EVLncRNAs 3.0: an updated comprehensive database for manually curated functional long non-coding RNAs validated by low-throughput experiments.

Long noncoding RNAs (lncRNAs) have emerged as crucial regulators across diverse biological processes and diseases. While high-throughput sequencing has enabled lncRNA discovery, functional characterization remains limited. The EVLncRNAs database is the first and exclusive repository for all experimentally validated functional lncRNAs from various species. After previous releases in 2018 and 2021, this update marks a major expansion through exhaustive manual curation of nearly 25 000 publications from 15 May 2020, to 15 May 2023. It incorporates substantial growth across all categories: a 154% increase in functional lncRNAs, 160% in associated diseases, 186% in lncRNA-disease associations, 235% in interactions, 138% in structures, 234% in circular RNAs, 235% in resistant lncRNAs and 4724% in exosomal lncRNAs. More importantly, it incorporated additional information include functional classifications, detailed interaction pathways, homologous lncRNAs, lncRNA locations, COVID-19, phase-separation and organoid-related lncRNAs. The web interface was substantially improved for browsing, visualization, and searching. ChatGPT was tested for information extraction and functional overview with its limitation noted. EVLncRNAs 3.0 represents the most extensive curated resource of experimentally validated functional lncRNAs and will serve as an indispensable platform for unravelling emerging lncRNA functions. The updated database is freely available at https://www.sdklab-biophysics-dzu.net/EVLncRNAs3/.

EVlncRNA-Dpred: improved prediction of experimentally validated lncRNAs by deep learning.

Long non-coding RNAs (lncRNAs) played essential roles in nearly every biological process and disease. Many algorithms were developed to distinguish lncRNAs from mRNAs in transcriptomic data and facilitated discoveries of more than 600 000 of lncRNAs. However, only a tiny fraction (<1%) of lncRNA transcripts (~4000) were further validated by low-throughput experiments (EVlncRNAs). Given the cost and labor-intensive nature of experimental validations, it is necessary to develop computational tools to prioritize those potentially functional lncRNAs because many lncRNAs from high-throughput sequencing (HTlncRNAs) could be resulted from transcriptional noises. Here, we employed deep learning algorithms to separate EVlncRNAs from HTlncRNAs and mRNAs. For overcoming the challenge of small datasets, we employed a three-layer deep-learning neural network (DNN) with a K-mer feature as the input and a small convolutional neural network (CNN) with one-hot encoding as the input. Three separate models were trained for human (h), mouse (m) and plant (p), respectively. The final concatenated models (EVlncRNA-Dpred (h), EVlncRNA-Dpred (m) and EVlncRNA-Dpred (p)) provided substantial improvement over a previous model based on support-vector-machines (EVlncRNA-pred). For example, EVlncRNA-Dpred (h) achieved 0.896 for the area under receiver-operating characteristic curve, compared with 0.582 given by sequence-based EVlncRNA-pred model. The models developed here should be useful for screening lncRNA transcripts for experimental validations. EVlncRNA-Dpred is available as a web server at https://www.sdklab-biophysics-dzu.net/EVlncRNA-Dpred/index.html, and the data and source code can be freely available along with the web server.

Interaction of Asn297-Linked Glycan Ligands with the Fc Fragment of the Immunoglobulin Class G1: A Molecular Dynamics Simulation Study.

The allosteric modulation of the homodimeric H10-03-6 protein to glycan ligands L1 and L2, and the STAB19 protein to glycan ligands L3 and L4, respectively, has been studied by molecular dynamics simulations and free energy calculations. The results revealed that the STAB19 protein has a significantly higher affinity for L3 (-11.38 ± 2.32 kcal/mol) than that for L4 (-5.51 ± 1.92 kcal/mol). However, the combination of the H10-03-6 protein with glycan L2 (1.23 ± 6.19 kcal/mol) is energetically unfavorable compared with that of L1 (-13.96 ± 0.35 kcal/mol). Further, the binding of glycan ligands L3 and L4 to STAB19 would result in the significant closure of the two CH2 domains of the STAB19 conformation with the decrease of the centroid distances between the two CH2 domains compared with the H10-03-6/L1/L2 complex. The CH2 domain closure of STAB19 relates directly to the formation of new hydrogen bonds and hydrophobic interactions between the residues Ser239, Val240, Asp265, Glu293, Asn297, Thr299, Ser337, Asp376, Thr393, Pro395, and Pro396 in STAB19 and glycan ligands L3 and L4, which suggests that these key residues would contribute to the specific regulation of STAB19 to L3 and L4. In addition, the distance analysis revealed that the EF loop in the H10-03-6/L1/L2 model presents a high flexibility and partial disorder compared with the stabilized STAB19/L3/L4 complex. These results will be helpful in understanding the specific regulation through the asymmetric structural characteristics in the CH2 and CH3 domains of the H10-03-6 and STAB19 proteins.

Conformational States of the GDP- and GTP-Bound HRAS Affected by A59E and K117R: An Exploration from Gaussian Accelerated Molecular Dynamics.

The HRAS protein is considered a critical target for drug development in cancers. It is vital for effective drug development to understand the effects of mutations on the binding of GTP and GDP to HRAS. We conducted Gaussian accelerated molecular dynamics (GaMD) simulations and free energy landscape (FEL) calculations to investigate the impacts of two mutations (A59E and K117R) on GTP and GDP binding and the conformational states of the switch domain. Our findings demonstrate that these mutations not only modify the flexibility of the switch domains, but also affect the correlated motions of these domains. Furthermore, the mutations significantly disrupt the dynamic behavior of the switch domains, leading to a conformational change in HRAS. Additionally, these mutations significantly impact the switch domain's interactions, including their hydrogen bonding with ligands and electrostatic interactions with magnesium ions. Since the switch domains are crucial for the binding of HRAS to effectors, any alterations in their interactions or conformational states will undoubtedly disrupt the activity of HRAS. This research provides valuable information for the design of drugs targeting HRAS.

EVLncRNAs 2.0: an updated database of manually curated functional long non-coding RNAs validated by low-throughput experiments.

Long non-coding RNAs (lncRNAs) play important functional roles in many diverse biological processes. However, not all expressed lncRNAs are functional. Thus, it is necessary to manually collect all experimentally validated functional lncRNAs (EVlncRNA) with their sequences, structures, and functions annotated in a central database. The first release of such a database (EVLncRNAs) was made using the literature prior to 1 May 2016. Since then (till 15 May 2020), 19 245 articles related to lncRNAs have been published. In EVLncRNAs 2.0, these articles were manually examined for a major expansion of the data collected. Specifically, the number of annotated EVlncRNAs, associated diseases, lncRNA-disease associations, and interaction records were increased by 260%, 320%, 484% and 537%, respectively. Moreover, the database has added several new categories: 8 lncRNA structures, 33 exosomal lncRNAs, 188 circular RNAs, and 1079 drug-resistant, chemoresistant, and stress-resistant lncRNAs. All records have checked against known retraction and fake articles. This release also comes with a highly interactive visual interaction network that facilitates users to track the underlying relations among lncRNAs, miRNAs, proteins, genes and other functional elements. Furthermore, it provides links to four new bioinformatics tools with improved data browsing and searching functionality. EVLncRNAs 2.0 is freely available at https://www.sdklab-biophysics-dzu.net/EVLncRNAs2/.

Influence of Different Aromatic Hydrophobic Residues on the Antimicrobial Activity and Membrane Selectivity of BRBR-NH2 Tetrapeptide.

The ultrashort linear antimicrobial tetrapeptide BRBR-NH2 with an unnatural residue biphenylalanine (B) has potent and rapid antimethicillin-resistant Staphylococcus aureus (MRSA) activity but lacks hemolytic activity. The anti-MRSA activity of BRBR-NH2 is 8-fold more potent than that of WRWR-NH2 and 16-fold more potent than that of FRFR-NH2. However, how to influence their antimicrobial activities and mechanisms through the substitution of different aromatic hydrophobic residues is still unclear. In this work, to study the effects of varying hydrophobic interactions and membrane selectivities of BRBR-NH2, we performed multiple long-time (1000 ns) molecular dynamics (MD) simulations to investigate the interactions of a red blood cell (RBC) membrane and a Gram-positive bacterial cell membrane with three different tetrapeptides (BRBR-NH2, WRWR-NH2, and FRFR-NH2) under different ratios of peptides and lipids and also explored the changes in the membrane and structural characteristics of peptides. The binding energy results show that BRBR-NH2 interacts weakly with the RBC membrane, while not all BRBR-NH2 can be adsorbed to the RBC membrane surface. The MD simulation results produced significant local membrane thinning of multiBRBR-NH2 peptides in the Gram-positive bacterial cell membrane. An in-depth analysis of structural features and peptide-membrane interactions suggests that the aggregation of BRBR-NH2 on the membrane surface plays a crucial role in the destruction of the cell membrane. Taken together with the observed local membrane thinning, the in-depth analysis demonstrated that the interactions between the lipid bilayer and the BRBR-NH2 aggregation surface result in a local disturbance of the membrane structure. It can be concluded that the high anti-MRSA activity of BRBR-NH2 is attributed to the aggregation of BRBR-NH2 on the membrane surface. On the other hand, WRWR-NH2 and FRFR-NH2 peptides tend to bind with the membrane surface in a monomeric form and cover the membrane surface in a carpet-like manner. Therefore, these results provide an advanced microscopic understanding of how hydrophobic interactions or hydrophobic residues affect the antimicrobial activity and mechanism of antimicrobial peptides (AMPs).

EVLncRNAs: a manually curated database for long non-coding RNAs validated by low-throughput experiments.

Long non-coding RNAs (lncRNAs) play important functional roles in various biological processes. Early databases were utilized to deposit all lncRNA candidates produced by high-throughput experimental and/or computational techniques to facilitate classification, assessment and validation. As more lncRNAs are validated by low-throughput experiments, several databases were established for experimentally validated lncRNAs. However, these databases are small in scale (with a few hundreds of lncRNAs only) and specific in their focuses (plants, diseases or interactions). Thus, it is highly desirable to have a comprehensive dataset for experimentally validated lncRNAs as a central repository for all of their structures, functions and phenotypes. Here, we established EVLncRNAs by curating lncRNAs validated by low-throughput experiments (up to 1 May 2016) and integrating specific databases (lncRNAdb, LncRANDisease, Lnc2Cancer and PLNIncRBase) with additional functional and disease-specific information not covered previously. The current version of EVLncRNAs contains 1543 lncRNAs from 77 species that is 2.9 times larger than the current largest database for experimentally validated lncRNAs. Seventy-four percent lncRNA entries are partially or completely new, comparing to all existing experimentally validated databases. The established database allows users to browse, search and download as well as to submit experimentally validated lncRNAs. The database is available at http://biophy.dzu.edu.cn/EVLncRNAs.

Different effects of cholesterol on membrane permeation of arginine and tryptophan revealed by bias-exchange metadynamics simulations.

Experiments have shown that cholesterol influences the membrane permeability of small molecules, amino acids, and cell-penetrating peptides. However, their exact translocation mechanisms under the influence of cholesterol remain poorly understood. Given the practical importance of cell-penetrating peptides and the existence of varied cholesterol contents in different cell types, it is necessary to examine the permeation of amino acids in cholesterol-containing membranes at atomic level of details. Here, bias-exchange metadynamics simulations were employed to investigate the molecular mechanism of the membrane permeation of two amino acids Arg and Trp important for cell-penetrating peptides in the presence of different concentrations of cholesterol. We found that the free energy barrier of Arg+ (the protonated form) permeation increased linearly as the cholesterol concentration increased, whereas the barrier of Trp permeation had a rapid increase from 0 mol. % to 20 mol. % cholesterol-containing membranes and nearly unchanged from 20 mol. % to 40 mol. % cholesterol-containing membranes. Arg0 becomes slightly more stable than Arg+ at the center of the dipalmitoylphosphatidylcholine (DPPC) membrane with 40 mol. % cholesterol concentrations. As a result, Arg+ has a similar permeability as Trp at 0 mol. % and 20 mol. % cholesterol, but a significantly lower permeability than Trp at 40 mol. % cholesterol. This difference is caused by the gradual reduction of water defects for Arg+ as the cholesterol concentration increases but lack of water defects for Trp in cholesterol-containing membranes. Strong but different orientation dependence between Arg+ and Trp permeations is observed. These results provide an improved microscopic understanding of amino-acid permeation through cholesterol-containing DPPC membrane systems.

Fast-Folding Pathways of the Thrombin-Binding Aptamer G-Quadruplex Revealed by a Markov State Model.

G-quadruplex structures participate in many important cellular processes. For a better understanding of their functions, knowledge of the mechanism by which they fold into the functional native structures is necessary. In this work, we studied the folding process of the thrombin-binding aptamer G-quadruplex. Enabled by a computational paradigm that couples an advanced sampling method and a Markov state model, four folding intermediates were identified, including an antiparallel G-hairpin, two G-triplex structures, and a double-hairpin conformation. Likewise, a misfolded structure with a nonnative distribution of syn/anti guanines was also observed. Based on these states, a transition path analysis revealed three fast-folding pathways, along which the thrombin-binding aptamer would fold to the native state directly, with no evidence of potential nonnative competing conformations. The results also showed that the TGT-loop plays an important role in the folding process. The findings of this research may provide general insight about the folding of other G-quadruplex structures.

Molecular Dynamics Simulations of Human Antimicrobial Peptide LL-37 in Model POPC and POPG Lipid Bilayers.

Cathelicidins are a large family of cationic antimicrobial peptides (AMPs) found in mammals with broad spectrum antimicrobial activity. LL-37 is the sole amphipathic α-helical AMP from human Cathelicidins family. In addition to its bactericidal capability, LL-37 has antiviral, anti-tumor, and immunoregulatory activity. Despite many experimental studies, its molecular mechanism of action is not yet fully understood. Here, we performed three independent molecular dynamics simulations (600 ns or more) of a LL-37 peptide in the presence of 256 lipid bilayers with 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPG) mimicking bacterial and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) mimicking mammalian membranes. We found that LL-37 can be quickly absorbed onto the POPG bilayer without loss of its helical conformation in the core region and with the helix lying in parallel to the bilayer. The POPG bilayer was deformed. In contrast, LL-37 is slower in reaching the POPC surface and loss much of its helical conformation during the interaction with the bilayer. LL-37 only partially entered the POPC bilayer without significant deformation of the membrane. The observed difference for different bilayers is largely due to the fact that LL-37 is positively charged, POPG is negatively charged, and POPC is neutral. Our simulation results demonstrated the initial stage of disruption of the bacterial membrane by LL-37 in atomic details. Comparison to experimental results on LL-37 and simulation studies in other systems was made.

Atomistic Analysis of ToxN and ToxI Complex Unbinding Mechanism.

ToxIN is a triangular structure formed by three protein toxins (ToxNs) and three specific noncoding RNA antitoxins (ToxIs). To respond to stimuli, ToxI is preferentially degraded, releasing the ToxN. Thus, the dynamic character is essential in the normal function interactions between ToxN and ToxI. Here, equilibrated molecular dynamics (MD) simulations were performed to study the stability of ToxN and ToxI. The results indicate that ToxI adjusts the conformation of 3' and 5' termini to bind to ToxN. Steered molecular dynamics (SMD) simulations combined with the recently developed thermodynamic integration in 3nD (TI3nD) method were carried out to investigate ToxN unbinding from the ToxIN complex. The potentials of mean force (PMFs) and atomistic pictures suggest the unbinding mechanism as follows: (1) dissociation of the 5' terminus from ToxN, (2) missing the interactions involved in the 3' terminus of ToxI without three nucleotides (G31, A32, and A33), (3) starting to unfold for ToxI, (4) leaving the binding package of ToxN for three nucleotides of ToxI, (5) unfolding of ToxI. This work provides information on the structure-function relationship at the atomistic level, which is helpful for designing new potent antibacterial drugs in the future.

Bias-Exchange Metadynamics Simulation of Membrane Permeation of 20 Amino Acids.

Thermodynamics of the permeation of amino acids from water to lipid bilayers is an important first step for understanding the mechanism of cell-permeating peptides and the thermodynamics of membrane protein structure and stability. In this work, we employed bias-exchange metadynamics simulations to simulate the membrane permeation of all 20 amino acids from water to the center of a dipalmitoylphosphatidylcholine (DPPC) membrane (consists of 256 lipids) by using both directional and torsion angles for conformational sampling. The overall accuracy for the free energy profiles obtained is supported by significant correlation coefficients (correlation coefficient at 0.5-0.6) between our results and previous experimental or computational studies. The free energy profiles indicated that (1) polar amino acids have larger free energy barriers than nonpolar amino acids; (2) negatively charged amino acids are the most difficult to enter into the membrane; and (3) conformational transitions for many amino acids during membrane crossing is the key for reduced free energy barriers. These results represent the first set of simulated free energy profiles of membrane crossing for all 20 amino acids.

Natural protein sequences are more intrinsically disordered than random sequences.

Most natural protein sequences have resulted from millions or even billions of years of evolution. How they differ from random sequences is not fully understood. Previous computational and experimental studies of random proteins generated from noncoding regions yielded inclusive results due to species-dependent codon biases and GC contents. Here, we approach this problem by investigating 10,000 sequences randomized at the amino acid level. Using well-established predictors for protein intrinsic disorder, we found that natural sequences have more long disordered regions than random sequences, even when random and natural sequences have the same overall composition of amino acid residues. We also showed that random sequences are as structured as natural sequences according to contents and length distributions of predicted secondary structure, although the structures from random sequences may be in a molten globular-like state, according to molecular dynamics simulations. The bias of natural sequences toward more intrinsic disorder suggests that natural sequences are created and evolved to avoid protein aggregation and increase functional diversity.

Effect of pH on the Aggregation of α-syn12 Dimer in Explicit Water by Replica-Exchange Molecular Dynamics Simulation.

The dimeric structure of the N-terminal 12 residues drives the interaction of α-synuclein protein with membranes. Moreover, experimental studies indicated that the aggregation of α-synuclein is faster at low pH than neutral pH. Nevertheless, the effects of different pH on the structural characteristics of the α-syn12 dimer remain poorly understood. We performed 500 ns temperature replica exchange molecular dynamics (T-REMD) simulations of two α-syn12 peptides in explicit solvent. The free energy surfaces contain ten highly populated regions at physiological pH, while there are only three highly populated regions contained at acidic pH. The anti-parallel ß-sheet conformations were found as the lowest free energy state. Additionally, these states are nearly flat with a very small barrier which indicates that these states can easily transit between themselves. The dimer undergoes a disorder to order transition from physiological pH to acidic pH and the α-syn12 dimer at acidic pH involves a faster dimerization process. Further, the Lys6-Asp2 contact may prevent the dimerization.

Molecular mechanism of calcitriol enhances membrane water permeability.

Helicobacter pylori (H. pylori) exhibits a unique membrane lipid composition, including dimyristoyl phosphatidylethanolamine (DMPE) and cholesterol, unlike other Gram-negative bacteria. Calcitriol has antimicrobial activity against H. pylori, but cholesterol enhances antibiotics resistance in H. pylori. This study explored the changes in membrane structure and the molecular mechanisms of cholesterol/calcitriol translocation using well-tempered metadynamics (WT-MetaD) simulations and microsecond conventional molecular dynamics (CMD) simulations. Calcitriol facilitated water transport across the membrane, while cholesterol had the opposite effect. The differing effects might result from the tail 25-hydroxyl group and a wider range of orientations of calcitriol in the DMPE/dimyristoyl phosphatidylglycerol (DMPG) (3:1) membrane. Calcitriol moves across the bilayer center without changing its orientation along the membrane Z-axis, becomes parallel to the membrane surface at the membrane-water interface, and then rotates approximately 90° in this interface. The translocation mechanism of calcitriol is quite different from the flip-flop of cholesterol. Moreover, calcitriol crossed from one layer to another more easily than cholesterol, causing successive perturbations to the hydrophobic core and increasing water permeation. These results improve our understanding of the relationship between cholesterol/calcitriol concentrations and the lipid bilayer structure and the role of lipid composition in water permeation.

Computational design and preparation of water-compatible noncovalent imprinted microspheres.

Herein, 2,4-dichlorophenoxyacetic acid (2,4-D) was used as a model template in a rational design strategy to produce water-compatible noncovalent imprinted microspheres. The proposed approach involved computational modelling for screening functional monomers and a simple method for preparing monodisperse and highly cross-linked microspheres. The fabricated non-imprinted polymer (NIP) and 2,4-d-imprinted polymer (2,4-d-MIP) were characterised, and their adsorption capabilities in an aqueous environment were evaluated. Results reveal that the pseudo-second-order kinetics model was appropriate for representing the adsorption of 2,4-D on NIP and 2,4-d-MIP, with R2 values of 0.97 and 0.99, respectively. The amount of 2,4-D adsorbed on 2,4-d-MIP (97.75 mg g-1) was considerably higher than those of phenoxyacetic acid (35.77 mg g-1), chlorogenic acid (9.72 mg g-1), spiramycin (1.56 mg g-1) and tylosin (1.67 mg g-1). Furthermore, it exhibited strong resistance to protein adsorption in an aqueous medium. These findings confirmed the feasibility of the proposed approach, providing a reference for the development of water-compatible noncovalent imprinted polymers.

The role of semidisorder in temperature adaptation of bacterial FlgM proteins.

Probabilities of disorder for FlgM proteins of 39 species whose optimal growth temperature ranges from 273 K (0°C) to 368 K (95°C) were predicted by a newly developed method called Sequence-based Prediction with Integrated NEural networks for Disorder (SPINE-D). We showed that the temperature-dependent behavior of FlgM proteins could be separated into two subgroups according to their sequence lengths. Only shorter sequences evolved to adapt to high temperatures (>318 K or 45°C). Their ability to adapt to high temperatures was achieved through a transition from a fully disordered state with little secondary structure to a semidisordered state with high predicted helical probability at the N-terminal region. The predicted results are consistent with available experimental data. An analysis of all orthologous protein families in 39 species suggests that such a transition from a fully disordered state to semidisordered and/or ordered states is one of the strategies employed by nature for adaptation to high temperatures.

Turn-directed α-ß conformational transition of α-syn12 peptide at different pH revealed by unbiased molecular dynamics simulations.

The transition from α-helical to ß-hairpin conformations of α-syn12 peptide is characterized here using long timescale, unbiased molecular dynamics (MD) simulations in explicit solvent models at physiological and acidic pH values. Four independent normal MD trajectories, each 2500 ns, are performed at 300 K using the GROMOS 43A1 force field and SPC water model. The most clustered structures at both pH values are ß-hairpin but with different turns and hydrogen bonds. Turn9-6 and four hydrogen bonds (HB9-6, HB6-9, HB11-4 and HB4-11) are formed at physiological pH; turn8-5 and five hydrogen bonds (HB8-5, HB5-8, HB10-3, HB3-10 and HB12-1) are formed at acidic pH. A common folding mechanism is observed: the formation of the turn is always before the formation of the hydrogen bonds, which means the turn is always found to be the major determinant in initiating the transition process. Furthermore, two transition paths are observed at physiological pH. One of the transition paths tends to form the most-clustered turn and improper hydrogen bonds at the beginning, and then form the most-clustered hydrogen bonds. Another transition path tends to form the most-clustered turn, and turn5-2 firstly, followed by the formation of part hydrogen bonds, then turn5-2 is extended and more hydrogen bonds are formed. The transition path at acidic pH is as the same as the first path described at physiological pH.

Effects of C-Terminal Lys-Arg Residue of AapA1 Protein on Toxicity and Structural Mechanism.

Previous experimental investigations have established the indispensability of the C-terminal Lys-Arg residues in the toxic activity of the AapA1 toxin protein. AapA1 is classified as a type I toxin-antitoxin (TA) bacterial toxin, and the precise impact of the C-terminal Lys-Arg residues on its structure and mechanism of action remains elusive. To address this knowledge gap, the present study employed molecular dynamics (MD) and enhanced sampling Well-tempered Two-dimensional Metadynamics (2D-MetaD) simulations to examine the behavior of the C-terminal Lys-Arg residues of truncated AapA1 toxin (AapA1-28) within the inner membrane of Escherichia coli. Specifically, the study focused on the elucidation of possible conformation states of AapA1-28 protein in POPE/POPG (3:1) bilayers and their interactions between the protein and POPE/POPG (3:1) bilayers. The findings of our investigation indicate that the AapA1-28 protein does not adopt a vertical orientation upon membrane insertion; rather, it assumes an angled conformation, with the side chain of Lys-23 directed toward the upper layer of the membrane. This non-transmembrane conformation of AapA1-28 protein impedes its ability to form pores within the membrane, resulting in reduced toxicity towards Escherichia coli. These results suggest that C-Terminal positively charged residues are essential for electrostatic binding to the negatively charged head group of bottom bilayer membrane, which stabilize the transmembrane conformation. These outcomes contribute to our comprehension of the impact of C-terminal charged residues on the structure and functionality of membrane-associated proteins, and provide an improved understanding of how protein sequence influences the antimicrobial effect.

Uptake, distribution, and elimination of selenite in earthworm Eisenia fetida at sublethal concentrations based on toxicokinetic model.

Natural and anthropogenic causes have promoted the rapid increase in environmental selenium (Se) levels, and the complex Se metabolism and dynamic in organisms make it challenging to evaluate the toxicity and ecological risks. In this study, the kinetics of selenite in earthworm Eisenia fetida were investigated based on toxicokinetic (TK) model (uptake-elimination phases: 14-14 days). The results showed the highest sub-tissue Se concentrations in pre-clitellum (PC), post-clitellum (PoC) parts, and total earthworms were 95.71, 70.40, and 79.94 mg/kg, respectively, which indicates the distinctive Se uptake capacities of E. fetida. Se kinetic rates in PCs were faster than that of the total E. fetida for both uptake (Kus = 0.30-0.80 mg/kg/day) and elimination phases (Kee = 0.024-0.056 mg/kg/day). Longer half-life times (LT1/2) were observed in the total earthworms (17.85-47.15 d) than PCs (12.28-29.22 d), while non-significant difference was found for the kinetic Se bioaccumulation factor (BAFk) in PC and total earthworms (12-19), which demonstrates that Se can be efficiently bioaccumulated and eliminated in earthworm PC part. Besides, the significant increase Se concentration in PoC with rapid elimination in PC also illustrates that earthworms can alleviate the Se stress by the transformation strategy of Se from the head to tail tissues. In conclusion, the investigation of Se kinetic accumulation and elimination characteristics in this study is helpful for understanding the metabolism and detoxification processes of Se in earthworms, and also providing a theoretical basis for further Se risk assessment using TK model.