showed π-sigma interactions with His244 and Val283.

The current investigation focused on separating Cerastes cerastes venom to produce the first Kunitz-type peptide. Based on its anti-trypsin effect, Cerastokunin, a 7.75 kDa peptide, was purified until homogenity by three steps of chromatography. Cerastokunin was found to include 67 amino acid residues that were obtained by de novo sequencing using LC-MALDI-MSMS. Upon alignment with Kunitz-type peptides, there was a high degree of similarity. Cerastokunin’s 3D structure had 12% α-helices and 21% β-strands with pI 8.48. Cerastokunin showed a potent anticoagulant effect by inhibiting the protease activity of thrombin and trypsin as well as blocking the intrinsic and extrinsic coagulation pathways. In both PT and aPPT, Cerastokunin increased the blood clotting time in a dose-dependent way. Using Lys48 and Gln192 for direct binding, Cerastokunin inhibited thrombin, Factor Xa and trypsin as shown by molecular docking. Cerastokunin exhibited a dose–response blockade of PARs-dependent pathway platelet once stimulated by thrombin. An increased concentration of Cerastokunin resulted in a larger decrease of tail thrombus in the mice-carrageenan model in an in vivo investigation when compared to the effects of antithrombotic medications. At all Cerastokunin doses up to 6 mg/kg, no in vivo toxicity was seen in challenged mice over the trial’s duration.

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It is demonstrated, for the first time, that a mass spectrometry approach (known as phylonumerics) can be successfully implemented for structural phylogenetics investigations to chart the evolution of a protein’s structure and function. Illustrated for the compact globular protein myoglobin, peptide masses produced from the proteolytic digestion of the protein across animal species generate trees congruent to the sequence tree counterparts. Single point mutations calculated during the same mass tree building step can be followed along interconnected branches of the tree and represent a viable structural metric. A mass tree built for 15 diverse animal species, easily resolve the birds from mammal species, and the ruminant mammals from the remainder of the animals. Mutations within helix-spanning peptide segments alter both the mass and structure of the protein in these segments. Greater evolution is found in the B-helix over the A, E, F, G and H helices. A further mass tree study, of six more closely related primate species, resolves gorilla from the other primates based on a P22S mutation within the B-helix. The remaining five primates are resolved into two groups based on whether they contain a glycine or serine at position 23 in the same helix. The orangutan is resolved from the gibbon and siamang by its G-helix C110S mutation, while homo sapiens are resolved from chimpanzee based on the Q116H mutation. All are associated with structural perturbations in such helices. These structure altering mutations can be tracked along interconnecting branches of a mass tree, to follow the protein’s structure and evolution, and ultimately the evolution of the species in which the proteins are expressed. Those that have the greatest impact on a protein’s structure, its function, and ultimately the evolution of the species, can be selectively tracked or monitored.

Nitric oxide (NO) induces protein posttranslational modification (PTM), known as S-nitrosylation, which has started to gain attention as a critical regulator of thousands of substrate proteins. However, our understanding of the biological consequences of this emerging PTM is incomplete because of the limited number of identified S-nitrosylated proteins (S–NO proteins). Recent advances in detection methods have effectively contributed to broadening the spectrum of discovered S–NO proteins. This article briefly reviews the progress in S–NO protein detection methods and discusses how these methods are involved in characterizing the biological consequences of this PTM. Additionally, we provide insight into S–NO protein-related diseases, focusing on the role of these proteins in mitigating the severity of infectious diseases.

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A recent study showed that just one point mutation F33 to Y in the complementarity-determining region 1 of heavy chain (H-CDR1) could lead to the auto-antibody losing its DNA binding ability. However, the potential molecular mechanisms have not been well elucidated. In this study, we investigated how the antibody lost the DNA binding ability caused by mutation F33 to Y in the H-CDR1. We found that the electrostatic force was not the primary driving force for the interaction between anti-DNA antibodies and the antigen single strand DNA (ssDNA), and that the H-CDR2 largely contributed to the binding of antigen ssDNA, even larger than H-CDR1. The H-F33Y mutation could increase the hydrogen-bond interaction but impair the pi-pi stacking interaction between the antibody and ssDNA. We further found that F33_H, W98_H and Y95_L in the wiletype antibody could form the stable pi-pi stacking interaction with the nucleotide bases of ssDNA. However, the Y33 in mutant could not form the parallel sandwich pi-pi stacking interaction with the ssDNA. To further confirm the importance of pi-pi stacking, the wildtype antibody and the mutants (F33Y_H, F33A_H, W98A_H and Y95A_L) were experimentally expressed in CHO cells and purified, and the results from ELISA clearly showed that all the mutants lost the ssDNA binding ability. Taken together, our findings may not only deepen the understanding of the underlying interaction mechanism between autoantibody and antigen, but also broad implications in the field of antibody engineer.

Lectins are sugar interacting proteins which bind specific glycans reversibly and have ubiquitous presence in all forms of life. They have diverse biological functions such as cell signaling, molecular recognition, etc. C-type lectins (CTL) are a group of proteins from the lectin family which have been studied extensively in animals and are reported to be involved in immune functions, carcinogenesis, cell signaling, etc. The carbohydrate recognition domain (CRD) in CTL has a highly variable protein sequence and proteins carrying this domain are also referred to as C-type lectin domain containing proteins (CTLD). Because of this low sequence homology, identification of CTLD from hypothetical proteins in the sequenced genomes using homology based programs has limitations. Machine learning (ML) tools use characteristic features to identify homologous sequences and it has been used to develop a tool for identification of CTLD. Initially 500 sequences of well annotated CTLD and 500 sequences of non CTLD were used in developing the machine learning model. The classifier program Linear SVC from sci kit library of python was used and characteristic features in CTLD sequences like dipeptide and tripeptide composition were used as training attributes in various classifiers. A precision, recall and multiple correlation coefficient (MCC) value of 0.92, 0.91 and 0.82 respectively were obtained when tested on external test set. On fine tuning of the parameters like kernel, C value, gamma, degree and increasing number of non CTLD sequences there was improvement in precision, recall and MCC and the corresponding values were 0.99, 0.99 and 0.96. New CTLD have also been identified in the hypothetical segment of human genome using the trained model. The tool is available on our local server for interested users.

Thrombosis is the formation of abnormal blood clots in the blood vessels that obstruct blood flow and lead to thrombosis. Current treatments for thrombosis are associated with serious side effects. Therefore there is a need for alternative natural therapy. A fibrinolytic protease was isolated from fresh leaves of Moringa oleifera Lam. and characterized for its potential to solubilize blood clots and hydrolyse fibrin under in-vitro conditions. The isolated protease showed a single protein band on native-PAGE. It showed optimum fibrinolytic activity at pH 8.0, 37 ^oC with 50 µg protein. The fibrinolytic activity of isolated protease was also confirmed by fibrin zymography. K_m and V_max of isolated protease were determined by the Lineweaver Burk plot. The isolated protease could solubilize 96.41% of blood clots by 96 h under in-vitro conditions. In-vitro fibrin hydrolysis and blood clot solubilization activities shown by an isolated protease from leaves of Moringa oleifera Lam. suggest its fibrinolytic potential to dissolve blood clots. Being a natural molecule and from a dietary plant it can be explored as an alternative natural therapy against thrombosis.

Antimicrobial peptides have gradually gained advantages over small molecule inhibitors for their multifunctional effects, synthesising accessibility and target specificity. The current study aims to determine an antimicrobial peptide to inhibit PknB, a serine/threonine protein kinase (STPK), by binding efficiently at the helically oriented hinge region. A library of 5626 antimicrobial peptides from publicly available repositories has been prepared and categorised based on the length. Molecular docking using ADCP helped to find the multiple conformations of the subjected peptides. For each peptide served as input the tool outputs 100 poses of the subjected peptide. To maintain an efficient binding for relatively a longer duration, only those peptides were chosen which were seen to bind constantly to the active site of the receptor protein over all the poses observed. Each peptide had different number of constituent amino acid residues; the peptides were classified based on the length into five groups. In each group the peptide length incremented upto four residues from the initial length form. Five peptides were selected for Molecular Dynamic simulation in Gromacs based on higher binding affinity. Post-dynamic analysis and the frame comparison inferred that neither the shorter nor the longer peptide but an intermediate length of 15 mer peptide bound well to the receptor. Residual substitution to the selected peptides was performed to enhance the targeted interaction. The new complexes considered were further analysed using the Elastic Network Model (ENM) for the functional site’s intrinsic dynamic movement to estimate the new peptide’s role. The study sheds light on prospects that besides the length of peptides, the combination of constituent residues equally plays a pivotal role in peptide-based inhibitor generation. The study envisages the challenges of fine-tuned peptide recovery and the scope of Machine Learning (ML) and Deep Learning (DL) algorithm development. As the study was primarily meant for generation of therapeutics for Tuberculosis (TB), the peptide proposed by this study demands meticulous invitro analysis prior to clinical applications.

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