Amino Acid Binding Research Articles

New insights into the evolution and function of the UMAMIT (USUALLY MULTIPLE ACIDS MOVE IN AND OUT TRANSPORTER) gene family.

UMAMIT proteins have been known as key players in amino acid transport. In Arabidopsis, functions of several UMAMITs have been characterized, but their precise mechanism, evolutionary history and functional divergence remain elusive. In this study, we conducted phylogenetic analysis of the UMAMIT gene family across key species in the evolutionary history of plants, ranging from algae to angiosperms. Our findings indicate that UMAMIT proteins underwent a substantial expansion from algae to angiosperms, accompanied by the stabilization of the EamA (the main domain of UMAMIT) structure. Phylogenetic studies suggest that UMAMITs may have originated from green algae and be divided into four subfamilies. These proteins first diversified in bryophytes and subsequently experienced gene duplication events in seed plants. Subfamily I was potentially associated with amino acid transport in seeds. Regarding subcellular localization, UMAMITs were predominantly localized in the plasma membrane and chloroplasts. However, members from clade 8 in subfamily III exhibited specific localization in the tonoplast. These members may have multiple functions, such as plant disease resistance and root development. Furthermore, our protein structure prediction revealed that the four-helix bundle motif is crucial in controlling the UMAMIT switch for exporting amino acid. We hypothesize that the specific amino acids in the amino acid binding region determine the type of amino acids being transported. Additionally, subfamily II contains genes that are specifically expressed in reproductive organs and roots in angiosperms, suggesting neofunctionalization. Our study highlights the evolutionary complexity of UMAMITs and underscores their crucial role in the adaptation and diversification of seed plants.

Microbial Enzymes for the Biodegradation of Polylactic Acid (PLA): Molecular Docking Simulation and Biodegradation Pathway Proposal

Polylactic acid (PLA), as a biodegradable polymer, finds widespread utility across diverse sectors, encompassing transportation, agriculture, biomedicine, textiles, electronics, and food packaging. Nonetheless, its degradation kinetics exhibit significant environmental sensitivity, necessitating the development of novel biotechnological methodologies to investigate the microbial and enzymatic constituents implicated in PLA biodegradation. In this review, molecular docking simulations are discussed to analyze the enzymatic degradation of PLA using specific enzymes: proteinase K, PLA depolymerase, and lipase. The binding energy, binding affinity, and dimensions of PLA-binding sites within the enzyme cavities have been examined for each enzyme. The binding amino acid residues mainly include serine, histidine, and aspartate for all plastics, while the interactions involve Van der Waals forces, conventional hydrogen bonding, carbon-hydrogen bonding, and Pi-interactions. Based on our synthesis of the literature, a theoretical PLA biodegradation pathway that illustrates the interaction pattern between PLA and the enzymes, as well as the degradation mechanism is proposed. Our review indicates that in natural environments, enzymes work synergistically, utilizing their unique properties to facilitate an efficient sequential catalytic process for PLA degradation. This integrative approach elucidates the mechanistic underpinnings and metabolic cascades governing PLA degradation, enriching insights into enzymatic catalysis and microbial enzyme-mediated plastic biotransformation. Consequently, a comprehensive understanding of these processes is paramount in optimizing biodegradation kinetics and enhancing the environmental performance of biodegradable polymers. This review provides a detailed framework for refining PLA management strategies and advancing sustainable polymer utilization.

Mechanistic Insights of Amino Acid Binding to Hydroxyapatite: Molecular Dynamics Charts Future Directions in Biomaterial Design.

Extensive efforts have been made to improve the understanding of hard tissue regeneration, essential for advancing medical applications like bone graft materials. However, the mechanisms of bone biomineralization, particularly the regulation of hydroxyapatite growth by proteins/peptides, remain debated. Small biomolecules such as amino acids are ideal for studying these mechanisms due to their simplicity and relevance as protein/peptide building blocks. This study investigates the binding affinity of four amino acids including glycine (Gly), proline (Pro), lysine (Lys), and aspartic acid (Asp) to the hydroxyapatite (HAP) (100) surface through molecular dynamics simulations. Our findings reveal that aspartic acid exhibits the most energetically favorable binding affinity, attributed to its additional carboxylate group (-COO-), which facilitates stronger interactions with Ca2+ ions on the HAP surface compared to other amino acids with single carboxylate groups. This highlights the critical role of specific functional groups in modulating binding strength, emphasizing that the presence of multiple binding sites in amino acids enhances binding stability. Interestingly, the study also uncovers the significance of water-mediated interactions, as the compact water layer above the HAP surface acts as a barrier, complicating direct binding and underscoring the need to consider solvation effects in simulations. Glycine, due to its small size, demonstrates a unique ability to penetrate this tightly bound water monolayer, suggesting that molecular size influences binding dynamics. These simulations offer detailed insights into the atomic-level interactions, providing a deeper understanding of binding affinity and stability. These insights are pertinent for designing peptides or proteins with enhanced interactions with biomaterials, particularly in mimicking natural bone-binding processes.

PDNAPred: Interpretable prediction of protein-DNA binding sites based on pre-trained protein language models

Protein-DNA interactions play critical roles in various biological processes and are essential for drug discovery. However, traditional experimental methods are labor-intensive and unable to keep pace with the increasing volume of protein sequences, leading to a substantial number of proteins lacking DNA-binding annotations. Therefore, developing an efficient computational method to identify protein-DNA binding sites is crucial. Unfortunately, most existing computational methods rely on manually selected features or protein structure information, making these methods inapplicable to large-scale prediction tasks. In this study, we introduced PDNAPred, a sequence-based method that combines two pre-trained protein language models with a designed CNN-GRU network to identify DNA-binding sites. Additionally, to tackle the issue of imbalanced dataset samples, we employed focal loss. Our comprehensive experiments demonstrated that PDNAPred significantly improved the accuracy of DNA-binding site prediction, outperforming existing state-of-the-art sequence-based methods. Remarkably, PDNAPred also achieved results comparable to advanced structure-based methods. The designed CNN-GRU network enhances its capability to detect DNA-binding sites accurately. Furthermore, we validated the versatility of PDNAPred by training it on RNA-binding site datasets, showing its potential as a general framework for amino acid binding site prediction. Finally, we conducted model interpretability analysis to elucidate the reasons behind PDNAPred's outstanding performance.

Antimicrobial activity of compounds identified by artificial intelligence discovery engine targeting enzymes involved in Neisseria gonorrhoeae peptidoglycan metabolism

BackgroundNeisseria gonorrhoeae (Ng) causes the sexually transmitted disease gonorrhoea. There are no vaccines and infections are treated principally with antibiotics. However, gonococci rapidly develop resistance to every antibiotic class used and there is a need for developing new antimicrobial treatments. In this study we focused on two gonococcal enzymes as potential antimicrobial targets, namely the serine protease L,D-carboxypeptidase LdcA (NgO1274/NEIS1546) and the lytic transglycosylase LtgD (NgO0626/NEIS1212). To identify compounds that could interact with these enzymes as potential antimicrobials, we used the AtomNet virtual high-throughput screening technology. We then did a computational modelling study to examine the interactions of the most bioactive compounds with their target enzymes. The identified compounds were tested against gonococci to determine minimum inhibitory and bactericidal concentrations (MIC/MBC), specificity, and compound toxicity in vitro.ResultsAtomNet identified 74 compounds that could potentially interact with Ng-LdcA and 84 compounds that could potentially interact with Ng-LtgD. Through MIC and MBC assays, we selected the three best performing compounds for both enzymes. Compound 16 was the most active against Ng-LdcA, with a MIC50 value < 1.56 µM and MBC50/90 values between 0.195 and 0.39 µM. In general, the Ng-LdcA compounds showed higher activity than the compounds directed against Ng-LtgD, of which compound 45 had MIC50 values of 1.56–3.125 µM and MBC50/90 values between 3.125 and 6.25 µM. The compounds were specific for gonococci and did not kill other bacteria. They were also non-toxic for human conjunctival epithelial cells as judged by a resazurin assay. To support our biological data, in-depth computational modelling study detailed the interactions of the compounds with their target enzymes. Protein models were generated in silico and validated, the active binding sites and amino acids involved elucidated, and the interactions of the compounds interacting with the enzymes visualised through molecular docking and Molecular Dynamics Simulations for 50 ns and Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA).ConclusionsWe have identified bioactive compounds that appear to target the N. gonorrhoeae LdcA and LtgD enzymes. By using a reductionist approach involving biological and computational data, we propose that compound Ng-LdcA-16 and Ng-LtgD-45 are promising anti-gonococcal compounds for further development.

Inflammation-oriented montmorillonite adjuvant enhanced oral delivery of anti-TNF-α nanobody against inflammatory bowel disease

Oral delivery of proteins faces challenges due to the harsh conditions of the gastrointestinal (GI) tract, including gastric acid and intestinal enzyme degradation. Permeation enhancers are limited in their ability to deliver proteins with high molecular weight and can potentially cause toxicity by opening tight junctions. To overcome these challenges, we propose the use of montmorillonite (MMT) as an adjuvant that possesses both inflammation-oriented abilities and the ability to regulate gut microbiota. This adjuvant can be used as a universal protein oral delivery technology by fusing with advantageous binding amino acid sequences. We demonstrated that anti-TNF-α nanobody (VII) can be intercalated into the MMT interlayer space. The carboxylate groups (-COOH) of aspartic acid (D) and glutamic acid (E) interact with the MMT surface through electrostatic interactions with sodium ions (Na+). The amino groups (NH2) of asparagine (N) and glutamine (Q) are primarily attracted to the MMT layers through hydrogen bonding with oxygen atoms on the surface. This binding mechanism protects VII from degradation and ensures its release in the intestinal tract, as well as retaining biological activity, leading to significantly enhanced therapeutic effects on colitis. Furthermore, VII@MMT increases the abundance of short-chain fatty acids (SCFAs)-producing strains, including Clostridia, Prevotellaceae, Alloprevotella, Oscillospiraceae, Clostridia_vadinBB60_group, and Ruminococcaceae, therefore enhance the production of SCFAs and butyrate, inducing regulatory T cells (Tregs) production to modulate local and systemic immune homeostasis. Overall, the MMT adjuvant provides a promising universal strategy for protein oral delivery by rational designed protein.

Bioaccumulation and biotransformation of selenium nanoparticles in soybean and natto, and the bioaccessibility of multi-elements and amino acids

Soybean is a food crop with strong selenium (Se) enrichment ability. Selenium nanoparticles (SeNPs) are a low-toxic Se source. To develop strategies in SeNPs biofortification of soybean and natto, the effects of Se enrichment and natto fermentation on selenoamino acids, mineral elements, free amino acids, γ-polyglutamic acid, nattokinase, and bioaccessibility were investigated. Soybean grains were able to convert SeNPs into selenomethionine (SeMet). Selenium enrichment and natto fermentation influenced the enrichment and distribution of multi-elements in soybean, as well as the composition of free and bound amino acids. Selenium enrichment had no significant effect on the bioaccessibility of amino acids. After natto fermentation, the bioaccessibility of SeMet, Fe, Mn, Cu, and Zn in the gastrointestinal tract increased significantly by 10.1–18.9 %. These findings indicate that SeNPs can enhance the Se content of soybean grains, and natto fermentation can further improve the nutritional quality of Se-enriched soybean.

MTORC1 phosphorylates and stabilizes LST2 to negatively regulate EGFR

TORC1 (target of rapamycin complex 1) is a highly conserved protein kinase that plays a central role in regulating cell growth. Given the role of mammalian TORC1 (mTORC1) in metabolism and disease, understanding mTORC1 downstream signaling and feedback loops is important. mTORC1 recognizes some of its substrates via a five amino acid binding sequence called the TOR signaling (TOS) motif. mTORC1 binding to a TOS motif facilitates phosphorylation of a distinct, distal site. Here, we show that LST2, also known as ZFYVE28, contains a TOS motif (amino acids 401 to 405) and is directly phosphorylated by mTORC1 at serine 670 (S670). mTORC1-mediated S670 phosphorylation promotes LST2 monoubiquitination on lysine 87 (K87). Monoubiquitinated LST2 is stable and displays a broad reticular distribution. When mTORC1 is inactive, unphosphorylated LST2 is degraded by the proteasome. The absence of LST2 enhances EGFR (epidermal growth factor receptor) signaling. We propose that mTORC1 negatively feeds back on its upstream receptor EGFR via LST2.

Molecular Docking of Brazilin from Secang Wood Plant (Caesalpinia sappan L.) as an Anti-Breast Cancer

Breast cancer is a disease characterized by abnormal cell growth, which can invade adjacent tissues or metastasize to other organs. Secang (Caesalpinia sappan L.) is a plant that has been used as an alternative medicine for a variety of health conditions, including some types of cancer. This study aims to determine whether the brazilin compound found in secang wood can interact with the target receptors estrogen alpha, 17-β-HSD-1, and NUDT5, potentially serving as an anticancer candidate. Molecular docking simulations were employed to identify the molecular interactions of brazilin against estrogen receptor alpha (ERα) (PDB ID: 3ERT), 17β-HSD-1 (PDB ID: 3HB5), and NUDT5 (PDB ID: 5NQR) using AutoDockTools software. The results showed that the best free-binding energy (ΔG) value obtained for brazilin against the 17-β-HSD-1 receptor was -9.16 kcal/mol, with an inhibition constant of 192.45 nM. The ΔG value of brazilin with estrogen alpha was -6.68 kcal/mol, and the ΔG value for brazilin against NUDT5 was -4.8 kcal/mol. Brazilin has a higher potency compared to innate ligands based on the docking result of estrogen alpha receptor and NUDT5. Some structural similarities and interactions occurred between the amino acids GLY186 and TYR155 in brazilin with the binding of amino acids formed in the innate ligand against the 17-β-HSD-1 receptor, thus showing similar affinity to the 17-β-HSD1 receptor. In silico approaches provided valuable insights into the potential of brazilin as an anti-breast cancer agent.

Development of theaflavins-loaded albumin nanoparticles and in silico analysis of theaflavins: BSA interaction

Theaflavins (TFs), bioactive compounds present in black tea manufactured from Camellia sinensis leaves have potential health benefits. Due to their instability and low bioavailability, we have encapsulated TFs into albumin nanoparticles (Alb-TFs-NP) and characterized them using different techniques. The mean particle size of Alb-TFs-NP was 125.9 nm with a low (0.23) polydispersity index and Zeta potential of -76.8 mV. Scanning electron microscopy (SEM) and Transmission electron microscopy (TEM) analysis revealed a spherical shape of Alb-TFs-NP with a smooth surface. The fluorescence of bovine serum albumin (BSA) and TFs was at 280 nm and 660 nm excitation and 690-700 nm emission respectively. The BSA-TFs complex interacts at distinct amino acid binding sites with good docking energy of TF1 (-10.5 kcal/mol-1), TF2 (-11.1 kcal/mol-1), TF2a (-11.2 kcal/mol-1) and TF3 (-10.4 kcal/mol-1) at the BSA active site. Primarily hydrogen bonding was involved in the BSA-TFs interaction. The study could further research the transport distribution and bioactivities of TFs in the human body.

Functional characterization of sesquiterpene synthase in Mongolian medicine Syringa oblata in heartwood formation

Lilac (Syringa oblata) is a well-known horticultural plant, and its aromatic heartwood is widely utilized in Traditional Mongolian Medicine for treating angina. However, limited research on the dynamic changes and mechanisms of aromatic substance formation during heartwood development hinders the analysis and utilization of its medicinal components. In this study, volatile metabolome analysis revealed that sesquiterpenes are the primary metabolites responsible for the aroma in heartwood, with cadinane and eremophilane types being the most prevalent. Among the identified sesquiterpene synthases, SoSTPS1-5 exhibited significantly increased expression in heartwood formation and was selected for further investigation. Molecular docking simulations predicted multiple amino acid binding sites and confirmed its ability to catalyze the formation of eremophilane, copaene, cadinane, germacrane, and elemane-type sesquiterpenes from FPP (farnesyl pyrophosphate). Co-expression and promoter analysis suggested a transcriptional regulatory network primarily involving WRKY transcription factors. Additionally, aiotic and biotic stress inducers, such as Ag+, Fusarium oxysporum, and especially MeJA, were found to activate the expression of SoSTPS1-5 and promote sesquiterpene accumulation. This study provides insights into the basis of medicinal substance formation and the potential mechanisms of sesquiterpene accumulation in lilac heartwood, laying a foundation for future research on the biosynthesis and utilization of its medicinal components.

GIHP: Graph convolutional neural network based interpretable pan-specific HLA-peptide binding affinity prediction.

Accurately predicting the binding affinities between Human Leukocyte Antigen (HLA) molecules and peptides is a crucial step in understanding the adaptive immune response. This knowledge can have important implications for the development of effective vaccines and the design of targeted immunotherapies. Existing sequence-based methods are insufficient to capture the structure information. Besides, the current methods lack model interpretability, which hinder revealing the key binding amino acids between the two molecules. To address these limitations, we proposed an interpretable graph convolutional neural network (GCNN) based prediction method named GIHP. Considering the size differences between HLA and short peptides, GIHP represent HLA structure as amino acid-level graph while represent peptide SMILE string as atom-level graph. For interpretation, we design a novel visual explanation method, gradient weighted activation mapping (Grad-WAM), for identifying key binding residues. GIHP achieved better prediction accuracy than state-of-the-art methods across various datasets. According to current research findings, key HLA-peptide binding residues mutations directly impact immunotherapy efficacy. Therefore, we verified those highlighted key residues to see whether they can significantly distinguish immunotherapy patient groups. We have verified that the identified functional residues can successfully separate patient survival groups across breast, bladder, and pan-cancer datasets. Results demonstrate that GIHP improves the accuracy and interpretation capabilities of HLA-peptide prediction, and the findings of this study can be used to guide personalized cancer immunotherapy treatment. Codes and datasets are publicly accessible at: https://github.com/sdustSu/GIHP.

Glutathione-Based Photoaffinity Probe Identifies Caffeine as a Positive Allosteric Modulator of the Calcium-Sensing Receptor.

The calcium-sensing receptor (CaSR), abundantly expressed in the parathyroid gland and kidney, plays a central role in calcium homeostasis. In addition, CaSR exerts multimodal roles, including inflammation, muscle contraction, and bone remodeling, in other organs and tissues. The diverse functions of CaSR are mediated by many endogenous and exogenous ligands, including calcium, amino acids, glutathione, cinacalcet, and etelcalcetide, that have distinct binding sites in CaSR. However, strategies to evaluate ligand interactions with CaSR remain limited. Here, we developed a glutathione-based photoaffinity probe, DAZ-G, that analyzes ligand binding to CaSR. We showed that DAZ-G binds to the amino acid binding site in CaSR and acts as a positive allosteric modulator of CaSR. Oxidized and reduced glutathione and phenylalanine effectively compete with DAZ-G conjugation to CaSR, while calcium, cinacalcet, and etelcalcetide have cooperative effects. An unexpected finding was that caffeine effectively competes with DAZ-G's conjugation to CaSR and acts as a positive allosteric modulator of CaSR. The effective concentration of caffeine for CaSR activation (<10 μM) is easily attainable in plasma by ordinary caffeine consumption. Our report demonstrates the utility of a new chemical probe for CaSR and discovers a new protein target of caffeine, suggesting that caffeine consumption can modulate the diverse functions of CaSR.

Proteomic and Phosphoproteomic analysis of thyroid papillary carcinoma: Identification of potential biomarkers for metastasis

Thyroid cancer has emerged as the most rapidly proliferating solid neoplasm. In this study, we included a cohort of patients who underwent sonographic assessment and surgical intervention at the Sir Run Run Shaw Hospital, associated with the School of Medicine at Zhejiang University, spanning from January 2019 to June 2020. Stratification of cases was based on a combination of preoperative ultrasonographic evaluations and postoperative histopathological diagnoses, resulting in three distinct groups: high-risk papillary thyroid carcinoma (PTC) labeled as C1, low-risk PTC designated as C2, and a control group (N) composed of benign thyroid tissue adjacent to the carcinoma. Proteomic and phosphoproteomic analyses were conducted on PTC specimens. The comparative assessment revealed that proteins up-regulated in the C1/N and C2/N groups were predominantly involved in functions such as amino acid binding, binding of phosphorylated compounds, and serine protease activity. Notably, proteins like NADH dehydrogenase, ATP synthase, oxidoreductases, and iron ion channels were significantly elevated in the C1 versus C2 comparative group. Through meticulous analysis of differential expression multiples, statistical significance, and involvement in metabolic pathways, this study identified eight potential biomarkers pertinent to PTC metastasis diagnostics, encompassing phosphorylated myosin 10, phosphorylated proline-directed protein kinase, leucine tRNA synthetase, 2-oxo-isovalerate dehydrogenase, succinic semialdehyde dehydrogenase, ADP/ATPtranslocase, pyruvate carboxylase, and fibrinogen. Therapeutic assays employing metformin, an AMP-activated protein kinase (AMPK) activator, alongside the phosphorylation-specific inhibitor ML-7 targeting Myosin10, demonstrated attenuated cellular proliferation, migration, and invasion capabilities in thyroid cancer cells, accompanied by a reduction in amino acid pools. Cellular colocalization and interaction studies elucidated that AMPK activation imposes an inhibitory influence on Myosin10 levels. The findings of this research corroborate the utility of proteomic and phosphoproteomic platforms in the identification of metastatic markers for PTC and suggest that modulation of AMPK activity, coupled with the inhibition of Myosin10 phosphorylation, may forge novel therapeutic avenues in the management of thyroid carcinoma. SignificanceThe significance of our research lies in its potential to transform the current understanding and management of thyroid papillary carcinoma (PTC), particularly in its metastatic form. By integrating both proteomic and phosphoproteomic analyses, our study not only sheds light on the molecular alterations associated with PTC but also identifies eight novel biomarkers that could serve as indicators of metastatic potential.

A theoretical approach on ADMET properties of an azo-ester based fluorophore (AEF), and it's energetics, binding stability and molecular interactions with select globular proteins

Molecular docking (Mol.Doc) approach of an azo-ester based fluorophore (AEF) with widely studied proteins like Human serum Albumin (HSA), Bovine serum Albumin (BSA), Beta lactoglobin (βLG) and Ovalbumin (OVA) were carried out. The binding affinity and strength of AEF-HSA complex is due to hydrogen-bonding (h-bonding) and hydrophobic interactions (predominantly attributed to pi-alkyl). AEF and HSA acts as h-bonding acceptor as well as donor. The energetically favored conformers of AEF-HSA complex are governed and stabilized by polar as well as non-polar amino acids. On the contrary, the pattern observed in all the conformers of AEF-BSA, AEF- βLG and AEF-OVA are energetically least favored (+ve ∆G) compared to that of HSA. The least binding affinity of AEF is towards OVA (Binding energy (BE) +581.15 Kcalmol−1 followed by βLG (+55.11) and BSA (+12.12) . Though BSA and HSA are structurally similar to each other, they vary in the binding stability with AEF. This is attributed to several unfavorable interactions that destabilize AEF-BSA complex which was not resulted in the complex existing between AEF-HSA. The energetically least stable complexes (AEF-BSA, AEF-βLG and AEF-OVA) are predominantly governed by hydrophobic interactions. However, several h-bonding interactions along with pi-sigma/pi-pi/pi-alkyl interactions result in destabilization of the above complexes. Interestingly, AEF-HSA complex stability is attributed to fewer number of hydrophobic interactions along with h-bonding interactions. The h-bonding interaction governs the stability of the complex which is the driving force. Docking studies illustrates that the binding of amino acids (AAs) in various subdomains play a significant role on the binding nature. The stability of AEF-HSA over other protein complexes in terms of BE is emphasized in the study. The energetically stable sites and sub-domains of AEF with HSA and BSA establish the site selective and site-specific nature of AEF with proteins. In silico studies provide an excellent and easier approach in establishing the molecular interactions existing between AEF with globular proteins. ADMET parameters of the guest molecule calculated exemplifies that AEF compound is less toxic and possesses high oral bioavailability. Based on the binding efficiency of AEF with albumins, the ADMET properties and drug likeliness approach of AEF provides an information on the application towards proteins in the concept of medicine and chemistry.

Neurochemical Anatomy of Cushing's Syndrome.

The neurochemical anatomy underlying Cushing's syndrome is examined for regional brain metabolism as well as neurotransmitter levels and receptor binding of biogenic amines and amino acids. Preliminary studies generally indicate that glucose uptake, blood flow, and activation on fMRI scans decreased in neocortical areas and increased in subcortical areas of patients with Cushing's syndrome or disease. Glucocorticoid-mediated increases in hippocampal metabolism occurred despite in vitro evidence of glucocorticoid-induced decreases in glucose uptake or consumption, indicating that in vivo increases are the result of indirect, compensatory, or preliminary responses. In animal studies, glucocorticoid administration decreased 5HT levels and 5HT1A receptor binding in several brain regions while adrenalectomy increased such binding. Region-specific effects were also obtained in regard to the dopaminergic system, with predominant actions of glucocorticoid-induced potentiation of reuptake blockers and releasing agents. More in-depth neuroanatomical analyses are warranted of these and amino acid-related neurotransmission.

Correlative Super-resolution Optical and Electron Microscopic Imaging of Intracellular Ribosomal RNA by a Terpyridine Iridium(III) Complex.

Ribosomal RNA (rRNA) plays a vital role in binding amino acids together, which dictates the primary structure of a protein. Visualization of its intracellular distribution and dynamics during protein synthesis enables a better understanding of the correlated biological essence. However, appropriate tools targeting live cell rRNA that are capable of multimodal imaging at the nanoscale are still lacking. Here, we rationally designed a series of terpyridine ammonium iridium(III) complexes, one of which is capable of selectively labeling rRNA in living cells. Its metal core and photostable nature allow further super-resolution STED imaging of rRNA found on the rough endoplasmic reticulum at a ∼40 nm resolution that is well correlated under correlative light and electron microscopy (CLEM). Interestingly, the Ir(III) complex demonstrated rRNA dynamics in living cells while boosting protein synthesis at the nanoscale. Our work offers a versatile tool to visualize rRNA synchronously under optical and electron microscopy, which provides a better understanding of rRNA evolution in living systems.

Framework for exploring the sensory repertoire of the human gut microbiota.

Bacteria sense changes in their environment and transduce signals to adjust their cellular functions accordingly. For this purpose, bacteria employ various sensors feeding into multiple signal transduction pathways. Signal recognition by bacterial sensors is studied mainly in a few model organisms, but advances in genome sequencing and analysis offer new ways of exploring the sensory repertoire of many understudied organisms. The human gut is a natural target of this line of study: it is a nutrient-rich and dynamic environment and is home to thousands of bacterial species whose activities impact human health. Many gut commensals are also poorly studied compared to model organisms and are mainly known through their genome sequences. To begin exploring the signals human gut commensals sense and respond to, we have designed a framework that enables the identification of sensory domains, prediction of signals that they recognize, and experimental verification of these predictions. We validate this framework's functionality by systematically identifying amino acid sensors in selected bacterial genomes and metagenomes, characterizing their amino acid binding properties, and demonstrating their signal transduction potential.IMPORTANCESignal transduction is a central process governing how bacteria sense and respond to their environment. The human gut is a complex environment with many living organisms and fluctuating streams of nutrients. One gut inhabitant, Escherichia coli, is a model organism for studying signal transduction. However, E. coli is not representative of most gut microbes, and signaling pathways in the thousands of other organisms comprising the human gut microbiota remain poorly understood. This work provides a foundation for how to explore signals recognized by these organisms.

BSA Binding and Aggregate Formation of a Synthetic Amino Acid with Potential for Promoting Fibroblast Proliferation: An In Silico, CD Spectroscopic, DLS, and Cellular Study.

This study presents the chemical synthesis, purification, and characterization of a novel non-natural synthetic amino acid. The compound was synthesized in solution, purified, and characterized using NMR spectroscopy, polarimetry, and melting point determination. Dynamic Light Scattering (DLS) analysis demonstrated its ability to form aggregates with an average size of 391 nm, extending to the low micrometric size range. Furthermore, cellular biological assays revealed its ability to enhance fibroblast cell growth, highlighting its potential for tissue regenerative applications. Circular dichroism (CD) spectroscopy showed the ability of the synthetic amino acid to bind serum albumins (using bovine serum albumin (BSA) as a model), and CD deconvolution provided insights into the changes in the secondary structures of BSA upon interaction with the amino acid ligand. Additionally, molecular docking using HDOCK software elucidated the most likely binding mode of the ligand inside the BSA structure. We also performed in silico oligomerization of the synthetic compound in order to obtain a model of aggregate to investigate computationally. In more detail, the dimer formation achieved by molecular self-docking showed two distinct poses, corresponding to the lowest and comparable energies, with one pose exhibiting a quasi-coplanar arrangement characterized by a close alignment of two aromatic rings from the synthetic amino acids within the dimer, suggesting the presence of π-π stacking interactions. In contrast, the second pose displayed a non-coplanar configuration, with the aromatic rings oriented in a staggered arrangement, indicating distinct modes of interaction. Both poses were further utilized in the self-docking procedure. Notably, iterative molecular docking of amino acid structures resulted in the formation of higher-order aggregates, with a model of a 512-mer aggregate obtained through self-docking procedures. This model of aggregate presented a cavity capable of hosting therapeutic cargoes and biomolecules, rendering it a potential scaffold for cell adhesion and growth in tissue regenerative applications. Overall, our findings highlight the potential of this synthetic amino acid for tissue regenerative therapeutics and provide valuable insights into its molecular interactions and aggregation behavior.

Phospholipid Membrane Interactions of Model Ac-WL-X-LL-OH Peptides Investigated by Solid-State Nuclear Magnetic Resonance.

The role of aromatic amino acids in peripheral protein membrane binding has been reported to involve cation-π interactions with choline lipids. In this study, we have investigated the interactions of the model pentapeptide Ac-WL-X-LL-OH (where X = L, Y, F, or W) with the phospholipid membrane using solid-state NMR. The effect of guest residue X on the peptide-lipid interactome was complementary to the seminal report on the interfacial hydrophobicity scale by Wimley and White. We found that the phospholipids retained a lamellar phase in the presence of each of the peptides with an aromatic X residue, whereas the Leu peptide perturbed the bilayer to an extent where an additional isotropic phase was observed. The solid-state NMR 13C and 31P data provide additional information on the influence of these short peptides on the membrane that has not been previously reported. The magnitude of membrane perturbation was in the order of guest residue X = L > Y~F > W, which is consistent with the relative amino acid interfacial affinity reported by Wimley and White. Further work is, however, required to uncover the behavior of the peptide and localization in the membrane domain due to ambiguity of the 13C NMR data. We have launched efforts in this regard for the objective of better understanding the role of aromatic amino acids in peripheral membrane protein binding.