Potential Binding Research Articles

Investigating the impact of SOD1 mutations on amyotrophic lateral sclerosis progression and potential drug repurposing through in silico analysis

Superoxide dismutase 1 (SOD1) is a vital enzyme responsible for attenuating oxidative stress through its ability to facilitate the dismutation of the superoxide radical into oxygen and hydrogen peroxide. The progressive loss of motor neurons characterize amyotrophic lateral sclerosis (ALS), a crippling neurodegenerative disease that is caused by mutations in the SOD1 gene. In this study, in silico mutational analysis was performed to study the various mutations, the pathogenicity and stability ΔΔG (binding free energy) of the variant of SOD1. x in the protein variant analysis showed a considerable destabilizing effect with a ΔΔG value of −4.2 kcal/mol, signifying a notable impact on protein stability. Molecular dynamics simulations were conducted on both wild-type and C146R mutant SOD1. RMSD profiles indicated that both maintained consistent structural conformation over time. Additionally, virtual screening of 3067 FDA-approved drugs against the mutant SOD1 identified two potential binders, Tucatinib (51039094) and Regorafenib (11167602), which interacted with Leu106, similar to the control drug, Ebselen. Further simulations assessed the dynamic properties of SOD1 in monomeric and dimeric forms while bound to these compounds. 11167602 maintained stable interaction with the monomeric SOD1 mutant, whereas 51039094 and Ebselen dissociated from the monomeric protein’s binding site. However, all three compounds were stably bound to the dimeric SOD1. MM/GBSA analysis revealed similar negative binding free energies for 11167602 and 51039094, identifying them as strong binders due to their interaction with Cys111. Experimental validation, including in vitro, cell-based, and in vivo assays are essential to confirm these candidates before advancing to clinical trials.

Design of a Water-Soluble CD20 Antigen with Computational Epitope Scaffolding.

The poor solubility of integral membrane proteins in water frequently hinders studies with these proteins, presenting challenges for structure determination and binding screens. For instance, the transmembrane protein CD20, which is an important target for treating B-cell malignancies, is not soluble in water and cannot be easily screened against potential protein binders with techniques like phage display or yeast display. Here, we use de novo protein design to create a water-soluble mimic of the CD20 dimer ("soluble CD20"). Soluble CD20 replaces the central transmembrane helix of CD20 with a water-soluble helix that dimerizes to form a coiled coil that structurally matches the dimer interface of native CD20 and presents the central extracellular loop of CD20 in a binding competent conformation. Unlike peptides derived from CD20, soluble CD20 binds tightly to monoclonal antibodies that recognize quaternary epitopes on the extracellular face of CD20. We demonstrate that soluble CD20 is easy to produce, remains folded above 60°C, and is compatible with binder screening via yeast display. Our results highlight the ability of computational protein design to scaffold conformational epitopes from membrane proteins for use in binding and protein engineering studies.

Identification of Novel Drug Molecules Against NS3-Like Helicase Enzyme of Alongshan Virus.

Alongshan virus (ALSV) is a novel tick-borne virus associated with human diseases. The ALSV is a segmented flavivirus from the family Flaviviridae. It is currently considered as tick-borne arbovirus. There is a high incidence of fever and headache among patients with ALSV infection, and some patients also present with fatigue, coma, depression, nausea, myalgia/arthralgia, and skin rashes. Neither a licensed vaccine nor a drug is currently available to treat ALSV. The development of new, practical, and innovative therapeutic approaches is needed to overcome the emergence of the pathogen. Research on drugs remains a complex, time-consuming, and expensive. The field of drug development has undergone a revolution due to the use ofcomputational approaches, which provide several benefits that speed up and improve the process of developing novel drugs. The goal of this study is to identify novel drug-like molecules against NS3-like helicase enzyme of Alongshan virus. Using molecular docking, the binding potential of the top three ligands to the specified targetwas determined. Molecular dynamic simulations wereused to identifythe stabilities of the best-dockedconformations followed by energy calculations and ADMET analysis. Three potential and promising compounds were identified by performing structure-based virtual screening of non-structural protein 3 (NS3) like helicase of Alongshan virus. The best-docked complexes identified through virtual screening were BDC-23169381, BDB-26412846, BDB-2641954. All these compounds had good pharmacokinetics characteristics and were identified as drug like.

The Correlation Between the Chemical Composition and the Microstructure of the Polysaccharides of Two Varieties of Mexican Red Prickly Pear Fruits.

The red prickly pear fruit (Opuntia ficus-indica L. Mill), endemic from Mexico's semi-desert regions and present in North Africa and Southern Europe, particularly Italy and Spain, is a valuable source of nutrients, bioactive compounds, and polysaccharides. This study used non-destructive techniques like microscopy and Raman and infrared (IR) spectroscopy to characterize polysaccharides extracted from two red prickly pear varieties. The polysaccharides constitute approximately 80% of the peel and 39-18% of the pulp; microscopy provided insights into its microstructural details, while Raman and IR spectroscopy enabled the identification of its specific functional groups. The results revealed distinct microstructural attributes: mucilage displays a microstructure influenced by the ratio of acidic to neutral sugar monomers; pectin exhibits a low degree of methoxylation alongside a characteristic egg-box structure facilitated by calcium ions; hemicellulose presents a delicate, porous layer; and cellulose reveals a layered microstructure supported by thin or robust fibers and calcium crystals. The functional groups identified via Raman and IR spectroscopy provided specific information that could be used to infer chemical interactions influenced by functional groups like hydroxyl, carboxyl, and methyl, suggesting potential binding, stabilization, and water retention properties that enhance their utility as functional ingredients in food products. These findings, obtained using non-destructive methods, enhance the understanding of the compositional and microstructural characteristics of polysaccharides in the red prickly pear, which, in turn, can be used to predict their promising technological applications as functional ingredients.

Multicomponent Synthesis of 2,4,5-Trisubstituted Thiazoles Using a Sustainable Carbonaceous Catalyst and Assessment of Its Herbicidal and Antibacterial Potential.

Herein, a novel, biocatalyzed, and on-water microwave-assisted multicomponent methodology have been developed for the synthesis of trisubstituted thiazoles (4a-4v). The reaction was catalyzed using a sulfonated peanut shell residue-derived carbonaceous catalyst (SPWB). The developed catalyst was characterized using Fourier transform infrared (FTIR), a Brunauer-Emmett-Teller (BET) surface area analyzer, a field emission scanning electron microscope (FE-SEM), energy-dispersive X-ray (EDX), and a particle size analyzer (PSA). The acidic sites have been established using acid-base back-titration methods. The molecular structures of all the synthesized compounds were validated using FT-IR, 1H NMR, 13C NMR, elemental, and HRMS analyses. Herbicidal potential was evaluated by using Raphanus sativus L. as a model. Furthermore, the antibacterial potential of thiazoles was evaluated against Staphylococcus aureus, Bacillus subtilis, Xanthomonas campestris, Escherichia coli, Micrococcus luteus, and Pseudomonas aeruginosa bacterial strains. The compound 4r displayed improved seed growth inhibition in Raphanus sativus L. versus a commercially available herbicide, i.e., pendimethalin. The antibacterial activity was promising against bacterial strains (MIC: 4-64 μg/mL). The compound 4r was the most potent against P. aeruginosa and S. aureus (MIC: 0.0076 μM) versus standard drug streptomycin (MIC: 0.0138 μM). Moreover, in silico studies performed with the most effective compound 4r against P. aeruginosa revealed its potential binding mode within the protein binding pocket. The biological data revealed compound 4r as a potential candidate for the development of potent herbicidal and antibacterial agents. In a nutshell, this study offers peanut shell biowaste to be a sustainable biomass for heterogeneous acid catalyst preparation and its application in the multicomponent synthesis of bioactive thiazoles, accommodating the concept of sustainable development goals and circular bioeconomy.

Modeling PET Data Acquired During Nonsteady Conditions: What If Brain Conditions Change During the Scan?

Researchers use dynamic PET imaging with target-selective tracer molecules to probe molecular processes. Kinetic models have been developed to describe these processes. The models are typically fitted to the measured PET data with the assumption that the brain is in a steady-state condition for the duration of the scan. The end results are quantitative parameters that characterize the molecular processes. The most common kinetic modeling endpoints are estimates of volume of distribution or the binding potential of a tracer. If the steady state is violated during the scanning period, the standard kinetic models may not apply. To address this issue, time-variant kinetic models have been developed for the characterization of dynamic PET data acquired while significant changes (e.g., short-lived neurotransmitter changes) are occurring in brain processes. These models are intended to extract a transient signal from data. This work in the PET field dates back at least to the 1990s. As interest has grown in imaging nonsteady events, development and refinement of time-variant models has accelerated. These new models, which we classify as belonging to the first, second, or third generation according to their innovation, have used the latest progress in mathematics, image processing, artificial intelligence, and statistics to improve the sensitivity and performance of the earliest practical time-variant models to detect and describe nonsteady phenomena. This review provides a detailed overview of the history of time-variant models in PET. It puts key advancements in the field into historical and scientific context. The sum total of the methods is an ongoing attempt to better understand the nature and implications of neurotransmitter fluctuations and other brief neurochemical phenomena.

In silico research on Novel Derivatives of N-(Acetylphenyl)-N-Ferrocenylmethyl-3-nitroaniline as DNA Binding Agents: Using Diverse Computational Methods, including Molecular Docking and ADME/Toxicity Assessment

This study presents an in silico investigation into the potential DNA binding properties of novel derivatives of N-(Acetylphenyl)-N-Ferrocenylmethylnitroaniline using different computational techniques, including molecular docking and ADME/Toxicity assessment, we explored the interaction between these derivatives and DNA. The results reveal promising candidates with strong binding affinities to DNA, substantiated by robust electrostatic interactions. Furthermore, our study sheds light on the ADME and toxicity profiles of these compounds, providing insights into their pharmacological potential. These findings offer valuable insights into the design and development of DNA-binding agents with potential applications in various biomedical fields.

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

Exploring phytochemical inhibitors of protein kinase C alpha for therapeutic targeting of Alzheimer's disease.

Alzheimer's disease (AD) is characterized by neurodegeneration linked to amyloid-β (Aβ) plaques and tau protein tangles. Protein kinase C alpha (PKCα) plays a crucial role in modulating amyloid-β protein precursor (AβPP) processing, potentially mitigating AD progression. Consequently, PKCα stands out as a promising target for AD therapy. Despite the identification of numerous inhibitors, the pursuit of more effective and precisely targeted PKCα inhibitors remains crucial. In this study, we employed an integrated virtual screening approach of molecular docking and molecular dynamics (MD) simulations to identify phytochemical inhibitors of PKCα from the IMPPAT database. Molecular docking screening via InstaDock identified compounds with strong binding affinities to PKCα. Subsequent ADMET and PASS analyses filtered out compounds with favorable pharmacokinetic profiles. Interaction analysis using Discovery Studio Visualizer and PyMOL further elucidated binding conformations of selected compounds with PKCα. Top hits underwent 200 ns MD simulations using GROMACS to validate stability of the interactions. Finally, we propose two phytochemicals, Kammogenin and Imperialine, with appreciable drug-likeliness and binding potential with PKCα. Taken together, the findings suggest Kammogenin and Imperialine as potential PKCα inhibitors, highlighting their therapeutic promise for AD after further validation.

Non‐invasive quantification of [18F]‐PI‐2620 binding to tau deposits in the brain using an image‐derived input function

AbstractBackgroundThis study quantified tau binding in the brain with 18F‐PI2620 PET using a non‐invasive Image‐Derived Input function(IDIF), derived using a new total‐body EXPLORER PET/CT scanner (Spencer et al.,2021). Additionally, we explored how PET scan duration influences the quantification of kinetic parameters across brain regions of interest(ROIs) that are vulnerable in Alzheimer’s Disease.MethodThe study cohort included 15 individuals (10 cognitively unimpaired, 3 mild cognitive impairment, and 2 AD; ages=68‐92 years; all tau negative) from the UC Davis ADRC. Dynamic total‐body 18F‐PI‐2620 PET images were acquired over 90 minutes using the uEXPLORER (resolution=2.344 mm isotropic voxels, framing protocol:30×2s,12×10s,7×60s,16×300s). Brain cropped PET images were motion corrected (Jenkinson et al.,2002), and linearly registered to individual T1‐weighted(T1W) MRIs (Jenkinson & Smith, 2001). Grey matter ROIs, including the medial temporal(MT), posterior cingulate(PC), and lateral parietal(LP) cortices, were obtained parcellating T1W images (Desikan et al.,2006).Dynamic time activity curves for each brain ROI were fitted to a reversible two‐tissue compartmental model(2TCM), accounting for delay, using a subject‐specific IDIF(plasma and metabolite‐corrected) derived from the descending aorta of the same images (Figure 1). ROI‐specific micro and macro kinetic parameters were estimated. Logan graphical analysis (Logan,2000) was also used to estimate total distribution volume(VT).Result2TCM with IDIF demonstrated high‐quality fits of 18F‐PI2620 binding across grey matter ROIs (Figure 1). Perfusion (K1) was observed to be reduced in MT compared to PC and LP (Figure 2A).All kinetic parameters remained relatively stable after the 60‐minute scan window across all ROIs. Notably, K1 showed stability after 30 minutes of scan duration across all ROIs (Figure 2 and 3).A strong correlation was observed between VT estimated using 2TCM and Logan plot analysis, across all ROIs LP(r=1.00, p<0.001), MT(r=0.96, p<0.001), PC(r =1.00, p<0.001).Additionally, significant negative correlation was observed between binding potential and perfusion across all ROIs (r=‐0.40, p=0.007).ConclusionThis study highlights the utility of a non‐invasive descending aorta IDIF derived using a total‐body EXPLORER PET/CT scanner to quantify 18F‐PI‐2620 grey matter kinetics. Preliminary findings suggest that a 60‐minute scan window may be sufficient for reliable quantification of kinetic parameters, while a 30‐minute scan time may suffice for perfusion alone. These findings warrant validation in a cohort involving tau positive individuals.

Classifying covalent protein binders by their targeted binding site.

Covalent protein targeting represents a powerful tool for protein characterization, identification, and activity modulation. The safety of covalent therapeutics was questioned for many years due to the possibility of off-target binding and subsequent potential toxicity. Researchers have recently, however, demonstrated many covalent binders as safe, potent, and long-acting therapeutics. Moreover, they have achieved selective targeting among proteins with high structural similarities, overcome mutation-induced resistance, and obtained higher potency compared to non-covalent binders. In this review, we highlight the different classes of binding sites on a target protein that could be addressed by a covalent binder. Upon folding, proteins generate various concavities available for covalent modifications. Selective targeting to a specific site is driven by differences in the geometry and physicochemical properties of the binding pocket residues as well as the geometry and reactivity of the covalent modifier "warhead". According to the warhead reactivity and the nature of the binding region, covalent binders can alter or lock a targeted protein conformation and inhibit or enhance its activity. We survey these various modification sites using case studies of recently discovered covalent binders, bringing to the fore the versatile application of covalent protein binders with respect to drug discovery approaches.

Structural insights into endogenous ligand selectivity and activation mechanisms of FFAR1 and FFAR2

Free fatty acid receptors (FFARs) play critical roles in metabolic regulation and are potential therapeutic targets for metabolic and inflammatory diseases. A comprehensive understanding of the activation mechanisms and endogenous ligand selectivity of FFARs is essential for drug discovery. Here, we report two cryoelectron microscopy structures of the human FFAR1 bound to the endogenous ligand docosahexaenoic acid (DHA) and Gi1 protein as well as FFAR2 in complex with butyrate and Gi1 at 3.2Å and 3.3Å resolution, respectively. These structures highlight that distinct locations and sizes of the orthosteric ligand binding pockets are crucial determinants of the endogenous ligand selectivity of this receptor subfamily. Additionally, computational analysis reveals a potential allosteric ligand binding pocket in FFAR2. Furthermore, we observe that the upward movement of helix V upon endogenous ligand binding is responsible for receptor activation. These insights will significantly aid in the development of drugs targeting this receptor family.

Dominance of dengue virus serotype-2 in Pakistan (2023-2024): Molecular characterization of the envelope gene and exploration of antiviral targets.

Dengue virus infection, caused by a single positive-stranded RNA virus from the Flaviviridae family, represents a significant public health challenge in tropical and subtropical regions. This virus has four serotypes (DENV-1, 2, 3, and 4), primarily transmitted by Aedes mosquitoes. Despite extensive research, effective antiviral treatments and vaccines remain elusive due to the viral diversity and the complex mechanisms such as antibody-dependent enhancement (ADE). In the current study, NS1-positive serum samples from dengue cases in Pakistan (2023-2024), were analyzed to determine the predominant serotype and characterize the envelope (E) gene for further exploration of antiviral targets. Out of 100 samples, 63 (63%) tested positive for DENV-2, indicating its predominance during this period, while two samples showed mixed infections with DENV-2 and DENV-3. The envelope gene was successfully amplified using nested PCR, validated through gel electrophoresis and sanger sequencing. Phylogenetic analysis revealed high similarity of the DENV-2 isolates to strains from China and India. Computational modeling of the envelope protein structure identified potential antiviral binding sites and further molecular docking studies suggested that specific antiviral compounds like Arbidol and Quercetin can inhibit early steps in viral infection. Additionally, BepiPred-3.0 predicted several B-cell epitopes, which could be useful for vaccine development. These findings enhance our understanding of dengue epidemiology in Pakistan and contribute to the development of targeted antiviral therapies, potentially informing future vaccination strategies and outbreak management.

Repurposing FDA-approved drugs for COVID-19: targeting the main protease through multi-phase in silico approach.

The COVID-19 pandemic has created an urgent need for effective therapeutic agents. The SARS-CoV-2 Main Protease (Mpro) plays a crucial role in viral replication and immune evasion, making it a key target for drug development. While several studies have explored Mpro inhibition, identifying FDA-approved drugs with potential efficacy remains a critical research focus. This study aims to identify FDA-approved drugs that could inhibit SARS-CoV-2 Mpro. Using computational screening, we seek compounds that share structural similarities with a known co-crystallized ligand (PRD_002214) and exhibit strong binding affinity to the enzyme, providing viable candidates for COVID-19 treatment. A systematic in silico approach was used, screening 3009 FDA-approved drugs. The initial screening focused on structural similarity to PRD_002214 (PDB ID: 6LU7), followed by molecular docking studies to predict binding affinity. Promising compounds were further analyzed through molecular dynamics (MD) simulations to evaluate their stability and interactions with Mpro over 100 ns. Of the 3009 FDA-approved drugs screened, 74 were selected for initial evaluation. After refinement, 28 compounds underwent docking analysis, with eight showing strong binding potential to Mpro. Molecular docking assessed the binding affinity and interaction of the selected compounds with Mpro. MD simulations were conducted on the top compound, Atazanavir, to study its dynamic interactions. MM-GBSA, PLIP, and PCAT analyses were used to validate binding affinity and interactions. Eight compounds, including Carfilzomib, Atazanavir, Darunavir, and others, exhibited promising binding affinities. Among them, Atazanavir showed the highest binding strength and was selected for further MD simulation studies. These simulations revealed that Atazanavir forms stable interactions with Mpro, demonstrating favorable binding and dynamic stability. The binding affinity was further confirmed through MM-GBSA, PLIP, and PCAT analyses, supporting Atazanavir's potential as an effective Mpro inhibitor. In silico results suggest that Atazanavir is a promising candidate for targeting SARS-CoV-2 Mpro, with strong binding affinity and dynamic stability. These findings support its potential as a lead compound for further preclinical and clinical testing, though in vitro and in vivo validation are needed to confirm its therapeutic efficacy against COVID-19.

From glia to cytokine signatures across the Alzheimer’s spectrum

AbstractBackgroundEarly neuroinflammation is involved in pathophysiology of Alzheimer’s Disease (AD) and contributes to faster clinical decline. Thus, neuroinflammation has emerged as a promising therapeutic target for dementia. However, a better understanding of the interaction between central and peripheral inflammation in human disease and in vivo biomarkers are required for successful clinical trials. Here we assess inflammatory patterns of serum cytokines and their relationship with central inflammation as quantified by TSPO PET (PK11195) in participants on the aging‐AD spectrum.MethodBlood samples were obtained from 56 participants, including30 controls, 22 patients with MCI and 14 with AD) Serum cytokines were quantified using the MesoScale Discovery V‐Plex‐Human Cytokine panel. We applied a Principal Component Analysis (PCA) across all participants to identify inflammatory profiles, which were compared across groups with ANOVA and post hoc tests. Individual scores of the resulting components were correlated with regional TSPO PET binding potentials, as index of microglial activation, and cognitive impairment (MMSE scores).ResultAnalyses on 30 identified 2 components (explaining 19.4 % and 10.8% of the variance, respectively). Both components were strongly represented by pro‐inflammatory cytokines (Figure 1A). One‐way analyses of variance on the first component could not detected statistically significant differences across the groups (χ2(2)=1.69, p=0.193), while individual scores of Component 2 (χ2(2)=8.46, p<0.001) were statistically higher in patients with AD as compared to patients with MCI and to controls (Figure 1B). Correlation analyses with regional TSPO PET values identified positive widespread associations with individual Component 2 scores in frontal, temporal and parietal regions (r > 0.250, p < 0.05; while associations with Component 1 where limited to the anterior frontal/temporal regions (Figure 1C). Individual scores of Component 2 but not Component 1 were significantly associated with worse cognitive performance (lower MMSE; r = ‐0.315, p = 0.01).ConclusionOur approach identified proinflammatory blood signatures that relate to central inflammation and cognitive impairment across the aging‐AD spectrum. These findings encourage the combination of TSPO imaging and blood‐based markers to clarify the interaction between peripheral and central inflammation in AD, and to identify promising therapeutic targets.

Functional Connectivity and Longitudinal Changes in Amyloid Pathology in Cognitively Healthy Older Adults

AbstractBackgroundAccumulation of amyloid beta in the brain is one of the first events in Alzheimer’s disease (AD) and starts decades before symptoms arise. It has been hypothesized that brain areas with higher levels of neuronal activation (‘hubs’) are more prone to amyloid deposition. In this study, we examined the regional relationship between cortical hubs and longitudinal changes in amyloid pathology in a sample of cognitively healthy older subjects.MethodParticipants were included from the EMIF‐AD PreclinAD cohort, a longitudinal study in cognitively healthy older monozygotic twins. Standard resting state functional MRI pre‐processing was performed with fMRIprep. Individual connectivity matrices were generated as the pairwise timeseries correlation between 100 regions in the Schaeffer atlas, and binarized using a proportional threshold of 0.25. Regional degree, the number of connections of each region, was taken as a continuous measure of functional 'hubness'. Degree was computed within the 100 individual regions, and averaged within 7 resting state networks. Dynamic [18F]Flutemetamol PET scans were used to visually assess amyloid status, and to quantify global and regional binding potential (BPND) at baseline and follow‐up (mean 4.4±0.5 years). We first assessed whether baseline regional degree could predict change in amyloid status using GEE to account for familial clustering. Next, we performed ROI‐wise analyses, assessing the relationship between group‐average regional values of degree and quantitative BPND (baseline and change) in the whole sample and according to amyloid subgroups (negative stable, converter, positive stable).ResultWe included 124 subjects (age 68.3±6.4, female 54%). In baseline amyloid visually negative subjects (n=111), a lower mean degree in the default mode network (β=‐0.26, p=0.008) was associated with higher chance of conversion from negative to positive amyloid status. In the ROI‐wise analyses, a lower degree was associated with higher baseline BPND and larger rate of increase over time (Figure 1). This relationship was most pronounced in the converter group (Figure 2).ConclusionWe found that in cognitively healthy individuals, decrease rather than increase in functional hubness is associated with amyloid load and accumulation. Possibly in this population of older adults, functional hubs are already affected by ageing, or early pathology.

Fluorinated Sulfonamides: Synthesis, Characterization, In Silico, Molecular Docking, ADME, DFT Predictions, and Structure-Activity Relationships, as Well as Assessments of Antimicrobial and Antioxidant Activities.

The design and synthesis of unique two series of fluorinated sulfonamides 3a-f and 5a-g utilizing nucleophilic aromatic substitution reactions of tetrafluorophthalonitrile 1 with various sulfonamides 2 under a variety of different reactions conditions were the key goals of the current research. The chemical composition of the generated products has been investigated via mass spectroscopy, 1HNMR, 13CNMR, infrared, and elemental analyzes. Antimicrobial studies were conducted in vitro to evaluate the activity of all new synthesized compounds against resistant strains. The first series showed high potency in very low concentrations. All compounds were studied against DPPH Radical Scavenging Activity and the other series showed high activity even in low molar ratio. In silico molecular docking was used to investigate the potential binding pathways for different receptors: dihydroprotien synthase protein (ID Code: 1AJ0) as an antibacterial and EGFRWT co-crystallized with erlotinib [PDB ID code 1m17]. Furthermore, synthesized compounds with good ADME predictions to the Lipinski rule of five demonstrated that the recently synthesized compounds had high drug-likeness qualities when the physicochemical parameter for the most powerful novel candidates was determined. Moreover, the DFT/B3LYP method functionalized with a 6-31G (d, p) basis set was employed to calculate quantum parameters, MEP analysis, HUMO, and LUMO.

Unlocking the role of miR-17: Driving G1-S cell cycle transition in oral tongue cancer through integrated bioinformatics and laboratory analyses.

This study aims to identify miRNA-mediated regulation of the cell cycle in oral tongue cancer. Comprehensive computational analysis was performed on the GEO dataset "GSE168227". DIANA Tool-mir path v.3, STRING, Cytoscape 3.6.0, Enrichr, and TargetScan Human 7.2 were utilized to identify and analyze miRNAs and their targets in oral tongue cancer. The identified miRNA and its target genes were further analyzed in oral tongue cancer patients using qPCR and immunohistochemistry (IHC). Computational analysis revealed miR-17 as a differentially expressed miRNA in oral tongue cancer. Database analysis indicated potential binding sites of miR-17 for CDKN1A and CCND1 mRNA at 3'-UTR. In oral tongue cancer samples, miR-17, CDKN1A, and CCND1expression were upregulated compared to controls. IHC demonstrated overexpression of p21 and Cyclin D1 across various tumor grades, with predominant cytoplasmic expression of p21 observed in oral tongue cancer samples. The findings suggest that miR-17 may regulate the G1-S transition of the cell cycle in oral tongue cancer. Further validation and functional studies are warranted to confirm their role as biomarkers.

Automation of Drug Discovery through Cutting-edge In-silico Research in Pharmaceuticals: Challenges and Future Scope.

The rapidity and high-throughput nature of in silico technologies make them advantageous for predicting the properties of a large array of substances. In silico approaches can be used for compounds intended for synthesis at the beginning of drug development when there is either no or very little compound available. In silico approaches can be used for impurities or degradation products. Quantifying drugs and related substances (RS) with pharmaceutical drug analysis (PDA) can also improve drug discovery (DD) by providing additional avenues to pursue. Potential future applications of PDA include combining it with other methods to make insilico predictions about drugs and RS. One possible outcome of this is a determination of the drug potential of nontoxic RS. ADME estimation, QSAR research, molecular docking, bioactivity prediction, and toxicity testing all involve impurity profiling. Before committing to DD, RS with minimal toxicity can be utilised in silico. The efficacy of molecular docking in getting a medication to market is still debated despite its refinement and improvement. Biomedical labs and pharmaceutical companies were hesitant to adopt molecular docking algorithms for drug screening despite their decades of development and improvement. Despite the widespread use of "force fields" to represent the energy exerted within and between molecules, it has been impossible to reliably predict or compute the binding affinities between proteins and potential binding medications.

In Vitro Antileishmanial and Immune Modulation of Trigonelline Against Leishmania major.

The mechanistic study of new pharmaceutical compounds is crucial for evaluating their efficacy, identifying potential side effects, and optimising drug formulations. This study aimed to investigate the mechanism of action of trigonelline on the promastigote and amastigote stages of Leishmania major (MRHO/IR/75/ER). An initial in silico study was conducted to examine the pharmacological effects of trigonelline using molecular docking to evaluate the potential binding affinity of trigonelline with nitrate, a crucial molecule in the macrophage immune response against Leishmania. In this experimental study, the inhibitory mechanism of trigonelline on promastigotes was evaluated by measuring metacaspase expression levels. In the amastigote stage of L. major, the expression levels of inducible nitric oxide synthase (iNOS), interleukin 12 (IL-12), interferon-gamma (IFN-γ), tumour necrosis factor alpha (TNF-α), transforming growth factor-β (TGF-β) and interleukin 10 (IL-10) genes were assessed using Real-time PCR. Trigonelline demonstrated a high-binding affinity to the iNOS molecule in computer modelling. In macrophages treated with various concentrations of trigonelline, glucantime and their combination, the expression levels of metacaspase, IL-12, TNF-α, IFN-γ and iNOS genes significantly increased compared to the control group (p < 0.05), whereas IL-10 and TGF-β gene expression levels significantly decreased (p < 0.05). Trigonelline exerts its antileishmanial effects through its high antioxidant properties, non-cytotoxicity to macrophages, and its ability to enhance apoptosis and cell cycle arrest in promastigotes of L. major.