Comparing cefotaxime and ceftriaxone in combating meningitis through nose-to-brain delivery using bio/chemoinformatics tools

Enhancing Effector Jurkat Cell Activity and Increasing Cytotoxicity against A549 Cells Using Nivolumab as an Anti-PD-1 Agent Loaded on Gelatin Nanoparticles

The current research investigated the use of gelatin nanoparticles (GNPs) for enhancing the cytotoxic effects of nivolumab, an immune checkpoint inhibitor. The unique feature of GNPs is their biocompatibility and functionalization potential, improving the delivery and the efficacy of immunotherapeutic drugs with fewer side effects compared to traditional treatments. This exploration of GNPs represents an innovative direction in the advancement of nanomedicine in oncology. Nivolumab-loaded GNPs were prepared and characterized. The optimum formulation had a particle size of 191.9 ± 0.67 nm, a polydispersity index of 0.027 ± 0.02, and drug entrapment of 54.67 ± 3.51%. A co-culture experiment involving A549 target cells and effector Jurkat cells treated with free nivolumab solution, and nivolumab-loaded GNPs, demonstrated that the latter had significant improvements in inhibition rate by scoring 87.88 ± 2.47% for drug-loaded GNPs against 60.53 ± 3.96% for the free nivolumab solution. The nivolumab-loaded GNPs had a lower IC50 value, of 0.41 ± 0.01 µM, compared to free nivolumab solution (1.22 ± 0.37 µM) at 72 h. The results indicate that administering nivolumab-loaded GNPs augmented the cytotoxicity against A549 cells by enhancing effector Jurkat cell activity compared to nivolumab solution treatment.

Essential considerations towards development of effective nasal antibiotic formulation: features, strategies, and future directions

INTRODUCTION

Intranasal antibiotic products are gaining popularity as a promising method of administering antibiotics, which provide numerous benefits, e.g. enhancing drug bioavailability, reducing adverse effects, and potentially minimizing resistance threats. However, some issues related to the antibiotic substances and nasal route challenges must be addressed to prepare effective formulations.

AREAS COVERED

This review focuses on the valuable points of nasal delivery as an alternative route for administering antibiotics, coupled with the challenges in the nasal cavity that might affect the formulations. Moreover, this review also highlights the application of nasal delivery to introduce antibiotics for local therapy, brain targeting, and systemic effects that have been conducted. In addition, this viewpoint provides strategies to maintain antibiotic stability and several crucial aspects to be considered for enabling effective nasal formulation.

EXPERT OPINION

In-depth knowledge and understanding regarding various key considerations with respect to the antibiotic substances and nasal route delivery requirement in preparing effective nasal antibiotic formulation would greatly improve the development of nasally administered antibiotic products, enabling better therapeutic outcomes of antibiotic treatment and establishing appropriate use of antibiotics, which in turn might reduce the chance of antibiotic resistance and enhance patient comfort.

Advances in the Applications of Bioinformatics and Chemoinformatics

Chemoinformatics involves integrating the principles of physical chemistry with computer-based and information science methodologies, commonly referred to as "in silico techniques", in order to address a wide range of descriptive and prescriptive chemistry issues, including applications to biology, drug discovery, and related molecular areas. On the other hand, the incorporation of machine learning has been considered of high importance in the field of drug design, enabling the extraction of chemical data from enormous compound databases to develop drugs endowed with significant biological features. The present review discusses the field of cheminformatics and proposes the use of virtual chemical libraries in virtual screening methods to increase the probability of discovering novel hit chemicals. The virtual libraries address the need to increase the quality of the compounds as well as discover promising ones. On the other hand, various applications of bioinformatics in disease classification, diagnosis, and identification of multidrug-resistant organisms were discussed. The use of ensemble models and brute-force feature selection methodology has resulted in high accuracy rates for heart disease and COVID-19 diagnosis, along with the role of special formulations for targeting meningitis and Alzheimer's disease. Additionally, the correlation between genomic variations and disease states such as obesity and chronic progressive external ophthalmoplegia, the investigation of the antibacterial activity of pyrazole and benzimidazole-based compounds against resistant microorganisms, and its applications in chemoinformatics for the prediction of drug properties and toxicity-all the previously mentioned-were presented in the current review.

In silico prediction of siRNA ionizable-lipid nanoparticles In vivo efficacy: Machine learning modeling based on formulation and molecular descriptors

In silico prediction of the in vivo efficacy of siRNA ionizable-lipid nanoparticles is desirable as it can save time and resources dedicated to wet-lab experimentation. This study aims to computationally predict siRNA nanoparticles in vivo efficacy. A data set containing 120 entries was prepared by combining molecular descriptors of the ionizable lipids together with two nanoparticles formulation characteristics. Input descriptor combinations were selected by an evolutionary algorithm. Artificial neural networks, support vector machines and partial least squares regression were used for QSAR modeling. Depending on how the data set is split, two training sets and two external validation sets were prepared. Training and validation sets contained 90 and 30 entries respectively. The results showed the successful predictions of validation set log (siRNA dose) with R_val ²= 0.86-0.89 and 0.75-80 for validation sets one and two, respectively. Artificial neural networks resulted in the best R_val ² for both validation sets. For predictions that have high bias, improvement of R_val ² from 0.47 to 0.96 was achieved by selecting the training set lipids lying within the applicability domain. In conclusion, in vivo performance of siRNA nanoparticles was successfully predicted by combining cheminformatics with machine learning techniques.

Meta-Analysis: A Convenient Tool for the Choice of Nose-to-Brain Nanocarriers

OBJECTIVES

The intranasal route represents a high promising route of administration aiming for brain delivery. Yet, it represents one of the most difficult and complicated routes. Accordingly, scientists are in a continuous search for novel drug delivery vehicles such as the lipid and polymeric nanoparticles that are apt to enhance the bioavailability of the administered drugs to reach the brain. In this study, a certain number of publications were selected from different databases and literature. Meta-analysis studies using two different algorithms (DerSimonian-Laird and inverse variance) followed aiming to explore the published studies and confirm by evidence the superiority of nanocarriers in enhancing the brain bioavailability of various drugs. Furthermore, the quantitative comparison of lipid versus polymeric nanosystems was performed.

METHODS

The area under the curve (AUC) as an important pharmacokinetic parameter extracted from in vivo animal studies was designated as the "effect" in the performed meta-analysis after normalization. Forest plots were generated.

KEY FINDINGS AND CONCLUSIONS

The meta-analysis confirmed the augmentation of the AUC after the comparison with traditional preparations such as solutions and suspensions. Most importantly, lipid nanoparticles were proven to be significantly superior to the polymeric counterparts.

In Silico Screening of Synthetic and Natural Compounds to Inhibit the Binding Capacity of Heavy Metal Compounds against EGFR Protein of Lung Cancer

Inorganic pollutant, specifically heavy metals’ contamination, is a significant matter of concern and is one of the key contributors in various health disorders including cancer. However, the interaction of heavy metals (HMs) with lung cancer has rarely been explored yet. Therefore, the present study was intended with the aim to identify the interactions of HMs with the target protein “epidermal growth factor receptor (EGFR)” of lung cancer and explore potential drug candidates, which could inhibit the active site of EGFR against HM exposure. The molecular operating environment (MOE) tool was used to study the interactions of HMs with EGFR protein. The drug-drug interaction (DDI) network approach was used to identify the potential drug candidates, which were further confirmed and compared with the commercial medicines/control group. Various compounds of twenty-three HMs were docked with EGFR protein. Out of which tinidazole, thallium bromodimethyl, and silver acetate (Sn, Ti, and Ag compounds) showed strong interactions with EGFR based on lowest-scoring values (-20.42, -7.86, and -7.74 kcal/mol, respectively). Among 1280 collected drug candidates, three synthetic compounds viz., ZINC00602803, ZINC00602685, and ZINC06718468 and three natural compounds (berberine chloride, transresveratrol, and ellagic acid) depicted strong binding capacity with EGFR. Specifically, the scoring value of ZINC00602803 (-30.99 kcal/mol) was even lowest than standard lung cancer drugs (afatinib, erlotinib, and gefitinib). Our findings revealed that both natural and synthetic compounds having strong associations with EGFR protein could be potential candidates to inhibit the interaction between HMs and lung cancer protein and can also be used as an alternative for the prevention and treatment of lung cancer. However, in vitro and in vivo studies should be conducted to validate the aforementioned natural and synthetic compounds.

Evaluation of Recent Intranasal Drug Delivery Systems to the Central Nervous System

Neurological diseases continue to increase in prevalence worldwide. Combined with the lack of modifiable risk factors or strongly efficacious therapies, these disorders pose a significant and growing burden on healthcare systems and societies. The development of neuroprotective or curative therapies is limited by a variety of factors, but none more than the highly selective blood-brain barrier. Intranasal administration can bypass this barrier completely and allow direct access to brain tissues, enabling a large number of potential new therapies ranging from bioactive peptides to stem cells. Current research indicates that merely administering simple solutions is inefficient and may limit therapeutic success. While many therapies can be delivered to some degree without carrier molecules or significant modification, a growing body of research has indicated several methods of improving the safety and efficacy of this administration route, such as nasal permeability enhancers, gelling agents, or nanocarrier formulations. This review shall discuss promising delivery systems and their role in expanding the clinical efficacy of this novel administration route. Optimization of intranasal administration will be crucial as novel therapies continue to be studied in clinical trials and approved to meet the growing demand for the treatment of patients with neurological diseases.

Do Polymeric Nanoparticles Really Enhance the Bioavailability of Oral Drugs? A Quantitative Answer Using Meta-Analysis

The oral route remains one of the most popular and important routes of administration for drugs—one that warrants the development of advanced drug delivery systems, such as polymeric nanoparticles capable of enhancing the absorption and bioavailability of the used drugs. In this work, a systematic review of published works on several databases, followed by a meta-analysis, were utilized in order to navigate the published studies and access literature-based evidence about the capability of polymeric nanoparticulate systems to augment the absorption and bioavailability of orally administered drugs. The pharmacokinetic parameter of the area under the curve (AUC) was utilized as the “effect” of this meta-analytical study. The meta-analysis demonstrated a significant increase in AUC compared to conventional formulations. Furthermore, comparing the synthetic polymeric nanoparticles, versus their naturally-based administered counterparts, as subgroups of the meta-analysis, revealed no significant differences.

The Role of Vitamin C in Amelioration of Hepatorenal Toxicity of Cefotaxime in Adult Albino Rats (Histological Study)

AIM: Antibiotics have a great risk property, for this reason, the present work aimed to study the toxic effect of cefotaxime on histological examination of liver and kidney tissues as well as to detect the protecting role of Vitamin C. METHODS: Thirty-two male adult albino rats were divided into four groups each with (eight animals) as following: Group (1): As control group and they injected with normal saline. Group (2): They were injected with 200 mg/kg B.W. of cefotaxime. Group (3): They were injected with Vitamin C in dose 100 mg/kg B.W. 1 h before they inject with 200 mg/kg B.W. of cefotaxime. Group (4): It was given Vitamin C in dose of 100 mg/kg B.W. Animals in all groups were injected intraperitoneally as single daily dose for 14 consecutive days. RESULTS: Results of cefotaxime treated group revealed that a significant liver tissue changes as hepatocytic vacuolation, necrosis, cholestasis with sinusoidal congestion, and dilatation also induced a histopathological change in the kidney including tubular epithelial degeneration, cast formation in renal tubules, inflammatory cells infiltration in the interstitium, and few glomeruli showed eosinophilic material deposition at the wall of bowman capsule. Adding Vitamin C to third group induces amelioration in the histological features of liver and kidney seen in Group (2) while group of Vitamin C only showed a histological picture similar to control group. CONCLUSION: From this study, we can conclude that Vitamin C has important hepato-renal protective effect.

Synchronizing In Silico, In Vitro, and In Vivo Studies for the Successful Nose to Brain Delivery of an Anticancer Molecule

Sesamol is a sesame seed constituent with reported activity against many types of cancer. In this work, two types of nanocarriers, solid lipid nanoparticles (SLNs) and polymeric nanoparticles (PNs), were exploited to improve sesamol efficiency against the glioma cancer cell line. The ability of the proposed systems for efficient brain targeting intranasally was also inspected. By the aid of two docking programs, the virtual loading pattern inside these nanocarriers was matched to the real experimental results. Interactions involved in sesamol-carrier binding were also assessed, followed by a discussion of how different scoring functions account for these interactions. The study is an extension of the computer-assisted drug formulation design series, which represents a promising initiative for an upcoming industrial innovation. The results proved the power of combined in silico tools in predicting members with the highest sesamol payload suitable for delivering a sufficient dose to the brain. Among nine carriers, glyceryl monostearate (GMS) and polycaprolactone (PCL) scored the highest sesamol payload practically and computationally. The EE % was 66.09 ± 0.92 and 61.73 ± 0.47 corresponding to a ΔG (binding energy) of -8.85 ± 0.16 and -5.04 ± 0.11, respectively. Dynamic light scattering evidenced the formation of 215.1 ± 7.2 nm and 414.25 ± 1.6 nm nanoparticles, respectively. Both formulations demonstrated an efficient cytotoxic effect and brain-targeting ability compared to the sesamol solution. This was evidenced by low IC₅₀ (38.50 ± 10.37 μM and 27.81 ± 2.76 μM) and high drug targeting efficiency (7.64 ± 1.89-fold and 13.72 ± 4.1-fold) and direct transport percentages (86.12 ± 3.89 and 92.198 ± 2.09) for GMS-SLNs and PCL-PNs, respectively. The results also showed how different formulations, having different compositions and characteristics, could affect the cytotoxic and targeting ability.

The contribution of nano-based strategies in overcoming ceftriaxone resistance: a literature review

Antimicrobial drug resistance, including resistance to multiple antibiotics, is continuously increasing. According to research findings, many bacteria resistant to other antibiotics were susceptible to ceftriaxone. However, over the last few years, ceftriaxone resistance has become growing and extremely worrisome challenge to the global healthcare system and several strategies have been initiated to contain the spread of antimicrobial drug resistance. Its extended use for therapeutic or preventative measures in humans and farm animals resulted in the development and spread of resistance. Recent advances in nanotechnology also offer novel formulations based on distinct types of nanostructure particles with different sizes and shapes, and flexible antimicrobial properties. For ceftriaxone, several nanostructured formulations through conjugation, intercalation, encapsulation with lipid carrier, and polymeric films have been investigated by different groups with promising results in combating the development of resistance. This review addressed the existing knowledge and practice on the contribution of nano-based delivery approaches in overcoming ceftriaxone resistance. Evidences have been generated from published research articles using major search electronic databases such as PubMed, Medline, Google Scholar, and Science Direct.

Role of Persistent Organic Pollutants in Breast Cancer Progression and Identification of Estrogen Receptor Alpha Inhibitors Using In-Silico Mining and Drug-Drug Interaction Network Approaches

Simple Summary

The role of persistent organic pollutants (POPs) in breast cancer progression and their bioaccumulation in adipose tissue has been reported. We used a computational approach to study molecular interactions of POPs with breast cancer proteins and identified natural and synthetic compounds to inhibit these interactions. Moreover, for comparative analysis, standard drugs and screened compounds were also docked against estrogen receptor alpha (ERα) and identification of the finest inhibitor was performed using in-silico mining and drug-drug interaction (DDI) network approaches. Based on scoring values, short-chained chlorinated paraffins demonstrated strong interactions with ERα compared to organo-chlorines and PCBs. Synthetic and natural compounds demonstrating strong associations with the active site of the ERα protein could be potential candidates to treat breast cancer specifically caused by POPs and other organic toxins and can be used as an alternative to standard drugs.

Abstract

The strong association between POPs and breast cancer in humans has been suggested in various epidemiological studies. However, the interaction of POPs with the ERα protein of breast cancer, and identification of natural and synthetic compounds to inhibit this interaction, is mysterious yet. Consequently, the present study aimed to explore the interaction between POPs and ERα using the molecular operating environment (MOE) tool and to identify natural and synthetic compounds to inhibit this association through a cluster-based approach. To validate whether our approach could distinguish between active and inactive compounds, a virtual screen (VS) was performed using actives (627 compounds) as positive control and decoys (20,818 compounds) as a negative dataset obtained from DUD-E. Comparatively, short-chain chlorinated paraffins (SCCPs), hexabromocyclododecane (HBCD), and perfluorooctanesulfonyl fluoride (PFOSF) depicted strong interactions with the ERα protein based on the lowest-scoring values of −31.946, −18.916, −17.581 kcal/mol, respectively. Out of 7856 retrieved natural and synthetic compounds, sixty were selected on modularity bases and subsequently docked with ERα. Based on the lowest-scoring values, ZINC08441573, ZINC00664754, ZINC00702695, ZINC00627464, and ZINC08440501 (synthetic compounds), and capsaicin, flavopiridol tectorgenin, and ellagic acid (natural compounds) showed incredible interactions with the active sites of ERα, even more convening and resilient than standard breast cancer drugs Tamoxifen, Arimidex and Letrozole. Our findings confirm the role of POPs in breast cancer progression and suggest that natural and synthetic compounds with high binding affinity could be more efficient and appropriate candidates to treat breast cancer after validation through in vitro and in vivo studies.

Zinc oxide nanoparticles conjugated with clinically-approved medicines as potential antibacterial molecules

At present, antibiotic resistance is one of the most pressing issues in healthcare globally. The development of new medicine for clinical applications is significantly less than the emergence of multiple drug-resistant bacteria, thus modification of existing medicines is a useful avenue. Among several approaches, nanomedicine is considered of potential therapeutic value. Herein, we have synthesized Zinc oxide nanoparticles (ZnO-NPs) conjugated with clinically-approved drugs (Quercetin, Ceftriaxone, Ampicillin, Naringin and Amphotericin B) with the aim to evaluate their antibacterial activity against several Gram-positive (Methicillin resistant Staphylococcus aureus, Streptococcus pneumoniae and Streptococcus pyogenes) and Gram-negative (Escherichia coli K1, Serratia marcescens and Pseudomonas aeruginosa) bacteria. The nanoparticles and their drug conjugates were characterized using UV-visible spectrophotometry, dynamic light scattering, Fourier transform infrared spectroscopy and atomic force microscopy. Antibacterial activity was performed by dilution colony forming unit method and finally 3-(4,5-dimethylthiazole-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays were performed to determine their cytotoxic effects against human cell lines. ZnO-NPs revealed maxima surface plasmon resonance band at 374 and after conjugation with beta-cyclodextrin at 379 nm, polydispersity with size in range of 25–45 nm with pointed shaped morphology. When conjugated with ZnO-NPs, drug efficacy against MDR bacteria was enhanced significantly. In particular, Ceftriaxone- and Ampicillin-conjugated ZnO-NPs exhibited potent antibacterial effects. Conversely, ZnO-NPs and drugs conjugated NPs showed negligible cytotoxicity against human cell lines except Amphotericin B (57% host cell death) and Amphotericin B-conjugated with ZnO-NPs (37% host cell death). In conclusion, the results revealed that drugs loaded on ZnO-NPs offer a promising approach to combat increasingly resistant bacterial infections.

Evolution of the Computational Pharmaceutics Approaches in the Modeling and Prediction of Drug Payload in Lipid and Polymeric Nanocarriers

This review describes different trials to model and predict drug payload in lipid and polymeric nanocarriers. It traces the evolution of the field from the earliest attempts when numerous solubility and Flory-Huggins models were applied, to the emergence of molecular dynamic simulations and docking studies, until the exciting practically successful era of artificial intelligence and machine learning. Going through matching and poorly matching studies with the wet lab-dry lab results, many key aspects were reviewed and addressed in the form of sequential examples that highlighted both cases.