Identification of promising methionine aminopeptidase enzyme inhibitors: A combine study of comprehensive virtual screening and dynamics simulation study.

Methionine aminopeptidase (MetAP) enzymes play a critical role in bacterial cell survival by cleaving formyl-methionine initiators at N-terminal of nascent protein, a process which is vital in proper protein folding. This makes MetAP an attractive and novel antibacterial target to unveil promising antibiotics. In this study, the crystal structure of R. prowazekii MetAP was used in structure-based virtual screening of drug libraries such as Asinex antibacterial library and Comprehensive Marine Natural Products Database (CMNPD) to identify promising lead molecules against the enzyme. This shortlisted three drug molecules; BDE-25098678, BDE-30686468 and BDD_25351157 as most potent leads that showed strong binding to the MetAP enzyme. The static docked conformation of the compounds to the MetAP was reevaluated in molecular dynamics simulation studies. The analysis observed the docked complexes as stable structure with no major local or global deviations noticed. These findings suggest the formation of strong intermolecular docked complexes, which showed stable dynamics and atomic level interactions network. The binding free energy analysis predicted net MMGBSA energy of complexes as: BDE-25098678 (-73.41 kcal/mol), BDE-30686468 (-59.93 kcal/mol), and BDD_25351157 (-75.39 kcal/mol). In case of MMPBSA, the complexes net binding energy was as; BDE-25098678 (-77.47 kcal/mol), BDE-30686468 (-69.47 kcal/mol), and BDD_25351157 (-75.6 kcal/mol). Further, the compounds were predicted to follow the famous Lipinski rule of five and have non-toxic, non-carcinogenic and non-mutagenic profile. The screened compounds might be used in experimental test to highlight the real anti- R. prowazekii MetAP activity.

Novel and Potential Small Molecule Scaffolds as DYRK1A Inhibitors by Integrated Molecular Docking-Based Virtual Screening and Dynamics Simulation Study.

The dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is a novel, promising and emerging biological target for therapeutic intervention in neurodegenerative diseases, especially in Alzheimer's disease (AD). The molMall database, comprising rare, diverse and unique compounds, was explored for molecular docking-based virtual screening against the DYRK1A protein, in order to find out potential inhibitors. Ligands exhibiting hydrogen bond interactions with key amino acid residues such as Ile165, Lys188 (catalytic), Glu239 (gk+1), Leu241 (gk+3), Ser242, Asn244, and Asp307, of the target protein, were considered potential ligands. Hydrogen bond interactions with Leu241 (gk+3) were considered key determinants for the selection. High scoring structures were also docked by Glide XP docking in the active sites of twelve DYRK1A related protein kinases, viz. DYRK1B, DYRK2, CDK5/p25, CK1, CLK1, CLK3, GSK3ß, MAPK2, MAPK10, PIM1, PKA, and PKCα, in order to find selective DYRK1A inhibitors. MM/GBSA binding free energies of selected ligand-protein complexes were also calculated in order to remove false positive hits. Physicochemical and pharmacokinetic properties of the selected six hit ligands were also computed and related with the proposed limits for orally active CNS drugs. The computational toxicity webserver ProTox-II was used to predict the toxicity profile of selected six hits (molmall IDs 9539, 11352, 15938, 19037, 21830 and 21878). The selected six docked ligand-protein systems were exposed to 100 ns molecular dynamics (MD) simulations to validate their mechanism of interactions and stability in the ATP pocket of human DYRK1A kinase. All six ligands were found to be stable in the ATP binding pocket of DYRK1A kinase.

Molecular and Structural Analysis of Specific Mutations from Saudi Isolates of SARS-CoV-2 RNA-Dependent RNA Polymerase and their Implications on Protein Structure and Drug-Protein Binding.

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has stressed the global health system to a significant level, which has not only resulted in high morbidity and mortality but also poses a threat for future pandemics. This situation warrants efforts to develop novel therapeutics to manage SARS-CoV-2 in specific and other emerging viruses in general. This study focuses on SARS-CoV2 RNA-dependent RNA polymerase (RdRp) mutations collected from Saudi Arabia and their impact on protein structure and function. The Saudi SARS-CoV-2 RdRp sequences were compared with the reference Wuhan, China RdRp using a variety of computational and biophysics-based approaches. The results revealed that three mutations-A97V, P323I and Y606C-may affect protein stability, and hence the relationship of protein structure to function. The apo wild RdRp is more dynamically stable with compact secondary structure elements compared to the mutants. Further, the wild type showed stable conformational dynamics and interaction network to remdesivir. The net binding energy of wild-type RdRp with remdesivir is -50.76 kcal/mol, which is more stable than the mutants. The findings of the current study might deliver useful information regarding therapeutic development against the mutant RdRp, which may further furnish our understanding of SARS-CoV-2 biology.

Validated Simultaneous Gradient Ultra-Performance Liquid Chromatographic Quantification of Some Proton Pump Inhibitor Drug Residues in Saudi Pharmaceutical Industrial Wastewater.

Monitoring and quantification of active pharmaceutical ingredients (APIs) in the environment constitute important and challenging tasks, as they are directly associated with human health. Three commonly used proton pump inhibitors (PPIs), namely, omeprazole sodium (OMP), pantoprazole sodium (PNT), and lansoprazole sodium (LNZ) are well separated and quantified using ultra-performance liquid chromatography (UPLC) in pharmaceutical industrial wastewater. The separation of the studied drugs was performed on a stationary phase with a WatersTM column (100 × 2.1 mm, 1.7 µm). The mobile phase was composed of methanol:0.05 M potassium dihydrogen phosphate buffer (adjusted to pH 7.5 using NaOH) (50:50, v/v). The elution process was done in gradient mode by changing the relative proportions of the mobile phase components with time to get an optimum separation pattern. The flow rate of the developing system was adjusted to 0.8 mL/minute. Detection of the separated drugs was performed at 230 nm. The studied drugs were quantified in the concentration range of 10-200 ng/mL for all drugs. The cited method was fully validated according to the international conference on harmonization (ICH-Q2B) guidelines, then it was applied successfully for quantification of the studied PPIs in real wastewater samples after their solid phase extraction (SPE).

Fabrication of Membrane Sensitive Electrodes for the Validated Electrochemical Quantification of Anti-Osteoporotic Drug Residues in Pharmaceutical Industrial Wastewater.

Accurate and precise application of ion-selective electrodes (ISEs) in the quantification of environmental pollutants is a strenuous task. In this work, the electrochemical response of alendronate sodium trihydrate (ALN) was evaluated by the fabrication of two sensitive and delicate membrane electrodes, viz. polyvinyl chloride (PVC) and glassy carbon (GC) electrodes. A linear response was obtained at concentrations from 1 × 10-5 to 1 × 10-2 M for both electrodes. A Nernstian slope of 29 mV/decade over a pH range of 8-11 for the PVC and GC membrane electrodes was obtained. All assay settings were carefully adjusted to obtain the best electrochemical response. The proposed technique was effectively applied for the quantification of ALN in pure form and wastewater samples, acquired from manufacturing industries. The proposed electrodes were effectively used for the determination of ALN in real wastewater samples without any prior treatment. The current findings guarantee the applicability of the fabricated ISEs for the environmental monitoring of ALN.

Synthesis, Anticancer Screening of Some Novel Trimethoxy Quinazolines and VEGFR2, EGFR Tyrosine Kinase Inhibitors Assay; Molecular Docking Studies.

A new series of 8-methoxy-2-trimethoxyphenyl-3-substituted quinazoline-4(3)-one compounds were designed, synthesized, and screened for antitumor activity against three cell lines, namely, Hela, A549, and MDA compared to docetaxel as reference drug. The molecular docking was performed using Autodock Vina program and 20 ns molecular dynamics (MD) simulation was performed using GROMACS 2018.1 software. Compound 6 was the most potent antitumor of the new synthesized compounds and was evaluated as a VEGFR2 and EGFR inhibitor with (IC50, 98.1 and 106 nM respectively) compared to docetaxel (IC50, 89.3 and 56.1 nM respectively). Compounds 2, 6, 10, and 8 showed strong cytotoxic activities against the Hela cell line with IC50 of, 2.13, 2.8, 3.98, and 4.94 µM, respectively, relative to docetaxel (IC50, 9.65 µM). Compound 11 showed strong cytotoxic activity against A549 cell line (IC50, 4.03 µM) relative to docetaxel (IC50, 10.8 µM). Whereas compounds 6 and 9 showed strong cytotoxic activity against MDA cell line (IC50, 0.79, 3.42 µM, respectively) as compared to docetaxel (IC50, 3.98 µM).

Discovery of anti-MERS-CoV small covalent inhibitors through pharmacophore modeling, covalent docking and molecular dynamics simulation.

Middle east respiratory syndrome coronavirus (MERS-CoV) is a fatal pathogen that poses a serious health risk worldwide and especially in the middle east countries. Targeting the MERS-CoV 3-chymotrypsin-like cysteine protease (3CLpro) with small covalent inhibitors is a significant approach to inhibit replication of the virus. The present work includes generating a pharmacophore model based on the X-ray crystal structures of MERS-CoV 3CLpro in complex with two covalently bound inhibitors. In silico screening of covalent chemical database having 31,642 compounds led to the identification of 378 compounds that fulfils the pharmacophore queries. Lipinski rules of five were then applied to select only compounds with the best physiochemical properties for orally bioavailable drugs. 260 compounds were obtained and subjected to covalent docking-based virtual screening to determine their binding energy scores. The top three candidate compounds, which were shown to adapt similar binding modes as the reported covalent ligands were selected. The mechanism and stability of binding of these compounds were confirmed by 100 ns molecular dynamic simulation followed by MM/PBSA binding free energy calculation. The identified compounds can facilitate the rational design of novel covalent inhibitors of MERS-CoV 3CLpro enzyme as anti-MERS CoV drugs.

Enzyme immobilization offers a robust tool to scale up the production of longer, diverse, natural glycosaminoglycan oligosaccharides.

Although structurally diverse, longer glycosaminoglycan (GAG) oligosaccharides are critical to understand human biology, few are available. The major bottleneck has been the predominant production of oligosaccharides, primarily disaccharides, upon enzymatic depolymerization of GAGs. In this work, we employ enzyme immobilization to prepare hexasaccharide and longer sequences of chondroitin sulfate in good yields with reasonable homogeneity. Immobilized chondroitinase ABC displayed good efficiency, robust operational pH range, broad thermal stability, high recycle ability and excellent distribution of products in comparison to the free enzyme. Diverse sequences could be chromatographically resolved into well-defined peaks and characterized using LC-MS. Enzyme immobilization technology could enable easier access to diverse longer GAG sequences.

Immobilization alters heparin cleaving properties of heparinase I.

We report here a novel observation that immobilization of heparinase I on CNBr-activated Sepharose results in heparin degradation properties that are different from heparinase I in the free solution form. Studies over a range of pHs (5-8) and temperatures (5-50°C) as well as under batch and flow conditions show that immobilized heparinase 1 displays altered pH and temperature optima, and a higher propensity for generation of longer chains (hexa- and octa-) with variable sulfation as compared to that in the free form, which is known to yield disaccharides. The immobilized enzyme retained good eliminase activity over at least five cycles of reuse. In combination, results suggest that heparinase I immobilization may offer a more productive route to longer, variably sulfated sequences.

Design, Synthesis, and Biological Evaluation of Ester and Ether Derivatives of Antisickling Agent 5-HMF for the Treatment of Sickle Cell Disease.

Candidate drugs to counter intracellular polymerization of deoxygenated sickle hemoglobin (Hb S) continue to represent a promising approach to mitigating the primary cause of the pathophysiology associated with sickle cell disease (SCD). One such compound is the naturally occurring antisickling agent, 5-hydroxymethyl-2-furfural (5-HMF), which has been studied in the clinic for the treatment of SCD. As part of our efforts to develop novel efficacious drugs with improved pharmacologic properties, we structurally modified 5-HMF into 12 ether and ester derivatives. The choice of 5-HMF as a pharmacophore was influenced by a combination of its demonstrated attractive hemoglobin modifying and antisickling properties, well-known safety profiles, and its reported nontoxic major metabolites. The derivatives were investigated for their time- and/or dose-dependent effects on important antisickling parameters, such as modification of hemoglobin, corresponding changes in oxygen affinity, and inhibition of red blood cell sickling. The novel test compounds bound and modified Hb and concomitantly increased the protein affinity for oxygen. Five of the derivatives exhibited 1.5- to 4.0-fold higher antisickling effects than 5-HMF. The binding mode of the compounds with Hb was confirmed by X-ray crystallography and, in part, helps explain their observed biochemical properties. Our findings, in addition to the potential therapeutic application, provide valuable insights and potential guidance for further modifications of these (and similar) compounds to enhance their pharmacologic properties.

Comparative analysis of INLIGHT™-labeled enzymatically depolymerized heparin by reverse-phase chromatography and high-performance mass spectrometry.

Structural characterization of the microheterogeneity of heparin, heparan sulfate, and other glycosaminoglycans is a major analytical challenge. We present the use of a stable isotope-labeled hydrazide tag (INLIGHT™) with high-resolution/accurate mass (HRAM) reverse-phase LC-MS/MS, which was recently introduced for detailed study of N-glycan heterogeneity, to characterize heparinase-digested heparin (digHep) products without the use of semi-volatile ion pairing reagents. Using both full scan LC-MS and data-dependent LC-MS/MS, we identified 116 unique digHep species, a feat possible because of INLIGHT™ labeling. Of these, 83 digHep products were structurally identified, including the 12 standard disaccharides as well as 34 tetra- (DP4), 26 hexa- (DP6), 21 octa- (DP8), and 2 decasaccharides (DP10). Each of the 116 digHep species co-eluted with both light and heavy INLIGHT™ tags (L/Havg = 1.039 ± 0.163); thus enhancing confidence in their identification via MS and MS/MS. This work sets the foundation for INLIGHT™-based comparative analyses of different forms of heparin, heparan sulfate, and other GAGs with high quantitative precision using mainstay reverse-phase HRAM LC-MS/MS. Graphical Abstract Reducing end labeling strategy for mapping depolymerized heparin/heparan sulfate products by reverse-phase LC-MS/MS.

Targeting XGHPRT enzyme to manage Helicobacter pylori induced gastric cancer: A multi-pronged machine learning, artificial intelligence and biophysics-based study.

Helicobacter pylori infects the stomach mucosa of over half of the global population and can lead to gastric cancer. This pathogen has demonstrated resistance to many frequently prescribed antibiotics, thereby underscoring the pressing need to identify novel therapeutic targets. The inhibition or disruption of nucleic acid biosynthesis constitutes a promising avenue for either restraining or eradicating bacterial proliferation. The synthesis of RNA and DNA precursors (6-oxopurine nucleoside monophosphates) is catalyzed by the XGHPRT enzyme. In this study, using machine learning, artificial intelligence and biophysics-based software, CHEMBRIDGE-10000196, CHEMBRIDGE-10000295, and CHEMBRIDGE-10000955 were predicted as promising binders to the XGHPRT with a binding score of -14.20, -13.64, and -12.08 kcal/mol, respectively, compared to a control guanosine-5'-monophosphate exhibiting a docking score of -10.52 kcal/mol. These agents formed strong interactions with Met33, Arg34, Ala57, Asp92, Ser93, and Gly94 at short distance. The docked complexes of the lead compounds exhibited stable dynamics during the simulation time with no global changes noticed. The docked complexes demonstrate a significantly stable MM-GBSA and MM-PBSA net binding energy of -60.1 and -61.18 kcal/mol for the CHEMBRIDGE-10000196 complex. The MM-GBSA net energy value of the CHEMBRIDGE-10000295 complex and the CHEMBRIDGE-10000955 complex is -71.17 and -65.29 kcal/mol, respectively. The CHEMBRIDGE-10000295 and CHEMBRIDGE-10000955 complexes displayed a net value of -71.91 and -63.49 kcal/mol, respectively, as per the MM-PBSA. The major driving intermolecular interactions for the docked complexes were found to be the electrostatic and van der Waals. The three filtered molecules hold potential for experimental evaluation of their potency against the XGHPRT enzyme.

System biology approach to identify the novel biomarkers in glioblastoma multiforme tumors by using computational analysis.

Introduction: The most common primary brain tumor in adults is glioblastoma multiforme (GBM), accounting for 45.2% of all cases. The characteristics of GBM, a highly aggressive brain tumor, include rapid cell division and a propensity for necrosis. Regretfully, the prognosis is extremely poor, with only 5.5% of patients surviving after diagnosis. Methodology: To eradicate these kinds of complicated diseases, significant focus is placed on developing more effective drugs and pinpointing precise pharmacological targets. Finding appropriate biomarkers for drug discovery entails considering a variety of factors, including illness states, gene expression levels, and interactions between proteins. Using statistical techniques like p-values and false discovery rates, we identified differentially expressed genes (DEGs) as the first step in our research for identifying promising biomarkers in GBM. Of the 132 genes, 13 showed upregulation, and only 29 showed unique downregulation. No statistically significant changes in the expression of the remaining genes were observed. Results: Matrix metallopeptidase 9 (MMP9) had the greatest degree in the hub biomarker gene identification, followed by (periostin (POSTN) at 11 and Hes family BHLH transcription factor 5 (HES5) at 9. The significance of the identification of each hub biomarker gene in the initiation and advancement of glioblastoma multiforme was brought to light by the survival analysis. Many of these genes participate in signaling networks and function in extracellular areas, as demonstrated by the enrichment analysis.We also identified the transcription factors and kinases that control proteins in the proteinprotein interactions (PPIs) of the DEGs. Discussion: We discovered drugs connected to every hub biomarker. It is an appealing therapeutic target for inhibiting MMP9 involved in GBM. Molecular docking investigations indicated that the chosen complexes (carmustine, lomustine, marimastat, and temozolomide) had high binding affinities of -6.3, -7.4, -7.7, and -8.7 kcal/mol, respectively, the mean root-mean-square deviation (RMSD) value for the carmustine complex and marimastat complex was 4.2 Å and 4.9 Å, respectively, and the lomustine and temozolomide complex system showed an average RMSD of 1.2 Å and 1.6 Å, respectively. Additionally, high stability in root-mean-square fluctuation (RMSF) analysis was observed with no structural conformational changes among the atomic molecules. Thus, these in silico investigations develop a new way for experimentalists to target lethal diseases in future.

Discovery of potential phytochemicals as inhibitors of TcdB, a major virulence factors of Clostridioides difficile.

Clostridioides difficile is a gram-positive bacterium which is associated with different gastrointestinal related infections, and the numbers of cases related to it are continuously increasing in the past few years. Owing to high prevalence and development of resistance towards available antibiotics, it is required to develop new therapeutics to combat C. difficile infection. The current study was aimed to identify novel phytochemicals that could bind and inhibits the TcdB, an exotoxin which is required for the pathogenesis of bacteria, and hence can be considered as the future drug candidates against C. difficile. ∼2500 therapeutically important phyto-compounds were docked against the active sites of TcdB protein by using AutoDock-Vina software. The interactions between the ligands and the binding site of the top five docked complexes, based on the docking scores, were further elucidated by Molecular Dynamics Simulations of 500 ns, Molecular Mechanics Energies combined with the Poisson-Boltzmann and Surface Area (MMPBSA) or Generalized Born and Surface Area (MMGBSA), and WaterSwap Analysis. Findings of molecular docking suggested that natural compounds A183, A704, A1528, A2083, and A2129 with distinct chemical scaffolds are best docked in the binding site of TcdB and their bonding remained stable throughout the simulation studies of 500 ns. Compounds A2129 and A704 can be considered as prospective drug candidates against Clostridioides difficile, however, further wet lab experiments are needed to confirm our study.Communicated by Ramaswamy H. Sarma.

Screening of marine natural products for potential inhibitors targeting biotin biosynthesis pathway in Mycobacterium tuberculosis.

Tuberculosis (TB) remains as one of the major public health concerns worldwide. A successful TB control and treatment is very challenging, due to continuing emergence of Mycobacterium tuberculosis strains resistant to known drugs. Therefore, the development of new drugs with different chemical and biological approaches is necessary to obtain more efficient anti-tubercular therapeutics. Biotin is an essential cofactor for lipid biosynthesis and gluconeogenesis in M. tuberculosis. M. tuberculosis relies on de novo biotin biosynthesis to obtain this vital cofactor since it cannot scavenge sufficient biotin from a mammalian host. In this study, comprehensive in silico methods including structure-based virtual screening, molecular docking, and molecular dynamic simulation analysis for ∼8000 marine natural products were performed against two essential enzymes involved in biotin synthesis and ligation of M. tuberculosis namely, pyridoxal 5'-phosphate-dependent transaminase (BioA) and mycobacterial biotin protein ligase (MtBPL). Two compounds; CMNPD10112 and CMNPD10113 are unveiled to bind the enzymes consistently and with high affinities. The binding pattern of compounds is further noticed in very stable binding modes as analyzed by molecular dynamics simulation and the mean RMSD of the complexes is within 4 Å. The intermolecular binding free energies validated complexes are less than -40 kcal/mol, which demonstrates strong and stable complexes formation. The identified hit compounds could be seeds for design of effective anti-mycobacterium therapeutics by inhibition of bacterial growth through blocking the biotin biosynthesis.Communicated by Ramaswamy H. Sarma.

Identification of Novel Genes and Pathways of Ovarian Cancer Using a Comprehensive Bioinformatic Framework.

Ovarian cancer (OC) is a significant contributor to gynecological cancer-related deaths worldwide, with a high mortality rate. Despite several advances in understanding the pathogenesis of OC, the molecular mechanisms underlying its development and prognosis remain poorly understood. Therefore, the current research study aimed to identify hub genes involved in the pathogenesis of OC that could serve as selective diagnostic and therapeutic targets. To achieve this, the dataset GEO2R was used to retrieve differentially expressed genes. The study identified a total of five genes (CDKN1A, DKK1, CYP1B1, NTS, and GDF15) that were differentially expressed in OC. Subsequently, a network analysis was performed using the STRING database, followed by the construction of a network using Cytoscape. The network analyzer tool in Cytoscape predicted 276 upregulated and 269 downregulated genes. Furthermore, KEGG analysis was conducted to identify different pathways related to OC. Subsequently, survival analysis was performed to validate gene expression alterations and predict hub genes, using a p-value of 0.05 as a threshold. Four genes (CDKN1A, DKK1, CYP1B1, and NTS) were predicted as significant hub genes, while one gene (GDF15) was predicted as non-significant. The adjusted P values of said predicted genes are 2.85E - 07, 5.49E - 06, 4.28E - 07, 1.43E - 07, and 3.70E - 07 for CDKN1A, DKK1, NTS, GDF15, and CYP1B1 respectively; additionally 6.08, 5.76, 5.74, 5.01, and 4.9 LogFc values of the said genes were predicted in GEO data set. In a boxplot analysis, the expression of these genes was analyzed in normal and tumor cells. The study found that three genes were highly expressed in tumor cells, while two genes (CDKN1A and DKK1) were more elevated in normal cells. According to the boxplot analysis for CDKN1A, 50% of tumor cells ranged between approx 3.8 and 5, while 50% of normal cells ranged between approx 6.9 and 7.9, which is greater than tumor cells. This shows that in normal cells, the CYP1B1 has a high expression level according to the GEPIA boxplot; addtionally the boxplot for DKK1 indicated that 50% of tumor cells ranged between approx 0 and 0.5, which was less than that of normal cells which ranged between approx 0.3 and 0.9. It shows that DKK1 is highly expressed in normal genes. Overall, the current study provides novel insights into the molecular mechanisms underlying OC. The identified hub genes and drug candidate targets could potentially serve as alternative diagnostic and therapeutic options for OC patients. Further research is needed to investigate the clinical significance of these findings and develop effective interventions that can improve the prognosis of patients with OC.

UPLC-MS/MS Method Development for Simultaneous Estimation of Diclofenac and Resveratrol-Loaded Liposomal Gel Formulation in Mice Skin Model: Application to Dermatokinetic Study.

The current research work describes the development of a simple, fast, sensitive and efficient bioanalytical UPLC/MS-MS method for the simultaneous estimation of diclofenac and resveratrol in mice skin samples. Quetiapine was used as an internal standard (IS). Analytical separation was performed on ACQUITY UPLC C18 Column (2.1 × 100 mm; 1.7 µm) using ammonium acetate (5 mM) in water and methanol (B) with isocratic elution at ratio of (50, 50 v/v) and flow rate of 0.4 mL/min. The duration of separation was maintained for 3 min. Electrospray ionization mass spectrometry in a positive and negative ionization mode was used for detection. Selective ion mode monitoring was used for the quantification of m/z 296.025> 249.93 for diclofenac, m/z 229.09 > 143.03 for resveratrol and MRM/ES+ve mode applied in m/z 384.25> 253.189 for IS transitions from parent to daughter ion. The lower detection and quantification limits were accomplished, and precision (repeatability and intermediate precision) with a coefficient of variation below 10% produced satisfactory results. The developed bioanalytical method was found to be useful for its suitability for the dermatokinetic evaluation of treatments through rat skin. Improvement in AUC (1.58-fold for diclofenac and 1.60-fold for resveratrol) and t1/2 in the dermis (2.13 for diclofenac and 2.21-fold for resveratrol) followed by epidermis was observed for diclofenac and resveratrol-loaded liposomal gel formulation over the conventional gel. Overall, the developed method for the dermatokinetic studies of the above-mentioned dual drugs-loaded liposome gel was found to be reproducible and effective for bioanalytical.

Integrativesubtractive proteomics, immunoinformatics, docking, and simulation approaches reveal candidate vaccine against Sin Nombre orthohantavirus.

The emergence of Sin Nombre orthohantavirus, an etiological agent of hantavirus cardiopulmonary syndrome, exacerbates the situation and imposes a heavy financial burden on healthcare organizations. Multidrug-resistant forms of the disease are prevalent, and there is currently no licensed commercial vaccine. Due to the numerous limitations of experimental vaccines, vaccines against various bacterial and viral diseases have developed via computational vaccine design. Several subtractive proteomics, immunoinformatics, docking, and simulation approaches were used in this study to develop a multi-epitope-based vaccine against Sin Nombre orthohantavirus. One possible antigenic protein-the glycoprotein precursor of surface glycoproteins (accession number >AAC42202.1)-was selected as a candidate for B cell-derived T cell epitopes mapping the detailed analysis of the core genome. Among the predicted epitopes, four epitopes (QVDWTKKSST, GLAASPPHL, SSYSYRRKLV, and MESGWSDTA), which were probably antigenic, nonallergenic, nontoxic, and water soluble, were used in the multi-epitope vaccine's construction. The shortlisted epitopes have the potency to cover 99.78% of the world's population, 97.93% of the Chinese population, and 97.36% of the Indian population. The epitopes were connected through AAY linkers and joined with >50S ribosomal adjuvant to enhance their efficacy. The vaccine comprises 182 amino acids with a molecular weight of 19.03770 kDa and an instability index of 26.52, indicating that the protein is stable. A molecular docking study revealed that the vaccine has a good binding affinity with TLR-4 and TLR-8, which is vital for inducing the immune system. Top-1 docked complexes of vaccine- TLR-4 and TLR-8 with the lowest binding energy of -12.52 kc/mol and -5.42 kc/mol, respectively, were considered for molecular dynamic simulation analysis. Furthermore, we predicted that the docked complexes are properly stable throughout simulation time in both normal mode and AMBER-based simulation analysis. The MMGBSA analysis calculated -122.17 and -125.4 net binding energies for the TLR-8- and TLR4-vaccine complexes, respectively, while the MMPBSA analysis estimated -115.63 and -118.19 for the TLR-8- and TLR4-vaccine complex, respectively, confirming that the binding stability with receptors is stable, which is important for inducing a strong response. However, the current work is computation-based, so experimental validation is highly recommended.

Analyzing the effect of mutations in SARS-CoV2 papain-like protease from Saudi isolates on protein structure and drug-protein binding: Molecular modelling and dynamics studies.

The continuous and rapid development of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus remains a health concern especially with the emergence of numerous variants and mutations worldwide. As with other RNA viruses, SARS-CoV-2 has a genetically high mutation rate. These mutations have an impact on the virus characteristics, including transmissibility, antigenicity and development of drug and vaccine resistance. This work was pursued to identify the differences that exist in the papain-like protease (PLPro) from 58 Saudi isolates in comparison to the first reported sequence from Wuhan, China and determine their implications on protein structure and the inhibitor binding. PLpro is a key protease enzyme for the host cells invasion and viral proteolytic cleavage, hence, it emerges as a valuable antiviral therapeutic target. Two mutations were identified including D108G and A249V and shown to increase the molecular flexibility of PLPro protein and alter the protein stability, particularly with D108G mutation. The effect of these mutations on the stability and dynamic behavior of PLPro structures as well as their effect on the binding of a known inhibitor; GRL0617 were further investigated by molecular docking and dynamic simulation.

Synthesis, characterization, biological evaluation and molecular docking of a new quinazolinone-based derivative as a potent dual inhibitor for VEGFR-2 and EGFR tyrosine kinases.

An efficient process for the preparation of a new ethyl 2-((3-(4-fluorophenyl)-6-methyl-4-oxo-3,4-dihydroquinazolin-2-yl)thio) acetate (5) was described. The prepared derivative was synthesized using the S-arylation method. Several analytical techniques, such as NMR, Raman and infrared spectroscopy, were used to characterize this compound. The compound was screened for cytotoxic activity against three human cancer cell lines: human cervical cancer (HeLa), human lung adenocarcinoma (A549) and triple negative breast cancer (MDA-MB-231) cells using an MTT assay. It exhibited potent cytotoxic activity against the tested cell lines with IC50 values in the low micromolar range when compared to a standard drug, docetaxel. It also displayed potent inhibitory activity towards VEGFR-2 and EGFR tyrosine kinases, reflecting its potential to act as an effective anti-cancer agent.Communicated by Ramaswamy H. Sarma.