Drug-receptor Interactions Research Articles

Deciphering the biophysical aspects of the interaction of 3,5,4'-trihydroxy-trans-stilbene with ribonuclease A: spectroscopic and computational studies.

Drug-receptor interaction is an important aspect in drug action, drug discovery, and pharmacological aspects. The molecule 3,5,4'-trihydroxy-trans-stilbene known as resveratrol is a natural polyphenol and exhibits diverse biological activities. Ribonuclease A catalyses the degradation of RNA by its ribonucleolytic activity. The report presents the binding interaction of resveratrol with RNase A using experimental and theoretical techniques. Experimental studies revealed the interaction strength of 104M-1 order with a single binding site. Resveratrol quenched the ribonuclease A fluorescence with a quenching constant of 104M-1 range. The accessible fraction of the fluorophore was found to be 0.75 besides non-radiative energy transfer from ribonuclease A to resveratrol. The donor-acceptor distance was 2.14nm from FRET calculations. No visible changes in the protein structure was evident from the circular dichroism studies. The interface residues involved in the interaction were obtained from docking studies. Further, the participation of the active site residues, His 12, His 119, and Lys 41 with interaction indicates the location of resveratrol near to the active site of ribonuclease A and indicates its possible potential to inhibit the ribonuclease A activity. The RMSD of less than 3Å indicates stable conformation of protein in the complex. The protein RMSF value in the complex less than 3Å shows no deviation of protein residues over time and thus suggests no conformational variation in the protein after binding.

Exploring Hypertension: The Role of AT1 Receptors, Sartans, and Lipid Bilayers.

The rational design of AT1 receptor antagonists represents a pivotal approach in the development of therapeutic agents targeting cardiovascular pathophysiology. Sartans, a class of compounds engineered to inhibit the binding and activation of Angiotensin II on the AT1 receptor, have demonstrated significant clinical efficacy. This review explores the multifaceted role of sartans in mitigating hypertension and related complications. We highlight the integration of crystallography, computational simulations, and NMR spectroscopy to elucidate sartan-AT1 receptor interactions, providing a foundation for the next-generation antagonist design. The review also delves into the challenges posed by the high lipophilicity and suboptimal bioavailability of sartans, emphasizing advancements in nanotechnology and novel drug delivery systems. Additionally, we discuss the impact of lipid bilayers on the AT1 receptor conformation and drug binding, underscoring the importance of the lipidic environment in receptor-drug interactions. We suggest that optimizing drug design to account for these factors could enhance the therapeutic potential of AT1 receptor antagonists, paving the way for improved cardiovascular health outcomes.

Exploring the Artificial Intelligence and Its Impact in Pharmaceutical Sciences: Insights Toward the Horizons Where Technology Meets Tradition.

The technological revolutions in computers and the advancement of high-throughput screening technologies have driven the application of artificial intelligence (AI) for faster discovery of drug molecules with more efficiency, and cost-friendly finding of hit or lead molecules. The ability of software and network frameworks to interpret molecular structures' representations and establish relationships/correlations has enabled various research teams to develop numerous AI platforms for identifying new lead molecules or discovering new targets for already established drug molecules. The prediction of biological activity, ADME properties, and toxicity parameters in early stages have reduced the chances of failure and associated costs in later clinical stages, which was observed at a high rate in the tedious, expensive, and laborious drug discovery process. This review focuses on the different AI and machine learning (ML) techniques with their applications mainly focused on the pharmaceutical industry. The applications of AI frameworks in the identification of molecular target, hit identification/hit-to-lead optimization, analyzing drug-receptor interactions, drug repurposing, polypharmacology, synthetic accessibility, clinical trial design, and pharmaceutical developments are discussed in detail. We have also compiled the details of various startups in AI in this field. This review will provide a comprehensive analysis and outline various state-of-the-art AI/ML techniques to the readers with their framework applications. This review also highlights the challenges in this field, which need to be addressed for further success in pharmaceutical applications.

In-silico ADME Evaluation and Molecular Docking of a Novel Compound’ 2-(4-Allylpiperazin-1-Yl)-1-(1-(4-Nitrophenyl)-1h-Tetrazol-5-Yl) Ethanone’ as Potential Antimicrobial Agents.

Molecular docking serves as a pivotal tool in comprehending drug-receptor interactions within modern-day drug design. In a previous report, new compounds 2-(4-allylpiperazin-1-yl)-1-(1-aryl-1H-tetrazol-5-yl) etalons were analyzed. Among these compounds, ‘2-(4-allylpiperazin-1-yl)-1-(1-(4-nitrophenyl)-1H-tetrazol-5-yl)ethanone’ was singled for molecular docking as it shows dual antibacterial and antifungal studies. Docking investigations revealed promising binding affinity of the compound towards Escherichia coli (1KZN), exhibiting significant antibacterial activity of docking grade -5.53 Kcal/mol, indicative of a fortified binding interaction. Conversely, the compound exhibited weaker binding affinity towards Candida albicans (1AI9) with a docking grade of -0.72 Kcal/mol. Negative binding energy signifies a robust alignment between the ligand and target protein, suggesting potential therapeutic efficacy against microbial activity. Moreover, in-silico ADMET calculations were conducted, and the synthesized compound confirms the drug-likeness within the defined parameters: molecular weight between 150 to 500 g/mol, TPSA polarity between 20 to 130 Å2 , lipophilicity ranging between -0.7 to +5.0 Log S not exceeding 6, flexibility not exceeding 9, and saturation not inferior to 0.25. The compound demonstrated compliance with these criteria, suggesting favorable in-vivo drug absorption and permeation characteristics.

Vibrational spectroscopic interpretation, solvent effect and molecular docking studies of TAAR1 partial agonist RO5263397

Density functional theory studies of TAAR1 (trace amine associated receptor 1) partial agonist RO5263397 carried out with precise and detailed spectroscopic investigation as well as validated experimentally. FT-IR, confocal Raman and UV–visible spectroscopic techniques were used to characterize the compound and corresponding theoretical calculations were carried out using DFT/B3LYP method with 6-311++G (d,p) basis set. Estimated and observed vibrational wavenumbers of the compound were assigned. UV–visible spectrum and FMOs (frontier molecular orbital) analysis reveals that the polarity affects the molecular reactivity and stability of the compound. Donor – acceptor interaction and second order perturbation energy have been explained using natural bond orbital analysis clarify the presence hydrogen bonds in the system. ELF and LOL studies visualises the localized and delocalized electrons in the title compound. RDG analysis evidences the various interactions present in the monomer and dimer of RO5263397. The structural importance of the compound were clearly examined using NMR spectral analysis. The existence of hydrogen bonding is validated by reactive site findings from Mulliken atomic charge distribution and molecule electrostatic potential surface studies. Information about distinct drug-receptor interactions obtained from molecular docking investigation offers the path of further study of molecular activity in various drug-receptor mechanism.

Histological evaluation of renal progenitor/stem cells, renal mesenchymal stem-like cells, and endothelial progenitor cells in chronic kidney disease and end-stage renal disease, and molecular docking analysis of drug-receptor interactions

Chronic kidney disease (CKD) and end-stage renal disease (ESRD) are prevalent and debilitating conditions with a significant impact on patients' quality of life. In this study, we conducted a comprehensive investigation into the histological characteristics of renal progenitor/stem cells (RPCs), renal mesenchymal stem-like cells, and endothelial progenitor cells (EPCs) in CKD and ESRD patients. Additionally, we performed a molecular docking analysis to explore potential drug-receptor interactions involving common medications prescribed to CKD patients. Our histological examination revealed a noteworthy increase in the number of CD24- and CD133-positive cells in CKD and ESRD patients, representing RPCs. These cells are implicated in kidney repair and regeneration, underscoring their potential role in CKD management. Moreover, we observed an elevation in the number of EPCs within the kidneys of CKD and ESRD patients, suggesting a protective role of EPCs in kidney preservation. The molecular docking analysis unveiled intriguing insights into potential drug interventions. Notably, digoxin exhibited the highest in-silico binding affinity to numerous receptors associated with the functions of RPCs, renal mesenchymal stem-like cells, and EPCs, emphasizing the potential multifaceted effects of this cardiac glycoside in CKD patients. Other drugs, including apixaban, glimepiride, and glibenclamide, also displayed strong in-silico affinities to specific receptors, indicating their potential influence on various renal cell functions. In conclusion, this study provides valuable insights into the histological alterations in renal cell populations in CKD and ESRD patients and underscores the potential roles of RPCs and EPCs in kidney repair and preservation. The molecular docking analysis reveals the complex interactions between common drugs and renal cells, suggesting the need for further in-vitro and in-vivo research to fully understand these relationships. These findings contribute to our understanding of CKD and offer new avenues for research into potential therapeutic interventions.

General quasi-equilibrium multivalent binding model to study diverse and complex drug-receptor interactions of biologics.

Pharmacokinetics and pharmacodynamics of many biologics are influenced by their complex binding to biological receptors. Biologics consist of diverse groups of molecules with different binding kinetics to its receptors including IgG with simple one-to-one drug receptor bindings, bispecific antibody (BsAb) that binds to two different receptors, and antibodies that can bind to six or more identical receptors. As the binding process is typically much faster than elimination (or internalization) and distribution processes, quasi-equilibrium (QE) binding models are commonly used to describe drug-receptor binding kinetics of biologics. However, no general QE modeling framework is available to describe complex binding kinetics for diverse classes of biologics. In this paper, we describe novel approaches of using differential algebraic equations (DAE) to solve three QE multivalent drug-receptor binding (QEMB) models. The first example describes the binding kinetics of three-body equilibria of BsAb that binds to 2 different receptors for trimer formation. The second example models an engineered IgG variant (Multabody) that can bind to 24 identical target receptors. The third example describes an IgG with modified neonatal Fc receptor (FcRn) binding affinity that competes for the same FcRn receptor as endogenous IgG. The model parameter estimates were obtained by fitting the model to all data simultaneously. The models allowed us to study potential roles of cooperative binding on bell-shaped drug exposure-response relationships of BsAb, and concentration-depended distribution of different drug-receptor complexes for Multabody. This DAE-based QEMB model platform can serve as an important tool to better understand complex binding kinetics of diverse classes of biologics.

Advancements and Perspectives in Folate‐Based Anticancer Drugs: Bridging Quantum and Classical Mechanics in Folate Receptor Research

AbstractThis review highlights the role of computational chemistry, specifically quantum and molecular mechanics, in the development of folate‐based anticancer drugs. Folate receptors (FRs) are overexpressed in cancerous cells, rendering these receptors a key focus in the design of targeted drug delivery systems. These computational tools are fundamental for analyzing drug–receptor interactions and overcoming the limitations of traditional drug development processes. A 10‐year literature survey demonstrated advancements in employing FRs for targeted cancer therapy. Key findings reveal that structural modifications to folate derivatives consistently enhance binding affinities and specificity toward FRα and FRβ. Computational methodologies predicted and analyzed molecular interactions, validated by experimental data. Functional groups play a crucial role in enhancing binding stability and interaction strength within FR binding pockets. Detailed structural insights into folate derivatives and antifolates interacting with FRs have identified critical residues involved in binding, aiding the design of targeted therapeutics.

Identifying and Exploring the Cognitive Nature of Threshold Concepts in Pharmacology to Improve Medical Students’ Learning

Phenomenon: Pharmacology is a fundamental healthcare discipline, but it can be difficult and counterintuitive for learners to learn. Navigation toward understanding pharmacology can be troublesome, but once the threshold to comprehension is crossed, learners can experience a transformative shift in their ways of thinking and practicing. We conducted an in-depth examination of threshold concepts within pharmacology, aiming to identify and prioritize their learning to improve the medical curriculum and enhance medical treatment and patient safety. Approach: We carried out a consensus generation process using the Nominal Group Technique (NGT) to identify potential threshold concepts in pharmacology. Participant groups of pharmacology experts and medical students considered, identified, reviewed, and ranked potential pharmacology threshold concepts within their own group. Then, using a logical, step-by-step approach, we combined the final ranked data from these multiple NGT sessions. We further analyzed these data using an abductive analysis approach; data were coded, categorized, reorganized, and conceptually mapped after critical evaluation. Conceptual themes were established corresponding to different phases of cognitive schema development. Findings: Six comprehensive conceptual themes were identified: Drug Mechanism of Action; Pharmacotherapeutics; Pharmacokinetics; Drug Receptor Interactions; Drug Terminology and Nomenclature; and Signaling Pathways. These concepts align with many of the key attributes of threshold concepts (e.g., troublesome, integrative and transformative). The cognitive schematic themes generated were (i) acquisition-troublesome; (ii) acquisition-transformative; (iii) automation-troublesome; (iv) automation-transformative. Insights: Transformative learning involves different stages of cognitive schema evolution, including acquisition, elaboration, and automation, and is influenced by both the inherent challenges of the concepts and limitations of human cognition. The high interactivity of these troublesome concepts challenge schema acquisition and automation. Troublesome concepts underpinning procedures or skills, while not easily explained by cognitive rules, can lead to slow, awkward, error-prone performance, creating additional barriers for practice. Integrating concepts into a coherent structure leads to the irreversible assimilation of knowledge and the transferability of both knowledge and skills, influencing learners’ epistemological transitions and ontological transformations at theoretical and professional levels. Further work on designing instructional models around assisting and automating schemas around identified troublesome knowledge, while addressing the impact of cognitive load, has the potential to promote transformational learning.

Exploring Scoring Function Space: Developing Computational Models for Drug Discovery.

The idea of scoring function space established a systems-level approach to address the development of models to predict the affinity of drug molecules by those interested in drug discovery. Our goal here is to review the concept of scoring function space and how to explore it to develop machine learning models to address protein-ligand binding affinity. We searched the articles available in PubMed related to the scoring function space. We also utilized crystallographic structures found in the protein data bank (PDB) to represent the protein space. The application of systems-level approaches to address receptor-drug interactions allows us to have a holistic view of the process of drug discovery. The scoring function space adds flexibility to the process since it makes it possible to see drug discovery as a relationship involving mathematical spaces. The application of the concept of scoring function space has provided us with an integrated view of drug discovery methods. This concept is useful during drug discovery, where we see the process as a computational search of the scoring function space to find an adequate model to predict receptor-drug binding affinity.

Computer Aided Drug Design (CADD) Supported Medication: A Guide to Improved Patient Care

Computer Aided Drug Design (CADD) supported medication structure fuses a wide scope of hypothetical and computational methodologies that functions as significant component of present-day drug discovery. CADD strategies have made key commitments to the occasion of medications that are in clinical use or in clinical preliminaries. Such techniques have risen and developed together with trial approaches used in drug formulation. This incorporates different database and different instruments used in the zone of bioinformatics like BLAST, FASTA, DRUG BANK and so forth this strategy is utilized to break down, create and find drugs closely resembling biologically active molecules. The ligand-oriented computer aided drug designing helped study of ligand that are found to associate with the objective target of interest to search their 2D and 3D structures. The significance of those methods stands to theorize the nature and class of the given target. CADD methods can build the odds of perceiving the compounds with useful qualities, prompting development and extend the possibilities of getting a compound over the numerous obstacles of preclinical testing. It tends to be utilized for quick calculation of chemical libraries so as to direct and quicken the beginning period improvement of newly active compounds. It likewise incorporates a wide assortment computational methodology like virtual library, virtual screening, lead optimization and so on. Over the ongoing years, computer aided drug designing (CADD) has been otherwise called in silico screening that has risen as a compelling methodology in view of drug finding and progression through varied advanced attributes. In silico screening additionally makes an approach to combination and screen the chose mixes for new and better therapeutics. CADD and bioinformatics instruments convey advantages, for example, cost sparing, time to market, in-sight information of drug receptor interactions that accelerate drug disclosure and improvement

Cardiotoxic Drugs: An Insight into its Pathologic Mechanisms

ABSTRACT: Cardiovascular diseases are among the major causes of mortality and morbidity worldwide Cardiotoxicity due to drugs is a common and significant adverse effect on cardiovascular health, acting through multifactorial pathological mechanisms. Drug-induced cardiotoxicity limits the use and further development of certain drugs. Keeping this in mind, this review discusses the crucial drug-receptor interactions involved in cardiotoxicity induced by some drugs such as cocaine, trastuzumab, isoproterenol, antidiabetic drugs like pioglitazone, theophylline, ergotamine, methysergide, anthracyclines, fluoropyrimidines, cisplatin, NSAIDs, and antiviral agents. The key receptors involved in the pathological mechanism behind the cardiotoxicity induced by these drugs are discussed, aiming to provide in-depth knowledge for future drug discovery and prevention of drug-induced cardiotoxicity.

Liquid-Vapor Coexistence and Spontaneous Evaporation at Atmospheric Pressure of Common Rigid Three-Point Water Models in Molecular Simulations.

Molecular dynamics (MD) simulations are widely used to investigate molecular systems at atomic resolution including biomolecular structures, drug-receptor interactions, and novel materials. Frequently, MD simulations are performed in an aqueous solution with explicit models of water molecules. Commonly, such models are parameterized to reproduce the liquid phase of water under ambient conditions. However, often, simulations at significantly higher temperatures are also of interest. Hence, it is important to investigate the equilibrium of the liquid and vapor phases of molecular models of water at elevated temperatures. Here, we evaluate the behavior of 11 common rigid three-point water models over a wide range of temperatures. From liquid-vapor coexistence simulations, we estimated the critical points and studied the spontaneous evaporation of these water models. Moreover, we investigated the influence of the system size, choice of the pressure-coupling algorithm, and rate of heating on the process and compared them with the experimental data. We found that modern rigid three-point water models reproduce the critical point surprisingly well. Furthermore, we discovered that the critical temperature correlates with the quadrupole moment of the respective water model. This indicates that the spatial arrangement of the partial charges is important for reproducing the liquid-vapor phase transition. Our findings may guide the selection of water models for simulations conducted at high temperatures.

UV-Visible Spectroscopy: A Review on its Pharmaceutical and Bio-allied Sciences Applications

Abstract: Ultraviolet-Visible (UV-Vis) spectroscopy has emerged as a powerful analytical tool with diverse applications in pharmaceutical and bio-allied sciences. This article provides a comprehensive overview of the extensive utility of UV-Vis spectroscopy, emphasizing its pivotal role in characterizing and analyzing various compounds critical for drug development and bio-allied research. In the pharmaceutical sector, UV-Vis spectroscopy is a fundamental technique for quantifying the concentrations of active pharmaceutical ingredients (APIs) in formulations. Its non-destructive nature and high sensitivity make it an indispensable tool for quality control, ensuring the consistency and potency of pharmaceutical products. Furthermore, this technique has been employed in the study of drug-receptor interactions to elucidate the molecular mechanisms underlying therapeutic effects. In bio-allied applications, UV-Vis spectroscopy is used to analyze biomolecules like proteins, nucleic acids, and enzymes. This technique allows for the study of protein conformational changes, DNA structure, and enzymatic activity, offering crucial insights into fundamental biological processes. Additionally, UV-Vis spectroscopy aids in determining biomarker concentrations, assisting in the early diagnosis and monitoring of various diseases. This article also explores recent advancements in UV-Vis spectroscopy, including the integration of nanomaterials and computational approaches to enhance sensitivity and selectivity. Moreover, it discusses the potential of UV-Vis spectroscopy in emerging areas such as personalized medicine and point- of-care diagnostics. As technology continues to evolve, UV-Visible spectroscopy is poised to significantly contribute to the ever-expanding landscape of pharmaceutical and bio-related research.

Structure-based drug design for protein arginine deiminase Type IV (PAD4) receptor: Chemoinformatics approach

Rheumatoid Arthritis (RA) is the second most common type of arthritis with symptoms first appearing in patients between 40 and 60 years of age. The number of older persons is projected to double to 1.5 billion in 2050, globally. Peptidylarginine deiminase Type 4 (PAD4), which catalyzes the conversion of peptidyl-arginine to peptidyl-citrulline, is widely believed to play a causative role in RA disease. Nonsteroidal anti-inflammatories (NSAIDs) and corticosteroids encompass a large group of clinically effective compounds whose mode of action is well established, these compounds relieve pain and reduce inflammation by preventing prostaglandin synthesis through inhibition of cyclooxygenase 2 and the production of arachidonic acid, respectively. We developed a computational protocol/pipeline, using virtual screening approaches to search for new chemical agents (NCA), capable of inhibiting the action of PAD4, in potential, in view of the treatment of RA. Our results allowed the selection of structures with suitable indices of pharmacokinetic properties and estimated low toxicological, in potential, important evidence for selection of more promising molecular candidates against the studied disease. Molecules ZINC20452582 and ZINC67673633 presented better results, as well as the drug-receptor interactions were similar to those observed between the crystallographic compound (GSK147) here used. They presented excellent results for predictions of metabolites, and they can be indicated as promising molecules, resulting from virtual screening approaches, as new PAD4 receptor inhibitors with activity against RA, in potential.

Synthesis and evaluation of 2-phenylamino-1,4-naphthoquinones derivatives as potential hypoglycaemic agents.

Due to the severe side effects revealed by most of the currently used antidiabetic medicines, search for finding new and safe drugs to manage diabetes is continued. Naphthoquinones possessing strong antioxidant properties have been employed as candidates for diabetes therapy. Present study is aimed at finding the antioxidant and hypoglycaemic potential of some novel derivatives of 2-phenylamino-1,4-naphthoquinones (PAN) including chloro, nitro, methyl and bromo (5a-d) derivatives synthesized by single pot experiment. Product crystals were purified by TLC and characterized by FT-IR. The antioxidant potential of the compounds was assayed through DPPH radical scavenging and reducing power activities noted as UV-vis. absorbance. The DPPH assay has showed the powerful antioxidant activity of nitro and bromo derivatives, while the nitro derivative showed the significant reduction potential towards FRAP assay. Hypoglycaemic potential of the compounds was studied in rat animal model. All synthesized compounds revealed better hypoglycaemic activity; however, the chloro-derivative exhibited the more potent hypoglycaemic activity showing about 43% reduction in the mean blood glucose levels of the treated animals. As the bioreduction of naphthoquinones may be influenced by changing its redox properties, it has been noticed that the e-donating resonance effect (+R) of 'chloro' group has shown the significant effects on biological activity through stabalization of its imine form which limits the potential of generation of free radicals during bioreduction of quinones and thus has been proposed as the reason of its hypoglycaemic activity. Future studies employing the properties of e-donating groups of PAN may optimize the drug-receptor interaction for better drug designing and drug development strategies against diabetes and also for the clinical trials.

Effect of antibiotics' electromagnetic spectrums on the bacterial growths: beyond drug-receptor interaction

Electromagnetic frequencies (EF) generated from different laboratory devices and appliances can interact with biological systems, including humans. Several studies have assessed the effect of electromagnetic frequencies on the growth of microorganisms, which revealed that EF could inhibit bacterial growth, decrease colony-forming units, or decrease viability depending on the field strength and frequency. Accordingly, in this study, we aimed to assess the effect of the antibiotics extracted electromagnetic spectrums on the growth of Staphylococcus aureus (S. aureus). Drugs digital electromagnetic spectrums of a mixture of antibiotics were generated using a DigiConPro® VITATEC device emitted using the supplied antenna and applied into a glass tube containing nutrient broth inoculated with S. aureus, and optical density was measured hourly for 6 hours. The post-exposure effect of antibiotics' electromagnetic spectrums was also determined on bacteria subcultured into blood agar. Antibiotics’ electromagnetic spectrums were seen to cause a statistically significant (p<0.05) decrease in the growth rate relative to the control after two hours of exposure that persisted until the stationary phase was reached. Also, this effect persisted after exposure and affected the next generation of bacteria and 4 hours dose of antibiotics’ electromagnetic spectrums was able to induce a huge reduction (5 times) in the bacterial growth compared to the control group and in reference to the zero time. As a conclusion, electromagnetic spectrums of the medications may have the same effect as the chemical compound, and the mechanism of drug action can be explained beyond the simple chemical-receptor interaction.

Novel phloretin-based combinations targeting glucose metabolism in hepatocellular carcinoma through GLUT2/PEPCK axis of action: in silico molecular modelling and in vivo studies.

Hepatocellular carcinoma (HCC) is commonly associated with disturbances in glucose metabolism and enhanced glycolysis. However, a controversial role for gluconeogenesis was reported to be tumor-promoting and tumor-suppressive. We investigated novel anti-HCC treatments through either the simultaneous inhibition of glycolysis and gluconeogenesis by "phloretin" and "sodium meta-arsenite", respectively (Combination 1); or the concurrent inhibition of glycolysis and induction of gluconeogenesis by phloretin and dexamethasone, respectively, (combination 2). A total of 110 Swiss albino mice were divided into eleven groups, HCC was induced by N, N-dimethyl-4-aminoazobenzene. We have measured the expression of the glucose transporter 2 (GLUT2), Phosphoenolpyruvate carboxykinases (PEPCK), Caspase-3, Beclin 1, Cyclin D1, and cytokeratin 18 genes; blood glucose and ATP levels; alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities. Furthermore, in silico molecular docking was performed to investigate the potential drug-receptor interactions. Histologically, the phloretin-based combinations resulted in a significant regression of malignant tissue compared to various treatments. GLUT2 and PEPCK mRNA analysis indicated successful off/on modulation of glycolysis and gluconeogenesis. Docking confirmed the potent binding between phloretin, sodium meta-arsenite, and dexamethasone with GLUT2, PEPCK, and Retinoid X Receptor Alpha, respectively. Molecularly, Combination 2 resulted in the highest reduction in cyclin D1, cytokeratin 18, and Beclin 1 expression contemporaneously with the upregulation in Caspase-3 levels. Biochemically, both combinations caused a significant reduction in ATP levels, ALT, and AST activity compared to the other groups. In conclusion, we propose two novel phloretin-based combinations that can be used in treating HCC through the regulation of glucose metabolism and ATP production.

Synthesis, characterization and biological investigations of some new Oxadiazoles: In-vitro and In-Silico approach

A series of new oxadiazole derivatives, namely 1-{2-substituted phenyl −5-[2-tifluoromethyl)-1H-indol-3-yl]-3-(2H)-ylethanone 1,3,4-oxadiazoles were synthesized and investigated in this research. Using AutoDockVina 4.2, the new compounds VIb and VIc were extensively investigated for their ADMET characteristics and in-silico drug receptor interactions with the target enzyme, GlcN-6-P synthase (PDB ID: 2FV5). The existence of an electron-withdrawing group and a lipophilic functional group substituted at the phenyl ring was observed to be more active than in other molecules. The new molecules drug ability was investigated using ADMET experiments performed by Swiss ADME software, and the newly synthesized compounds qualified for ADME characteristics and followed Lipinski’s rule of five. FTIR, 1H NMR, 13CNMR, and mass spectrometry tools were used to characterize the prepared substances. The prepared substances were screened for antibacterial activity against gram-positive (Bacillus subtilis, Staphylococcus aureus) and gram-negative microbes (Pseudomonas aeruginosa and Escherichia coli) using cup plate and MIC techniques. These substances were also screened for antifungal activity against Aspergillus niger and Candida albicans, with Ampicillin and Amphotericin B serving as standard references. The compounds VIb and VIc have more antibacterial action than antifungal activity among the synthesized substances. Compounds VIa to VIf were examined for in vitro antioxidant activity and compounds VIb and VIc has displayed significant antioxidant potentials with IC50 values 45.16 and 38.14 in DPPH assay. The compounds VIa–f were tested for anticancer activity using MDA-MB 361 cell lines using MTT assays, and the IC50 values were recorded, out of which VIb and VIc displayed the lowest IC50 values. In-silico drug receptor interactions with the target enzyme, phosphoinositide-3-kinase (PI3K), with PDB ID: 3MJW were predicted as supportive evidence for the anticancer properties of the synthesized scaffolds.

Synthesis, biological evaluation and in silico studies of some new analogues of 3,5-vdisubstituted thiazolidin-2,4-dione.

Background: A new series of 3,5-disubstituted thiazolidin-2,4-dione molecules werederived and characterized using various spectral techniques (1H NMR, IR, carbon, hydrogen, nitrogen, etc.) and physicochemical parameters. Materials & methods: The molecules were derived using Knoevenagel condensation followed by Mannich reaction and further synthesized analogues were screened for their antioxidant and antimicrobial potential using 2,2-diphenyl-1-picrylhydrazyl free radical scavenging method and serial tube dilution method, respectively, along with in silico studies (docking and absorption, distribution, metabolism and excretion parameters) to explore the drug-receptor interaction and druglikeness. Results & conclusion: In antimicrobial screening, the analogs MP2, MM6, MM7 and MM8 displayed promising activity while molecule MM4 exhibited better antioxidant potential in the series. In molecular docking analysis, the best-fitted analogs, namely, MM6 and MM7, showed good interactions.