In-silico screening of potential target transporters for glycyrrhetinic acid (GA) via deep learning prediction of drug-target interactions

Membrane transporters in Plants: Key players in abiotic and biotic stress tolerance and nutritional transport

Various abiotic and biotic stressors, including water extremes, temperature fluctuations, salinity, and heavy metals, pathogens and diseases significantly reduce global crop yields. Rapid plant responses are essential for adapting and minimizing metabolic losses. In this context, plant transporters (PTs) are essential for modulating stress responses by enabling the passage of diverse molecules and ions through the plasma membrane. Plant transporters play a pivotal role in regulating water and facilitating nutrient uptake, maintaining cellular equilibrium including osmotic regulation, detoxification, biofortification and orchestrating source-to-sink dynamics across different environmental stages in plants. In this review, we delved into recent discoveries concerning diverse transporter families such as ABC, MATE, NRAMP, SWEET, Symporters, STP, KUP, COPT/Ctr, NPF, NRT, PHT, YSL, ZIP and STP. Understanding the functions of these transporters is paramount for elucidating stress tolerance mechanisms and enhancing crop resilience through breeding and gene editing. These specialized plant membrane transporters play a crucial role in securing sustainable economic yields and maintaining high-quality produce, particularly in challenging growth conditions. We explored their contributions to plant robust growth via their crucial role in NPK and secondary metabolite transport. Through an integrated analysis of transporter dynamics during stress, we unveiled the nexus between nutrient management and stress resilience. We also clustered promising techniques that has been achieved to identify PTs such as function-driven screens, phenotype-driven screens and in silico-based approaches and provide a comprehensive overview of these transporters, offering valuable insights for the research community. This review also discusses future prospects for the use of bioinformatic computational tools in constructing signaling networks to improve our understanding of the behavior of transporters under abiotic and biotic stress. In this review, we highlight examples with case studies that illustrated how new technology and computational tools has been utilized in advanced identification and characterization of PTs functions. By strategically manipulating these transporters, we can pave the way for the development of "Plants for the Future."

Computational analysis of polymorphic residues in maltose and maltotriose transporters of a wild Saccharomyces cerevisiae strain

The metabolism of maltose and maltotriose, the primary sugars in brewing wort, depends on an efficient transport system. However, most Saccharomyces cerevisiae strains transport maltotriose inefficiently, leaving residual α-glucosides in the final product. Proteins involved in maltotriose transport exhibit diverse polymorphic sequences linked to sugar transport efficiency. In this study, a wild S. cerevisiae strain was placed under adaptive selection, resulting in a strain with a 65 and 44% increase in maltose and maltotriose transport rates, respectively. Genes encoding maltose and maltotriose transporters, including MALx1, MPHx, and AGT1, were detected in both the native and adapted strains. One variant of Mal31p, carrying a polymorphism at position 371 in transmembrane helix 7, was identified. This helix has been reported to have a high likelihood of undergoing polymorphisms. Bioinformatics analysis revealed structural changes affecting substrate interactions and channel dynamics, with the polymorphism conferring greater protein flexibility and reducing electrostatic interactions. These results suggest that the residue at position 371 in maltose and maltotriose transporters is a key element distinct from those previously reported. Additionally, we propose a significant set of polymorphic residues within these transporters potentially resulting from the evolution of these proteins.

A novel method for exploration and prediction of the bioactive target of rice bran-derived peptide (KF-8) by integrating computational methods and experiments

The investigation into the bioactive peptide's activity and target action poses a significant challenge in the field of food. An active peptide prepared from rice bran, KF-8, was confirmed to possess antioxidant activity in our previous study, but the specific target was unclear. This study used eight target prediction tools based on artificial intelligence and chemoinformatics to preliminarily screen potential antioxidant targets by integrating different computational methods. Then five different types of docking software were comparatively analyzed to further clarify their interaction sites and possible modes of action. The results showed that SIRT1 and CXCR4 are potential antioxidant targets of KF-8. Different docking software suggested that KF-8 interacts with SIRT1 and CXCR4 as major residues. Meanwhile, the results of Immunofluorescence co-localization experiments showed that the co-localization coefficients of KF-8 with SIRT1 and CXCR4 reached 0.5879 and 0.5684. This study provides new alternative means for the discovery of active peptide targets.

Identification of TonB-dependent siderophore receptor inhibitors against Flavobacterium columnare using a structure-based high-throughput virtual screening method

TonB-dependent siderophore receptors play a critical transport role for Flavobacterium columnare virulence formation and growth, and have become valuable targets for the development of novel antimicrobial agents. Traditional Chinese medicine has demonstrated notable efficacy in the treatment of fish diseases and includes potential antibacterial agents. Herein, we performed molecular docking-based virtual screening to discover novel TonB-dependent siderophore receptor inhibitors from traditional Chinese medicine and provide information for developing novel antibacterial agents. Firstly, we efficiently obtained 11 potential inhibitors with desirable drug-like characteristics from thousands of compounds in the TCM library based on virtual screening and property prediction. The antibacterial activity of Enoxolone, along with its interaction characteristics, were determined via an MIC assay and molecular dynamic simulation. Transcriptional profiling, along with validation experiments, subsequently revealed that an insufficient uptake of iron ions by bacteria upon binding to the TonB-dependent siderophore receptors is the antibacterial mechanism of Enoxolone. Finally, Enoxolone's acceptable toxicity was illustrated through immersion experiments. In summary, we have used virtual screening techniques for the first time in the development of antimicrobial agents in aquaculture. Through this process, we have identified Enoxolone as a promising compound targeting the TonB-dependent siderophore receptor of F. columnare. In addition, our findings will provide new ideas for the advancement of innovative antimicrobial medications in aquaculture.