The Protein Journal最新文献

Protein–protein interactions are crucial for the entry of viruses into the cell. Understanding the mechanism of interactions is essential in studying human-virus association, developing new biologics and drug candidates, as well as viral infections and antiviral responses. Experimental methods to analyze human-virus protein–protein interactions based on protein sequence data are time-consuming and labor-intensive, so machine learning models are being developed to predict interactions and determine large-scale interactomes between species. The present work highlights the importance of sequence features in classifying interacting and non-interacting proteins from the protein sequence data. Higher dimensional amino acid sequence features such as Amino Acid Composition (AAC), Dipeptide Composition (DPC), Grouped Amino Acid Composition (GAAC), Pseudo-Amino Acid Composition (PAAC) etc., are extracted. Following feature extraction, three datasets were created: Dataset 1 contains all of the extracted features. While Datasets 2 and 3 contain the most relevant features obtained through dimensionality reduction. To analyze the importance of high-dimensional features and their participation in protein–protein interactions, a random forest classifier is trained on three datasets. With dimensionality reduction, the model exhibited exceptional accuracy, indicating that dimensionality reduction fails to capture the complexity of interactions and the underlying relationships between human and viral proteins. As a result of retaining high-dimensional features, it is possible to capture all the characteristics of protein–protein interactions that resemble host–pathogen associations, leading to the development of biologically meaningful models. Our proposed approach is a more realistic and comprehensive classification model, leading to deeper insights and better applications in virology and drug development.

Hemin, a byproduct of hemoglobin degradation, inflicts oxidative insult to cells. Following its accumulation, several proteins are recruited for heme detoxification with heme oxygenase playing the key role. Chaperones play a protective role primarily by preventing protein degradation and unfolding. They also are known to have miscellaneous secondary roles during similar situations. To discover a secondary role of chaperones during heme stress we studied the role of the chaperone HSPA8 in the detoxification of hemin. In-silico studies indicated that HSPA8 has a well-defined biophoric environment to bind hemin. Through optical difference spectroscopy, we found that HSPA8 binds hemin through its N-terminal domain with a K_d value of 5.9 ± 0.04 µM and transforms into a hemoprotein. The hemoprotein was tested for exhibiting peroxidase activity using guaiacol as substrate. The complex formed reacts with H₂O₂ and exhibits classical peroxidase activity with an ability to oxidize aromatic and halide substrates. HSPA8 is dose-dependently catalyzing heme polymerization through its N-terminal domain. The IR results reveal that the polymer formed exhibits structural similarities to β-hematin suggesting its covalent nature. The polymerization mechanism was tested through optical spectroscopy, spin-trap, and activity inhibition experiments. The results suggest that the polymerization occurs through a peroxidase-H₂O₂ system involving a one-electron transfer mechanism, and the formation of free radical and radical-radical interaction. It highlights a possible role of the HSPA8-hemin complex in exhibiting cytoprotective function during pathological conditions like malaria, sickle cell disease, etc.

Recent clinical data have identified infant patients with lethal ITPA deficiencies. ITPA is known to modulate ITP concentrations in cells and has a critical function in neural development which is not understood. Polymorphism of the ITPA gene affects outcomes for both ribavirin and thiopurine based therapies and nearly one third of the human population is thought to harbor ITPA polymorphism. In a previous site-directed mutagenesis alanine screen of the ITPA substrate selectivity pocket, we identified the ITPA mutant, E22A, as a gain-of function mutant with enhanced ITP hydrolysis activity. Here we report a rational enzyme engineering experiment to investigate the biochemical properties of position 22 ITPA mutants and find that the E22D ITPA has two- and four-fold improved substrate selectivity for ITP over the canonical purine triphosphates ATP and GTP, respectively, while maintaining biological activity. The novel E22D ITPA should be considered as a platform for further development of ITPA therapies.

Therapeutic proteins are potent, fast-acting drugs that are highly effective in treating various conditions. Medicinal protein usage has increased in the past 10 years, and it will evolve further as we better understand disease molecular pathways. However, it is associated with high processing costs, limited stability, difficulty in being administered as an oral medication, and the inability of large proteins to penetrate tissue and reach their target locations. Many methods have been developed to overcome the problems with the stability and chaperone activity of therapeutic proteins, viz., the addition of external agents (changing the properties of the surrounding solvent by using stabilizing excipients, e.g., amino acids, sugars, polyols) and internal agents (chemical modifications that influence its structural properties, e.g., mutations, glycosylation). However, these methods must completely clear protein instability and chaperone issues. There is still much work to be done on finetuning chaperone proteins to increase their biological efficacy and stability. Methylglyoxal (MGO), a potent dicarbonyl compound, reacts with proteins and forms covalent cross-links. Much research on MGO scavengers has been conducted since they are known to alter protein structure, which may result in alterations in biological activity and stability. MGO is naturally produced within our body, however, its impact on chaperones and protein stability needs to be better understood and seems to vary based on concentration. This review highlights the efforts of several research groups on the effect of MGO on various proteins. It also addresses the impact of MGO on a client protein, α-crystallin, to understand the potential solutions to the protein’s chaperone and stability problems.

Graphical Abstract

Angiotensin-converting enzyme 2 (ACE2) has a specific interaction with the coronavirus spike protein, enabling its entry into human cells. This membrane enzyme converts angiotensin II into angiotensin 1–7, which has an essential role in protecting the heart and improving lung function. Many therapeutic properties have been attributed to the human recombinant ACE2 (hrACE2), especially in combating complications related to diabetes mellitus and hypertension, as well as, preventing the coronavirus from entering the target tissues. In the current study, we designed an appropriate gene construct for the hybrid protein containing the ACE2 catalytic subunit and the B subunit of cholera toxin (CTB-ACE2). This structural feature will probably help the recombinant hybrid protein enter the mucosal tissues, including the lung tissue. Optimization of this hybrid protein expression was investigated in BL21 bacterial host cells. Also, the hybrid protein was identified with an appropriate antibody using the ELISA method. A large amount of the hybrid protein (molecular weight of ~ 100 kDa) was expressed as the inclusion body when the induction was performed in the presence of 0.25 mM IPTG and 1% sucrose for 10 h. Finally, the protein structural features were assessed using several biophysical methods. The fluorescence emission intensity and oligomeric size distribution of the CTB-ACE2 suggested a temperature-dependent alteration. The β-sheet and α-helix were also dominant in the hybrid protein structure, and this protein also displays acceptable chemical stability. In overall, according to our results, the efficient expression and successful purification of the CTB-ACE2 protein may pave the path for its therapeutic applications against diseases such as covid-19, diabetes mellitus and hypertension.

Graphical Abstract

AKR1B1 and AKR1B10 are important members of aldo–keto reductase family which plays a significant role in cancer progression by modulating cellular metabolism. These enzymes are involved in various metabolic processes, including the synthesis and metabolism of hormones, detoxification of reactive aldehydes, and the reduction of various endogenous and exogenous compounds. This study aimed to explore the potential of strychnine as an anticancer agent by targeting AKR1B1 and AKR1B10 via drug repurposing approach. To assess the drug-like properties of strychnine, a physiologically based pharmacokinetic (PKPB) model and High Throughput Pharmacokinetics (HTPK) approach were employed. The obtained results fell within the expected range for drug molecules, confirming its suitability for further investigation. Additionally, density functional theory (DFT) studies were conducted to gain insight into the electronic properties contributing to the drug molecule’s reactivity. Building upon the promising DFT results, molecular docking analysis using the AutoDock tool was performed to examine the binding interactions between strychnine and the proposed targets, AKR1B1 and AKR1B10. Findings from the molecular docking studies suggested a higher probability of strychnine acting as an inhibitor of AKR1B1 and AKR1B10 with docking scores of − 30.84 and − 29.36 kJ/mol respectively. To validate the stability of the protein–ligand complex, Molecular Dynamic Simulation (MDS) studies were conducted, revealing the formation of a stable complex between the enzymes and strychnine. This comprehensive approach sheds light on the potential effectiveness of strychnine as a treatment for breast, lung, liver, and pancreatic cancers, as well as related malignancies. The novel insights gained from the physiologically based pharmacokinetic modeling, density functional theory, molecular docking, and molecular dynamics simulations collectively support the prospect of strychnine as a promising molecule for anticancer therapy. Further investigations are warranted to validate these findings and explore the therapeutic potential of strychnine in preclinical and clinical settings.

Eis (Enhanced intracellular survival) protein is an aminoglycoside acetyltransferase enzyme classified under the family – GNAT (GCN5-related family of N-acetyltransferases) secreted by Mycobacterium tuberculosis (Mtb). The enzymatic activity of Eis results in the acetylation of kanamycin, thereby impairing the drug’s action. In this study, we expressed and purified recombinant Eis (rEis) to determine the enzymatic activity of Eis and its potential inhibitor. Glide-enhanced precision docking was used to perform molecular docking with chosen ligands. Quercetin was found to interact Eis with a maximum binding affinity of -8.379 kcal/mol as compared to other ligands. Quercetin shows a specific interaction between the positively charged amino acid arginine in Eis and the aromatic ring of quercetin through π-cation interaction. Further, the effect of rEis was studied on the antibiotic activity of kanamycin A in the presence and absence of quercetin. It was observed that the activity of rEis aminoglycoside acetyltransferase decreased with increasing quercetin concentration. The results from the disk diffusion assay confirmed that increasing the concentration of quercetin inhibits the rEis protein activity. In conclusion, quercetin may act as a potential Eis inhibitor.

Protein sequence comparison remains a challenging work for the researchers owing to the computational complexity due to the presence of 20 amino acids compared with only four nucleotides in Genome sequences. Further, protein sequences of different species are of different lengths; it throws additional changes to the researchers to develop methods, specially alignment-free methods, to compare protein sequences. In this work, an efficient technique to compare protein sequences is developed by a graphical representation. First, the classified grouping of 20 amino acids with a cardinality of 4 based on polar class is considered to narrow down the representational range from 20 to 4. Then a unit vector technique based on a two-quadrant Cartesian system is proposed to provide a new two-dimensional graphical representation of the protein sequence. Now, two approaches are proposed to cope with the varying lengths of protein sequences from various species: one uses Dynamic Time Warping (DTW), while the other one uses a two-dimensional Fast Fourier Transform (2D FFT). Next, the effectiveness of these two techniques is analyzed using two evaluation criteria—quantitative measures based on symmetric distance (SD) and computational speed. An analysis is performed on five data sets of 9 ND4, 9 ND5, 9 ND6, 12 Baculovirus, and 24 TF proteins under the two methods. It is found that the FFT-based method produces the same results as DTW but in less computational time. It is found that the result of the proposed method agrees with the known biological reference. Further, the present method produces better clustering than the existing ones.