Target Binding Sites Research Articles

Identification and Ranking of Binding Sites from Structural Ensembles: Application to SARS-CoV-2

Target identification and evaluation is a critical step in the drug discovery process. Although time-intensive and complex, the challenge becomes even more acute in the realm of infectious disease, where the rapid emergence of new viruses, the swift mutation of existing targets, and partial effectiveness of approved antivirals can lead to outbreaks of significant public health concern. The COVID-19 pandemic, caused by the SARS-CoV-2 virus, serves as a prime example of this, where despite the allocation of substantial resources, Paxlovid is currently the only effective treatment. In that case, significant effort pre-pandemic had been expended to evaluate the biological target for the closely related SARS-CoV. In this work, we utilize the computational hot spot mapping method, FTMove, to rapidly identify and rank binding sites for a set of nine SARS-CoV-2 drug/potential drug targets. FTMove takes into account protein flexibility by mapping binding site hot spots across an ensemble of structures for a given target. To assess the applicability of the FTMove approach to a wide range of drug targets for viral pathogens, we also carry out a comprehensive review of the known SARS-CoV-2 ligandable sites. The approach is able to identify the vast majority of all known sites and a few additional sites, which may in fact be yet to be discovered as ligandable. Furthermore, a UMAP analysis of the FTMove features for each identified binding site is largely able to separate predicted sites with experimentally known binders from those without known binders. These results demonstrate the utility of FTMove to rapidly identify actionable sites across a range of targets for a given indication. As such, the approach is expected to be particularly useful for assessing target binding sites for any emerging pathogen, as well as for indications in other disease areas, and providing actionable starting points for structure-based drug design efforts.

MiRNASNP-v4: a comprehensive database for miRNA-related SNPs across 17 species.

Single nucleotide polymorphisms (SNPs) within microRNAs (miRNAs) and their target binding sites can influence miRNA biogenesis and target regulation, thereby participating in a variety of diseases and biological processes. Current miRNA-related SNP databases are often species-limited or based on outdated data. Therefore, we updated our miRNASNP database to version 4 by updating data, expanding the species from Homo sapiens to 17 species, and introducing several new features. In miRNASNP-v4, 82580 SNPs in miRNAs and 24836179 SNPs in 3'UTRs of genes across 17 species were identified and their potential effects on miRNA secondary structure and target binding were characterized. In addition, compared to the last release, miRNASNP-v4 includes the following improvements: (i) gene enrichment analysis for gained or lost miRNA target genes; (ii) identification of miRNA-related SNPs associated with drug response and immune infiltration in human cancers; (iii) inclusion of experimentally supported immune-related miRNAsand (iv) online prediction tools for 17 animal species. With the extensive data and user-friendly web interface, miRNASNP-v4 will serve as an invaluable resource for functional studies of SNPs and miRNAs in multiple species. The database is freely accessible at http://gong_lab.hzau.edu.cn/miRNASNP/.

Sequence-Unconstrained DNA Computing: DSN cycling and PER circuitry for dynamic miRNAs analysis and multifunctional logic operations

DNA strand displacement and enzyme-driven catalysis are pivotal in regulating molecular interactions and constructing molecular logic circuits. However, their application in intricate hierarchical cascading networks has been hindered by sequence crosstalk restrictions on the multiple inputs and outputs. In this study, we present a sequence-unconstrained strategy to implement versatile molecular logic circuits, relying on duplex-specific nuclease (DSN)-assisted cycling and primer exchange reaction (PER) amplification circuitry (DSN-PER). Employing linear capture probe (CP) conjugated with magnetic beads (MBs) significantly minimizes crosstalk reactions compared to the previous molecular beacon probe (MBP) for DNA barcoding. Importantly, the sequence design of “barcodes” is fully independent of target binding sites on MBs, allowing for the sensitive detection of a broad range of microRNAs (miRNAs) using the DSN-PER method. Specifically, this platform supports the programming of common logic computations (YES, NOT, OR, INHIBIT, AND, and NOR) and hierarchical circuit operation (OR-AND) in response to a specific pattern of varying miRNAs. These versatile logic circuits offer unique features with flexible sequence design, potentially broadening the applications of dynamic nucleic acid nanotechnologies in multiplexed bio-computation, intelligent diagnostics, and sophisticated DNA nanodevices.

A Modular Biosensor Design for Quantitative Measurement of Free Nedd8.

The objective of our study was to develop a genetically encoded biosensor for quantification of Nedd8, a post-translational modifier that regulates cellular signals through conjugation to other proteins. Perturbations in the balance of free (i.e., unconjugated) and conjugated Nedd8 caused by defects in Nedd8 enzymes or cellular stress are implicated in various diseases. Despite the biological and biomedical importance of Nedd8 dynamics, no method exists for direct quantification of free Nedd8, hindering the study of Nedd8 and activities of its associated enzymes. Genetically encoded biosensors are established as tools to study other dynamic systems, but limitations of current biosensor design methods make them poorly suited for free Nedd8 quantification. We have developed a modular method to design genetically encoded biosensors that employs a target binding domain and two reporter domains positioned on opposite sides of the target binding site. Target quantification is based on competition between target binding and the interaction of the reporter domains. We applied our design strategy to free Nedd8 quantification by developing a selective binder for free Nedd8 and combining it with fluorescent or split nanoluciferase reporters. Our sensors produced quantifiable and specific signals for free Nedd8 and enabled real-time monitoring of deneddylation by DEN1 with a physiological substrate. Our sensor design will be useful for high-throughput screening for deneddylation inhibitors, which have potential in treatment of cancers such as acute lymphoblastic leukemia. The modular design strategy can be extended to develop genetically encoded quantitative biosensors for other proteins of interest.

Prediction of antibiotic resistance mechanisms using a protein language model.

Antibiotic resistance has emerged as a major global health threat, with an increasing number of bacterial infections becoming difficult to treat. Predicting the underlying resistance mechanisms of antibiotic resistance genes (ARGs) is crucial for understanding and combating this problem. However, existing methods struggle to accurately predict resistance mechanisms for ARGs with low similarity to known sequences and lack sufficient interpretability of the prediction models. In this study, we present a novel approach for predicting ARG resistance mechanisms using ProteinBERT, a protein language model (pLM) based on deep learning. Our method outperforms state-of-the-art techniques on diverse ARG datasets, including those with low homology to the training data, highlighting its potential for predicting the resistance mechanisms of unknown ARGs. Attention analysis of the model reveals that it considers biologically relevant features, such as conserved amino acid residues and antibiotic target binding sites, when making predictions. These findings provide valuable insights into the molecular basis of antibiotic resistance and demonstrate the interpretability of pLMs, offering a new perspective on their application in bioinformatics. The source code is available for free at https://github.com/hmdlab/ARG-BERT. The output results of the model are published at https://waseda.box.com/v/ARG-BERT-suppl.

In vivo absorption, in vitro simulated digestion, and fecal fermentation properties of Imperata cylindrica polysaccharides and their effects on gut microbiota

Recently we have investigated polysaccharide from Imperata cylindrica (ICP) for its physicochemical structure and biological activities. However, the digestion characteristics have yet to be understood. This study investigated the digestion and metabolism characteristics of ICP through in vivo fluorescence tracking, in vitro simulated digestion, fecal fermentation experiments, and microbial sequencing. The results showed that ICP significant distribution in the gastrointestinal tract and kidneys. ICP underwent slight degradation during simulated gastric and intestinal digestion. During fecal fermentation, the utilization degree of ICP and the concentration of short-chain fatty acids (SCFAs) increased. ICP promoted the increase of beneficial microbial abundance. To understand the impact of ICP on the integrity and health of intestinal tissues, molecular docking was employed to preliminarily predict the interaction between ICP and key proteins. The results revealed that ICP could recognize and bind to key proteins through high-affinity targeting binding sites.

MoPPIt: De Novo Generation of Motif-Specific Binders with Protein Language Models.

The ability to precisely target specific motifs on disease-related proteins, whether conserved epitopes on viral proteins, intrinsically disordered regions within transcription factors, or breakpoint junctions in fusion oncoproteins, is essential for modulating their function while minimizing off-target effects. Current methods struggle to achieve this specificity without reliable structural information. In this work, we introduce a motif-specific PPI targeting algorithm, moPPIt, for de novo generation of motif-specific peptide binders from the target protein sequence alone. At the core of moPPIt is BindEvaluator, a transformer-based model that interpolates protein language model embeddings of two proteins via a series of multi-headed self-attention blocks, with a key focus on local motif features. Trained on over 510,000 annotated PPIs, BindEvaluator accurately predicts target binding sites given protein-protein sequence pairs with a test AUC > 0.94, improving to AUC > 0.96 when fine-tuned on peptide-protein pairs. By combining BindEvaluator with our PepMLM peptide generator and genetic algorithm-based optimization, moPPIt generates peptides that bind specifically to user-defined residues on target proteins. We demonstrate moPPIt's efficacy in computationally designing binders to specific motifs, first on targets with known binding peptides and then extending to structured and disordered targets with no known binders. In total, moPPIt serves as a powerful tool for developing highly specific peptide therapeutics without relying on target structure or structure-dependent latent spaces.

In Silico Evaluation of Molecular Docking, Molecular Dynamic, and ADME Study of New Nabumetone Schiff Base Derivatives (1,3,4-oxadiazole or 1,3,4-thiadiazole ring) Promising Antiproliferation Action Against Lung Cancer

A total of eight novel Nabumetone Schiff Base Derivatives with 1,3,4-oxadiazole or 1,3,4-thiadiazole rings have been proposed to evaluate their potential effectiveness against the epidermal growth factor receptor (EGFR). Molecular docking was conducted with the crystalline structure of EGFR (code: 4HJO), wherein the eight compounds of Nabumetone Schiff Base Derivatives with 1,3,4-oxadiazole or 1,3,4-thiadiazole ring derivatives docked to determine their binding affinity to the target binding site. Using GOLD software (CCDC) version 5.43, computer predictions were made, and the compounds were designed using ChemDraw version 22.2 (professional version). Subsequently, their selectivity with EGFR was assessed, with erlotinib selected as a control for comparison. In silico ADME studies were conducted, revealing the significant potential for binding, and drug-likeness was assessed using the Swiss ADME website. Additionally, Molecular Dynamic simulations of compound N3 complexes with EGFR were performed using Schrodinger Suite 2023 software for 50 ns, estimating RMSD, RMSF, Ligand-Protein Contacts, and Ligand Torsion Profile results. Result Showing the best binding energy within receptor pocket with a promising activity against EGFR protein receptor. The highest PLP fitness levels were found in compounds N1, N2, and N3 for lung cancer cell protein (89.1, 89.02, and 87.95, respectively, average value), All compounds were found to adhere to Lipinski's rule of five, with high absorption from the gastrointestinal tract (except N4), and none of the proposed compounds were able to pass through the blood-brain barrier. Molecular dynamic result, Mean Protein RMSD 1.8 Å, ligand RMSD 1.6 Å, and RMSF reveals that the protein amino acids interacting with the ligand remain within a distance of less than 1 Å. In conclusion, these findings offer a promising direction for the development of effective treatments for lung cancer

Virtual screening and molecular dynamics simulation of natural compounds as potential inhibitors of serine/threonine kinase 16 for anticancer drug discovery.

Serine/threonine kinase 16 (STK 16) is involved in many facets of cellular regulation; activation of STK 16 plays a crucial role in the migration of cancer cells. Therefore, it is a novel target for the discovery of anticancer agents. Herein, virtual screening and dynamics simulation were used to screen a large library of natural compounds against STK 16 using Schrodinger suit 2021-2 and GROMACS 2021.6. The results predicted five molecules with high binding affinity against the target, with NPC132329 (Arcyriaflavin C) and NPC160898 having higher binding affinity and molecular mechanics generalized born surface area (MM/GBSA), suggesting that it is better than the standard inhibitor. The molecular dymanics (MD) simulation studies showed that the STK 16-NPC132329 complex has the lowest root mean square deviation, and STK 16-NPC160898 was the most stable compared with the standard drug and selective STK 16 inhibitor. The minimal fluctuation was observed in the STK 16-NPC132329 and STK 16-NPC160898 complexes based on the root mean square fluctuation trajectory with NPC132329 and NPC160898 forming 2 and 3 hydrogen bonds respectively with the amino acid residue of the target's binding site. Overall, NPC132329 and NPC160898 are better STK 16 inhibitors than the standard drug and selective inhibitor, which can be further studied to discover novel anticancer drugs.

Gene expression and anticancer evaluation of Kigelia africana (Lam.) Benth. Extracts using MDA-MB-231 and MCF-7 cell lines.

In recent years, a cancer research trend has shifted towards identifying novel therapeutic compounds from natural assets for the management of cancer. In this study, we aimed to assess the cytotoxic activity of Kigelia Africana (KA) extracts on breast cancer (MDA-MB-231 and MCF-7) and noncancerous kidney cells (HEK-293T) to develop an efficient anticancer medication. We used gas chromatography mass spectrometry (GC-MS to analyze the constituents of EKA and HKA extracts meanwhile the crystal violet and the MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide) assays were used to examine the possible cytotoxic effects of plant extracts on our cancer cell lines along with non-cancerous control. The quantitative real-time PCR (RT-PCR) was run on cell samples to evaluate the differential expression of cell proliferative markers of cancer (BCL-2 and TP53). These phytochemicals have been reported to have binding affinity for some other growth factors and receptors as well which was evaluated by the in-silico molecular docking against Bcl2, EGFR, HER2, and TP53. Our Morphological observation showed a significant difference in the cell morphology and proliferation potential which was decreased under the effect of plant extracts treatment as compared to the control samples. The ethanol extract exhibited a marked antiproliferative activity towards MDA-MB-231 and MCF-7 cell lines with IC50 = 20 and 32 μg/mL, respectively. Quantitative RT-PCR gene expression investigation revealed that the IC50 concentration of ethanolic extract regulated the levels of mRNA expression of apoptotic genes. With the target and active binding site amino acids discovered in the molecular docking investigation, TP53/Propanoic acid, 3-(2, 3, 6-trimethyl-1, 4-dioxaspiro [4.4] non-7-yl)-, methyl ester (-7.1 kcal/mol) is the best-docked ligand. The use of this plant in folk remedies justifies its high in vitro anti-cancer capabilities. This work highlights the role of phytochemicals in the inhibition of cancer proliferation. Based on all these findings, it can be concluded that EKA extract has promising anti-proliferative effect on cancerous cells but more study is required in future to further narrow down the active ingredients of total crude extract with specific targets in cancer cells.

Discovery and Synthesis of Hydroxy-l-Proline Blockers of the Neutral Amino Acid Transporters SLC1A4 (ASCT1) and SLC1A5 (ASCT2).

As a conformationally restricted amino acid, hydroxy-l-proline is a versatile scaffold for the synthesis of diverse multi-functionalized pyrrolidines for probing the ligand binding sites of biological targets. With the goal to develop new inhibitors of the widely expressed amino acid transporters SLC1A4 and SLC1A5 (also known as ASCT1 and ASCT2), we synthesized and functionally screened synthetic hydroxy-l-proline derivatives using electrophysiological and radiolabeled uptake methods against amino acid transporters from the SLC1, SLC7, and SLC38 solute carrier families. We have discovered a novel class of alkoxy hydroxy-pyrrolidine carboxylic acids (AHPCs) that act as selective high-affinity inhibitors of the SLC1 family neutral amino acid transporters SLC1A4 and SLC1A5. AHPCs were computationally docked into a homology model and assessed with respect to predicted molecular orientation and functional activity. The series of hydroxyproline analogs identified here represent promising new agents to pharmacologically modulate SLC1A4 and SLC1A5 amino acid exchangers which are implicated in numerous pathophysiological processes such as cancer and neurological diseases.

Circ-METTL15 stimulates the aggressive behaviors of papillary thyroid cancer cells by coordinating the miR-200c-3p/XIAP axis.

Papillary thyroid carcinoma (PTC) is the most common form of thyroid cancer. The critical importance of circular RNA (circRNA) in a range of cancer types has been lately recognized. However, research on the functions of circRNAs in PTC has been limited thus far. Therefore, this research aimed at exploring the function and mechanism of circ-methyltransferase-like 15 (METTL15) in PTC cells. Quantitative measurements of circ-METTL15, miR-200c-3p, and X-linked inhibitor of apoptosis protein (XIAP) in PTC cells were conducted using reverse transcription-quantitative polymerase chain reaction or Western blot analysis. To investigate cell growth, cell counting kit-8 and colony formation tests were employed, apoptosis was analyzed using flow cytometry, and migration and invasion were studied through Transwell assays. The targeted binding sites between miR-200c-3p and circ-METTL15 or XIAP were predicted by starBase and then verified by dual luciferase reporter assay. circ-METTL15 and XIAP were upregulated in the PTC cells, while miR-200c-3p was downregulated. Downregulating circ-METTL15 or upregulating miR-200c-3p resulted in inhibited proliferation, migration, and invasion of PTC cells, while promoting apoptosis. miR-200c-3p was the downstream molecule of circ-METTL15, and XIAP was the direct target of miR-200c-3p. Forcing XIAP expression obstructed circ-METTL15 silencing to inhibit PTC cell activity. By coopting miR-200c-3p/XIAP, Circ-METTL15 stimulates aggressive behavior in PTC cells.

The effect of LINC9137 targeting miR-140-3p-NKAIN3 signal axis on the development of goose testis sertoli cells

Sertoli cells (SC) are a type of important cells in the testes, which can provide transport proteins, regulatory proteins, growth factors, and other cytokines for the spermatogenic process. They participate in the regulation of the maturation and differentiation of spermatogenic cells and play an important supporting role in the migration, proliferation, and differentiation of germ cells at all levels in the testes. Previous studies found differential expression of LINC9137, miR-140-3p, and Sodium/Potassium Transporting ATPase Interacting 3 (NKAIN3) genesin high and low sperm motility goose testicular tissues. This study investigated the effects of the LINC9137-miR-140-3p-NKAIN3 signal axis on the proliferation and apoptosis of goose testicular sertoli cells at the cellular level, respectively. The results showed that through acridine orange staining, oil red O staining, Alkaline phosphatase (AKP) staining, and RT qPCR assay, it was comprehensively identified that the cultured testicular sertoli cells were purified in vitro. Through the dual luciferase activity detection test, it was found that LINC9137 has a targeted binding site with miR-140-3p and NKAIN3. In addition, this study found that overexpression of miR-140-3p significantly inhibited the expression of LINC9137 and NKAIN3 in sertoli cells, and their expression was significantly increased when miR-140-3p was interfered with. By measuring cell proliferation activity and apoptosis related gene expression, it was found that overexpression of LINC9137 decreased cell proliferation activity (P > 0.05), while the expression level of apoptosis factor Bcl2 Associated X Protein (Bax)/B-cell lymphoma-2 (Bcl2) increased (P > 0.05). On the contrary, when interfering with LINC9137, the cell proliferation activity of sertoli cells was significantly increased (P < 0.01), and the expression level of apoptosis factor Bax/Bcl2 was significantly reduced (P < 0.05); The effect of miR-140-3p on the proliferation and apoptosis of sertoli cells is opposite to that of LINC9137. Meanwhile, this study co transfected overexpressed LINC9137 and miR-140-3p plasmids into sertoli cells, and found that the effect of LINC9137 overexpression on supporting cell proliferation was weakened by miR-140-3p. This study elucidates the role and function of the LINC9137 miR-140-3p-NKAIN3 signaling axis in the development of goose testes and spermatogenesis, establishes a regulatory network related to spermatogenesis, and provides a theoretical basis for studying the genetic regulation of goose spermatogenesis.

Abstract 5776: Target identification, selectivity profiling and binding site mapping of small molecule and peptide drugs by LiP-MS

Abstract Target identification in the cellular context is a critical step for both target-based and phenotypic drug discovery. Limited proteolysis coupled with mass spectrometry (LiP-MS) has emerged as a powerful technique for target deconvolution of small molecules or peptides in cell lysate without compound modification or genetic manipulation of cell lines [1,2,3,4]. Utilizing a non-specific protease under well-controlled conditions, LiP-MS exploits drug-induced structural alteration or steric hindrance on protein targets and utilizes quantitative mass spectrometry to probe over 250’000 peptides covering more than 9000 proteins in the proteome. To aid target ID, this workflow incorporates a 7-concentration dose response experiment and a machine-learning framework [1] to compute a LiP-score to rank identified target proteins, as well as predict potential binding site. In this study, we present target deconvolution results on four small molecule compounds and one peptide compound with very distinct pharmacological profile: 1) staurosporine, a broad-specific kinase inhibitor; 2) roniciclib, a failed clinical-stage pan-CDK inhibitor; 3) selumetinib, an allosteric, non-ATP-competitive MEK 1 and 2 inhibitor; 4) NST-628, a newly developed non-degradating molecular glue inhibiting the RAS/MAPK pathway; and 5) Acetyl-calpastatin, a 24 amino-acid polypeptide inhibitor of calpain 1 and 2. Target ID experiment with staurosporine and roniciclib yielded &amp;gt; 150 and 68 kinase targets were identified respectively. For the pan-kinase inhibitor roniciclib, both cell-cycle CDKs (CDK1/cyclin B, CDK2/cyclin E, CDK4 cyclin D) and transcriptional CDK9 were among the targets. For Selumetinib, LiP-score ranking identified MEK1 and MEK2 as the top two targets, and only kinases among a total of 23 targets. Furthermore, mapping the LiP-peptides from this experiment onto MEK1 showed that they are in close proximity to the selumetinib allosteric binding site on co-crystal structure. Last but not least, we assessed the target landscape of NST-628, a novel non-degrading molecular glue and identified MEK1 and MEK2 clearly as the primary targets. This finding is in line with orthogonal data obtained from X-ray crystallography [5]. Collectively, this data demonstrates that LiP-MS can be deployed to effectively identify protein drug targets and predict binding sites in complex cellular millieu independent of the compound’s mechanism of action and without compound modification or labeling. These capabilities make LiP-MS a powerful addition to the target deconvolution toolbox. [1] Piazza and Beaton et al. Nature Comm 2020 [2] Hendricks and Beaton et al. ACS Chem Bio 2021 [3] AACR 2022 [4] AACR 2023 [5] AACR-NCI-EORTC 2023 Citation Format: Fabio Sabino, Martin Soste, Dominique Kamber, Maria Stella Ritorto, Klaus Hoeflich, Michael Hale, Bradley Quade, Xin Huang, Nigel Beaton, Roland Bruderer, Yuehan Feng, Lukas Reiter. Target identification, selectivity profiling and binding site mapping of small molecule and peptide drugs by LiP-MS [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5776.

Calcium mediated static and dynamic allostery in S100A12: Implications for target recognition by S100 proteins.

Structure and functions of S100 proteins are regulated by two distinct calcium binding EF hand motifs. In this work, we used solution-state NMR spectroscopy to investigate the cooperativity between the two calcium binding sites and map the allosteric changes at the target binding site. To parse the contribution of the individual calcium binding events, variants of S100A12 were designed to selectively bind calcium to either the EF-I (N63A) or EF-II (E31A) loop, respectively. Detailed analysis of the backbone chemical shifts for wildtype protein and its mutants indicates that calcium binding to the canonical EF-II loop is the principal trigger for the conformational switch between 'closed' apo to the 'open' Ca2+ -bound conformation of the protein. Elimination of binding in S100-specific EF-I loop has limited impact on the calcium binding affinity of the EF-II loop and the concomitant structural rearrangement. In contrast, deletion of binding in the EF-II loop significantly attenuates calcium affinity in the EF-I loop and the structure adopts a 'closed' apo-like conformation. Analysis of experimental amide nitrogen (15 N) relaxation rates (R1 , R2 , and 15 N-{1 H} NOE) and molecular dynamics (MD) simulations demonstrate that the calcium bound state is relatively floppy with pico-nanosecond motions induced in functionally relevant domains responsible for target recognition such as the hinge domain and the C-terminal residues. Experimental relaxation studies combined with MD simulations show that while calcium binding in the EF-I loop alone does not induce significant motions in the polypeptide chain, EF-I regulates fluctuations in the polypeptide in the presence of bound calcium in the EF-II loop. These results offer novel insights into the dynamic regulation of target recognition by calcium binding and unravels the role of cooperativity between the two calcium binding events in S100A12.

Circ-LDLRAD3/miR-655-3p/MAPK1 axis enhances cell migration and invasion in papillary thyroid carcinoma.

Papillary thyroid carcinoma (PTC) is a prevalent histological subtype of thyroid cancer, whose occurrence and development may be related to circRNA dysregulation. This research proposed to unravel circ-LDLRAD3-related mechanisms in PTC. First, circ-LDLRAD3, miR-655-3p .and MAPK1 levels in PTC were quantitatively measured. Then, plasmid vectors or oligonucleotides that interfere with circ-LDLRAD3, miR-655-3p, or MAPK1 were transfected into PTC cells, followed by the analysis of proliferation, apoptosis, migration, and invasion. Finally, the targeted binding sites between miR-655-3p and circ-LDLRAD3 or MAPK1 were predicted by starBase and experimentally verified. Statistically, PTC samples expressed high circ-LDLRAD3 and MAPK1 and low miR-655-3p. Knocking down circ-LDLRAD3 or enhancing miR-655-3p hindered PTC cell proliferation, migration, and invasion, and forced apoptosis. circ-LDLRAD3 bound to miR-655-3p to affect MAPK1 expression. Elevating MAPK1 rescued circ-LDLRAD3 knockdown-allowed obstruction of PTC cell growth. In conclusion, circ-LDLRAD3 stimulates PTC development by releasing miR-655-3p-targeted MAPK1.

VSpipe-GUI, an Interactive Graphical User Interface for Virtual Screening and Hit Selection.

Virtual screening of large chemical libraries is essential to support computer-aided drug development, providing a rapid and low-cost approach for further experimental validation. However, existing computational packages are often for specialised users or platform limited. Previously, we developed VSpipe, an open-source semi-automated pipeline for structure-based virtual screening. We have now improved and expanded the initial command-line version into an interactive graphical user interface: VSpipe-GUI, a cross-platform open-source Python toolkit functional in various operating systems (e.g., Linux distributions, Windows, and Mac OS X). The new implementation is more user-friendly and accessible, and considerably faster than the previous version when AutoDock Vina is used for docking. Importantly, we have introduced a new compound selection module (i.e., spatial filtering) that allows filtering of docked compounds based on specified features at the target binding site. We have tested the new VSpipe-GUI on the Hepatitis C Virus NS3 (HCV NS3) protease as the target protein. The pocket-based and interaction-based modes of the spatial filtering module showed efficient and specific selection of ligands from the virtual screening that interact with the HCV NS3 catalytic serine 139.

Molecular Investigation and Preliminary Validation of Candidate Genes Associated with Neurological Damage in Heat Stroke.

Heat stroke (HS) is a severe medical condition characterized by a systemic inflammatory response that may precipitate multi-organ dysfunction, with a particular predilection for inducing profound central nervous system impairments. We aim to employ bioinformatics techniques for the retrieval and analysis of genes associated with heat stroke-induced neurological damage. We performed a comprehensive analysis of the GSE64778 dataset from the Sequence Read Archive, resulting in the identification of 1178 significantly differentially expressed genes (DEGs). We retrieved 2914 genes associated with heat stroke from the GeneCards database and 2377 genes associated with heat stroke from the Comparative Toxicogenomics Database (CTD). The intersection of the top 300 DEGs in the GSE64778 dataset intersected with the search results of GeneCards and CTD, yielding 25 final candidates for DEGs associated with heat stroke. Gene Ontology functional annotation results indicated that the target genes were mainly involved in apoptosis, stress response, and negative regulation of cellular processes and function in processes such as protein dimerization and protein binding. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed a predominant enrichment of candidate target genes within the PI3K-AKT signaling pathway. Subsequent protein-protein interaction network analysis highlighted HSP90aa1 as a central gene, indicating its pivotal role by possessing the highest number of edges among the genes enriched in the PI3K-AKT signaling pathway. Quantitative reverse transcription-polymerase chain reaction analysis performed on blood samples from patients validated the expression of Hsp90aa1 in individuals exhibiting early neurological damage in HS, consistent with the findings from the mRNA bioinformatics analysis. Additionally, the bioinformatics analysis of the upstream microRNAs (miRNAs) regulating HSP90aa1 and the target miRNAs associated with candidate long non-coding RNAs (lncRNAs) identified three lncRNAs, eight miRNAs, and one mRNA in the regulatory network. The DIANA Tools database and algorithms were employed for pathway enrichment and correlation analysis, revealing a significant association between LOC102547734 and MIR-206-3p, with the latter being identified as a target binding site Moreover, the analysis unveiled a correlation between MIR-206-3p and HSP90aa1, implicating the latter as a potential target binding site within the regulatory network.

Exosomes Derived from hucMSCs Primed with IFN-γ Suppress the NF-κB Signal Pathway in LPS-Induced ALI by Modulating the miR-199b-5p/AFTPH Axis.

Exosomes (exos) are primarily responsible for the process of mesenchymal stem cells (MSCs) treatment for acute lung injury (ALI), but the mechanism remains unclear, particularly in altered microenvironment. Therefore, this study aimed to investigate the potential mechanism of exos derived from human umbilical cord mesenchymal stem cells (hucMSCs) primed with interferon-gamma (IFN-γ) on ALI and to propose a promising and cell-free strategy. This study extracted exos from hucMSCs supernatant primed and unprimed with IFN-γ marked with IFN-γ-exos and CON-exos, which were identified and traced. IFN-γ-exos administration to ALI models suppressed the NF-κB signaling pathway compared to CON-exos, which were quantified through western blot and immunohistochemical staining. Reverse transcription-quantitative polymerase chain reaction validated miR-199b-5p expression in the IFN-γ-exos and CON-exos treatment groups. Data analysis, a dual-luciferase reporter assay, and cell transfection were conducted to investigate the target binding between miR-199b-5p and Aftiphilin (AFTPH), with AFTPH expression analyzed via cell immunofluorescence and western blot. Co-immunoprecipitation was conducted for the interaction between AFTPH and NF-κB p65. The result revealed that miR-199b-5p was down-regulated in the IFN-γ-exos treatment group, which had a target binding site with AFTPH, and an interaction with NF-κB p65. Consequently, IFN-γ-exos inhibited the NF-κB signaling pathway in ALI in vitro and in vivo through the miR-199b-5p/AFTPH axis. Our results demonstrated new directions of novel and targeted treatment for ALI.

IGF2BP3 regulates the expression of RRM2 and promotes the progression of rheumatoid arthritis via RRM2/Akt/MMP-9 pathway.

Rheumatoid arthritis (RA) is a common inflammatory and autoimmune disease. Ribonucleotide Reductase Regulatory Subunit M2 (RRM2) is a crucial and a rate-limiting enzyme responsible for deoxynucleotide triphosphate(dNTP) production. We have found a high expression level of RRM2 in patients with RA, but the molecular mechanism of its action remains unclear. We analyzed the expression of hub genes in RA using GSE77298 datasets downloaded from Gene Expression Omnibus database. RRM2 and insulin-like growth factor-2 messenger ribonucleic acid (mRNA)-binding protein 3 (IGF2BP3) gene knockdown was achieved by infection with lentiviruses. The expression of RRM2, IGF2BP3, matrix metalloproteinase (MMP)-1, and MMP-9 were detected via western blotting assay. Cell viability was detected via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. MeRIP-qRT-PCR was performed to test the interaction of IGF2BP3 and RRM2 mRNA via m6A modification. Cell proliferation was determined by clone formation assay. Migration and invasion assays were performed using transwell Boyden chamber. RRM2 and IGF2BP3 were highly expressed in clinical specimens and tumor necrosis factor alpha (TNF-α) and interleukin (IL)-1β-stimulated synovial cells. RRM2 and IGF2BP3 knockdown inhibited the proliferation, migration, and invasion of MH7A cells. The inhibitory effects of IGF2BP3 knockdown were effectively reversed by simultaneously overexpressing RRM2 in MH7A cells. By analyzing N6-methyladenosine (m6A)2Target database, five m6A regulatory target binding sites for IGF2BP3 were identified in RRM2 mRNA, suggesting a direct relationship between IGF2BP3 and RRM2 mRNA. Additionally, in RRM2 small hairpin (sh)RNA lentivirus-infected cells, the levels of phosphorylated Akt and MMP-9 were significantly decreased compared with control shRNA lentivirus-infected cells. The present study demonstrated that RRM2 promoted the Akt phosphorylation leading to high expression of MMP-9 to promote the migration and invasive capacities of MH7A cells. Overall, IGF2BP promotes the expression of RRM2, and regulates the migration and invasion of MH7A cells via Akt/MMP-9 pathway to promote RA progression.