The Protein Journal最新文献

Universal stress proteins (USPs) are widely distributed and play crucial roles in cellular responses to biotic and abiotic stresses. These roles include regulating cell growth and development, cell motility, hypoxia responses, and ion sequestration. With the increasing frequency and intensity of extreme weather events due to climate change, pathogens have developed different strategies to withstand environmental stresses, in which USPs play a significant role in their survival and virulence. In this study, we analyzed the importance of USPs in various organisms, such as archaea, plants, and fungi, as a parameter that influences their survival. We discussed the different types Of USPs and their role, aiming to carry out fundamental research in this field to identify significant constraints for better understanding of USP functions at molecular level. Additionally, we discussed concepts and research techniques that could help overcome these hurdles and facilitate new molecular approaches to better understand and target USPs as important stress adaptation and survival regulators. Although the precise characteristics of USPs are still unclear, numerous innovative uses have already been developed, tested, and implemented. Complementary approaches to basic research and applications, as well as new technology and analytical techniques, may offer insights into the cryptic but crucial activities of USPs in various living systems.

Graphical Abstract

Shows the different environmental stresses faced by plants and microbes and how they respond by generating stress proteins, which are enhanced when stressors trigger organisms and help the organism in stress tolerance and resistance and the pathogenesis of microbes.

The paper introduces a novel probability descriptor for genome sequence comparison, employing a generalized form of Jensen-Shannon divergence. This divergence metric stems from a one-parameter family, comprising fractions up to a maximum value of half. Utilizing this metric as a distance measure, a distance matrix is computed for the new probability descriptor, shaping Phylogenetic trees via the neighbor-joining method. Initial exploration involves setting the parameter at half for various species. Assessing the impact of parameter variation, trees drawn at different parameter values (half, one-fourth, one-eighth). However, measurement scales decrease with parameter value increments, with higher similarity accuracy corresponding to lower scale values. Ultimately, the highest accuracy aligns with the maximum parameter value of half. Comparative analyses against previous methods, evaluating via Symmetric Distance (SD) values and rationalized perception, consistently favor the present approach's results. Notably, outcomes at the maximum parameter value exhibit the most accuracy, validating the method's efficacy against earlier approaches.

Protein–DNA and protein–RNA interactions are involved in many biological processes and regulate many cellular functions. Moreover, they are related to many human diseases. To understand the molecular mechanism of protein–DNA binding and protein–RNA binding, it is important to identify which residues in the protein sequence bind to DNA and RNA. At present, there are few methods for specifically identifying the binding sites of disease-related protein–DNA and protein–RNA. In this study, so we combined four machine learning algorithms into an ensemble classifier (EPDRNA) to predict DNA and RNA binding sites in disease-related proteins. The dataset used in model was collated from UniProt and PDB database, and PSSM, physicochemical properties and amino acid type were used as features. The EPDRNA adopted soft voting and achieved the best AUC value of 0.73 at the DNA binding sites, and the best AUC value of 0.71 at the RNA binding sites in 10-fold cross validation in the training sets. In order to further verify the performance of the model, we assessed EPDRNA for the prediction of DNA-binding sites and the prediction of RNA-binding sites on the independent test dataset. The EPDRNA achieved 85% recall rate and 25% precision on the protein–DNA interaction independent test set, and achieved 82% recall rate and 27% precision on the protein–RNA interaction independent test set. The online EPDRNA webserver is freely available at http://www.s-bioinformatics.cn/epdrna.

The immune system maintains constant surveillance to prevent the infiltration of both endogenous and exogenous threats into host organisms. The process is regulated by effector immune cells that combat external pathogens and regulatory immune cells that inhibit excessive internal body inflammation, ultimately establishing a state of homeostasis within the body. Disruption to this process could lead to autoimmunity, which is often associated with the malfunction of both T cells and B cells with T cells playing a more major role. A number of therapeutic mediators for autoimmune diseases are available, from conventional disease-modifying drugs to biologic agents and small molecule inhibitors. Recently, ribosomally synthesized peptides, specifically cyclotides from plants are currently attracting more attention as potential autoimmune disease therapeutics due to their decreased toxicity compared to small molecules inhibitors as well as their remarkable stability against a number of factors. This review provides a concise overview of various cyclotides exhibiting immunomodulatory properties and their potential as therapeutic interventions for autoimmune diseases.

Metallothioneins are a group of cysteine-rich proteins that play an important role in the homeostasis and detoxification of heavy metals. The objective of this research was to explore the significance of metallothionein in Trichoderma harzianum tolerance to zinc. At the inhibitory concentration of 1000 ppm, the fungus adsorbed 16.7 ± 0.4 mg/g of metal. The HPLC and SDS-PAGE electrophoresis data suggested that the fungus production of metallothionein was twice as high in the presence of zinc as in the control group. The examination of the genes; metallothionein expression activator (MEA) and Cu fist revealed that the MEA, with a C₂H₂ zinc finger domain, increased significantly in the presence of zinc. It was observed that in T. harzianum, the enhanced expression of the metallothionein gene was managed by the metallothionein activator under zinc overload conditions. According to our knowledge, this is the first report on the role of metallothionein in the resistance of T. harzianum to zinc.

The present study aims at understanding the effect of organic solvents on the specific proteolytic activity and operational stability of asclepain cI in aqueous-organic media, using correlations between geometrical and structural parameters of asclepain cI. These correlations were determined by molecular dynamics (MD) simulations and the secondary structure of the enzyme validated by Fourier-transform Infrared (FTIR) spectroscopy. Asclepain cI exhibited significantly higher catalytic potential in 29 of the 42 aqueous-organic media tested, composed by 0.1 mM TRIS hydrochloride buffer pH 8 (TCB) and an organic solvent, than in buffer alone. Asclepain cI in water-organic miscible systems showed high FTIR spectral similarity with that obtained in TCB, while in immiscible systems the enzyme acquired different secondary structures than in buffer. Among the conditions studied, asclepain cI showed the highest catalytic potential in 50% v/v ethyl acetate in TCB. According to MD simulations, that medium elicited solvation and flexibility changes around the active center of asclepain cI and conducted to a new secondary structure with the active center preserved. These results provide valuable insights into the elucidation of the molecular mechanism of asclepain cI tolerance to organic solvents and pave the way for its future application for the synthesis of peptides in aqueous-organic media.

Graphical Abstract

Protein–protein interactions (PPIs) involve the physical or functional contact between two or more proteins. Generally, proteins that can interact with each other always have special relationships. Some previous studies have reported that gene ontology (GO) terms are related to the determination of PPIs, suggesting the special patterns on the GO terms of proteins in PPIs. In this study, we explored the special GO term patterns on human PPIs, trying to uncover the underlying functional mechanism of PPIs. The experimental validated human PPIs were retrieved from STRING database, which were termed as positive samples. Additionally, we randomly paired proteins occurring in positive samples, yielding lots of negative samples. A simple calculation was conducted to count the number of positive samples for each GO term pair, where proteins in samples were annotated by GO terms in the pair individually. The similar number for negative samples was also counted and further adjusted due to the great gap between the numbers of positive and negative samples. The difference of the above two numbers and the relative ratio compared with the number on positive samples were calculated. This ratio provided a precise evaluation of the occurrence of GO term pairs for positive samples and negative samples, indicating the latent GO term patterns for PPIs. Our analysis unveiled several nuclear biological processes, including gene transcription, cell proliferation, and nutrient metabolism, as key biological functions. Interactions between major proliferative or metabolic GO terms consistently correspond with significantly reported PPIs in recent literature.

Protein aggregation is related to numerous pathological conditions like Alzheimer’s and Parkinson’s disease. In our study, we have shown that an already existing FDA-approved drug; methotrexate (MTX) can be reprofiled on preformed α-chymotrypsinogen A (α-Cgn A) aggregates. The zymogen showed formation of aggregates upon interaction with mercuric ions, with increasing concentration of Hg₂Cl₂ (0-150 µM). The hike in ThT and ANS fluorescence concomitant with blue shift, bathochromic shift and the hyperchromic effect in the CR absorbance, RLS and turbidity measurements, substantiate the zymogen β-rich aggregate formation. The secondary structural alterations of α- Cgn A as analyzed by CD measurements, FTIR and Raman spectra showed the transformation of native β-barrel conformation to β-inter-molecular rich aggregates. The native α- Cgn A have about 30% α-helical content which was found to be about 3% in presence of mercuric ions suggesting the formation of aggregates. The amorphous aggregates were visualized by SEM. On incubation of Hg₂Cl₂ treated α- Cgn A with increasing concentration of the MTX resulted in reversing aggregates to the native-like structure. These results were supported by remarkable decrease in ThT and ANS fluorescence intensities and CR absorbance and also consistent with CD, FTIR, and Raman spectroscopy data. MTX was found to increase the α-helical content of the zymogen from 3 to 15% proposing that drug is efficient in disrupting the β-inter-molecular rich aggregates and reverting it to native like structure. The SEM images are in accordance with CD data showing the disintegration of aggregates. The most effective concentration of the drug was found to be 120 µM. Molecular docking analysis showed that MTX molecule was surrounded by the hydrophobic residues including Phe39, His40, Arg145, Tyr146, Thr151, Gly193, Ser195, and Gly216 and conventional hydrogen bonds, including Gln73 (bond length: 2.67Å), Gly142 (2.59Å), Thr144 (2.81Å), Asn150 (2.73Å), Asp153 (2.71Å), and Cys191 (2.53Å). This investigation will help to find the use of already existing drugs to cure protein misfolding-related abnormalities.

S100A8 and S100A9 belong to the calcium-binding, damage associated molecular pattern (DAMP) proteins shown to aggravate the pathogenesis of rheumatoid arthritis (RA) through their interaction with the TLR4, RAGE and CD36 receptors. S100A8 and S100A9 proteins tend to exist in monomeric, homo and heterodimeric forms, which have been implicated in the pathogenesis of RA, via interacting with Pattern Recognition receptors (PRRs). The study aims to assess the influence of changes in the structure and biological assembly of S100A8 and S100A9 proteins as well as their interaction with significant receptors in RA through computational methods and surface plasmon resonance (SPR) analysis. Molecular docking analysis revealed that the S100A9 homodimer and S100A8/A9 heterodimer showed higher binding affinity towards the target receptors. Most S100 proteins showed good binding affinity towards TLR4 compared to other receptors. Based on the 50 ns MD simulations, TLR4, RAGE, and CD36 formed stable complexes with the monomeric and dimeric forms of S100A8 and S100A9 proteins. However, SPR analysis showed that the S100A8/A9 heterodimers formed stable complexes and exhibited high binding affinity towards the receptors. SPR data also indicated that TLR4 and its interactions with S100A8/A9 proteins may play a primary role in the pathogenesis of RA, with additional contributions from CD36 and RAGE interactions. Subsequent in vitro and in vivo investigations are warranted to corroborate the involvement of S100A8/A9 and the expression of TLR4, RAGE, and CD36 in the pathophysiology of RA.