Genome-level therapeutic targets identification and chimeric Vaccine designing against the Blastomyces dermatitidis.

Blastomyces dermatitidis is a thermally dimorphic fungus that can cause serious and sometimes fatal infections, including blastomycosis. After spore inhalation, a pulmonary infection develops, which can be asymptomatic and have lethal effects, such as acute respiratory distress syndrome. Its most common extra-pulmonary sites are the central nervous system, bones, skin, and genito-urinary systems. Currently, no vaccine has been approved by the FDA to prevent this infection. In the study, a peptide-based vaccine was developed against blastomycosis by using subtractive proteomics and reverse vaccinology approaches. It focuses on mining the whole genome of B. dermatitidis, identifying potential therapeutic targets, and pinpointing potential epitopes for both B- and T-cells that are immunogenic, non-allergenic, non-toxic, and highly antigenic. Multi-epitope constructs were generated by incorporating appropriate linker sequences. A linker (EAAAK) was also added to incorporate an adjuvant sequence to increase immunological potential. The addition of adjuvants and linkers ultimately resulted in the formation of a vaccine construct in which the number of amino acids was 243 and the molecular weight was 26.18 kDa. The designed antigenic and non-allergenic vaccine constructs showed suitable physicochemical properties. The vaccine's structures were predicted, and further analysis verified their interactions with the human TLR-4 receptor through protein-protein docking. Additionally, MD simulation showed a potent interaction between prioritized vaccine-receptor complexes. Immune simulation predicted that the final vaccine injections resulted in significant immune responses for the T- and B-cell immune responses. Moreover, in silico cloning ensured a high expression possibility of the lead vaccine in the E. coli (K12) vector. This study offers an initiative for the development of effective vaccines against B. dermatitidis; however, it is necessary to validate the designed vaccine's immunogenicity experimentally.

Identifying plant-derived antiviral alkaloids as dual inhibitors of SARS-CoV-2 main protease and spike glycoprotein through computational screening.

COVID-19 is currently considered the ninth-deadliest pandemic, spreading through direct or indirect contact with infected individuals. It has imposed a consistent strain on both the financial and healthcare resources of many countries. To address this challenge, there is a pressing need for the development of new potential therapeutic agents for the treatment of this disease. To identify potential antiviral agents as novel dual inhibitors of SARS-CoV-2, we retrieved 404 alkaloids from 12 selected medicinal antiviral plants and virtually screened them against the renowned catalytic sites and favorable interacting residues of two essential proteins of SARS-CoV-2, namely, the main protease and spike glycoprotein. Based on docking scores, 12 metabolites with dual inhibitory potential were subjected to drug-likeness, bioactivity scores, and drug-like ability analyses. These analyses included the ligand-receptor stability and interactions at the potential active sites of target proteins, which were analyzed and confirmed through molecular dynamic simulations of the three lead metabolites. We also conducted a detailed binding free energy analysis of pivotal SARS-CoV-2 protein inhibitors using molecular mechanics techniques to reveal their interaction dynamics and stability. Overall, our results demonstrated that 12 alkaloids, namely, adouetine Y, evodiamide C, ergosine, hayatinine, (+)-homoaromoline, isatithioetherin C, N,alpha-L-rhamnopyranosyl vincosamide, pelosine, reserpine, toddalidimerine, toddayanis, and zanthocadinanine, are shortlisted as metabolites based on their interactions with target proteins. All 12 lead metabolites exhibited a higher unbound fraction and therefore greater distribution compared with the standards. Particularly, adouetine Y demonstrated high docking scores but exhibited a nonspontaneous binding profile. In contrast, ergosine and evodiamide C showed favorable binding interactions and superior stability in molecular dynamics simulations. Ergosine demonstrated exceptional performance in several key pharmaceutical metrics. Pharmacokinetic evaluations revealed that ergosine exhibited pronounced bioactivity, good absorption, and optimal bioavailability. Additionally, it was predicted not to cause skin sensitivity and was found to be non-hepatotoxic. Importantly, ergosine and evodiamide C emerged as superior drug candidates for dual inhibition of SARS-CoV-2 due to their strong binding affinity and drug-like ability, comparable to known inhibitors like N3 and molnupiravir. This study is limited by its in silico nature and demands the need for future in vitro and in vivo studies to confirm these findings.

Development of a subunit vaccine against the cholangiocarcinoma causing Opisthorchis viverrini: a computational approach.

Opisthorchis viverrini is the etiological agent of the disease opisthorchiasis and related cholangiocarcinoma (CCA). It infects fish-eating mammals and more than 10 million people in Southeast Asia suffered from opisthorchiasis with a high fatality rate. The only effective drug against this parasite is Praziquantel, which has significant side effects. Due to the lack of appropriate treatment options and the high death rate, there is a dire need to develop novel therapies against this pathogen. In this study, we designed a multi-epitope chimeric vaccine design against O. viverrini by using immunoinformatics approaches. Non-allergenic and immunogenic MHC-1, MHC-2, and B cell epitopes of three candidate proteins thioredoxin peroxidase (Ov-TPx-1), cathepsin F1 (Ov-CF-1) and calreticulin (Ov-CALR) of O. viverrini, were predicted to construct a potent multiepitope vaccine. The coverage of the HLA-alleles of these selected epitopes was determined globally. Four vaccine constructs made by different adjuvants and linkers were evaluated in the context of their physicochemical properties, antigenicity, and allergenicity. Protein-protein docking and MD simulation found that vaccines 3 was more stable and had a higher binding affinity for TLR2 and TLR4 immune receptors. In-silico restriction cloning of vaccine model led to the formation of plasmid constructs for expression in a suitable host. Finally, the immune simulation showed strong immunological reactions to the engineered vaccine. These findings suggest that the final vaccine construct has the potential to be validated by in vivo and in vitro experiments to confirm its efficacy against the CCA causing O. viverrini.

From waste to wealth: iron oxide doped hydroxyapatite-based biosensor for the colorimetric detection of ascorbic acid.

Ascorbic acid plays a pivotal role in the human body. It maintains the robustness, enlargement, and elasticity of the collagen triple helix. However, the abnormal concentration of ascorbic acid causes various diseases, such as scurvy, cardiovascular diseases, gingival bleeding, urinary stones, diarrhea, stomach convulsions, etc. In the present work, an iron-doped hydroxyapatite (HAp@Fe2O3)-based biosensor was developed for the colorimetric detection of ascorbic acid based on a low-cost, biocompatible, and ubiquitous material. Due to the catalytic nature of HAp owing to the acidic and basic moieties within the structure, it was used as a template for HAp@Fe2O3 synthesis. This approach provides an active as well as large surface area for the sensing of ascorbic acid. The synthesized platform was characterized by various techniques, such as UV-Vis, FTIR, SEM, XRD, TGA, EDX, etc. The HAp@Fe2O3 demonstrated inherent peroxidase-like activity in the presence of 3,3',5,5'-tetramethylbenzidine (TMB) oxidized with the assistance of H2O2. It resulted in the color changing to blue-green, and after the addition of ascorbic acid, the color changed to colorless, resulting in the reduction of TMB. To achieve optimal sensing parameters, experimental conditions were optimized. The quantity of HAp@Fe2O3, H2O2, pH, TMB, time, and the concentration of ascorbic acid were fine-tuned. The linear range for the proposed sensor was 0.6-56 µM, along with a limit of detection of 0.16 µM and a limit of quantification of 0.53 µM. The proposed sensor detects ascorbic acid within 75 seconds at room temperature. The proposed platform was also applied to quantitatively check the concentration of ascorbic acid in a physiological solution.

Nanozyme-based sensing of dopamine using cobalt-doped hydroxyapatite nanocomposite from waste bones.

Dopamine is one of the most important neurotransmitters and plays a crucial role in various neurological, renal, and cardiovascular systems. However, the abnormal levels of dopamine mainly point to Parkinson's, Alzheimer's, cardiovascular diseases, etc. Hydroxyapatite (HAp), owing to its catalytic nature, nanoporous structure, easy synthesis, and biocompatibility, is a promising matrix material. These characteristics make HAp a material of choice for doping metals such as cobalt. The synthesized cobalt-doped hydroxyapatite (Co-HAp) was used as a colorimetric sensing platform for dopamine. The successful synthesis of the platform was confirmed by characterization with FTIR, SEM, EDX, XRD, TGA, etc. The platform demonstrated intrinsic peroxidase-like activity in the presence of H2O2, resulting in the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB). The proposed sensor detected dopamine in a linear range of 0.9-35 µM, a limit of detection of 0.51 µM, limit of quantification of 1.7 µM, and an R2 of 0.993. The optimization of the proposed sensor was done with different parameters, such as the amount of mimic enzyme, H2O2, pH, TMB concentration, and time. The proposed sensor showed the best response at 5 mg of the mimic enzyme, pH 5, 12 mM TMB, and 8 mM H2O2, with a short response time of only 2 min. The fabricated platform was successfully applied to detect dopamine in physiological solutions.

Identification of Novel Quinolone and Quinazoline Alkaloids as Phosphodiesterase 10A Inhibitors for Parkinson's Disease through a Computational Approach.

Phosphodiesterases (PDEs) are vital in signal transduction, specifically by hydrolyzing cAMP and cGMP. Within the PDE family, PDE10A is notable for its prominence in the striatum and its regulatory function over neurotransmitters in medium-spiny neurons. Given the dopamine deficiency in Parkinson's disease (PD) that affects striatal pathways, PDE10A inhibitors could offer therapeutic benefits by modulating D1 and D2 receptor signaling. This study was motivated by the successful history of quinazoline/quinazoline scaffolds in the inhibition of PDE10A. This study involved detailed in silico evaluations through docking followed by pharmacological, pharmacophoric, and pharmacokinetic analyses, prioritizing central nervous system (CNS)-active drug criteria. Seven cyclic peptides, those featuring the quinazoline/quinazoline moiety at both termini, exhibited notably enhanced docking scores compared to those of the remaining alkaloids within the screened library. We identified 7 quinolines and 1 quinazoline including Lepadin G, Aspernigerin, CJ-13536, Aurachin A, 2-Undecyl-4(1H)-quinolone, Huajiaosimuline 3-Prenyl-4-prenyloxyquinolin-2-one, and Isaindigotone that followed the standard CNS active drug criteria. The dominant quinoline ring in our study and its related quinazoline were central to our evaluations; therefore, the pharmacophoric features of these scaffolds were highlighted. The top alkaloids met all CNS-active drug properties; while nonmutagenic and without PAINS alerts, many indicated potential hepatotoxicity. Among the compounds, Huajiaosimuline was particularly significant due to its alignment with lead-likeness and CNS-active criteria. Aspernigerin demonstrated its affinity for numerous dopamine receptors, which signifies its potential to alter dopaminergic neurotransmission that is directly related to PD. Interestingly, the majority of these alkaloids had biological targets primarily associated with G protein-coupled receptors, critical in PD pathophysiology. They exhibit superior excretion parameters and toxicity end-points compared to the standard. Notably, selected alkaloids demonstrated stability in the binding pocket of PDE10A according to the molecular dynamic simulation results. Our findings emphasize the potential of these alkaloids as PDE10A inhibitors. Further experimental studies may be necessary to confirm their actual potency in inhibiting PDE10A before exploring their therapeutic potential in PD.

Decrypting the multi-genome data for chimeric vaccine designing against the antibiotic resistant Yersinia pestis.

Yersinia pestis, the causative agent of plague, is a gram-negative bacterium that can be fatal if not treated properly. Three types of plague are currently known: bubonic, septicemic, and pneumonic plague, among which the fatality rate of septicemic and pneumonic plague is very high. Bubonic plague can be treated, but only if antibiotics are used at the initial stage of the infection. But unfortunately, Y. pestis has also shown resistance to certain antibiotics such as kanamycin, minocycline, tetracycline, streptomycin, sulfonamides, spectinomycin, and chloramphenicol. Despite tremendous progress in vaccine development against Y. pestis, there is no proper FDA-approved vaccine available to protect people from its infections. Therefore, effective broad-spectrum vaccine development against Y. pestis is indispensable. In this study, vaccinomics-assisted immunoinformatics techniques were used to find possible vaccine candidates by utilizing the core proteome prepared from 58 complete genomes of Y. pestis. Human non-homologous, pathogen-essential, virulent, and extracellular and membrane proteins are potential vaccine targets. Two antigenic proteins were prioritized for the prediction of lead epitopes by utilizing reverse vaccinology approaches. Four vaccine designs were formulated using the selected B- and T-cell epitopes coupled with appropriate linkers and adjuvant sequences capable of inducing potent immune responses. The HLA allele population coverage of the T-cell epitopes selected for vaccine construction was also analyzed. The V2 constructs were top-ranked and selected for further analysis on the basis of immunological, physicochemical, and immune-receptor docking interactions and scores. Docking and molecular dynamic simulations confirmed the stability of construct V2 interactions with the host immune receptors. Immune simulation analysis anticipated the strong immune profile of the prioritized construct. In silico restriction cloning ensured the feasible cloning ability of the V2 construct in the expression system of E. coli strain K12. It is anticipated that the designed vaccine construct may be safe, effective, and able to elicit strong immune responses against Y. pestis infections and may, therefore, merit investigation using in vitro and in vivo assays.

Uric acid quantification via colorimetric detection utilizing silver oxide-modified activated carbon nanoparticles functionalized with ionic liquid.

Uric acid (UA) is a significant indicator of human health because it is linked to several diseases, including renal failure, kidney stones, arthritis, and gout. Uric acid buildup in the joints is the source of chronic and painful diseases. When UA is present in large quantities, it causes tissue injury in the joints that are afflicted. In this research, silver oxide-doped activated carbon nanoparticles were synthesized and then functionalized with an ionic liquid. The synthesized nanomaterial assembly was employed as a colorimetric sensing platform for uric acid. Activated carbon offers a large internal surface area that acts as a good carrier for catalytic reactions. A salt-melting approach was used to synthesize the silver oxide-doped activated carbon nanocomposite. The synthesis was confirmed through various techniques, such as UV-vis spectrophotometer, FTIR, XRD, SEM, and EDX. The colorimetric change from blue-green to colorless was observed with the naked eye and confirmed by UV-vis spectroscopy. To obtain the best colorimetric change, several parameters, such as pH, capped NP loading, TMB concentration, hydrogen peroxide concentration, and time, were optimized. The optimized experimental conditions for the proposed sensor were pH 4 with 35 µL of NPs, a 40 mM TMB concentration, and a 4 minutes incubation time. The sensor linear range is 0.001-0.36 µM, with an R2 value of 0.999. The suggested sensor limits of detection and quantification are 0.207 and 0.69 nM, respectively. Potential interferers, such as ethanol, methanol, urea, Ca2+, K+, and dopamine, did not affect the detection of uric acid.

Colorimetric sensing of hydrogen peroxide using capped Morus nigra-sawdust deposited zinc oxide nanoparticles via Trigonella foenum extract.

Hydrogen peroxide (H2O2) is one of the main byproducts of most enzymatic reactions, and its detection is very important in disease conditions. Due to its essential role in healthcare, the food industry, and environmental research, accurate H2O2 determination is a prerequisite. In the present work, Morus nigra sawdust deposited zinc oxide (ZnO) nanoparticles (NPs) were synthesized by the use of Trigonella foenum extract via a hydrothermal process. The synthesized platform was characterized by various techniques, including UV-Vis, FTIR, XRD, SEM, EDX, etc. FTIR confirmed the presence of a Zn‒O characteristic peak, and XRD showed the hexagonal phase of ZnO NPs with a 35 nm particle size. The EDX analysis confirmed the presence of Zn and O. SEM images showed that the as-prepared nanoparticles are distributed uniformly on the surface of sawdust. The proposed platform (acetic acid-capped ZnO NPs deposited sawdust) functions as a mimic enzyme for the detection of H2O2 in the presence of 3,3',5,5'-tetramethylbenzidine (TMB) colorimetrically. To get the best results, many key parameters, such as the amount of sawdust-deposited nanoparticles, TMB concentration, pH, and incubation time were optimized. With a linear range of 0.001-0.360 µM and an R2 value of 0.999, the proposed biosensor's 0.81 nM limit of quantification (LOQ) and 0.24 nM limit of detection (LOD) were predicted, respectively. The best response for the proposed biosensor was observed at pH 7, room temperature, and 5 min of incubation time. The acetic acid-capped sawdust deposited ZnO NPs biosensor was also used to detect H2O2 in blood serum samples of diabetic patients and suggest a suitable candidate for in vitro diagnostics and commercial purposes.

In-silico evaluation of natural alkaloids against the main protease and spike glycoprotein as potential therapeutic agents for SARS-CoV-2.

Severe Acute Respiratory Syndrome Corona Virus (SARS-CoV-2) is the causative agent of COVID-19 pandemic, which has resulted in global fatalities since late December 2019. Alkaloids play a significant role in drug design for various antiviral diseases, which makes them viable candidates for treating COVID-19. To identify potential antiviral agents, 102 known alkaloids were subjected to docking studies against the two key targets of SARS-CoV-2, namely the spike glycoprotein and main protease. The spike glycoprotein is vital for mediating viral entry into host cells, and main protease plays a crucial role in viral replication; therefore, they serve as compelling targets for therapeutic intervention in combating the disease. From the selection of alkaloids, the top 6 dual inhibitory compounds, namely liensinine, neferine, isoliensinine, fangchinoline, emetine, and acrimarine F, emerged as lead compounds with favorable docked scores. Interestingly, most of them shared the bisbenzylisoquinoline alkaloid framework and belong to Nelumbo nucifera, commonly known as the lotus plant. Docking analysis was conducted by considering the key active site residues of the selected proteins. The stability of the top three ligands with the receptor proteins was further validated through dynamic simulation analysis. The leads underwent ADMET profiling, bioactivity score analysis, and evaluation of drug-likeness and physicochemical properties. Neferine demonstrated a particularly strong affinity for binding, with a docking score of -7.5025 kcal/mol for main protease and -10.0245 kcal/mol for spike glycoprotein, and therefore a strong interaction with both target proteins. Of the lead alkaloids, emetine and fangchinoline demonstrated the lowest toxicity and high LD50 values. These top alkaloids, may support the body's defense and reduce the symptoms by their numerous biological potentials, even though some properties naturally point to their direct antiviral nature. These findings demonstrate the promising anti-COVID-19 properties of the six selected alkaloids, making them potential candidates for drug design. This study will be beneficial in effective drug discovery and design against COVID-19 with negligible side effects.

Paracetamol-Mediated Synthesis of Silver Nanoparticles and Their Functionalization with Ionic Liquid for the Colorimetric Biosensing of Ascorbic Acid.

Ascorbic acid is a vital biomolecule for human beings. When the body's level of ascorbic acid is abnormal, it can lead to a number of illnesses. Its appropriate concentration is necessary for the oxidation of prostaglandins and cyclic adenosine monophosphate, the production of dopamine, norepinephrine, epinephrine, and carnitine, and the expansion and durability of the collagen triple helix in humans. In the present work, silver nanoparticle synthesis was performed through a paracetamol-mediated approach. Different characterization techniques, such as X-ray diffractometry (XRD), energy dispersive X-ray (EDX), Fourier transform infrared (FTIR), and scanning electron microscopy (SEM), were used to confirm the prepared nanoparticles. Subsequently, the prepared Ag NPs functionalized with an ionic liquid were used as a sensing platform for ascorbic acid in blood serum samples. To achieve the best possible results, the proposed biosensor was optimized with different parameters such as TMB concentration, time, amount of capped nanoparticles (NPs), and pH. The proposed biosensor offers a sensitive and straightforward method for ascorbic acid with a linear range from 2 × 10-9 to 3.22 × 10-7 M, an LOD of 1.3 × 10-8 M, an LOQ of 4.3 × 10-8 M, and an R2 of 0.9996, Moreover, applications of the proposed biosensor were successfully used for the detection of ascorbic acid in samples of human plasma, suggesting that Ag NPs with high peroxidase-like activity, high stability, and facile synthesis exhibited promising applications in biomedical fields.

Computer-aided identification of Mycobacterium tuberculosis resuscitation-promoting factor B (RpfB) inhibitors from Gymnema sylvestre natural products.

Tuberculosis (TB), an infectious disease caused by multi-drug resistant Mycobacterium tuberculosis (Mtb), has been a global health concern. Mtb affects over a third of the world's population, causing two million deaths annually due to its dormancy and propensity to spread infection during this period. Resuscitation-promoting factor B (RpfB) plays a pivotal role in the growth of Mtb during dormant periods, making it a critical target for eliminating Mtb and curing TB. Gymnema sylvestre is a famous medicinal plant with several medicinal properties, including antimicrobial activity; however, the therapeutic potential of the various reported metabolites of this plant against Mtb has not yet been explored. The aim of this study was to explore the reported natural products of G. sylvestre against the RpfB of the Mtb. A total of 131 reported secondary metabolites of this plant were collected and virtually screened against the RpfB. We particularly targeted the Glu292 residue of RpfB as it is crucial for the catalysis of this protein. From our in-house library, 114 compounds showed a binding affinity higher than the standard drug. The binding stability of the top three lead compounds was further confirmed through MD simulation analysis. Drug likeness analyses indicated that the ten hits had zero violations of the Lipinski rule of five. In addition, analyses of pharmacokinetics, toxicity, and target prediction revealed that the top compounds are devoid of toxicity and do not affect human proteins. Additionally, they reflect multifaceted approach as anti-TB agents. Our selected hits not only exhibit molecular properties favoring physiological compatibility but also exhibit properties enhancing their potential efficacy as therapeutic candidates. The compounds investigated here are worthy of experimental validation for the discovery of novel treatments against TB. Further, this study also provides a promising avenue for research on the pharmacological potential of G. sylvestre.

Structural informatics approach for designing an epitope-based vaccine against the brain-eating Naegleria fowleri.

Primary Amoebic Meningoencephalitis (PAM), a severe lethal brain disease, is caused by a parasite, Naegleria fowleri, also known as the "brain-eating amoeba". The chances of a patient's recovery after being affected by this parasite are very low. Only 5% of people are known to survive this life-threatening infection. Despite the fact that N. fowleri causes a severe, fatal infection, there is no proper treatment available to prevent or cure it. In this context, it is necessary to formulate a potential vaccine that could be able to combat N. fowleri infection. The current study aimed at developing a multi-epitope subunit vaccine against N. fowleri by utilizing immunoinformatics techniques and reverse vaccinology approaches. The T- and B-cell epitopes were predicted by various tools. In order to choose epitopes with the ability to trigger both T- and B-cell-mediated immune responses, the epitopes were put through a screening pipeline including toxicity, antigenicity, cytokine-inductivity, and allergenicity analysis. Three vaccine constructs were designed from the generated epitopes linked with linkers and adjuvants. The modeled vaccines were docked with the immune receptors, where vaccine-1 showed the highest binding affinity. Binding affinity and stability of the docked complex were confirmed through normal mode analysis and molecular dynamic simulations. Immune simulations developed the immune profile, and in silico cloning affirmed the expression probability of the vaccine construct in Escherichia coli (E. coli) strain K12. This study demonstrates an innovative preventative strategy for the brain-eating amoeba by developing a potential vaccine through immunoinformatics and reverse vaccinology approaches. This study has great preventive potential for Primary Amoebic Meningoencephalitis, and further research is required to assess the efficacy of the designed vaccine.

Deciphering the Immunogenicity of Monkeypox Proteins for Designing the Potential mRNA Vaccine.

The Monkeypox virus (MPXV), an orthopox virus, is responsible for monkeypox in humans, a zoonotic disease similar to smallpox. This infection first appeared in the 1970s in humans and then in 2003, after which it kept on spreading all around the world. To date, various antivirals have been used to cure this disease, but now, MPXV has developed resistance against these, thus increasing the need for an alternative cure for this deadly disease. In this study, we devised a reverse vaccinology approach against MPXV using a messenger RNA (mRNA) vaccine by pinning down the antigenic proteins of this virus. By using bioinformatic tools, we predicted prospective immunogenic B and T lymphocyte epitopes. Based on cytokine inducibility score, nonallergenicity, nontoxicity, antigenicity, and conservancy, the final epitopes were selected. Our analysis revealed the stable structure of the mRNA vaccine and its efficient expression in host cells. Furthermore, strong interactions were demonstrated with toll-like receptors 2 (TLR2) and 4 (TLR4) according to the molecular dynamic simulation studies. The in silico immune simulation analyses revealed an overall increase in the immune responses following repeated exposure to the designed vaccine. Based on our findings, the vaccine candidate designed in this study has the potential to be tested as a promising novel mRNA therapeutic vaccine against MPXV infection.

Proteome level analysis of drug-resistant Prevotella melaninogenica for the identification of novel therapeutic candidates.

The management of infectious diseases has become more critical due to the development of novel pathogenic strains with enhanced resistance. Prevotella melaninogenica, a gram-negative bacterium, was found to be involved in various infections of the respiratory tract, aerodigestive tract, and gastrointestinal tract. The need to explore novel drug and vaccine targets against this pathogen was triggered by the emergence of antimicrobial resistance against reported antibiotics to combat P. melaninogenica infections. The study involves core genes acquired from 14 complete P. melaninogenica strain genome sequences, where promiscuous drug and vaccine candidates were explored by state-of-the-art subtractive proteomics and reverse vaccinology approaches. A stringent bioinformatics analysis enlisted 18 targets as novel, essential, and non-homologous to humans and having druggability potential. Moreover, the extracellular and outer membrane proteins were subjected to antigenicity, allergenicity, and physicochemical analysis for the identification of the candidate proteins to design multi-epitope vaccines. Two candidate proteins (ADK95685.1 and ADK97014.1) were selected as the best target for the designing of a vaccine construct. Lead B- and T-cell overlapped epitopes were joined to generate potential chimeric vaccine constructs in combination with adjuvants and linkers. Finally, a prioritized vaccine construct was found to have stable interactions with the human immune cell receptors as confirmed by molecular docking and MD simulation studies. The vaccine construct was found to have cloning and expression ability in the bacterial cloning system. Immune simulation ensured the elicitation of significant immune responses against the designed vaccine. In conclusion, our study reported novel drug and vaccine targets and designed a multi-epitope vaccine against the P. melaninogenica infection. Further experimental validation will help open new avenues in the treatment of this multi-drug-resistant pathogen.

Cobalt oxide modified sulfur and phosphorus Co-doped g-C3N4 for screening of urinary human albumin.

The fabrication of a heteroatom-doped nanocomposite based on cobalt oxide modified sulfur, phosphorus co-doped carbon nitride (Co3O4/SP-CN) with increased active sites is reported. The synthesized nanocomposite offers surprisingly high electrocatalytic oxidation efficacy toward human albumin (HA) despite its agglomeration. This improved efficacy of Co3O4/SP-CN nanocomposite could be attributed to its increased adsorption sites and surface defects, fast charge transportation capability, and conductivity. Additionally, morphological and compositional analysis of the fabricated Co3O4/SP-CN material has been performed  through scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photon spectroscopy (XPS), and Raman spectroscopy. The fabricated electrode shows remarkable amperometric response against the HA with a limit of detection of 8.39 nM and linear range of 20-4000 nM at applied potential of 0.25 V versus Ag/AgCl in 0.1 M PBS (pH 8.2). The designed Co3O4/SP-CN electrode has been successfully applied to monitor HA in  urine samples of diabetic patient with recovery percentage from 94.1 and 92.1% and with relative standard deviation (RSD) values of 5.8 and 7.8%. According to the best of our knowledge, this is the first report to use a Co3O4/SP-CN-based graphitic pencil (GP) electrode for monitoring of HA for early diagnosis of diabetic nephropathy.

Co-Doped CeO2/Activated C Nanocomposite Functionalized with Ionic Liquid for Colorimetric Biosensing of H2O2 via Peroxidase Mimicking.

Hydrogen peroxide acts as a byproduct of oxidative metabolism, and oxidative stress caused by its excess amount, causes different types of cancer. Thus, fast and cost-friendly analytical methods need to be developed for H2O2. Ionic liquid (IL)-coated cobalt (Co)-doped cerium oxide (CeO2)/activated carbon (C) nanocomposite has been used to assess the peroxidase-like activity for the colorimetric detection of H2O2. Both activated C and IL have a synergistic effect on the electrical conductivity of the nanocomposites to catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB). The Co-doped CeO2/activated C nanocomposite has been synthesized by the co-precipitation method and characterized by UV-Vis spectrophotometry, FTIR, SEM, EDX, Raman spectroscopy, and XRD. The prepared nanocomposite was functionalized with IL to avoid agglomeration. H2O2 concentration, incubation time, pH, TMB concentration, and quantity of the capped nanocomposite were tuned. The proposed sensing probe gave a limit of detection of 1.3 × 10-8 M, a limit of quantification of 1.4 × 10-8 M, and an R2 of 0.999. The sensor gave a colorimetric response within 2 min at pH 6 at room temperature. The co-existing species did not show any interference during the sensing probe. The proposed sensor showed high sensitivity and selectivity and was used to detect H2O2 in cancer patients' urine samples.

Computer-aided genomic data analysis of drug-resistant Neisseria gonorrhoeae for the Identification of alternative therapeutic targets.

Neisseria gonorrhoeae is an emerging multidrug resistance pathogen that causes sexually transmitted infections in men and women. The N. gonorrhoeae has demonstrated an emerging antimicrobial resistance against reported antibiotics, hence fetching the attention of researchers to address this problem. The present in-silico study aimed to find putative novel drug and vaccine targets against N. gonorrhoeae infection by the application of bioinformatics approaches. Core genes set of 69 N. gonorrhoeae strains was acquired from complete genome sequences. The essential and non-homologous metabolic pathway proteins of N. gonorrhoeae were identified. Moreover, different bioinformatics databases were used for the downstream analysis. The DrugBank database scanning identified 12 novel drug targets in the prioritized list. They were preferred as drug targets against this bacterium. A viable vaccine is unavailable so far against N. gonorrhoeae infection. In the current study, two outer-membrane proteins were prioritized as vaccine candidates via reverse vaccinology approach. The top lead B and T-cells overlapped epitopes were utilized to generate a chimeric vaccine construct combined with immune-modulating adjuvants, linkers, and PADRE sequences. The top ranked prioritized vaccine construct (V7) showed stable molecular interaction with human immune cell receptors as inferred during the molecular docking and MD simulation analyses. Considerable response for immune cells was interpreted by in-silico immune studies. Additional tentative validation is required to ensure the effectiveness of the prioritized vaccine construct against N. gonorrhoeae infection. The identified proteins can be used for further rational drug and vaccine designing to develop potential therapeutic entities against the multi-drug resistant N. gonorrhoeae.

Recent Approaches for Downplaying Antibiotic Resistance: Molecular Mechanisms.

Antimicrobial resistance (AMR) is a ubiquitous public health menace. AMR emergence causes complications in treating infections contributing to an upsurge in the mortality rate. The epidemic of AMR in sync with a high utilization rate of antimicrobial drugs signifies an alarming situation for the fleet recovery of both animals and humans. The emergence of resistant species calls for new treatments and therapeutics. Current records propose that health drug dependency, veterinary medicine, agricultural application, and vaccination reluctance are the primary etymology of AMR gene emergence and spread. Recently, several encouraging avenues have been presented to contest resistance, such as antivirulent therapy, passive immunization, antimicrobial peptides, vaccines, phage therapy, and botanical and liposomal nanoparticles. Most of these therapies are used as cutting-edge methodologies to downplay antibacterial drugs to subdue the resistance pressure, which is a featured motive of discussion in this review article. AMR can fade away through the potential use of current cutting-edge therapeutics, advancement in antimicrobial susceptibility testing, new diagnostic testing, prompt clinical response, and probing of new pharmacodynamic properties of antimicrobials. It also needs to promote future research on contemporary methods to maintain host homeostasis after infections caused by AMR. Referable to the microbial ability to break resistance, there is a great ultimatum for using not only appropriate and advanced antimicrobial drugs but also other neoteric diverse cutting-edge therapeutics.

Structural Consequences of IRS-2 nsSNPs and Implication for Insulin Receptor Substrate-2 Protein Stability.

Single-Nucleotide Polymorphisms (SNPs) are common genetic variations implicated in human diseases. The non-synonymous SNPs (nsSNPs) affect the proteins' structures and their molecular interactions with other interacting proteins during the accomplishment of biochemical processes. This ultimately causes proteins functional perturbation and disease phenotypes. The Insulin receptor substrate-2 (IRS-2) protein promotes glucose absorption and participates in the biological regulation of glucose metabolism and energy production. Several IRS-2 SNPs are reported in association with type 2 diabetes and obesity in human populations. However, there are no comprehensive reports about the protein structural consequences of these nsSNPs. Keeping in view the pathophysiological consequences of the IRS-2 nsSNPs, we designed the current study to understand their possible structural impact on coding protein. The prioritized list of the deleterious IRS-2 nsSNPs was acquired from multiple bioinformatics resources, including VEP (SIFT, PolyPhen, and Condel), PROVEAN, SNPs&GO, PMut, and SNAP2. The protein structure stability assessment of these nsSNPs was performed by MuPro and I-Mutant-3.0 servers via structural modeling approaches. The atomic-level structural and molecular dynamics (MD) impact of these nsSNPs were examined using GROMACS 2019.2 software package. The analyses initially predicted 8 high-risk nsSNPs located in the highly conserved regions of IRS-2. The MD simulation analysis eventually prioritized the N232Y, R218C, and R104H nsSNPs that predicted to significantly compromise the structure stability and may affect the biological function of IRS-2. These nsSNPs are predicted as high-risk candidates for diabetes and obesity. The validation of protein structural impact of these shortlisted nsSNPs may provide biochemical insight into the IRS-2-mediated type-2 diabetes.